Disruptive Innovation

The Christensen Collection

Clayton M. Christensen

Michael E. Raynor

Jeff Dyer

Hal Gregersen

Harvard Business Review Press

Boston, Massachusetts

Collection first published May 2012

ISBN: 978-14221-8998-6

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Contents

"How Will You Measure Your Life?"

The Innovator's Dilemma

The Innovator's Solution

The Innovator's DNA

How Will You Measure Your Life?

Clayton M. Christensen

This article first appeared in Harvard Business Review in July/August 2010.

Copyright (c) 2010 Harvard Business School Publishing. All rights reserved.

Editor’s Note: When the members of the class of 2010 entered business school, the economy was strong and their post-graduation ambitions could be limitless. Just a few weeks later, the economy went into a tailspin. They’ve spent the past two years recalibrating their worldview and their definition of success.

The students seem highly aware of how the world has changed (as the sampling of views in this article shows). In the spring, Harvard Business School’s graduating class asked HBS professor Clay Christensen to address them—but not on how to apply his principles and thinking to their post-HBS careers. The students wanted to know how to apply them to their personal lives. He shared with them a set of guidelines that have helped him find meaning in his own life. Though Christensen’s thinking comes from his deep religious faith, we believe that these are strategies anyone can use. And so we asked him to share them with the readers of HBR. To learn more about Christensen’s work, visit his HBR Author Page.

Idea in Brief

Harvard Business School’s Christensen teaches aspiring MBAs how to apply management and innovation theories to build stronger companies. But he also believes that these models can help people lead better lives. In this article, he explains how, exploring questions everyone needs to ask. How can I be happy in my career? How can I be sure that my relationship with my family is an enduring source of happiness? And how can I live my life with integrity? The answer to the first question comes from Frederick Herzberg’s assertion that the most powerful motivator isn’t money; it’s the opportunity to learn, grow in responsibilities, contribute, and be recognized. That’s why management, if practiced well, can be the noblest of occupations; no others offer as many ways to help people find those opportunities. It isn’t about buying, selling, and investing in companies, as many think. The principles of resource allocation can help people attain happiness at home. If not managed masterfully, what emerges from a firm’s resource allocation process can be very different from the strategy management intended to follow. That’s true in life too: If you’re not guided by a clear sense of purpose, you’re likely to fritter away your time and energy on obtaining the most tangible, short-term signs of achievement, not what’s really important to you. And just as a focus on marginal costs can cause bad corporate decisions, it can lead people astray. The marginal cost of doing something wrong “just this once” always seems alluringly low. You don’t see the end result to which that path leads. The key is to define what you stand for and draw the line in a safe place.

Clayton M. Christensen is the Kim B. Clark Professor of Business Administration at Harvard Business School. He is the author of the book How Will You Measure Your Life?, which is based on this article.

How Will You Measure Your Life?

BEFORE I PUBLISHED The Innovator’s Dilemma, I got a call from Andrew Grove, then the chairman of Intel. He had read one of my early papers about disruptive technology, and he asked if I could talk to his direct reports and explain my research and what it implied for Intel. Excited, I flew to Silicon Valley and showed up at the appointed time, only to have Grove say, “Look, stuff has happened. We have only 10 minutes for you. Tell us what your model of disruption means for Intel.” I said that I couldn’t—that I needed a full 30 minutes to explain the model, because only with it as context would any comments about Intel make sense. Ten minutes into my explanation, Grove interrupted: “Look, I’ve got your model. Just tell us what it means for Intel.”

I insisted that I needed 10 more minutes to describe how the process of disruption had worked its way through a very different industry, steel, so that he and his team could understand how disruption worked. I told the story of how Nucor and other steel minimills had begun by attacking the lowest end of the market—steel reinforcing bars, or rebar—and later moved up toward the high end, undercutting the traditional steel mills.

When I finished the minimill story, Grove said, “OK, I get it. What it means for Intel is ...,” and then went on to articulate what would become the company’s strategy for going to the bottom of the market to launch the Celeron processor.

I’ve thought about that a million times since. If I had been suckered into telling Andy Grove what he should think about the microprocessor business, I’d have been killed. But instead of telling him what to think, I taught him how to think—and then he reached what I felt was the correct decision on his own.

That experience had a profound influence on me. When people ask what I think they should do, I rarely answer their question directly. Instead, I run the question aloud through one of my models. I’ll describe how the process in the model worked its way through an industry quite different from their own. And then, more often than not, they’ll say, “OK, I get it.” And they’ll answer their own question more insightfully than I could have.

My class at HBS is structured to help my students understand what good management theory is and how it is built. To that backbone I attach different models or theories that help students think about the various dimensions of a general manager’s job in stimulating innovation and growth. In each session we look at one company through the lenses of those theories—using them to explain how the company got into its situation and to examine what managerial actions will yield the needed results.

On the last day of class, I ask my students to turn those theoretical lenses on themselves, to find cogent answers to three questions: First, how can I be sure that I’ll be happy in my career? Second, how can I be sure that my relationships with my spouse and my family become an enduring source of happiness? Third, how can I be sure I’ll stay out of jail? Though the last question sounds lighthearted, it’s not. Two of the 32 people in my Rhodes scholar class spent time in jail. Jeff Skilling of Enron fame was a classmate of mine at HBS. These were good guys—but something in their lives sent them off in the wrong direction.

As the students discuss the answers to these questions, I open my own life to them as a case study of sorts, to illustrate how they can use the theories from our course to guide their life decisions.

One of the theories that gives great insight on the first question—how to be sure we find happiness in our careers—is from Frederick Herzberg, who asserts that the powerful motivator in our lives isn’t money; it’s the opportunity to learn, grow in responsibilities, contribute to others, and be recognized for achievements. I tell the students about a vision of sorts I had while I was running the company I founded before becoming an academic. In my mind’s eye I saw one of my managers leave for work one morning with a relatively strong level of self-esteem. Then I pictured her driving home to her family 10 hours later, feeling unappreciated, frustrated, underutilized, and demeaned. I imagined how profoundly her lowered self-esteem affected the way she interacted with her children. The vision in my mind then fast-forwarded to another day, when she drove home with greater self-esteem—feeling that she had learned a lot, been recognized for achieving valuable things, and played a significant role in the success of some important initiatives. I then imagined how positively that affected her as a spouse and a parent. My conclusion: Management is the most noble of professions if it’s practiced well. No other occupation offers as many ways to help others learn and grow, take responsibility and be recognized for achievement, and contribute to the success of a team. More and more MBA students come to school thinking that a career in business means buying, selling, and investing in companies. That’s unfortunate. Doing deals doesn’t yield the deep rewards that come from building up people.

I want students to leave my classroom knowing that.

Create a Strategy for Your Life

A theory that is helpful in answering the second question—How can I ensure that my relationship with my family proves to be an enduring source of happiness?—concerns how strategy is defined and implemented. Its primary insight is that a company’s strategy is determined by the types of initiatives that management invests in. If a company’s resource allocation process is not managed masterfully, what emerges from it can be very different from what management intended. Because companies’ decision-making systems are designed to steer investments to initiatives that offer the most tangible and immediate returns, companies shortchange investments in initiatives that are crucial to their long-term strategies.

Over the years I’ve watched the fates of my HBS classmates from 1979 unfold; I’ve seen more and more of them come to reunions unhappy, divorced, and alienated from their children. I can guarantee you that not a single one of them graduated with the deliberate strategy of getting divorced and raising children who would become estranged from them. And yet a shocking number of them implemented that strategy. The reason? They didn’t keep the purpose of their lives front and center as they decided how to spend their time, talents, and energy.

The Class of 2010

“I CAME TO BUSINESS SCHOOL knowing exactly what I wanted to do—and I’m leaving choosing the exact opposite. I’ve worked in the private sector all my life, because everyone always told me that’s where smart people are. But I’ve decided to try government and see if I can find more meaning there.

“I used to think that industry was very safe. The recession has shown us that nothing is safe.”

Ruhana Hafiz, Harvard Business School, Class of 2010

Her Plans: To join the FBI as a special adviser (a management track position)

“You could see a shift happening at HBS. Money used to be number one in the job search. When you make a ton of money, you want more of it. Ironic thing. You start to forget what the drivers of happiness are and what things are really important. A lot of people on campus see money differently now. They think, ‘What’s the minimum I need to have, and what else drives my life?’ instead of ‘What’s the place where I can get the maximum of both?’”

Patrick Chun, Harvard Business School, Class of 2010

His Plans: To join Bain Capital

“The financial crisis helped me realize that you have to do what you really love in life. My current vision of success is based on the impact I can have, the experiences I can gain, and the happiness I can find personally, much more so than the pursuit of money or prestige. My main motivations are (1) to be with my family and people I care about; (2) to do something fun, exciting, and impactful; and (3) to pursue a long-term career in entrepreneurship, where I can build companies that change the way the world works.”

Matt Salzberg, Harvard Business School, Class of 2010

His Plans: To work for Bessemer Venture Partners

“Because I’m returning to McKinsey, it probably seems like not all that much has changed for me. But while I was at HBS, I decided to do the dual degree at the Kennedy School. With the elections in 2008 and the economy looking shaky, it seemed more compelling for me to get a better understanding of the public and nonprofit sectors. In a way, that drove my return to McKinsey, where I’ll have the ability to explore private, public, and nonprofit sectors.

“The recession has made us step back and take stock of how lucky we are. The crisis to us is ‘Are we going to have a job by April?’ Crisis to a lot of people is ‘Are we going to stay in our home?’”

John Coleman, Harvard Business School, Class of 2010

His Plans: To return to McKinsey & Company

It’s quite startling that a significant fraction of the 900 students that HBS draws each year from the world’s best have given little thought to the purpose of their lives. I tell the students that HBS might be one of their last chances to reflect deeply on that question. If they think that they’ll have more time and energy to reflect later, they’re nuts, because life only gets more demanding: You take on a mortgage; you’re working 70 hours a week; you have a spouse and children.

For me, having a clear purpose in my life has been essential. But it was something I had to think long and hard about before I understood it. When I was a Rhodes scholar, I was in a very demanding academic program, trying to cram an extra year’s worth of work into my time at Oxford. I decided to spend an hour every night reading, thinking, and praying about why God put me on this earth. That was a very challenging commitment to keep, because every hour I spent doing that, I wasn’t studying applied econometrics. I was conflicted about whether I could really afford to take that time away from my studies, but I stuck with it—and ultimately figured out the purpose of my life.

Had I instead spent that hour each day learning the latest techniques for mastering the problems of autocorrelation in regression analysis, I would have badly misspent my life. I apply the tools of econometrics a few times a year, but I apply my knowledge of the purpose of my life every day. It’s the single most useful thing I’ve ever learned. I promise my students that if they take the time to figure out their life purpose, they’ll look back on it as the most important thing they discovered at HBS. If they don’t figure it out, they will just sail off without a rudder and get buffeted in the very rough seas of life. Clarity about their purpose will trump knowledge of activity-based costing, balanced scorecards, core competence, disruptive innovation, the four Ps, and the five forces.

My purpose grew out of my religious faith, but faith isn’t the only thing that gives people direction. For example, one of my former students decided that his purpose was to bring honesty and economic prosperity to his country and to raise children who were as capably committed to this cause, and to each other, as he was. His purpose is focused on family and others—as mine is.

The choice and successful pursuit of a profession is but one tool for achieving your purpose. But without a purpose, life can become hollow.

Allocate Your Resources

Your decisions about allocating your personal time, energy, and talent ultimately shape your life’s strategy.

I have a bunch of “businesses” that compete for these resources: I’m trying to have a rewarding relationship with my wife, raise great kids, contribute to my community, succeed in my career, contribute to my church, and so on. And I have exactly the same problem that a corporation does. I have a limited amount of time and energy and talent. How much do I devote to each of these pursuits?

Allocation choices can make your life turn out to be very different from what you intended. Sometimes that’s good: Opportunities that you never planned for emerge. But if you misinvest your resources, the outcome can be bad. As I think about my former classmates who inadvertently invested for lives of hollow unhappiness, I can’t help believing that their troubles relate right back to a short-term perspective.

When people who have a high need for achievement—and that includes all Harvard Business School graduates—have an extra half hour of time or an extra ounce of energy, they’ll unconsciously allocate it to activities that yield the most tangible accomplishments. And our careers provide the most concrete evidence that we’re moving forward. You ship a product, finish a design, complete a presentation, close a sale, teach a class, publish a paper, get paid, get promoted. In contrast, investing time and energy in your relationship with your spouse and children typically doesn’t offer that same immediate sense of achievement. Kids misbehave every day. It’s really not until 20 years down the road that you can put your hands on your hips and say, “I raised a good son or a good daughter.” You can neglect your relationship with your spouse, and on a day-to-day basis, it doesn’t seem as if things are deteriorating. People who are driven to excel have this unconscious propensity to underinvest in their families and overinvest in their careers—even though intimate and loving relationships with their families are the most powerful and enduring source of happiness.

If you study the root causes of business disasters, over and over you’ll find this predisposition toward endeavors that offer immediate gratification. If you look at personal lives through that lens, you’ll see the same stunning and sobering pattern: people allocating fewer and fewer resources to the things they would have once said mattered most.

Create a Culture

There’s an important model in our class called the Tools of Cooperation, which basically says that being a visionary manager isn’t all it’s cracked up to be. It’s one thing to see into the foggy future with acuity and chart the course corrections that the company must make. But it’s quite another to persuade employees who might not see the changes ahead to line up and work cooperatively to take the company in that new direction. Knowing what tools to wield to elicit the needed cooperation is a critical managerial skill.

The theory arrays these tools along two dimensions—the extent to which members of the organization agree on what they want from their participation in the enterprise, and the extent to which they agree on what actions will produce the desired results. When there is little agreement on both axes, you have to use “power tools”—coercion, threats, punishment, and so on—to secure cooperation. Many companies start in this quadrant, which is why the founding executive team must play such an assertive role in defining what must be done and how. If employees’ ways of working together to address those tasks succeed over and over, consensus begins to form. MIT’s Edgar Schein has described this process as the mechanism by which a culture is built. Ultimately, people don’t even think about whether their way of doing things yields success. They embrace priorities and follow procedures by instinct and assumption rather than by explicit decision—which means that they’ve created a culture. Culture, in compelling but unspoken ways, dictates the proven, acceptable methods by which members of the group address recurrent problems. And culture defines the priority given to different types of problems. It can be a powerful management tool.

In using this model to address the question, How can I be sure that my family becomes an enduring source of happiness?, my students quickly see that the simplest tools that parents can wield to elicit cooperation from children are power tools. But there comes a point during the teen years when power tools no longer work. At that point parents start wishing that they had begun working with their children at a very young age to build a culture at home in which children instinctively behave respectfully toward one another, obey their parents, and choose the right thing to do. Families have cultures, just as companies do. Those cultures can be built consciously or evolve inadvertently.

If you want your kids to have strong self-esteem and confidence that they can solve hard problems, those qualities won’t magically materialize in high school. You have to design them into your family’s culture—and you have to think about this very early on. Like employees, children build self-esteem by doing things that are hard and learning what works.

Avoid the “Marginal Costs” Mistake

We’re taught in finance and economics that in evaluating alternative investments, we should ignore sunk and fixed costs, and instead base decisions on the marginal costs and marginal revenues that each alternative entails. We learn in our course that this doctrine biases companies to leverage what they have put in place to succeed in the past, instead of guiding them to create the capabilities they’ll need in the future. If we knew the future would be exactly the same as the past, that approach would be fine. But if the future’s different—and it almost always is—then it’s the wrong thing to do.

This theory addresses the third question I discuss with my students—how to live a life of integrity (stay out of jail). Unconsciously, we often employ the marginal cost doctrine in our personal lives when we choose between right and wrong. A voice in our head says, “Look, I know that as a general rule, most people shouldn’t do this. But in this particular extenuating circumstance, just this once, it’s OK.” The marginal cost of doing something wrong “just this once” always seems alluringly low. It suckers you in, and you don’t ever look at where that path ultimately is headed and at the full costs that the choice entails. Justification for infidelity and dishonesty in all their manifestations lies in the marginal cost economics of “just this once.”

I’d like to share a story about how I came to understand the potential damage of “just this once” in my own life. I played on the Oxford University varsity basketball team. We worked our tails off and finished the season undefeated. The guys on the team were the best friends I’ve ever had in my life. We got to the British equivalent of the NCAA tournament—and made it to the final four. It turned out the championship game was scheduled to be played on a Sunday. I had made a personal commitment to God at age 16 that I would never play ball on Sunday. So I went to the coach and explained my problem. He was incredulous. My teammates were, too, because I was the starting center. Every one of the guys on the team came to me and said, “You’ve got to play. Can’t you break the rule just this one time?”

I’m a deeply religious man, so I went away and prayed about what I should do. I got a very clear feeling that I shouldn’t break my commitment—so I didn’t play in the championship game.

In many ways that was a small decision—involving one of several thousand Sundays in my life. In theory, surely I could have crossed over the line just that one time and then not done it again. But looking back on it, resisting the temptation whose logic was “In this extenuating circumstance, just this once, it’s OK” has proven to be one of the most important decisions of my life. Why? My life has been one unending stream of extenuating circumstances. Had I crossed the line that one time, I would have done it over and over in the years that followed.

The lesson I learned from this is that it’s easier to hold to your principles 100% of the time than it is to hold to them 98% of the time. If you give in to “just this once,” based on a marginal cost analysis, as some of my former classmates have done, you’ll regret where you end up. You’ve got to define for yourself what you stand for and draw the line in a safe place.

Remember the Importance of Humility

I got this insight when I was asked to teach a class on humility at Harvard College. I asked all the students to describe the most humble person they knew. One characteristic of these humble people stood out: They had a high level of self-esteem. They knew who they were, and they felt good about who they were. We also decided that humility was defined not by self-deprecating behavior or attitudes but by the esteem with which you regard others. Good behavior flows naturally from that kind of humility. For example, you would never steal from someone, because you respect that person too much. You’d never lie to someone, either.

It’s crucial to take a sense of humility into the world. By the time you make it to a top graduate school, almost all your learning has come from people who are smarter and more experienced than you: parents, teachers, bosses. But once you’ve finished at Harvard Business School or any other top academic institution, the vast majority of people you’ll interact with on a day-to-day basis may not be smarter than you. And if your attitude is that only smarter people have something to teach you, your learning opportunities will be very limited. But if you have a humble eagerness to learn something from everybody, your learning opportunities will be unlimited. Generally, you can be humble only if you feel really good about yourself—and you want to help those around you feel really good about themselves, too. When we see people acting in an abusive, arrogant, or demeaning manner toward others, their behavior almost always is a symptom of their lack of self-esteem. They need to put someone else down to feel good about themselves.

Choose the Right Yardstick

This past year I was diagnosed with cancer and faced the possibility that my life would end sooner than I’d planned. Thankfully, it now looks as if I’ll be spared. But the experience has given me important insight into my life.

I have a pretty clear idea of how my ideas have generated enormous revenue for companies that have used my research; I know I’ve had a substantial impact. But as I’ve confronted this disease, it’s been interesting to see how unimportant that impact is to me now. I’ve concluded that the metric by which God will assess my life isn’t dollars but the individual people whose lives I’ve touched.

I think that’s the way it will work for us all. Don’t worry about the level of individual prominence you have achieved; worry about the individuals you have helped become better people. This is my final recommendation: Think about the metric by which your life will be judged, and make a resolution to live every day so that in the end, your life will be judged a success.

Originally published in July 2010. Reprint R1007B

The Innovator's Dilemma:

When New Technologies Cause Great Firms to Fail

Clayton M. Christensen

Harvard Business Review Press

Boston, Massachusetts

Copyright

Copyright © 1997 by the President and Fellows of Harvard College

All rights reserved

First eBook Edition: January 1997

ISBN: 978-0-875-84585-2

THE MANAGEMENT OF INNOVATION AND CHANGE SERIES

Michael L. Tushman and Andrew H. Van de Ven, Series Editors

Emerging Patterns of Innovation: Sources of Japan’s Technological Edge

Fumio Kodama, with a Foreword by Lewis M. Branscomb

Crisis Renewal: Meeting the Challenge of Organizational Change

David K. Hurst

Winning through Innovation: A Practical Guide to Leading Organizational

Change and Renewal

Michael L. Tushman

Charles A. O’Reilly III

Imitation to Innovation: The Dynamics of Korea’s Technological Learning

Linsu Kim

The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail

Clayton M. Christensen

Contents

Copyright

In Gratitude

Introduction

PART ONE: WHY GREAT COMPANIES CAN FAIL

1 How Can Great Firms Fail? Insights from the Hard Disk Drive Industry

2 Value Networks and the Impetus to Innovate

3 Disruptive Technological Change in the Mechanical Excavator Industry

4 What Goes Up, Can’t Go Down

PART TWO: MANAGING DISRUPTIVE TECHNOLOGICAL CHANGE

5 Give Responsibility for Disruptive Technologies to Organizations Whose Customers Need Them

6 Match the Size of the Organization to the Size of the Market

7 Discovering New and Emerging Markets

8 How to Appraise Your Organization’s Capabilities and Disabilities

9 Performance Provided, Market Demand, and the Product Life Cycle

10 Managing Disruptive Technological Change: A Case Study

11 The Dilemmas of Innovation: A Summary

The Innovator’s Dilemma Book Group Guide

About the Author

In Gratitude

Although this book lists only one author, in reality the ideas it molds together were contributed and refined by many extraordinarily insightful and selfless colleagues. The work began when Professors Kim Clark, Joseph Bower, Jay Light, and John McArthur took the risk of admitting and financing a middle-aged man’s way into and through the Harvard Business School’s doctoral program in 1989. In addition to these mentors, Professors Richard Rosenbloom, Howard Stevenson, Dorothy Leonard, Richard Walton, Bob Hayes, Steve Wheelwright, and Kent Bowen helped throughout my doctoral research to keep my thinking sharp and my standards for evidence high, and to embed what I was learning within the streams of strong scholarship that had preceded what I was attempting to research. None of these professors needed to spend so much of their busy lives guiding me as they did, and I will be forever grateful for what they taught me about the substance and process of scholarship.

I am similarly indebted to the many executives and employees of companies in the disk drive industry who opened their memories and records to me as I tried to understand what had driven them in the particular courses they had taken. In particular, James Porter, editor of Disk/Trend Report, opened his extraordinary archives of data, enabling me to measure what has happened in the disk drive industry with a level of completeness and accuracy that could be done in few other settings. The model of the industry’s evolution and revolution that these men and women helped me construct has formed the theoretical backbone for this book. I hope they find it to be a useful tool for making sense of their past, and a helpful guide for some of their decisions in the future.

During my tenure on the Harvard Business School faculty, other colleagues have helped refine this book’s ideas even more. Professors Rebecca Henderson and James Utterback of MIT, Robert Burgelman of Stanford, and David Garvin, Gary Pisano, and Marco Iansiti of the Harvard Business School have been particularly helpful. Research associates Rebecca Voorheis, Greg Rogers, Bret Baird, Jeremy Dann, Tara Donovan, and Michael Overdorf; editors Marjorie Williams, Steve Prokesch, and Barbara Feinberg; and assistants Cheryl Druckenmiller, Meredith Anderson, and Marguerite Dole, have likewise contributed untold amounts of data, advice, insight, and work.

I am grateful to my students, with whom I have discussed and refined the ideas put forward in this book. On most days I leave class wondering why I get paid and why my students pay tuition, given that it is I who have learned the most from our interactions. Every year they leave our school with their degrees and scatter around the world, without understanding how much they have taught their teachers. I love them and hope that those who come across this book will be able to recognize in it the fruits of their puzzled looks, questions, comments, and criticisms.

My deepest gratitude is to my family—my wife Christine and our children Matthew, Ann, Michael, Spencer, and Catherine. With unhesitating faith and support they encouraged me to pursue my lifelong dream to be a teacher, amidst all of the demands of family life. Doing this research on disruptive technologies has indeed been disruptive to them in terms of time and absence from home, and I am forever grateful for their love and support. Christine, in particular, is the smartest and most patient person I have known. Most of the ideas in this book went home on some night over the past five years in half-baked condition and returned to Harvard the next morning having been clarified, shaped, and edited through my conversations with her. She is a great colleague, supporter, and friend. I dedicate this book to her and our children.

Clayton M. Christensen

Harvard Business School

Boston, Massachusetts

April 1997

Introduction

This book is about the failure of companies to stay atop their industries when they confront certain types of market and technological change. It’s not about the failure of simply any company, but of good companies—the kinds that many managers have admired and tried to emulate, the companies known for their abilities to innovate and execute. Companies stumble for many reasons, of course, among them bureaucracy, arrogance, tired executive blood, poor planning, short-term investment horizons, inadequate skills and resources, and just plain bad luck. But this book is not about companies with such weaknesses: It is about well-managed companies that have their competitive antennae up, listen astutely to their customers, invest aggressively in new technologies, and yet still lose market dominance.

Such seemingly unaccountable failures happen in industries that move fast and in those that move slow; in those built on electronics technology and those built on chemical and mechanical technology; in manufacturing and in service industries. Sears Roebuck, for example, was regarded for decades as one of the most astutely managed retailers in the world. At its zenith Sears accounted for more than 2 percent of all retail sales in the United States. It pioneered several innovations critical to the success of today’s most admired retailers: for example, supply chain management, store brands, catalogue retailing, and credit card sales. The esteem in which Sears’ management was held shows in this 1964 excerpt from Fortune: “How did Sears do it? In a way, the most arresting aspect of its story is that there was no gimmick. Sears opened no big bag of tricks, shot off no skyrockets. Instead, it looked as though everybody in its organization simply did the right thing, easily and naturally. And their cumulative effect was to create an extraordinary powerhouse of a company.” [1]

Yet no one speaks about Sears that way today. Somehow, it completely missed the advent of discount retailing and home centers. In the midst of today’s catalogue retailing boom, Sears has been driven from that business. Indeed, the very viability of its retailing operations has been questioned. One commentator has noted that “Sears’ Merchandise Group lost $1.3 billion (in 1992) even before a $1.7 billion restructuring charge. Sears let arrogance blind it to basic changes taking place in the American marketplace.” [2] Another writer has complained,

Sears has been a disappointment for investors who have watched its stock sink dismally in the face of unkept promises of a turnaround. Sears’ old merchandising approach—a vast, middle-of-the-road array of mid-priced goods and services—is no longer competitive. No question, the constant disappointments, the repeated predictions of a turnaround that never seems to come, have reduced the credibility of Sears’ management in both the financial and merchandising communities. [3]

It is striking to note that Sears received its accolades at exactly the time—in the mid-1960s—when it was ignoring the rise of discount retailing and home centers, the lower-cost formats for marketing name-brand hard goods that ultimately stripped Sears of its core franchise. Sears was praised as one of the best-managed companies in the world at the very time it let Visa and MasterCard usurp the enormous lead it had established in the use of credit cards in retailing.

In some industries this pattern of leadership failure has been repeated more than once. Consider the computer industry. IBM dominated the mainframe market but missed by years the emergence of minicomputers, which were technologically much simpler than mainframes. In fact, no other major manufacturer of mainframe computers became a significant player in the minicomputer business. Digital Equipment Corporation created the minicomputer market and was joined by a set of other aggressively managed companies: Data General, Prime, Wang, Hewlett-Packard, and Nixdorf. But each of these companies in turn missed the desktop personal computer market. It was left to Apple Computer, together with Commodore, Tandy, and IBM’s stand-alone PC division, to create the personal-computing market. Apple, in particular, was uniquely innovative in establishing the standard for user-friendly computing. But Apple and IBM lagged five years behind the leaders in bringing portable computers to market. Similarly, the firms that built the engineering workstation market—Apollo, Sun, and Silicon Graphics—were all newcomers to the industry.

As in retailing, many of these leading computer manufacturers were at one time regarded as among the best-managed companies in the world and were held up by journalists and scholars of management as examples for all to follow. Consider this assessment of Digital Equipment, made in 1986: “Taking on Digital Equipment Corp. these days is like standing in front of a moving train. The $7.6 billion computer maker has been gathering speed while most rivals are stalled in a slump in the computer industry.” [4] The author proceeded to warn IBM to watch out, because it was standing on the tracks. Indeed, Digital was one of the most prominently featured companies in the McKinsey study that led to the book In Search of Excellence.[5]

Yet a few years later, writers characterized DEC quite differently:

Digital Equipment Corporation is a company in need of triage. Sales are drying up in its key minicomputer line. A two-year-old restructuring plan has failed miserably. Forecasting and production planning systems have failed miserably. Cost-cutting hasn’t come close to restoring profitability…. But the real misfortune may be DEC’s lost opportunities. It has squandered two years trying halfway measures to respond to the low-margin personal computers and workstations that have transformed the computer industry. [6]

In Digital’s case, as in Sears, the very decisions that led to its decline were made at the time it was so widely regarded as being an astutely managed firm. It was praised as a paragon of managerial excellence at the very time it was ignoring the arrival of the desktop computers that besieged it a few years later.

Sears and Digital are in noteworthy company. Xerox long dominated the market for plain paper photocopiers used in large, high-volume copying centers. Yet it missed huge growth and profit opportunities in the market for small tabletop photocopiers, where it became only a minor player. Although steel minimills have now captured 40 percent of the North American steel market, including nearly all of the region’s markets for bars, rods, and structural steel, not a single integrated steel company— American, Asian, or European—had by 1995 built a plant using minimill technology. Of the thirty manufacturers of cable-actuated power shovels, only four survived the industry’s twenty-five-year transition to hydraulic excavation technology.

As we shall see, the list of leading companies that failed when confronted with disruptive changes in technology and market structure is a long one. At first glance, there seems to be no pattern in the changes that overtook them. In some cases the new technologies swept through quickly; in others, the transition took decades. In some, the new technologies were complex and expensive to develop. In others, the deadly technologies were simple extensions of what the leading companies already did better than anyone else. One theme common to all of these failures, however, is that the decisions that led to failure were made when the leaders in question were widely regarded as among the best companies in the world.

There are two ways to resolve this paradox. One might be to conclude that firms such as Digital, IBM, Apple, Sears, Xerox, and Bucyrus Erie must never have been well managed. Maybe they were successful because of good luck and fortuitous timing, rather than good management. Maybe they finally fell on hard times because their good fortune ran out. Maybe. An alternative explanation, however, is that these failed firms were as well-run as one could expect a firm managed by mortals to be—but that there is something about the way decisions get made in successful organizations that sows the seeds of eventual failure.

The research reported in this book supports this latter view: It shows that in the cases of well-managed firms such as those cited above, good management was the most powerful reason they failed to stay atop their industries. Precisely because these firms listened to their customers, invested aggressively in new technologies that would provide their customers more and better products of the sort they wanted, and because they carefully studied market trends and systematically allocated investment capital to innovations that promised the best returns, they lost their positions of leadership.

What this implies at a deeper level is that many of what are now widely accepted principles of good management are, in fact, only situationally appropriate. There are times at which it is right not to listen to customers, right to invest in developing lower-performance products that promise lower margins, and right to aggressively pursue small, rather than substantial, markets. This book derives a set of rules, from carefully designed research and analysis of innovative successes and failures in the disk drive and other industries, that managers can use to judge when the widely accepted principles of good management should be followed and when alternative principles are appropriate.

These rules, which I call principles of disruptive innovation, show that when good companies fail, it often has been because their managers either ignored these principles or chose to fight them. Managers can be extraordinarily effective in managing even the most difficult innovations if they work to understand and harness the principles of disruptive innovation. As in many of life’s most challenging endeavors, there is great value in coming to grips with “the way the world works,” and in managing innovative efforts in ways that accommodate such forces.

The Innovator’s Dilemma is intended to help a wide range of managers, consultants, and academics in manufacturing and service businesses—high tech or low—in slowly evolving or rapidly changing environments. Given that aim, technology, as used in this book, means the processes by which an organization transforms labor, capital, materials, and information into products and services of greater value. All firms have technologies. A retailer like Sears employs a particular technology to procure, present, sell, and deliver products to its customers, while a discount warehouse retailer like PriceCostco employs a different technology. This concept of technology therefore extends beyond engineering and manufacturing to encompass a range of marketing, investment, and managerial processes. Innovation refers to a change in one of these technologies.

THE DILEMMA

To establish the theoretical depth of the ideas in this book, the breadth of their usefulness, and their applicability to the future as well as the past, I have divided this book into two parts. Part One, chapters 1 through 4, builds a framework that explains why sound decisions by great managers can lead firms to failure. The picture these chapters paint is truly that of an innovator’s dilemma: the logical, competent decisions of management that are critical to the success of their companies are also the reasons why they lose their positions of leadership. Part Two, chapters 5 through 10, works to resolve the dilemma. Building on our understanding of why and under what circumstances new technologies have caused great firms to fail, it prescribes managerial solutions to the dilemma—how executives can simultaneously do what is right for the near-term health of their established businesses, while focusing adequate resources on the disruptive technologies that ultimately could lead to their downfall.

Building a Failure Framework

I begin this book by digging deep before extending the discussion to draw general conclusions. The first two chapters recount in some detail the history of the disk drive industry, where the saga of “good-companies-hitting-hard-times” has been played out over and over again. This industry is an ideal field for studying failure because rich data about it exist and because, in the words of Harvard Business School Dean Kim B. Clark, it is “fast history.” In just a few years, market segments, companies, and technologies have emerged, matured, and declined. Only twice in the six times that new architectural technologies have emerged in this field has the industry’s dominant firm maintained its lead in the subsequent generation. This repetitive pattern of failure in the disk drive industry allowed me first to develop a preliminary framework that explained why the best and largest firms in the early generations of this industry failed and then to test this framework across subsequent cycles in the industry’s history to see whether it was robust enough to continue to explain failures among the industry’s more recent leaders.

Chapters 3 and 4 then deepen our understanding of why the leading firms stumbled repeatedly in the disk drive industry and, simultaneously, test the breadth of the framework’s usefulness by examining the failure of firms in industries with very different characteristics. Hence, chapter 3, exploring the mechanical excavator industry, finds that the same factors that precipitated the failure of the leading disk drive makers also proved to be the undoing of the leading makers of mechanical excavators, in an industry that moves with a very different pace and technological intensity. Chapter 4 completes the framework and uses it to show why integrated steel companies worldwide have proven so incapable of blunting the attacks of the minimill steel makers.

WHY GOOD MANAGEMENT CAN LEAD TO FAILURE

The failure framework is built upon three findings from this study. The first is that there is a strategically important distinction between what I call sustaining technologies and those that are disruptive. These concepts are very different from the incremental-versus-radical distinction that has characterized many studies of this problem. Second, the pace of technological progress can, and often does, outstrip what markets need. This means that the relevance and competitiveness of different technological approaches can change with respect to different markets over time. And third, customers and financial structures of successful companies color heavily the sorts of investments that appear to be attractive to them, relative to certain types of entering firms.

Sustaining versus Disruptive Technologies

Most new technologies foster improved product performance. I call these sustaining technologies. Some sustaining technologies can be discontinuous or radical in character, while others are of an incremental nature. What all sustaining technologies have in common is that they improve the performance of established products, along the dimensions of performance that mainstream customers in major markets have historically valued. Most technological advances in a given industry are sustaining in character. An important finding revealed in this book is that rarely have even the most radically difficult sustaining technologies precipitated the failure of leading firms.

Occasionally, however, disruptive technologies emerge: innovations that result in worse product performance, at least in the near-term. Ironically, in each of the instances studied in this book, it was disruptive technology that precipitated the leading firms’ failure.

Disruptive technologies bring to a market a very different value proposition than had been available previously. Generally, disruptive technologies underperform established products in mainstream markets. But they have other features that a few fringe (and generally new) customers value. Products based on disruptive technologies are typically cheaper, simpler, smaller, and, frequently, more convenient to use. There are many examples in addition to the personal desktop computer and discount retailing examples cited above. Small off-road motorcycles introduced in North America and Europe by Honda, Kawasaki, and Yamaha were disruptive technologies relative to the powerful, over-the-road cycles made by Harley-Davidson and BMW. Transistors were disruptive technologies relative to vacuum tubes. Health maintenance organizations were disruptive technologies to conventional health insurers. In the near future, “internet appliances” may become disruptive technologies to suppliers of personal computer hardware and software.

Trajectories of Market Need versus Technology Improvement

The second element of the failure framework, the observation that technologies can progress faster than market demand, illustrated in Figure I.1, means that in their efforts to provide better products than their competitors and earn higher prices and margins, suppliers often “overshoot” their market: They give customers more than they need or ultimately are willing to pay for. And more importantly, it means that disruptive technologies that may underperform today, relative to what users in the market demand, may be fully performance-competitive in that same market tomorrow.

Many who once needed mainframe computers for their data processing requirements, for example, no longer need or buy mainframes. Mainframe performance has surpassed the requirements of many original customers, who today find that much of what they need to do can be done on desktop machines linked to file servers. In other words, the needs of many computer users have increased more slowly than the rate of improvement provided by computer designers. Similarly, many shoppers who in 1965 felt they had to shop at department stores to be assured of quality and selection now satisfy those needs quite well at Target and Wal-Mart.

Figure I.1 The Impact of Sustaining and Disruptive Technological Change

Disruptive Technologies versus Rational Investments

The last element of the failure framework, the conclusion by established companies that investing aggressively in disruptive technologies is not a rational financial decision for them to make, has three bases. First, disruptive products are simpler and cheaper; they generally promise lower margins, not greater profits. Second, disruptive technologies typically are first commercialized in emerging or insignificant markets. And third, leading firms’ most profitable customers generally don’t want, and indeed initially can’t use, products based on disruptive technologies. By and large, a disruptive technology is initially embraced by the least profitable customers in a market. Hence, most companies with a practiced discipline of listening to their best customers and identifying new products that promise greater profitability and growth are rarely able to build a case for investing in disruptive technologies until it is too late.

TESTING THE FAILURE FRAMEWORK

This book defines the problem of disruptive technologies and describes how they can be managed, taking care to establish what researchers call the internal and external validity of its propositions. Chapters 1 and 2 develop the failure framework in the context of the disk drive industry, and the initial pages of chapters 4 through 8 return to that industry to build a progressively deeper understanding of why disruptive technologies are such vexatious phenomena for good managers to confront successfully. The reason for painting such a complete picture of a single industry is to establish the internal validity of the failure framework. If a framework or model cannot reliably explain what happened within a single industry, it cannot be applied to other situations with confidence.

Chapter 3 and the latter sections of chapters 4 through 9 are structured to explore the external validity of the failure framework—the conditions in which we might expect the framework to yield useful insights. Chapter 3 uses the framework to examine why the leading makers of cable excavators were driven from the earthmoving market by makers of hydraulic machines, and chapter 4 discusses why the world’s integrated steel makers have floundered in the face of minimill technology. Chapter 5 uses the model to examine the success of discount retailers, relative to conventional chain and department stores, and to probe the impact of disruptive technologies in the motor control and printer industries. Chapter 6 examines the emerging personal digital assistant industry and reviews how the electric motor control industry was upended by disruptive technology. Chapter 7 recounts how entrants using disruptive technologies in motorcycles and logic circuitry dethroned industry leaders; chapter 8 shows how and why computer makers fell victim to disruption; and chapter 9 spotlights the same phenomena in the accounting software and insulin businesses. Chapter 10 applies the framework to a case study of the electric vehicle, summarizing the lessons learned from the other industry studies, showing how they can be used to assess the opportunity and threat of electric vehicles, and describing how they might be applied to make an electric vehicle commercially successful. Chapter 11 summarizes the book’s findings.

Taken in sum, these chapters present a theoretically strong, broadly valid, and managerially practical framework for understanding disruptive technologies and how they have precipitated the fall from industry leadership of some of history’s best-managed companies.

HARNESSING THE PRINCIPLES OF DISRUPTIVE INNOVATION

Colleagues who have read my academic papers reporting the findings recounted in chapters 1 through 4 were struck by their near-fatalism. If good management practice drives the failure of successful firms faced with disruptive technological change, then the usual answers to companies’ problems—planning better, working harder, becoming more customer-driven, and taking a longer-term perspective—all exacerbate the problem. Sound execution, speed-to-market, total quality management, and process reengineering are similarly ineffective. Needless to say, this is disquieting news to people who teach future managers!

Chapters 5 through 10, however, suggest that although the solution to disruptive technologies cannot be found in the standard tool kit of good management, there are, in fact, sensible ways to deal effectively with this challenge. Every company in every industry works under certain forces—laws of organizational nature—that act powerfully to define what that company can and cannot do. Managers faced with disruptive technologies fail their companies when these forces overpower them.

By analogy, the ancients who attempted to fly by strapping feathered wings to their arms and flapping with all their might as they leapt from high places invariably failed. Despite their dreams and hard work, they were fighting against some very powerful forces of nature. No one could be strong enough to win this fight. Flight became possible only after people came to understand the relevant natural laws and principles that defined how the world worked: the law of gravity, Bernoulli’s principle, and the concepts of lift, drag, and resistance. When people then designed flying systems that recognized or harnessed the power of these laws and principles, rather than fighting them, they were finally able to fly to heights and distances that were previously unimaginable.

The objective of chapters 5 through 10 is to propose the existence of five laws or principles of disruptive technology. As in the analogy with manned flight, these laws are so strong that managers who ignore or fight them are nearly powerless to pilot their companies through a disruptive technology storm. These chapters show, however, that if managers can understand and harness these forces, rather than fight them, they can in fact succeed spectacularly when confronted with disruptive technological change. I am particularly anxious that managers read these chapters for understanding, rather than for simple answers. I am very confident that the great managers about whom this book is written will be very capable on their own of finding the answers that best fit their circumstances. But they must first understand what has caused those circumstances and what forces will affect the feasibility of their solutions. The following paragraphs summarize these principles and what managers can do to harness or accommodate them.

Principle #1: Companies Depend on Customers and Investors for Resources

The history of the disk drive industry shows that the established firms stayed atop wave after wave of sustaining technologies (technologies that their customers needed), while consistently stumbling over simpler disruptive ones. This evidence supports the theory of resource dependence.[7] Chapter 5 summarizes this theory, which states that while managers may think they control the flow of resources in their firms, in the end it is really customers and investors who dictate how money will be spent because companies with investment patterns that don’t satisfy their customers and investors don’t survive. The highest-performing companies, in fact, are those that are the best at this, that is, they have well-developed systems for killing ideas that their customers don’t want. As a result, these companies find it very difficult to invest adequate resources in disruptive technologies—lower-margin opportunities that their customers don’t want—until their customers want them. And by then it is too late.

Chapter 5 suggests a way for managers to align or harness this law with their efforts to confront disruptive technology. With few exceptions, the only instances in which mainstream firms have successfully established a timely position in a disruptive technology were those in which the firms’ managers set up an autonomous organization charged with building a new and independent business around the disruptive technology. Such organizations, free of the power of the customers of the mainstream company, ensconce themselves among a different set of customers—those who want the products of the disruptive technology. In other words, companies can succeed in disruptive technologies when their managers align their organizations with the forces of resource dependence, rather than ignoring or fighting them.

The implication of this principle for managers is that, when faced with a threatening disruptive technology, people and processes in a mainstream organization cannot be expected to allocate freely the critical financial and human resources needed to carve out a strong position in the small, emerging market. It is very difficult for a company whose cost structure is tailored to compete in high-end markets to be profitable in low-end markets as well. Creating an independent organization, with a cost structure honed to achieve profitability at the low margins characteristic of most disruptive technologies, is the only viable way for established firms to harness this principle.

Principle #2: Small Markets Don’t Solve the Growth Needs of Large Companies

Disruptive technologies typically enable new markets to emerge. There is strong evidence showing that companies entering these emerging markets early have significant first-mover advantages over later entrants. And yet, as these companies succeed and grow larger, it becomes progressively more difficult for them to enter the even newer small markets destined to become the large ones of the future.

To maintain their share prices and create internal opportunities for employees to extend the scope of their responsibilities, successful companies need to continue to grow. But while a $40 million company needs to find just $8 million in revenues to grow at 20 percent in the subsequent year, a $4 billion company needs to find $800 million in new sales. No new markets are that large. As a consequence, the larger and more successful an organization becomes, the weaker the argument that emerging markets can remain useful engines for growth.

Many large companies adopt a strategy of waiting until new markets are “large enough to be interesting.” But the evidence presented in chapter 6 shows why this is not often a successful strategy.

Those large established firms that have successfully seized strong positions in the new markets enabled by disruptive technologies have done so by giving responsibility to commercialize the disruptive technology to an organization whose size matched the size of the targeted market. Small organizations can most easily respond to the opportunities for growth in a small market. The evidence is strong that formal and informal resource allocation processes make it very difficult for large organizations to focus adequate energy and talent on small markets, even when logic says they might be big someday.

Principle #3: Markets that Don’t Exist Can’t Be Analyzed

Sound market research and good planning followed by execution according to plan are hallmarks of good management. When applied to sustaining technological innovation, these practices are invaluable; they are the primary reason, in fact, why established firms led in every single instance of sustaining innovation in the history of the disk drive industry. Such reasoned approaches are feasible in dealing with sustaining technology because the size and growth rates of the markets are generally known, trajectories of technological progress have been established, and the needs of leading customers have usually been well articulated. Because the vast majority of innovations are sustaining in character, most executives have learned to manage innovation in a sustaining context, where analysis and planning were feasible.

In dealing with disruptive technologies leading to new markets, however, market researchers and business planners have consistently dismal records. In fact, based upon the evidence from the disk drive, motorcycle, and microprocessor industries, reviewed in chapter 7, the only thing we may know for sure when we read experts’ forecasts about how large emerging markets will become is that they are wrong.

In many instances, leadership in sustaining innovations—about which information is known and for which plans can be made—is not competitively important. In such cases, technology followers do about as well as technology leaders. It is in disruptive innovations, where we know least about the market, that there are such strong first-mover advantages. This is the innovator’s dilemma.

Companies whose investment processes demand quantification of market sizes and financial returns before they can enter a market get paralyzed or make serious mistakes when faced with disruptive technologies. They demand market data when none exists and make judgments based upon financial projections when neither revenues or costs can, in fact, be known. Using planning and marketing techniques that were developed to manage sustaining technologies in the very different context of disruptive ones is an exercise in flapping wings.

Chapter 7 discusses a different approach to strategy and planning that recognizes the law that the right markets, and the right strategy for exploiting them, cannot be known in advance. Called discovery-based planning, it suggests that managers assume that forecasts are wrong, rather than right, and that the strategy they have chosen to pursue may likewise be wrong. Investing and managing under such assumptions drives managers to develop plans for learning what needs to be known, a much more effective way to confront disruptive technologies successfully.

Principle #4: An Organization’s Capabilities Define Its Disabilities

When managers tackle an innovation problem, they instinctively work to assign capable people to the job. But once they’ve found the right people, too many managers then assume that the organization in which they’ll work will also be capable of succeeding at the task. And that is dangerous—because organizations have capabilities that exist independently of the people who work within them. An organization’s capabilities reside in two places. The first is in its processes—the methods by which people have learned to transform inputs of labor, energy, materials, information, cash, and technology into outputs of higher value. The second is in the organization’s values, which are the criteria that managers and employees in the organization use when making prioritization decisions. People are quite flexible, in that they can be trained to succeed at quite different things. An employee of IBM, for example, can quite readily change the way he or she works, in order to work successfully in a small start-up company. But processes and values are not flexible. A process that is effective at managing the design of a minicomputer, for example, would be ineffective at managing the design of a desktop personal computer. Similarly, values that cause employees to prioritize projects to develop high-margin products, cannot simultaneously accord priority to low-margin products. The very processes and values that constitute an organization’s capabilities in one context, define its disabilities in another context.

Chapter 8 will present a framework that can help a manager understand precisely where in his or her organization its capabilities and disabilities reside. Drawing on studies in the disk drive and computer industries, it offers tools that managers can use to create new capabilities, when the processes and values of the present organization would render it incapable of successfully addressing a new problem.

Principle #5: Technology Supply May Not Equal Market Demand

Disruptive technologies, though they initially can only be used in small markets remote from the mainstream, are disruptive because they subsequently can become fully performance-competitive within the mainstream market against established products. As depicted in Figure I.1 (on page xvi), this happens because the pace of technological progress in products frequently exceeds the rate of performance improvement that mainstream customers demand or can absorb. As a consequence, products whose features and functionality closely match market needs today often follow a trajectory of improvement by which they overshoot mainstream market needs tomorrow. And products that seriously underperform today, relative to customer expectations in mainstream markets, may become directly performance-competitive tomorrow.

Chapter 9 shows that when this happens, in markets as diverse as disk drives, accounting software, and diabetes care, the basis of competition— the criteria by which customers choose one product over another— changes. When the performance of two or more competing products has improved beyond what the market demands, customers can no longer base their choice upon which is the higher performing product. The basis of product choice often evolves from functionality to reliability, then to convenience, and, ultimately, to price.

Many students of business have described phases of the product life cycle in various ways. But chapter 9 proposes that the phenomenon in which product performance overshoots market demands is the primary mechanism driving shifts in the phases of the product life cycle.

In their efforts to stay ahead by developing competitively superior products, many companies don’t realize the speed at which they are moving up-market, over-satisfying the needs of their original customers as they race the competition toward higher-performance, higher-margin markets. In doing so, they create a vacuum at lower price points into which competitors employing disruptive technologies can enter. Only those companies that carefully measure trends in how their mainstream customers use their products can catch the points at which the basis of competition will change in the markets they serve.

LESSONS FOR SPOTTING DISRUPTIVE THREATS AND OPPORTUNITIES

Some managers and researchers familiar with these ideas have arrived at this point in the story in an anxious state because the evidence is very strong that even the best managers have stumbled badly when their markets were invaded by disruptive technologies. Most urgently, they want to know whether their own businesses are targets for an attacking disruptive technologist and how they can defend their business against such an attack before it is too late. Others, interested in finding entrepreneurial opportunities, wonder how they can identify potentially disruptive technologies around which new companies and markets can be built.

Chapter 10 addresses these questions in a rather unconventional way. Rather than offering a checklist of questions to ask or analyses to perform, it creates a case study of a particularly vexing but well-known problem in technological innovation: the electric vehicle. Positioning myself in the role of protagonist—as the program manager responsible for electric vehicle development in a major automobile manufacturing company wrestling with the mandate of the California Air Resources Board to begin selling electric vehicles in that state—I explore the question of whether electric vehicles are in fact a disruptive technology and then suggest ways to organize this program, set its strategy, and manage it to succeed. In the spirit of all case studies, the purpose of this chapter is not to advance what I believe to be the correct answer to this innovator’s challenge. Rather, it suggests a methodology and a way of thinking about the problem of managing disruptive technological change that should prove useful in many other contexts.

Chapter 10 thus takes us deeply into the innovator’s dilemma that “good” companies often begin their descent into failure by aggressively investing in the products and services that their most profitable customers want. No automotive company is currently threatened by electric cars, and none contemplates a wholesale leap into that arena. The automobile industry is healthy. Gasoline engines have never been more reliable. Never before has such high performance and quality been available at such low prices. Indeed, aside from governmental mandates, there is no reason why we should expect the established car makers to pursue electric vehicles.

Established Technology

Disruptive Technology

Silver halide photographic film

Digital photography

Wireline telephony

Mobile telephony

Circuit-switched telecommunications networks

Packet-switched communications networks

Notebook computers

Hand-held digital appliances

Desktop personal computers

Sony Playstation II, Internet appliances

Full-service stock brokerage

On-line stock brokerage

New York & NASDAQ stock exchanges

Electronic Communications Networks (ECNs)

Full-fee underwriting of new equity and debt issues

Dutch auctions of new equity and debt issues, conducted on the Internet

Credit decisions based upon the personal judgment of bank lending officers

Automated lending decisions based upon credit scoring systems

Bricks & mortar retailing

On-line retailing

Industrial materials distributors

Internet-based sites such as Chemdex and E-steel

Printed greeting cards

Free greeting cards, downloadable over the Internet

Electric utility companies

Distributed power generation (gas turbines, micro-turbines, fuel cells)

Graduate schools of management

Corporate universities and in-house management training programs

Classroom and campus-based instruction

Distance education, typically enabled by the Internet

Standard textbooks

Custom-assembled, modular digital textbooks

Offset printing

Digital printing

Manned fighter and bomber aircraft

Unmanned aircraft

Microsoft Windows operating systems and applications software written in C++.

Internet Protocols (IP), and Java software protocols

Medical doctors

Nurse practitioners

General hospitals

Outpatient clinics and in-home patient care

Open surgery

Arthroscopic and endoscopic surgery

Cardiac bypass surgery

Angioplasty

Magnetic resonance imaging (MRI) and Computer Tomography (CT) Scanning

Ultrasound—initially floor-standing machines, ultimately portable machines

But the electric car is a disruptive technology and potential future threat. The innovator’s task is to ensure that this innovation—the disruptive technology that doesn’t make sense—is taken seriously within the company without putting at risk the needs of present customers who provide profit and growth. As chapter 10 concretely lays out, the problem can be resolved only when new markets are considered and carefully developed around new definitions of value—and when responsibility for building the business is placed within a focused organization whose size and interest are carefully aligned with the unique needs of the market’s customers.

WHERE DISRUPTIONS ARE HAPPENING TODAY

One of the most gratifying aspects of my life since the first edition of The Innovator’s Dilemma was published has been the number of people who have called, representing industries that I had never thought about, who have suggested that forces similar to those historical examples I described in these pages are disrupting their industries as well. Some of these are described in the table on the previous page. Not surprisingly, the Internet looms as an infrastructural technology that is enabling the disruption of many industries.

Each of the innovations in the right column—in the form of a new technology or a new business model—is now in the process of disrupting the established order described in the left column. Will the companies that currently lead their industries using the technologies in the left column survive these attacks? My hope is that the future might be different than the past. I believe that the future can be different, if managers will recognize these disruptions for what they are, and address them in a way that accounts for or harnesses the fundamental principles described in the pages that follow.

NOTES

1. John McDonald, “Sears Makes It Look Easy,” Fortune, May, 1964, 120–121.

2. Zina Moukheiber, “Our Competitive Advantage,” Forbes, April 12, 1993, 59.

3. Steve Weiner, “It’s Not Over Until It’s Over,” Forbes, May 28, 1990, 58.

4. Business Week, March 24, 1986, 98.

5. Thomas J. Peters and Robert H. Waterman, In Search of Excellence (New York: Harper & Row, 1982).

6. Business Week, May 9, 1994, 26.

7. Jeffrey Pfeffer and Gerald R. Salancik, The External Control of Organizations: A Resource Dependence Perspective (New York: Harper & Row, 1978).

Part One

WHY GREAT COMPANIES

CAN FAIL

CHAPTER ONE

How Can Great Firms Fail? Insights from the Hard Disk Drive Industry

When I began my search for an answer to the puzzle of why the best firms can fail, a friend offered some sage advice. “Those who study genetics avoid studying humans,” he noted. “Because new generations come along only every thirty years or so, it takes a long time to understand the cause and effect of any changes. Instead, they study fruit flies, because they are conceived, born, mature, and die all within a single day. If you want to understand why something happens in business, study the disk drive industry. Those companies are the closest things to fruit flies that the business world will ever see.”

Indeed, nowhere in the history of business has there been an industry like disk drives, where changes in technology, market structure, global scope, and vertical integration have been so pervasive, rapid, and unrelenting. While this pace and complexity might be a nightmare for managers, my friend was right about its being fertile ground for research. Few industries offer researchers the same opportunities for developing theories about how different types of change cause certain types of firms to succeed or fail or for testing those theories as the industry repeats its cycles of change.

This chapter summarizes the history of the disk drive industry in all its complexity. Some readers will be interested in it for the sake of history itself. [1] But the value of understanding this history is that out of its complexity emerge a few stunningly simple and consistent factors that have repeatedly determined the success and failure of the industry’s best firms. Simply put, when the best firms succeeded, they did so because they listened responsively to their customers and invested aggressively in the technology, products, and manufacturing capabilities that satisfied their customers’ next-generation needs. But, paradoxically, when the best firms subsequently failed, it was for the same reasons—they listened responsively to their customers and invested aggressively in the technology, products, and manufacturing capabilities that satisfied their customers’ next-generation needs. This is one of the innovator’s dilemmas: Blindly following the maxim that good managers should keep close to their customers can sometimes be a fatal mistake.

The history of the disk drive industry provides a framework for understanding when “keeping close to your customers” is good advice—and when it is not. The robustness of this framework could only be explored by researching the industry’s history in careful detail. Some of that detail is recounted here, and elsewhere in this book, in the hope that readers who are immersed in the detail of their own industries will be better able to recognize how similar patterns have affected their own fortunes and those of their competitors.

HOW DISK DRIVES WORK

Disk drives write and read information that computers use. They comprise read-write heads mounted at the end of an arm that swings over the surface of a rotating disk in much the same way that a phonograph needle and arm reach over a record; aluminum or glass disks coated with magnetic material; at least two electric motors, a spin motor that drives the rotation of the disks and an actuator motor that moves the head to the desired position over the disk; and a variety of electronic circuits that control the drive’s operation and its interface with the computer. See Figure 1.1 for an illustration of a typical disk drive.

The read-write head is a tiny electromagnet whose polarity changes whenever the direction of the electrical current running through it changes. Because opposite magnetic poles attract, when the polarity of the head becomes positive, the polarity of the area on the disk beneath the head switches to negative, and vice versa. By rapidly changing the direction of current flowing through the head’s electromagnet as the disk spins beneath the head, a sequence of positively and negatively oriented magnetic domains are created in concentric tracks on the disk’s surface. Disk drives can use the positive and negative domains on the disk as a binary numeric system—1 and 0—to “write” information onto disks. Drives read information from disks in essentially the opposite process: Changes in the magnetic flux fields on the disk surface induce changes in the micro current flowing through the head.

Figure 1.1 Primary Components of a Typical Disk Drive

EMERGENCE OF THE EARLIEST DISK DRIVES

A team of researchers at IBM’s San Jose research laboratories developed the first disk drive between 1952 and 1956. Named RAMAC (for Random Access Method for Accounting and Control), this drive was the size of a large refrigerator, incorporated fifty twenty-four-inch disks, and could store 5 megabytes (MB) of information (see Figure 1.2). Most of the fundamental architectural concepts and component technologies that defined today’s dominant disk drive design were also developed at IBM. These include its removable packs of rigid disks (introduced in 1961); the floppy disk drive (1971); and the Winchester architecture (1973). All had a powerful, defining influence on the way engineers in the rest of the industry defined what disk drives were and what they could do.

Figure 1.2 The First Disk Drive, Developed by IBM

Source: Courtesy of International Business Machines Corporation.

As IBM produced drives to meet its own needs, an independent disk drive industry emerged serving two distinct markets. A few firms developed the plug-compatible market (PCM) in the 1960s, selling souped-up copies of IBM drives directly to IBM customers at discount prices. Although most of IBM’s competitors in computers (for example, Control Data, Burroughs, and Univac) were integrated vertically into the manufacture of their own disk drives, the emergence in the 1970s of smaller, nonintegrated computer makers such as Nixdorf, Wang, and Prime spawned an original equipment market (OEM) for disk drives as well. By 1976 about $1 billion worth of disk drives were produced, of which captive production accounted for 50 percent and PCM and OEM for about 25 percent each.

The next dozen years unfolded a remarkable story of rapid growth, market turbulence, and technology-driven performance improvements. The value of drives produced rose to about $18 billion by 1995. By the mid-1980s the PCM market had become insignificant, while OEM output grew to represent about three-fourths of world production. Of the seventeen firms populating the industry in 1976—all of which were relatively large, diversified corporations such as Diablo, Ampex, Memorex, EMM, and Control Data—all except IBM’s disk drive operation had failed or had been acquired by 1995. During this period an additional 129 firms entered the industry, and 109 of those also failed. Aside from IBM, Fujitsu, Hitachi, and NEC, all of the producers remaining by 1996 had entered the industry as start-ups after 1976.

Some have attributed the high mortality rate among the integrated firms that created the industry to its nearly unfathomable pace of technological change. Indeed, the pace of change has been breathtaking. The number of megabits (Mb) of information that the industry’s engineers have been able to pack into a square inch of disk surface has increased by 35 percent per year, on average, from 50 Kb in 1967 to 1.7 Mb in 1973, 12 Mb in 1981, and 1100 Mb by 1995. The physical size of the drives was reduced at a similar pace: The smallest available 20 MB drive shrank from 800 cubic inches (in. 3 ) in 1978 to 1.4 in. 3 by 1993—a 35 percent annual rate of reduction.

Figure 1.3 shows that the slope of the industry’s experience curve (which correlates the cumulative number of terabytes (one thousand gigabytes) of disk storage capacity shipped in the industry’s history to the constant-dollar price per megabyte of memory) was 53 percent—meaning that with each doubling of cumulative terabytes shipped, cost per megabyte fell to 53 percent of its former level. This is a much steeper rate of price decline than the 70 percent slope observed in the markets for most other microelectronics products. The price per megabyte has declined at about 5 percent per quarter for more than twenty years.

THE IMPACT OF TECHNOLOGICAL CHANGE

My investigation into why leading firms found it so difficult to stay atop the disk drive industry led me to develop the “technology mudslide hypothesis”: Coping with the relentless onslaught of technology change was akin to trying to climb a mudslide raging down a hill. You have to scramble with everything you’ve got to stay on top of it, and if you ever once stop to catch your breath, you get buried.

Figure 1.3 Disk Drive Price Experience Curve

Source: Data are from various issues of Disk/Trend Report.

To test this hypothesis, I assembled and analyzed a database consisting of the technical and performance specifications of every model of disk drive introduced by every company in the world disk drive industry for each of the years between 1975 and 1994. [2] This database enabled me to identify the firms that led in introducing each new technology; to trace how new technologies were diffused through the industry over time; to see which firms led and which lagged; and to measure the impact each technological innovation had on capacity, speed, and other parameters of disk drive performance. By carefully reconstructing the history of each technological change in the industry, the changes that catapulted entrants to success or that precipitated the failure of established leaders could be identified.

This study led me to a very different view of technology change than the work of prior scholars on this question had led me to expect. Essentially, it revealed that neither the pace nor the difficulty of technological change lay at the root of the leading firms’ failures. The technology mudslide hypothesis was wrong.

The manufacturers of most products have established a trajectory of performance improvement over time. [3] Intel, for example, pushed the speed of its microprocessors ahead by about 20 percent per year, from its 8 megahertz (MHz) 8088 processor in 1979 to its 133 MHz Pentium chip in 1994. Eli Lilly and Company improved the purity of its insulin from 50,000 impure parts per million (ppm) in 1925 to 10 ppm in 1980, a 14 percent annual rate of improvement. When a measurable trajectory of improvement has been established, determining whether a new technology is likely to improve a product’s performance relative to earlier products is an unambiguous question.

But in other cases, the impact of technological change is quite different. For instance, is a notebook computer better than a mainframe? This is an ambiguous question because the notebook computer established a completely new performance trajectory, with a definition of performance that differs substantially from the way mainframe performance is measured. Notebooks, as a consequence, are generally sold for very different uses.

This study of technological change over the history of the disk drive industry revealed two types of technology change, each with very different effects on the industry’s leaders. Technologies of the first sort sustained the industry’s rate of improvement in product performance (total capacity and recording density were the two most common measures) and ranged in difficulty from incremental to radical. The industry’s dominant firms always led in developing and adopting these technologies. By contrast, innovations of the second sort disrupted or redefined performance trajectories—and consistently resulted in the failure of the industry’s leading firms. [4]

The remainder of this chapter illustrates the distinction between sustaining and disruptive technologies by describing prominent examples of each and summarizing the role these played in the industry’s development. This discussion focuses on differences in how established firms came to lead or lag in developing and adopting new technologies, compared with entrant firms. To arrive at these examples, each new technology in the industry was examined. In analyzing which firms led and lagged at each of these points of change, I defined established firms to be those that had been established in the industry prior to the advent of the technology in question, practicing the prior technology. I defined entrant firms as those that were new to the industry at that point of technology change. Hence, a given firm would be considered an entrant at one specific point in the industry’s history, for example, at the emergence of the 8-inch drive. Yet the same firm would be considered an established firm when technologies that emerged subsequent to the firm’s entry were studied.

SUSTAINING TECHNOLOGICAL CHANGES

In the history of the disk drive industry, most technology changes have sustained or reinforced established trajectories of product performance improvement. Figure 1.4, which compares the average recording density of drives that employed successive generations of head and disk technologies, maps an example of this. The first curve plots the density of drives that used conventional particulate oxide disk technology and ferrite head technology; the second charts the average density of drives that used new-technology thin-film heads and disks; the third marks the improvements in density achievable with the latest head technology, magneto-resistive heads. [5]

The way such new technologies as these emerge to surpass the performance of the old resembles a series of intersecting technology S-curves. [6] Movement along a given S-curve is generally the result of incremental improvements within an existing technological approach, whereas jumping onto the next technology curve implies adopting a radically new technology. In the cases measured in Figure 1.4, incremental advances, such as grinding the ferrite heads to finer, more precise dimensions and using smaller and more finely dispersed oxide particles on the disk’s surface, led to the improvements in density from 1 to 20 megabits per square inch (Mbpsi) between 1976 and 1989. As S-curve theory would predict, the improvement in recording density obtainable with ferrite/ oxide technology began to level off toward the end of the period, suggesting a maturing technology. The thin-film head and disk technologies’ effect on the industry sustained performance improvement at its historical rate. Thin-film heads were barely established in the early 1990s, when even more advanced magneto-resistive head technology emerged. The impact of magneto-resistive technology sustained, or even accelerated, the rate of performance improvement.

Figure 1.4 Impact of New Read-Write Head Technologies in Sustaining the Trajectory of Improvement in Recording Density

Source: Data are from various issues of Disk/Trend Report.

Figure 1.5 describes a sustaining technological change of a very different character: an innovation in product architecture, in which the 14-inch Winchester drive is substituted for removable disk packs, which had been the dominant design between 1962 and 1978. Just as in the thin-film for ferrite/oxide substitution, the impact of Winchester technology sustained the historically established rate of performance improvement. Similar graphs could be constructed for most other technological innovations in the industry, such as embedded servo systems, RLL and PRML recording codes, higher RPM motors, and embedded interfaces. Some of these were straightforward technology improvements; others were radical departures. But all had a similar impact on the industry: They helped manufacturers to sustain the rate of historical performance improvement that their customers had come to expect. [7]

In literally every case of sustaining technology change in the disk drive industry, established firms led in development and commercialization. The emergence of new disk and head technologies illustrates this.

In the 1970s, some manufacturers sensed that they were reaching the limit on the number of bits of information they could pack onto oxide disks. In response, disk drive manufacturers began studying ways of applying super-thin films of magnetic metal on aluminum to sustain the historical rate of improvements in recording density. The use of thin-film coatings was then highly developed in the integrated circuit industry, but its application to magnetic disks still presented substantial challenges. Experts estimate that the pioneers of thin-film disk technology—IBM, Control Data, Digital Equipment, Storage Technology, and Ampex—each took more than eight years and spent more than $50 million in that effort. Between 1984 and 1986, about two-thirds of the producers active in 1984 introduced drives with thin-film disks. The overwhelming majority of these were established industry incumbents. Only a few entrant firms attempted to use thin-film disks in their initial products, and most of those folded shortly after entry.

Figure 1.5 Sustaining Impact of the Winchester Architecture on the Recording Density of 14-inch Disk Drives

Source: Data are from various issues of Disk/Trend Report.

The same pattern was apparent in the emergence of thin-film heads. Manufacturers of ferrite heads saw as early as 1965 the approaching limit to improvements in this technology; by 1981 many believed that the limits of precision would soon be reached. Researchers turned to thin-film technology, produced by sputtering thin films of metal on the recording head and then using photolithography to etch much finer electromagnets than could be attained with ferrite technology. Again, this proved extraordinarily difficult. Burroughs in 1976, IBM in 1979, and other established firms first successfully incorporated thin-film heads in disk drives. In the period between 1982 and 1986, during which some sixty firms entered the rigid disk drive industry, only four (all commercial failures) attempted to do so using thin-film heads in their initial products as a source of performance advantage. All other entrant firms—even aggressively performance-oriented firms such as Maxtor and Conner Peripherals—found it preferable to learn their way using conventional ferrite heads first, before tackling thin-film technology.

As was the case with thin-film disks, the introduction of thin-film heads entailed the sort of sustained investment that only established firms could handle. IBM and its rivals each spent more than $100 million developing thin-film heads. The pattern was repeated in the next-generation magneto-resistive head technology: The industry’s largest firms—IBM, Seagate, and Quantum—led the race.

The established firms were the leading innovators not just in developing risky, complex, and expensive component technologies such as thin-film heads and disks, but in literally every other one of the sustaining innovations in the industry’s history. Even in relatively simple innovations, such as RLL recording codes (which took the industry from double-to triple-density disks), established firms were the successful pioneers, and entrant firms were the technology followers. This was also true for those architectural innovations—for example, 14-inch and 2.5-inch Winchester drives— whose impact was to sustain established improvement trajectories. Established firms beat out the entrants.

Figure 1.6 summarizes this pattern of technology leadership among established and entrant firms offering products based on new sustaining technologies during the years when those technologies were emerging. The pattern is stunningly consistent. Whether the technology was radical or incremental, expensive or cheap, software or hardware, component or architecture, competence-enhancing or competence-destroying, the pattern was the same. When faced with sustaining technology change that gave existing customers something more and better in what they wanted, the leading practitioners of the prior technology led the industry in the development and adoption of the new. Clearly, the leaders in this industry did not fail because they became passive, arrogant, or risk-averse or because they couldn’t keep up with the stunning rate of technological change. My technology mudslide hypothesis wasn’t correct.

Figure 1.6 Leadership of Established Firms in Sustaining Technologies

Source: Data are from various issues of Disk/Trend Report.

FAILURE IN THE FACE OF DISRUPTIVE TECHNOLOGICAL CHANGES

Most technological change in the disk drive industry has consisted of sustaining innovations of the sort described above. In contrast, there have been only a few of the other sort of technological change, called disruptive technologies. These were the changes that toppled the industry’s leaders.

The most important disruptive technologies were the architectural innovations that shrunk the size of the drives—from 14-inch diameter disks to diameters of 8, 5.25, and 3.5-inches and then from 2.5 to 1.8 inches. Table 1.1 illustrates the ways these innovations were disruptive. Based on 1981 data, it compares the attributes of a typical 5.25-inch drive, a new architecture that had been in the market for less than a year, with those of a typical 8-inch drive, which at that time was the standard drive used by minicomputer manufacturers. Along the dimensions of performance important to established minicomputer manufacturers—capacity, cost per megabyte, and access time—the 8-inch product was vastly superior. The 5.25-inch architecture did not address the perceived needs of minicomputer manufacturers at that time. On the other hand, the 5.25-inch drive had features that appealed to the desktop personal computer market segment just emerging in the period between 1980 and 1982. It was small and lightweight, and, priced at around $2,000, it could be incorporated into desktop machines economically.

Generally disruptive innovations were technologically straightforward, consisting of off-the-shelf components put together in a product architecture that was often simpler than prior approaches. [8] They offered less of what customers in established markets wanted and so could rarely be initially employed there. They offered a different package of attributes valued only in emerging markets remote from, and unimportant to, the mainstream.

The trajectory map in Figure 1.7 shows how this series of simple but disruptive technologies proved to be the undoing of some very aggressive, astutely managed disk drive companies. Until the mid-1970s, 14-inch drives with removable packs of disks accounted for nearly all disk drive sales. The 14-inch Winchester architecture then emerged to sustain the trajectory of recording density improvement. Nearly all of these drives (removable disks and Winchesters) were sold to mainframe computer manufacturers, and the same companies that led the market in disk pack drives led the industry’s transition to the Winchester technology.

Table 1.1 A Disruptive Technology Change: The 5.25-inch Winchester Disk Drive (1981)

Attribute

8-Inch Drives (Minicomputer Market)

5.25-Inch Drives (Desktop Computer Market)

Capacity (megabytes)

60

10

Physical volume (cubic inches)

566

150

Weight (pounds)

21

6

Access time (milliseconds)

30

160

Cost per megabyte

$50

$200

Unit cost

$3000

$2000

Source: Data are from various issues of Disk/Trend Report.

Figure 1.7 Intersecting Trajectories of Capacity Demanded versus Capacity Supplied in Rigid Disk Drives

Source: Clayton M. Christensen, “The Rigid Disk Drive Industry: A History of Commercial and Technological Turbulence,” Business History Review 67, no. 4 (Winter 1993): 559. Reprinted by permission.

The trajectory map shows that the hard disk capacity provided in the median priced, typically configured mainframe computer system in 1974 was about 130 MB per computer. This increased at a 15 percent annual rate over the next fifteen years—a trajectory representing the disk capacity demanded by the typical users of new mainframe computers. At the same time, the capacity of the average 14-inch drive introduced for sale each year increased at a faster, 22 percent rate, reaching beyond the mainframe market to the large scientific and supercomputer markets. [9]

Between 1978 and 1980, several entrant firms—Shugart Associates, Micropolis, Priam, and Quantum—developed smaller 8-inch drives with 10, 20, 30, and 40 MB capacity. These drives were of no interest to mainframe computer manufacturers, which at that time were demanding drives with 300 to 400 MB capacity. These 8-inch entrants therefore sold their disruptive drives into a new application—minicomputers. [10] The customers—Wang, DEC, Data General, Prime, and Hewlett-Packard—did not manufacture mainframes, and their customers often used software substantially different from that used in mainframes. These firms hitherto had been unable to offer disk drives in their small, desk-side minicomputers because 14-inch models were too big and expensive. Although initially the cost per megabyte of capacity of 8-inch drives was higher than that of 14-inch drives, these new customers were willing to pay a premium for other attributes that were important to them—especially smaller size. Smallness had little value to mainframe users.

Once the use of 8-inch drives became established in minicomputers, the hard disk capacity shipped with the median-priced minicomputer grew about 25 percent per year: a trajectory determined by the ways in which minicomputer owners learned to use their machines. At the same time, however, the 8-inch drive makers found that, by aggressively adopting sustaining innovations, they could increase the capacity of their products at a rate of more than 40 percent per year—nearly double the rate of increase demanded by their original “home” minicomputer market. In consequence, by the mid-1980s, 8-inch drive makers were able to provide the capacities required for lower-end mainframe computers. Unit volumes had grown significantly so that the cost per megabyte of 8-inch drives had declined below that of 14-inch drives, and other advantages became apparent: For example, the same percentage mechanical vibration in an 8-inch drive, as opposed to a 14-inch drive, caused much less variance in the absolute position of the head over the disk. Within a three-to-four-year period, therefore, 8-inch drives began to invade the market above them, substituting for 14-inch drives in the lower-end mainframe computer market.

As the 8-inch products penetrated the mainframe market, the established manufacturers of 14-inch drives began to fail. Two-thirds of them never introduced an 8-inch model. The one-third that introduced 8-inch models did so about two years behind the 8-inch entrant manufacturers. Ultimately, every 14-inch drive maker was driven from the industry. [11]

The 14-inch drive makers were not toppled by the 8-inch entrants because of technology. The 8-inch products generally incorporated standard off-the-shelf components, and when those 14-inch drive makers that did introduce 8-inch models got around to doing so, their products were very performance-competitive in capacity, areal density, access time, and price per megabyte. The 8-inch models introduced by the established firms in 1981 were nearly identical in performance to the average of those introduced that year by the entrant firms. In addition, the rates of improvement in key attributes (measured between 1979 and 1983) were stunningly similar between established and entrant firms. [12]

Held Captive by Their Customers

Why were the leading drive makers unable to launch 8-inch drives until it was too late? Clearly, they were technologically capable of producing these drives. Their failure resulted from delay in making the strategic commitment to enter the emerging market in which the 8-inch drives initially could be sold. Interviews with marketing and engineering executives close to these companies suggest that the established 14-inch drive manufacturers were held captive by customers. Mainframe computer manufacturers did not need an 8-inch drive. In fact, they explicitly did not want it: they wanted drives with increased capacity at a lower cost per megabyte. The 14-inch drive manufacturers were listening and responding to their established customers. And their customers—in a way that was not apparent to either the disk drive manufacturers or their computer-making customers—were pulling them along a trajectory of 22 percent capacity growth in a 14-inch platform that would ultimately prove fatal. [13]

Figure 1.7 maps the disparate trajectories of performance improvement demanded in the computer product segments that emerged later, compared to the capacity that changes in component technology and refinements in system design made available within each successive architecture. The solid lines emanating from points A, B, C, D, and E measure the disk drive capacity provided with the median-priced computer in each category, while the dotted lines from the same points measure the average capacity of all disk drives introduced for sale in each architecture, for each year. These transitions are briefly described below.

The Advent of the 5.25-inch Drive

In 1980, Seagate Technology introduced 5.25-inch disk drives. Their capacities of 5 and 10 MB were of no interest to minicomputer manufacturers, who were demanding drives of 40 and 60 MB from their suppliers. Seagate and other firms that entered with 5.25-inch drives in the period 1980 to 1983 (for example, Miniscribe, Computer Memories, and International Memories) had to pioneer new applications for their products and turned primarily to desktop personal computer makers. By 1990, the use of hard drives in desktop computers was an obvious application for magnetic recording. It was not at all clear in 1980, however, when the market was just emerging, that many people could ever afford or use a hard drive on the desktop. The early 5.25-inch drive makers found this application (one might even say that they enabled it) by trial and error, selling drives to whomever would buy them.

Once the use of hard drives was established in desktop PCs, the disk capacity shipped with the median-priced machine (that is, the capacity demanded by the general PC user) increased about 25 percent per year. Again, the technology improved at nearly twice the rate demanded in the new market: The capacity of new 5.25-inch drives increased about 50 percent per year between 1980 and 1990. As in the 8-inch for 14-inch substitution, the first firms to produce 5.25-inch drives were entrants; on average, established firms lagged behind entrants by two years. By 1985, only half of the firms producing 8-inch drives had introduced 5.25-inch models. The other half never did.

Growth in the use of 5.25-inch drives occurred in two waves. The first followed creation of a new application for rigid disk drives: desktop computing, in which product attributes such as physical size, relatively unimportant in established applications, were highly valued. The second wave followed substitution of 5.25-inch disks for larger drives in established minicomputer and mainframe computer markets, as the rapidly increasing capacity of 5.25-inch drives intersected the more slowly growing trajectories of capacity demanded in these markets. Of the four leading 8-inch drive makers—Shugart Associates, Micropolis, Priam, and Quantum—only Micropolis survived to become a significant manufacturer of 5.25-inch drives, and that was accomplished only with Herculean managerial effort, as described in chapter 5.

The Pattern Is Repeated: The Emergence of the 3.5-inch Drive

The 3.5-inch drive was first developed in 1984 by Rodime, a Scottish entrant. Sales of this architecture were not significant, however, until Conner Peripherals, a spinoff of 5.25-inch drive makers Seagate and Miniscribe, started shipping product in 1987. Conner had developed a small, lightweight drive architecture that was much more rugged than its 5.25-inch ancestors. It handled electronically functions that had previously been managed with mechanical parts, and it used microcode to replace functions that had previously been addressed electronically. Nearly all of Conner’s first year revenues of $113 million [14] came from Compaq Computer, which had aided Conner’s start-up with a $30 million investment. The Conner drives were used primarily in a new application—portable and laptop machines, in addition to “small footprint” desktop models—where customers were willing to accept lower capacities and higher costs per megabyte to get lighter weight, greater ruggedness, and lower power consumption.

Seagate engineers were not oblivious to the coming of the 3.5-inch architecture. Indeed, in early 1985, less than one year after Rodime introduced the first 3.5-inch drive and two years before Conner Peripherals started shipping its product, Seagate personnel showed working 3.5-inch prototype drives to customers for evaluation. The initiative for the new drives came from Seagate’s engineering organization. Opposition to the program came primarily from the marketing organization and Seagate’s executive team; they argued that the market wanted higher capacity drives at a lower cost per megabyte and that 3.5-inch drives could never be built at a lower cost per megabyte than 5.25-inch drives.

Seagate’s marketers tested the 3.5-inch prototypes with customers in the desktop computing market it already served—manufacturers like IBM, and value-added resellers of full-sized desktop computer systems. Not surprisingly, they indicated little interest in the smaller drive. They were looking for capacities of 40 and 60 megabytes for their next-generation machines, while the 3.5-inch architecture could provide only 20 MB—and at higher costs. [15]

In response to lukewarm reviews from customers, Seagate’s program manager lowered his 3.5-inch sales estimates, and the firm’s executives canceled the program. Their reasoning? The markets for 5.25-inch products were larger, and the sales generated by spending the engineering effort on new 5.25-inch products would create greater revenues for the company than would efforts targeted at new 3.5-inch products.

In retrospect, it appears that Seagate executives read the market—at least their own market—very accurately. With established applications and product architectures of their own, such as the IBM XT and AT, these customers saw no value in the improved ruggedness or the reduced size, weight, and power consumption of 3.5-inch products.

Seagate finally began shipping 3.5-inch drives in early 1988—the same year in which the performance trajectory of 3.5-inch drives (shown in Figure 1.7) intersected the trajectory of capacity demanded in desktop computers. By that time, the industry had shipped, cumulatively, nearly $750 million in 3.5-inch products. Interestingly, according to industry observers, as of 1991 almost none of Seagate’s 3.5-inch products had been sold to manufacturers of portable/laptop/notebook computers. In other words, Seagate’s primary customers were still desktop computer manufacturers, and many of its 3.5-inch drives were shipped with frames for mounting them in computers designed for 5.25-inch drives.

The fear of cannibalizing sales of existing products is often cited as a reason why established firms delay the introduction of new technologies. As the Seagate-Conner experience illustrates, however, if new technologies enable new market applications to emerge, the introduction of new technology may not be inherently cannibalistic. But when established firms wait until a new technology has become commercially mature in its new applications and launch their own version of the technology only in response to an attack on their home markets, the fear of cannibalization can become a self-fulfilling prophecy.

Although we have been looking at Seagate’s response to the development of the 3.5-inch drive architecture, its behavior was not atypical; by 1988, only 35 percent of the drive manufacturers that had established themselves making 5.25-inch products for the desktop PC market had introduced 3.5-inch drives. Similar to earlier product architecture transitions, the barrier to development of a competitive 3.5-inch product does not appear to have been engineering-based. As in the 14-to 8-inch transition, the new-architecture drives introduced by the incumbent, established firms during the transitions from 8 to 5.25 inches and from 5.25 to 3.5 inches were fully performance-competitive with those of entrant drives. Rather, the 5.25-inch drive manufacturers seem to have been misled by their customers, notably IBM and its direct competitors and resellers, who themselves seemed as oblivious as Seagate to the potential benefits and possibilities of portable computing and the new disk drive architecture that might facilitate it.

Prairietek, Conner, and the 2.5-inch Drive

In 1989 an industry entrant in Longmont, Colorado, Prairietek, upstaged the industry by announcing a 2.5-inch drive, capturing nearly all $30 million of this nascent market. But Conner Peripherals announced its own 2.5-inch product in early 1990 and by the end of that year had claimed 95 percent of the 2.5-inch drive market. Prairietek declared bankruptcy in late 1991, by which time each of the other 3.5-inch drivemakers— Quantum, Seagate, Western Digital, and Maxtor—had introduced 2.5-inch drives of their own.

What had changed? Had the incumbent leading firms finally learned the lessons of history? Not really. Although Figure 1.7 shows the 2.5-inch drive had significantly less capacity than the 3.5-inch drives, the portable computing markets into which the smaller drives were sold valued other attributes: weight, ruggedness, low power consumption, small physical size, and so on. Along these dimensions, the 2.5-inch drive offered improved performance over that of the 3.5-inch product: It was a sustaining technology. In fact, the computer makers who bought Conner’s 3.5-inch drive—laptop computer manufacturers such as Toshiba, Zenith, and Sharp—were the leading makers of notebook computers, and these firms needed the smaller 2.5-inch drive architecture. Hence, Conner and its competitors in the 3.5-inch market followed their customers seamlessly across the transition to 2.5-inch drives.

In 1992, however, the 1.8-inch drive emerged, with a distinctly disruptive character. Although its story will be recounted in detail later, it suffices to state here that by 1995, it was entrant firms that controlled 98 percent of the $130 million 1.8-inch drive market. Moreover, the largest initial market for 1.8-inch drives wasn’t in computing at all. It was in portable heart monitoring devices!

Figure 1.8 summarizes this pattern of entrant firms’ leadership in disruptive technology. It shows, for example, that two years after the 8-inch drive was introduced, two-thirds of the firms producing it (four of six), were entrants. And, two years after the first 5.25-inch drive was introduced, 80 percent of the firms producing these disruptive drives were entrants.

Figure 1.8 Leadership of Entrant Firms in Disruptive Technology

Source: Data are from various issues of Disk/Trend Report.

SUMMARY

There are several patterns in the history of innovation in the disk drive industry. The first is that the disruptive innovations were technologically straightforward. They generally packaged known technologies in a unique architecture and enabled the use of these products in applications where magnetic data storage and retrieval previously had not been technologically or economically feasible.

The second pattern is that the purpose of advanced technology development in the industry was always to sustain established trajectories of performance improvement: to reach the higher-performance, higher-margin domain of the upper right of the trajectory map. Many of these technologies were radically new and difficult, but they were not disruptive. The customers of the leading disk drive suppliers led them toward these achievements. Sustaining technologies, as a result, did not precipitate failure.

The third pattern shows that, despite the established firms’ technological prowess in leading sustaining innovations, from the simplest to the most radical, the firms that led the industry in every instance of developing and adopting disruptive technologies were entrants to the industry, not its incumbent leaders.

This book began by posing a puzzle: Why was it that firms that could be esteemed as aggressive, innovative, customer-sensitive organizations could ignore or attend belatedly to technological innovations with enormous strategic importance? In the context of the preceding analysis of the disk drive industry, this question can be sharpened considerably. The established firms were, in fact, aggressive, innovative, and customer-sensitive in their approaches to sustaining innovations of every sort. But the problem established firms seem unable to confront successfully is that of downward vision and mobility, in terms of the trajectory map. Finding new applications and markets for these new products seems to be a capability that each of these firms exhibited once, upon entry, and then apparently lost. It was as if the leading firms were held captive by their customers, enabling attacking entrant firms to topple the incumbent industry leaders each time a disruptive technology emerged. [16] Why this happened, and is still happening, is the subject of the next chapter.

APPENDIX 1.1:

A NOTE ON THE DATA AND METHOD

USED TO GENERATE FIGURE 1.7

The trajectories mapped in Figure 1.7 were calculated as follows. Data on the capacity provided with computers was obtained from Data Sources, an annual publication listing the technical specifications of all computer models available from every computer manufacturer. For instances in which particular models were available with different features and configurations, the manufacturer provided Data Sources with a “typical” system configuration with defined random access memory (RAM) capacity, performance specifications of peripheral equipment (including disk drives), list prices, and year of introduction. For instances in which a given computer model was offered for sale over a sequence of years, the hard disk capacity provided in the typical configuration typically increased. Data Sources used the categories mainframe, mini/midrange, desktop personal, portable and laptop, and notebook. As of 1993, 1.8-inch drives were not being used in hand-held computers, so no data on that potential market existed.

For Figure 1.7, for each year and each class of computers, all models available for sale were ranked by price and the hard disk capacity provided with the median-priced model identified. The best-fit lines through the resultant time series were plotted as the solid lines in Figure 1.7 for expository simplification to indicate the trend in typical machines. In reality, of course, there is a wide band around these lines. The frontier of performance—the highest capacity offered with the most expensive computers—was substantially higher than the typical values shown.

The dotted lines in Figure 1.7 represent the best-fit line through the unweighted average capacity of all disk drives introduced for sale in each given architecture for each year. This data was taken from Disk/Trend Report. Again, for expository simplification, only this average line is shown. There was a wide band of capacities introduced for sale in each year, so that the frontier or highest capacity drive introduced in each year was substantially above the average shown. Stated in another way, a distinction must be made between the full range of products available for purchase and those in typical systems. The upper and lower bands around the median and average figures shown in Figure 1.7 are generally parallel to the lines shown.

Because higher capacity drives were available in the market than were offered with the median-priced systems, the solid-line trajectories in Figure 1.7, as I state in the text, represent the capacities “demanded” in each market. In other words, the capacity per machine was not constrained by technological availability. Rather, it represents the selection of hard disk capacity by computer users, given the prevailing cost.

NOTES

1. A more complete history of the disk drive industry can be found in Clayton M. Christensen, “The Rigid Disk Drive Industry: A History of Commercial and Technological Turbulence,” Business History Review (67), Winter, 1993, 531–588. This history focuses only on the manufacturers of rigid disk drives or hard drives—products on which data are stored on rigid metal platters. Companies manufacturing floppy disk drives (removable diskettes of flexible mylar coated with iron oxide on which data are stored) historically were different firms from those making hard disk drives.

2. Much of the data for this analysis came from Disk/Trend Report, a highly respected annual market research publication, augmented with more detailed product-specification sheets obtained from the disk drive manufacturers themselves. I am grateful to the editors and staff at Disk/Trend, Inc., for their patient and generous assistance in this project.

3. The concept of trajectories of technological progress was examined by Giovanni Dosi in “Technological Paradigms and Technological Trajectories,” Research Policy (11), 1982, 147–162.

4. The ways in which the findings of this study differ from those of some earlier scholars of technology change while building upon those of others are discussed in greater detail in chapter 2.

5. The first technology for making heads built an electromagnet by wrapping a fine thread of copper wire around a core of iron oxide (ferrite); hence the term ferrite head. Incremental improvements to this approach involved learning to grind the ferrite to finer and finer dimensions, using better lapping techniques, and strengthening the ferrite by doping it with barium. Thin-film heads were made photolithographically, using technology similar to that used in making integrated circuits on silicon wafers to etch the electromagnet on the surface of the head. This was difficult because it involved much thicker layers of material than were common in IC manufacturing. The third technology, adopted starting in the mid-1990s, was called magneto-resistive heads. These were also made with thin-film photolithography, but used the principle that changes in the magnetic flux field on the disk surface changed the electrical resistivity of the circuitry in the head. By measuring changes in resistivity rather than changes in the direction of current flow, magneto-resistive heads were much more sensitive, and hence permitted denser data recording, than prior technology. In the evolution of disk technology, the earliest disks were made by coating fine needle-shaped particles of iron oxide—literally rust—over the surface of a flat, polished aluminum platter. Hence, these disks were called oxide disks. Incremental improvements to this technology involved making finer and finer iron oxide particles, and dispersing them more uniformly, with fewer uncoated voids on the aluminum platter’s surface. This was supplanted by a sputtering technology, also borrowed from semiconductor processing, that coated the aluminum platter with a thin film of metal a few angstroms thick. The thinness of this layer; its continuous, rather than particulate nature; and the process’s flexibility in depositing magnetic materials with higher coercivity, enabled denser recording on thin-film disks than was feasible on oxide disks.

6. Richard J. Foster, Innovation: The Attacker’s Advantage (New York: Summit Books, 1986).

7. The examples of technology change presented in Figures 1.1 and 1.2 introduce some ambiguity to the unqualified term discontinuity, as used by Giovanni Dosi (see “Technological Paradigms and Technological Trajectories,” Research Policy [11] 1982), Michael L. Tushman and Philip Anderson (see “Technological Discontinuities and Organizational Environments,” Administrative Science Quarterly [31], 1986), and others. The innovations in head and disk technology described in Figure 1.4 represent positive discontinuities in an established technological trajectory, while the trajectory-disrupting technologies charted in Figure 1.7 represent negative discontinuities. As will be shown below, established firms seemed quite capable of leading the industry over positive discontinuities, but generally lost their industry lead when faced with negative discontinuities.

8. This tendency consistently appears across a range of industries. Richard S. Rosenbloom and Clayton M. Christensen (in “Technological Discontinuities, Organizational Capabilities, and Strategic Commitments,” Industrial and Corporate Change [3], 1994, 655–685) suggest a much broader set of industries in which leading firms may have been toppled by technologically straightforward disruptive innovations than is covered in this book.

9. A summary of the data and procedures used to generate Figure 1.7 is included in Appendix 1.1.

10. The minicomputer market was not new in 1978, but it was a new application for Winchester-technology disk drives.

11. This statement applies only to independent drive makers competing in the OEM market. Some of the vertically integrated computer makers, such as IBM, have survived across these generations with the benefit of a captive internal market. Even IBM, however, addressed the sequence of different emerging markets for disk drives by creating autonomous “start-up” disk drive organizations to address each one. Its San Jose organization focused on high-end (primarily mainframe) applications. A separate division in Rochester, MN, focused on mid-range computers and workstations. IBM created a different organization in Fujisawa, Japan, to produce drives for the desktop personal computer market.

12. This result is very different from that observed by Rebecca M. Henderson (see The Failure of Established Firms in the Face of Technological Change: A Study of the Semiconductor Photolithographic Alignment Industry, dissertation, Harvard University, 1988), who found the new-architecture aligners produced by the established manufacturers to be inferior in performance to those produced by entrant firms. One possible reason for these different results is that the successful entrants in the photolithographic aligner industry studied by Henderson brought to the new product a well-developed body of technological knowledge and experience developed and refined in other markets. In the case studied here, none of the entrants brought such well-developed knowledge with them. Most, in fact, were de novo start-ups composed of managers and engineers who had defected from established drive manufacturing firms.

13. This finding is similar to the phenomenon observed by Joseph L. Bower, who saw that explicit customer demands have tremendous power as a source of impetus in the resource allocation process: “When the discrepancy (the problem to be solved by a proposed investment) was defined in terms of cost and quality, the projects languished. In all four cases, the definition process moved toward completion when capacity to meet sales was perceived to be inadequate…. In short, pressure from the market reduces both the probability and the cost of being wrong.” Although Bower specifically refers to manufacturing capacity, the same fundamental phenomenon—the power of the known needs of known customers in marshaling and directing the investments of a firm—affects response to disruptive technology. See Joseph L. Bower, Managing the Resource Allocation Process (Homewood, IL: Richard D. Irwin, 1970) 254.

14. In booking $113 million in revenues, Conner Peripherals set a record for booking more revenues in its first year of operation than any manufacturing company in United States history.

15. This finding is consistent with what Robert Burgelman has observed. He noted that one of the greatest difficulties encountered by corporate entrepreneurs has been finding the right “beta test sites” where products could be interactively developed and refined with customers. Generally, a new venture’s entrée to the customer was provided by the salesperson representing the firm’s established product lines. This helped the firm develop new products for established markets but not to identify new applications for new technology. See Robert A. Burgelman and Leonard Sayles, Inside Corporate Innovation (New York: The Free Press, 1986) 76–80.

16. I believe this insight—that attacking firms have an advantage in disruptive innovations but not in sustaining ones—clarifies, but is not in conflict with, Foster’s assertions about the attacker’s advantage. The historical examples Foster uses to substantiate his theory generally seem to have been disruptive innovations. See Richard J. Foster, Innovation: The Attacker’s Advantage (New York: Summit Books, 1986).

CHAPTER TWO

Value Networks and the Impetus to Innovate

From the earliest studies of the problems of innovation, scholars, consultants, and managers have tried to explain why leading firms frequently stumble when confronting technology change. Most explanations either zero in on managerial, organizational, and cultural responses to technological change or focus on the ability of established firms to deal with radically new technology; doing the latter requires a very different set of skills from those that an established firm historically has developed. Both approaches, useful in explaining why some companies stumble in the face of technological change, are summarized below. The primary purpose of this chapter, however, is to propose a third theory of why good companies can fail, based upon the concept of a value network. The value network concept seems to have much greater power than the other two theories in explaining what we observed in the disk drive industry.

ORGANIZATIONAL AND MANAGERIAL EXPLANATIONS OF FAILURE

One explanation for why good companies fail points to organizational impediments as the source of the problem. While many analyses of this type stop with such simple rationales as bureaucracy, complacency, or “risk-averse” culture, some remarkably insightful studies exist in this tradition. Henderson and Clark, [1] for example, conclude that companies’ organizational structures typically facilitate component-level innovations, because most product development organizations consist of subgroups that correspond to a product’s components. Such systems work very well as long as the product’s fundamental architecture does not require change. But, say the authors, when architectural technology change is required, this type of structure impedes innovations that require people and groups to communicate and work together in new ways.

This notion has considerable face validity. In one incident recounted in Tracy Kidder’s Pulitzer Prize–winning narrative, The Soul of a New Machine, Data General engineers developing a next-generation minicomputer intended to leapfrog the product position of Digital Equipment Corporation were allowed by a friend of one team member into his facility in the middle of the night to examine Digital’s latest computer, which his company had just bought. When Tom West, Data General’s project leader and a former long-time Digital employee, removed the cover of the DEC minicomputer and examined its structure, he saw “Digital’s organization chart in the design of the product.” [2]

Because an organization’s structure and how its groups work together may have been established to facilitate the design of its dominant product, the direction of causality may ultimately reverse itself: The organization’s structure and the way its groups learn to work together can then affect the way it can and cannot design new products.

CAPABILITIES AND RADICAL TECHNOLOGY AS AN EXPLANATION

In assessing blame for the failure of good companies, the distinction is sometimes made between innovations requiring very different technological capabilities, that is, so-called radical change, and those that build upon well-practiced technological capabilities, often called incremental innovations. [3] The notion is that the magnitude of the technological change relative to the companies’ capabilities will determine which firms triumph after a technology invades an industry. Scholars who support this view find that established firms tend to be good at improving what they have long been good at doing, and that entrant firms seem better suited for exploiting radically new technologies, often because they import the technology into one industry from another, where they had already developed and practiced it.

Clark, for example, has reasoned that companies build the technological capabilities in a product such as an automobile hierarchically and experientially. [4] An organization’s historical choices about which technological problems it would solve and which it would avoid determine the sorts of skills and knowledge it accumulates. When optimal resolution of a product or process performance problem demands a very different set of knowledge than a firm has accumulated, it may very well stumble. The research of Tushman, Anderson, and their associates supports Clark’s hypothesis. [5] They found that firms failed when a technological change destroyed the value of competencies previously cultivated and succeeded when new technologies enhanced them.

The factors identified by these scholars undoubtedly affect the fortunes of firms confronted with new technologies. Yet the disk drive industry displays a series of anomalies accounted for by neither set of theories. Industry leaders first introduced sustaining technologies of every sort, including architectural and component innovations that rendered prior competencies irrelevant and made massive investments in skills and assets obsolete. Nevertheless, these same firms stumbled over technologically straightforward but disruptive changes such as the 8-inch drive.

The history of the disk drive industry, indeed, gives a very different meaning to what constitutes a radical innovation among leading, established firms. As we saw, the nature of the technology involved (components versus architecture and incremental versus radical), the magnitude of the risk, and the time horizon over which the risks needed to be taken had little relationship to the patterns of leadership and followership observed. Rather, if their customers needed an innovation, the leading firms somehow mustered the resources and wherewithal to develop and adopt it. Conversely, if their customers did not want or need an innovation, these firms found it impossible to commercialize even technologically simple innovations.

VALUE NETWORKS AND NEW PERSPECTIVE ON THE DRIVERS OF FAILURE

What, then, does account for the success and failure of entrant and established firms? The following discussion synthesizes from the history of the disk drive industry a new perspective on the relation between success or failure and changes in technology and market structure. The concept of the value network—the context within which a firm identifies and responds to customers’ needs, solves problems, procures input, reacts to competitors, and strives for profit—is central to this synthesis. [6] Within a value network, each firm’s competitive strategy, and particularly its past choices of markets, determines its perceptions of the economic value of a new technology. These perceptions, in turn, shape the rewards different firms expect to obtain through pursuit of sustaining and disruptive innovations. [7] In established firms, expected rewards, in their turn, drive the allocation of resources toward sustaining innovations and away from disruptive ones. This pattern of resource allocation accounts for established firms’ consistent leadership in the former and their dismal performance in the latter.

Value Networks Mirror Product Architecture

Companies are embedded in value networks because their products generally are embedded, or nested hierarchically, as components within other products and eventually within end systems of use. [8] Consider a 1980s-vintage management information system (MIS) for a large organization, as illustrated in Figure 2.1. The architecture of the MIS ties together various components—a mainframe computer; peripherals such as line printers and tape and disk drives; software; a large, air-conditioned room with cables running under a raised floor; and so on. At the next level, the mainframe computer is itself an architected system, comprising such components as a central processing unit, multi-chip packages and circuit boards, RAM circuits, terminals, controllers, and disk drives. Telescoping down still further, the disk drive is a system whose components include a motor, actuator, spindle, disks, heads, and controller. In turn, the disk itself can be analyzed as a system composed of an aluminum platter, magnetic material, adhesives, abrasives, lubricants, and coatings.

Although the goods and services constituting such a system of use may all be produced within a single, extensively integrated corporation such as AT&T or IBM, most are tradable, especially in more mature markets. This means that, while Figure 2.1 is drawn to describe the nested physical architecture of a product system, it also implies the existence of a nested network of producers and markets through which the components at each level are made and sold to integrators at the next higher level in the system. Firms that design and assemble disk drives, for example, such as Quantum and Maxtor, procure read-write heads from firms specializing in the manufacture of those heads, and they buy disks from other firms and spin motors, actuator motors, and integrated circuitry from still others. At the next higher level, firms that design and assemble computers may buy their integrated circuits, terminals, disk drives, IC packaging, and power supplies from various firms that manufacture those particular products. This nested commercial system is a value network.

Figure 2.1 A Nested, or Telescoping, System of Product Architectures

Source: Reprinted from Research Policy 24, Clayton M. Christensen and Richard S. Rosenbloom, “Explaining the Attacker’s Advantage: Technological Paradigms, Organizational Dynamics, and the Value Network,” 233–257, 1995 with kind permission of Elsevier Science–NL, Sara Burgerhartstraat 25, 1055 KV Amsterdam, The Netherlands.

Figure 2.2 illustrates three value networks for computing applications: Reading top to bottom they are the value network for a corporate MIS system-of-use, for portable personal computing products, and for computer-automated design (CAD). Drawn only to convey the concept of how networks are bounded and may differ from each other, these depictions are not meant to represent complete structures.

Metrics of Value

The way value is measured differs across networks. [9] In fact, the unique rank-ordering of the importance of various product performance attributes defines, in part, the boundaries of a value network. Examples in Figure 2.2, listed to the right of the center column of component boxes, show how each value network exhibits a very different rank-ordering of important product attributes, even for the same product. In the top-most value network, disk drive performance is measured in terms of capacity, speed, and reliability, whereas in the portable computing value network, the important performance attributes are ruggedness, low power consumption, and small size. Consequently, parallel value networks, each built around a different definition of what makes a product valuable, may exist within the same broadly defined industry.

Although many components in different systems-of-use may carry the same labels (for example, each network in Figure 2.2 involves read-write heads, disk drives, RAM circuits, printers, software, and so on), the nature of components used may be quite different. Generally, a set of competing firms, each with its own value chain, [10] is associated with each box in a network diagram, and the firms supplying the products and services used in each network often differ (as illustrated in Figure 2.2 by the firms listed to the left of the center column of component boxes).

As firms gain experience within a given network, they are likely to develop capabilities, organizational structures, and cultures tailored to their value network’s distinctive requirements. Manufacturing volumes, the slope of ramps to volume production, product development cycle times, and organizational consensus identifying the customer and the customer’s needs may differ substantially from one value network to the next.

Figure 2.2 Examples of Three Value Networks

Source: Reprinted from Research Policy 24, Clayton M. Christensen and Richard S. Rosenbloom, “Explaining the Attacker’s Advantage: Technological Paradigms, Organizational Dynamics, and the Value Network,” 233–257, 1995 with kind permission of Elsevier Science—NL, Sara Burgerhartstraat 25, 1055 KV Amsterdam, The Netherlands.

Given the data on the prices, attributes, and performance characteristics of thousands of disk drive models sold between 1976 and 1989, we can use a technique called hedonic regression analysis to identify how markets valued individual attributes and how those attribute values changed over time. Essentially, hedonic regression analysis expresses the total price of a product as the sum of individual so-called shadow prices (some positive, others negative) that the market places on each of the product’s characteristics. Figure 2.3 shows some results of this analysis to illustrate how different value networks can place very different values on a given performance attribute. Customers in the mainframe computer value network in 1988 were willing on average to pay $1.65 for an incremental megabyte of capacity; but moving across the minicomputer, desktop, and portable computing value networks, the shadow price of an incremental megabyte of capacity declines to $1.50, $1.45, and $1.17, respectively. Conversely, portable and desktop computing customers were willing to pay a high price in 1988 for a cubic inch of size reduction, while customers in the other networks placed no value on that attribute at all. [11]

Figure 2.3 Difference in the Valuation of Attributes Across Different Value Networks

Cost Structures and Value Networks

The definition of a value network goes beyond the attributes of the physical product. For example, competing within the mainframe computer network shown in Figure 2.2 entails a particular cost structure. Research, engineering, and development costs are substantial. Manufacturing overheads are high relative to direct costs because of low unit volumes and customized product configurations. Selling directly to end users involves significant sales force costs, and the field service network to support the complicated machines represents a substantial ongoing expense. All these costs must be incurred in order to provide the types of products and services customers in this value network require. For these reasons, makers of mainframe computers, and makers of the 14-inch disk drives sold to them, historically needed gross profit margins of between 50 percent and 60 percent to cover the overhead cost structure inherent to the value network in which they competed.

Competing in the portable computer value network, however, entails a very different cost structure. These computer makers incur little expense researching component technologies, preferring to build their machines with proven component technologies procured from vendors. Manufacturing involves assembling millions of standard products in low-labor-cost regions. Most sales are made through national retail chains or by mail order. As a result, companies in this value network can be profitable with gross margins of 15 percent to 20 percent. Hence, just as a value network is characterized by a specific rank-ordering of product attributes valued by customers, it is also characterized by a specific cost structure required to provide the valued products and services.

Each value network’s unique cost structure is illustrated in Figure 2.4. Gross margins typically obtained by manufacturers of 14-inch disk drives, about 60 percent, are similar to those required by mainframe computer makers: 56 percent. Likewise, the margins 8-inch drive makers earned were similar to those earned by minicomputer companies (about 40 percent), and the margins typical of the desktop value network, 25 percent, also typified both the computer makers and their disk drive suppliers.

The cost structures characteristic of each value network can have a powerful effect on the sorts of innovations firms deem profitable. Essentially, innovations that are valued within a firm’s value network, or in a network where characteristic gross margins are higher, will be perceived as profitable. Those technologies whose attributes make them valuable only in networks with lower gross margins, on the other hand, will not be viewed as profitable, and are unlikely to attract resources or managerial interest. (We will explore the impact of each value network’s characteristic cost structures upon the established firms’ mobility and fortunes more fully in chapter 4.)

Figure 2.4 Characteristic Cost Structures of Different Value Networks

Source: Data are from company annual reports and personal interviews with executives from several representative companies in each network.

In sum, the attractiveness of a technological opportunity and the degree of difficulty a producer will encounter in exploiting it are determined by, among other factors, the firm’s position in the relevant value network. As we shall see, the manifest strength of established firms in sustaining innovation and their weakness in disruptive innovation—and the opposite manifest strengths and weaknesses of entrant firms—are consequences not of differences in technological or organizational capabilities between incumbent and entrant firms, but of their positions in the industry’s different value networks.

TECHNOLOGY S-CURVES AND VALUE NETWORKS

The technology S-curve forms the centerpiece of thinking about technology strategy. It suggests that the magnitude of a product’s performance improvement in a given time period or due to a given amount of engineering effort is likely to differ as technologies mature. The theory posits that in the early stages of a technology, the rate of progress in performance will be relatively slow. As the technology becomes better understood, controlled, and diffused, the rate of technological improvement will accelerate. [12] But in its mature stages, the technology will asymptotically approach a natural or physical limit such that ever greater periods of time or inputs of engineering effort will be required to achieve improvements. Figure 2.5 illustrates the resulting pattern.

Many scholars have asserted that the essence of strategic technology management is to identify when the point of inflection on the present technology’s S-curve has been passed, and to identify and develop whatever successor technology rising from below will eventually supplant the present approach. Hence, as depicted by the dotted curve in Figure 2.5, the challenge is to successfully switch technologies at the point where S-curves of old and new intersect. The inability to anticipate new technologies threatening from below and to switch to them in a timely way has often been cited as the cause of failure of established firms and as the source of advantage for entrant or attacking firms. [13]

How do the concepts of S-curves and of value networks relate to each other? [14] The typical framework of intersecting S-curves illustrated in Figure 2.5 is a conceptualization of sustaining technological changes within a single value network, where the vertical axis charts a single measure of product performance (or a rank-ordering of attributes). Note its similarity to Figure 1.4, which measured the sustaining impact of new recording head technologies on the recording density of disk drives. Incremental improvements within each technology drove improvements along each of the individual curves, while movement to new head technologies involved a more radical leap. Recall that there was not a single example in the history of technological innovation in the disk drive industry of an entrant firm leading the industry or securing a viable market position with a sustaining innovation. In every instance, the firms that anticipated the eventual flattening of the current technology and that led in identifying, developing, and implementing the new technology that sustained the overall pace of progress were the leading practitioners of the prior technology. These firms often incurred enormous financial risks, committing to new technologies a decade or more in advance and wiping out substantial bases of assets and skills. Yet despite these challenges, managers of the industry’s established firms navigated the dotted line course shown in Figure 2.5 with remarkable, consistent agility.

Figure 2.5 The Conventional Technology S-Curve

Source: Clayton M. Christensen, “Exploring the Limits of the Technology S-Curve. Part I: Component Technologies,” Production and Operations Management 1, no. 4 (Fall 1992): 340. Reprinted by permission.

A disruptive innovation, however, cannot be plotted in a figure such as 2.5, because the vertical axis for a disruptive innovation, by definition, must measure different attributes of performance than those relevant in established value networks. Because a disruptive technology gets its commercial start in emerging value networks before invading established networks, an S-curve framework such as that in Figure 2.6 is needed to describe it. Disruptive technologies emerge and progress on their own, uniquely defined trajectories, in a home value network. If and when they progress to the point that they can satisfy the level and nature of performance demanded in another value network, the disruptive technology can then invade it, knocking out the established technology and its established practitioners, with stunning speed.

Figures 2.5 and 2.6 illustrate clearly the innovator’s dilemma that precipitates the failure of leading firms. In disk drives (and in the other industries covered later in this book), prescriptions such as increased investments in R&D; longer investment and planning horizons; technology scanning, forecasting, and mapping; as well as research consortia and joint ventures are all relevant to the challenges posed by the sustaining innovations whose ideal pattern is depicted in Figure 2.5. Indeed, the evidence suggests that many of the best established firms have applied these remedies and that they can work when managed well in treating sustaining technologies. But none of these solutions addresses the situation in Figure 2.6, because it represents a threat of a fundamentally different nature.

Figure 2.6 Disruptive Technology S-Curve

Source: Clayton M. Christensen, “Exploring the Limits of the Technology S-Curve. Part I: Component Technologies,” Production and Operations Management 1, no. 4 (Fall 1992): 361. Reprinted by permission.

MANAGERIAL DECISION MAKING AND DISRUPTIVE TECHNOLOGICAL CHANGE

Competition within the value networks in which companies are embedded defines in many ways how the firms can earn their money. The network defines the customers’ problems to be addressed by the firm’s products and services and how much can be paid for solving them. Competition and customer demands in the value network in many ways shape the firms’ cost structure, the firm size required to remain competitive, and the necessary rate of growth. Thus, managerial decisions that make sense for companies outside a value network may make no sense at all for those within it, and vice versa.

We saw, in chapter 1, a stunningly consistent pattern of successful implementation of sustaining innovations by established firms and their failure to deal with disruptive ones. The pattern was consistent because the managerial decisions that led to those outcomes made sense. Good managers do what makes sense, and what makes sense is primarily shaped by their value network.

This decision-making pattern, outlined in the six steps below, emerged from my interviews with more than eighty managers who played key roles in the disk drive industry’s leading firms, both incumbents and entrants, at times when disruptive technologies had emerged. In these interviews I tried to reconstruct, as accurately and from as many points of view as possible, the forces that influenced these firms’ decision-making processes regarding the development and commercialization of technologies either relevant or irrelevant to the value networks in which the firms were at the time embedded. My findings consistently showed that established firms confronted with disruptive technology change did not have trouble developing the requisite technology: Prototypes of the new drives had often been developed before management was asked to make a decision. Rather, disruptive projects stalled when it came to allocating scarce resources among competing product and technology development proposals (allocating resources between the two value networks shown at right and left in Figure 2.6, for example). Sustaining projects addressing the needs of the firms’ most powerful customers (the new waves of technology within the value network depicted in Figure 2.5) almost always preempted resources from disruptive technologies with small markets and poorly defined customer needs.

This characteristic pattern of decisions is summarized in the following pages. Because the experience was so archetypical, the struggle of Seagate Technology, the industry’s dominant maker of 5.25-inch drives, to successfully commercialize the disruptive 3.5-inch drive is recounted in detail to illustrate each of the steps in the pattern. [15]

Step 1: Disruptive Technologies Were First Developed within Established Firms

Although entrants led in commercializing disruptive technologies, their development was often the work of engineers at established firms, using bootlegged resources. Rarely initiated by senior management, these architecturally innovative designs almost always employed off-the-shelf components. Thus, engineers at Seagate Technology, the leading 5.25-inch drive maker, were, in 1985, the second in the industry to develop working prototypes of 3.5-inch models. They made some eighty prototype models before the issue of formal project approval was raised with senior management. The same thing happened earlier at Control Data and Memorex, the dominant 14-inch drive makers, where engineers had designed working 8-inch drives internally, nearly two years before the product appeared in the market.

Step 2: Marketing Personnel Then Sought Reactions from Their Lead Customers

The engineers then showed their prototypes to marketing personnel, asking whether a market for the smaller, less expensive (and lower performance) drives existed. The marketing organization, using its habitual procedure for testing the market appeal of new drives, showed the prototypes to lead customers of the existing product line, asking them for an evaluation. [16] Thus, Seagate marketers tested the new 3.5-inch drives with IBM’s PC Division and other makers of XT-and AT-class desktop personal computers—even though the drives had significantly less capacity than the mainstream desktop market demanded.

Not surprisingly, therefore, IBM showed no interest in Seagate’s disruptive 3.5-inch drives. IBM’s engineers and marketers were looking for 40 and 60 MB drives, and they already had a slot for 5.25-inch drives designed into their computer; they needed new drives that would take them further along their established performance trajectory. Finding little customer interest, Seagate’s marketers drew up pessimistic sales forecasts. In addition, because the products were simpler, with lower performance, forecast profit margins were lower than those for higher performance products, and Seagate’s financial analysts, therefore, joined their marketing colleagues in opposing the disruptive program. Working from such input, senior managers shelved the 3.5-inch drive—just as it was becoming firmly established in the laptop market.

This was a complex decision, made in a context of competing proposals to expend the same resources to develop new products that marketers felt were critical to remaining competitive with current customers and achieving aggressive growth and profit targets. “We needed a new model,” recalled a former Seagate manager, “which could become the next ST412 [a very successful product generating $300 million sales annually in the desktop market that was near the end of its life cycle]. Our forecasts for the 3.5-inch drive were under $50 million because the laptop market was just emerging, and the 3.5-inch product just didn’t fit the bill.”

Seagate managers made an explicit decision not to pursue the disruptive technology. In other cases, managers did approve resources for pursuing a disruptive product—but, in the day-to-day decisions about how time and money would actually be allocated, engineers and marketers, acting in the best interests of the company, consciously and unconsciously starved the disruptive project of resources necessary for a timely launch.

When engineers at Control Data, the leading 14-inch drive maker, were officially chartered to develop CDC’s initial 8-inch drives, its customers were looking for an average of 300 MB per computer, whereas CDC’s earliest 8-inch drives offered less than 60 MB. The 8-inch project was given low priority, and engineers assigned to its development kept getting pulled off to work on problems with 14-inch drives being designed for more important customers. Similar problems plagued the belated launches of Quantum’s and Micropolis’s 5.25-inch products.

Step 3: Established Firms Step Up the Pace of Sustaining Technological Development

In response to the needs of current customers, the marketing managers threw impetus behind alternative sustaining projects, such as incorporating better heads or developing new recording codes. These gave customers what they wanted and could be targeted at large markets to generate the necessary sales and profits for maintaining growth. Although often involving greater development expense, such sustaining investments appeared far less risky than investments in the disruptive technology: The customers existed, and their needs were known.

Seagate’s decision to shelve the 3.5-inch drive in 1985 to 1986, for example, seems starkly rational. Its view downmarket (in terms of the disk drive trajectory map) was toward a small total market forecast for 1987 for 3.5-inch drives. Gross margins in that market were uncertain, but manufacturing executives predicted that costs per megabyte for 3.5-inch drives would be much higher than for 5.25-inch drives. Seagate’s view upmarket was quite different. Volumes in 5.25-inch drives with capacities of 60 to 100 MB were forecast to be $500 million by 1987. Companies serving the 60 to 100 MB market were earning gross margins of between 35 and 40 percent, whereas Seagate’s margins in its high-volume 20 MB drives were between 25 and 30 percent. It simply did not make sense for Seagate to put its resources behind the 3.5-inch drive when competing proposals to move upmarket by developing its ST251 line of drives were also being actively evaluated.

After Seagate executives shelved the 3.5-inch project, the firm began introducing new 5.25-inch models at a dramatically accelerated rate. In 1985, 1986, and 1987, the numbers of new models annually introduced as a percentage of the total number of its models on the market in the prior year were 57, 78, and 115 percent, respectively. And during the same period, Seagate incorporated complex and sophisticated new component technologies such as thin-film disks, voice-coil actuators, [17] RLL codes, and embedded SCSI interfaces. Clearly, the motivation in doing this was to win the competitive wars against other established firms, which were making similar improvements, rather than to prepare for an attack by entrants from below. [18]

Step 4: New Companies Were Formed, and Markets for the Disruptive Technologies Were Found by Trial and Error

New companies, usually including frustrated engineers from established firms, were formed to exploit the disruptive product architecture. The founders of the leading 3.5-inch drive maker, Conner Peripherals, were disaffected employees from Seagate and Miniscribe, the two largest 5.25-inch manufacturers. The founders of 8-inch drive maker Micropolis came from Pertec, a 14-inch drive manufacturer, and the founders of Shugart and Quantum defected from Memorex. [19]

The start-ups, however, were as unsuccessful as their former employers in attracting established computer makers to the disruptive architecture. Consequently, they had to find new customers. The applications that emerged in this very uncertain, probing process were the minicomputer, the desktop personal computer, and the laptop computer. In retrospect, these were obvious markets for hard drives, but at the time, their ultimate size and significance were highly uncertain. Micropolis was founded before the emergence of the desk-side minicomputer and word processor markets in which its products came to be used. Seagate began when personal computers were simple toys for hobbyists, two years before IBM introduced its PC. And Conner Peripherals got its start before Compaq knew the potential size of the portable computer market. The founders of these firms sold their products without a clear marketing strategy— essentially selling to whoever would buy. Out of what was largely a trial-and-error approach to the market, the ultimately dominant applications for their products emerged.

Step 5: The Entrants Moved Upmarket

Once the start-ups had discovered an operating base in new markets, they realized that, by adopting sustaining improvements in new component technologies, [20] they could increase the capacity of their drives at a faster rate than their new market required. They blazed trajectories of 50 percent annual improvement, fixing their sights on the large, established computer markets immediately above them on the performance scale.

The established firms’ views downmarket and the entrant firms’ views upmarket were asymmetrical. In contrast to the unattractive margins and market size that established firms saw when eyeing the new, emerging markets for simpler drives, the entrants saw the potential volumes and margins in the upscale, high-performance markets above them as highly attractive. Customers in these established markets eventually embraced the new architectures they had rejected earlier, because once their needs for capacity and speed were met, the new drives’ smaller size and architectural simplicity made them cheaper, faster, and more reliable than the older architectures. Thus, Seagate, which started in the desktop personal computer market, subsequently invaded and came to dominate the minicomputer, engineering workstation, and mainframe computer markets for disk drives. Seagate, in turn, was driven from the desktop personal computer market for disk drives by Conner and Quantum, the pioneering manufacturers of 3.5-inch drives.

Step 6: Established Firms Belatedly Jumped on the Bandwagon to Defend Their Customer Base

When the smaller models began to invade established market segments, the drive makers that had initially controlled those markets took their prototypes off the shelf (where they had been put in Step 3) and introduced them in order to defend their customer base in their own market. By this time, of course, the new architecture had shed its disruptive character and become fully performance-competitive with the larger drives in the established markets. Although some established manufacturers were able to defend their market positions through belated introduction of the new architecture, many found that the entrant firms had developed insurmountable advantages in manufacturing cost and design experience, and they eventually withdrew from the market. The firms attacking from value networks below brought with them cost structures set to achieve profitability at lower gross margins. The attackers therefore were able to price their products profitably, while the defending, established firms experienced a severe price war.

For established manufacturers that did succeed in introducing the new architectures, survival was the only reward. None ever won a significant share of the new market; the new drives simply cannibalized sales of older products to existing customers. Thus, as of 1991, almost none of Seagate’s 3.5-inch drives had been sold to portable/laptop manufacturers: Its 3.5-inch customers still were desktop computer manufacturers, and many of its 3.5-inch drives continued to be shipped with frames permitting them to be mounted in XT-and AT-class computers designed to accommodate 5.25-inch drives.

Control Data, the 14-inch leader, never captured even a 1 percent share of the minicomputer market. It introduced its 8-inch drives nearly three years after the pioneering start-ups did, and nearly all of its drives were sold to its existing mainframe customers. Miniscribe, Quantum, and Micropolis all had the same cannibalistic experience when they belatedly introduced disruptive technology drives. They failed to capture a significant share of the new market, and at best succeeded in defending a portion of their prior business.

The popular slogan “stay close to your customers” appears not always to be robust advice. [21] One instead might expect customers to lead their suppliers toward sustaining innovations and to provide no leadership—or even to explicitly mislead—in instances of disruptive technology change. [22]

FLASH MEMORY AND THE VALUE NETWORK

The predictive power of the value network framework is currently being tested with the emergence of flash memory: a solid-state semiconductor memory technology that stores data on silicon memory chips. Flash differs from conventional dynamic random access memory (DRAM) technology in that the chip retains the data even when the power is off. Flash memory is a disruptive technology. Flash chips consume less than 5 percent of the power that a disk drive of equivalent capacity would consume, and because they have no moving parts, they are far more rugged than disk memory. Flash chips have disadvantages, of course. Depending on the amount of memory, the cost per megabyte of flash can be between five and fifty times greater than disk memory. And flash chips are not as robust for writing: They can only be overwritten a few hundred thousand times before wearing out, rather than a few million times for disk drives.

The initial applications for flash memory were in value networks quite distant from computing; they were in devices such as cellular phones, heart monitoring devices, modems, and industrial robots in which individually packaged flash chips were embedded. Disk drives were too big, too fragile, and used too much power to be used in these markets. By 1994, these applications for individually packaged flash chips—“socket flash” in industry parlance—accounted for $1.3 billion in industry revenues, having grown from nothing in 1987.

In the early 1990s, the flash makers produced a new product format, called a flash card: credit card–sized devices on which multiple flash chips, linked and governed by controller circuitry, were mounted. The chips on flash cards were controlled by the same control circuitry, SCSI (Small Computer Standard Interface, an acronym first used by Apple), as was used in disk drives, meaning that in concept, a flash card could be used like a disk drive for mass storage. The flash card market grew from $45 million in 1993 to $80 million in 1994, and forecasters were eyeing a $230 million flash card market by 1996.

Will flash cards invade the disk drive makers’ core markets and supplant magnetic memory? If they do, what will happen to the disk drive makers? Will they stay atop their markets, catching this new technological wave? Or will they be driven out?

The Capabilities Viewpoint

Clark’s concept of technological hierarchies (see note 4) focuses on the skills and technological understanding that a company accumulates as the result of the product and process technology problems it has addressed in the past. In evaluating the threat to the disk drive makers of flash memory, someone using Clark’s framework, or the related findings of Tushman and Anderson (see note 5), would focus on the extent to which disk drive makers have historically developed expertise in integrated circuit design and in the design and control of devices composed of multiple integrated circuits. These frameworks would lead us to expect that drive makers will stumble badly in their attempts to develop flash products if they have limited expertise in these domains and will succeed if their experience and expertise are deep.

On its surface, flash memory involves radically different electronics technology than the core competence of disk drive makers (magnetics and mechanics). But such firms as Quantum, Seagate, and Western Digital have developed deep expertise in custom integrated circuit design through embedding increasingly intelligent control circuitry and cache memory in their drives. Consistent with the practice in much of the ASIC (application-specific integrated circuit) industry, their controller chips are fabricated by independent, third-party fabricators that own excess clean room semiconductor processing capacity.

Each of today’s leading disk drive manufacturers got its start by designing drives, procuring components from independent suppliers, assembling them either in its own factories or by contract, and then selling them. The flash card business is very similar. Flash card makers design the card and procure the component flash chips; they design and have fabricated an interface circuit, such as SCSI, to govern the drive’s interaction with the computing device; they assemble them either in-house or by contract; and they then market them.

In other words, flash memory actually builds upon important competencies that many drive makers have developed. The capabilities viewpoint, therefore, would lead us to expect that disk drive makers may not stumble badly in bringing flash storage technology to the market. More specifically, the viewpoint predicts that those firms with the deepest experience in IC design—Quantum, Seagate, and Western Digital—will bring flash products to market quite readily. Others, which historically outsourced much of their electronic circuit design, may face more of a struggle.

This has, indeed, been the case to date. Seagate entered the flash market in 1993 via its purchase of a 25 percent equity stake in Sundisk Corporation. Seagate and SunDisk together designed the chips and cards; the chips were fabricated by Matsushita, and the cards were assembled by a Korean manufacturer, Anam. Seagate itself marketed the cards. Quantum entered with a different partner, Silicon Storage Technology, which designed the chips that were then fabricated and assembled by contract.

The Organizational Structure Framework

Flash technology is what Henderson and Clark would call radical technology. Its product architecture and fundamental technological concept are novel compared to disk drives. The organizational structure viewpoint would predict that, unless they created organizationally independent groups to design flash products, established firms would stumble badly. Seagate and Quantum did, indeed, rely on independent groups and did develop competitive products.

The Technology S-Curve Framework

The technology S-curve is often used to predict whether an emerging technology is likely to supplant an established one. The operative trigger is the slope of the curve of the established technology. If the curve has passed its point of inflection, so that its second derivative is negative (the technology is improving at a decreasing rate), then a new technology may emerge to supplant the established one. Figure 2.7 shows that the S-curve for magnetic disk recording still has not hit its point of inflection: Not only is the areal density improving, as of 1995, it was improving at an increasing rate.

The S-curve framework would lead us to predict, therefore, that whether or not established disk drive companies possess the capability to design flash cards, flash memory will not pose a threat to them until the magnetic memory S-curve has passed its point of inflection and the rate of improvement in density begins to decline.

Insights from the Value Network Framework

The value network framework asserts that none of the foregoing frameworks is a sufficient predictor of success. Specifically, even where established firms did not possess the requisite technological skills to develop a new technology, they would marshal the resources to develop or acquire them if their customers demanded it. Furthermore, the value network suggests that technology S-curves are useful predictors only with sustaining technologies. Disruptive technologies generally improve at a parallel pace with established ones—their trajectories do not intersect. The S-curve framework, therefore, asks the wrong question when it is used to assess disruptive technology. What matters instead is whether the disruptive technology is improving from below along a trajectory that will ultimately intersect with what the market needs.

Figure 2.7 Improvements in Areal Density of New Disk Drives (Densities in Millions of Bits per Square Inch)

Source: Data are from various issues of Disk/Trend Report.

The value network framework would assert that even though firms such as Seagate and Quantum are able technologically to develop competitive flash memory products, whether they invest the resources and managerial energy to build strong market positions in the technology will depend on whether flash memory can be initially valued and deployed within the value networks in which the firms make their money.

As of 1996, flash memory can only be used in value networks different from those of the typical disk drive maker. This is illustrated in Figure 2.8, which plots the average megabytes of capacity of flash cards introduced each year between 1992 and 1995, compared with the capacities of 2.5-and 1.8-inch drives and with the capacity demanded in the notebook computer market. Even though they are rugged and consume little power, flash cards simply don’t yet pack the capacity to become the main mass storage devices in notebook computers. And the price of the flash capacity required to meet what the low end of the portable computing market demands (about 350 MB in 1995) is too high: The cost of that much flash capacity would be fifty times higher than comparable disk storage. [23]

Figure 2.8 Comparison of Disk Drive Memory Capacity to Flash Card

Source: Data are from various issues of Disk/Trend Report.

The low power consumption and ruggedness of flash certainly have no value and command no price premium on the desktop. There is, in other words, no way to use flash today in the markets where firms such as Quantum and Seagate make their money.

Hence, because flash cards are being used in markets completely different from those Quantum and Seagate typically engage—palmtop computers, electronic clipboards, cash registers, electronic cameras, and so on—the value network framework would predict that firms similar to Quantum and Seagate are not likely to build market-leading positions in flash memory. This is not because the technology is too difficult or their organizational structures impede effective development, but because their resources will become absorbed in fighting for and defending larger chunks of business in the mainstream disk drive value networks in which they currently make their money.

Indeed, the marketing director for a leading flash card producer observed, “We’re finding that as hard disk drive manufacturers move up to the gigabyte range, they are unable to be cost competitive at the lower capacities. As a result, disk drive makers are pulling out of markets in the 10 to 40 megabyte range and creating a vacuum into which flash can move.” [24]

The drive makers’ efforts to build flash card businesses have in fact floundered. By 1995, neither Quantum nor Seagate had built market shares of even 1 percent of the flash card market. Both companies subsequently concluded that the opportunity in flash cards was not yet substantial enough, and withdrew their products from the market the same year. Seagate retained its minority stake in SunDisk (renamed SanDisk), however, a strategy which, as we shall see, is an effective way to address disruptive technology.

IMPLICATIONS OF THE VALUE NETWORK FRAMEWORK FOR INNOVATION

Value networks strongly define and delimit what companies within them can and cannot do. This chapter closes with five propositions about the nature of technological change and the problems successful incumbent firms encounter, which the value network perspective highlights.

1. The context, or value network, in which a firm competes has a profound influence on its ability to marshal and focus the necessary resources and capabilities to overcome the technological and organizational hurdles that impede innovation. The boundaries of a value network are determined by a unique definition of product performance—a rank-ordering of the importance of various performance attributes differing markedly from that employed in other systems-of-use in a broadly defined industry. Value networks are also defined by particular cost structures inherent in addressing customers’ needs within the network.

2. A key determinant of the probability of an innovative effort’s commercial success is the degree to which it addresses the well-understood needs of known actors within the value network. Incumbent firms are likely to lead their industries in innovations of all sorts—architecture and components—that address needs within their value network, regardless of intrinsic technological character or difficulty. These are straightforward innovations; their value and application are clear. Conversely, incumbent firms are likely to lag in the development of technologies—even those in which the technology involved is intrinsically simple—that only address customers’ needs in emerging value networks. Disruptive innovations are complex because their value and application are uncertain, according to the criteria used by incumbent firms.

3. Established firms’ decisions to ignore technologies that do not address their customers’ needs become fatal when two distinct trajectories interact. The first defines the performance demanded over time within a given value network, and the second traces the performance that technologists are able to provide within a given technological paradigm. The trajectory of performance improvement that technology is able to provide may have a distinctly different slope from the trajectory of performance improvement demanded in the system-of-use by downstream customers within any given value network. When the slopes of these two trajectories are similar, we expect the technology to remain relatively contained within its initial value network. But when the slopes differ, new technologies that are initially performance-competitive only within emerging or commercially remote value networks may migrate into other networks, providing a vehicle for innovators in new networks to attack established ones. When such an attack occurs, it is because technological progress has diminished the relevancce of differences in the rank-ordering of performance attributes across different value networks. For example, the disk drive attributes of size and weight were far more important in the desktop computing value network than they were in the mainframe and minicomputer value networks. When technological progress in 5.25-inch drives enabled manufacturers to satisfy the attribute prioritization in the mainframe and minicomputer networks, which prized total capacity and high speed, as well as that in the desktop network, the boundaries between the value networks ceased to be barriers to entry for 5.25-inch drive makers.

4. Entrant firms have an attacker’s advantage over established firms in those innovations—generally new product architectures involving little new technology per se—that disrupt or redefine the level, rate, and direction of progress in an established technological trajectory. This is so because such technologies generate no value within the established network. The only way established firms can lead in commercializing such technologies is to enter the value network in which they create value. As Richard Tedlow noted in his history of retailing in America (in which supermarkets and discount retailing play the role of disruptive technologies), “the most formidable barrier the established firms faced is that they did not want to do this.” [25]

5. In these instances, although this “attacker’s advantage” is associated with a disruptive technology change, the essence of the attacker’s advantage is in the ease with which entrants, relative to incumbents, can identify and make strategic commitments to attack and develop emerging market applications, or value networks. At its core, therefore, the issue may be the relative flexibility of successful established firms versus entrant firms to change strategies and cost structures, not technologies.

These propositions provide new dimensions for analyzing technological innovation. In addition to the required capabilities inherent in new technologies and in the innovating organization, firms faced with disruptive technologies must examine the implications of innovation for their relevant value networks. The key considerations are whether the performance attributes implicit in the innovation will be valued within the networks already served by the innovator; whether other networks must be addressed or new ones created in order to realize value for the innovation; and whether market and technological trajectories may eventually intersect, carrying technologies that do not address customers’ needs today to squarely address their needs in the future.

These considerations apply not simply to firms grappling with the most modern technologies, such as the fast-paced, complex advanced electronic, mechanical, and magnetics technologies covered in this chapter. Chapter 3 examines them in the context of a very different industry: earthmoving equipment.

NOTES

1. See Rebecca M. Henderson and Kim B. Clark, “Architectural Innovation: The Reconfiguration of Existing Systems and the Failure of Established Firms” Administrative Science Quarterly (35), 1990, 9–30.

2. Tracy Kidder, The Soul of a New Machine (New York: Avon Books, Inc., 1981).

3. A few scholars have sought to measure the proportion of technological progress attributable to radical versus incremental advances. In an empirical study of a series of novel processes in petroleum refining, for example, John Enos found that half the economic benefits of new technology came from process improvements introduced after a new technology was commercially established. See J. L. Enos, “Invention and Innovation in the Petroleum Refining Industry,” in The Rate and Direction of Inventive Activity: Economic and Social Factors, National Bureau of Economic Research Report (Princeton, NJ: Princeton University Press, 1962), 299–321. My study of the disk drive industry has shown the same result. Half the advance in areal density (megabits per square inch of disk surface) can be attributed to new component technologies and half to incremental improvements in existing components and refinements in system design. See Clayton M. Christensen,

“Exploring the Limits of the Technology S-Curve,” Production and Operations Management (1), 1992, 334–366.

4. See Kim B. Clark, “The Interaction of Design Hierarchies and Market Concepts in Technological Evolution,” Research Policy (14), 1985, 235–251. Clark suggests, for example, that the early selections by automotive engineers of gasoline over steam or electrically powered engines defined the technical agenda for subsequent generations of engineers, who consequently did not pursue refinements in electric or steam propulsion. Clark has thus shown that the design skills and technological knowledge resident in companies today result from the cumulative choices engineers have made of what to tackle versus what to leave alone. Clark posits that technological improvements requiring that companies build upon or extend an existing cumulative body of knowledge favor an industry’s established firms. Conversely, when changes require a completely different body of knowledge, established firms will be at a disadvantage compared to firms that had already accumulated a different hierarchically structured body of knowledge, most likely in another industry.

5. See, for example, Michael L. Tushman and Philip Anderson, “Technological Discontinuities and Organizational Environments,” Administrative Science Quarterly (31), 1986, 439–465; and Philip Anderson and Michael Tushman, “Technological Discontinuities and Dominant Designs,” Administrative Science Quarterly (35), 1990, 604–633.

6. The concept of value network builds on Giovanni Dosi’s concept of technological paradigms. See Giovanni Dosi, “Technological Paradigms and Technological Trajectories, Research Policy (11), 1982, 147–162. Dosi characterizes a technological paradigm as a “pattern of solution of selected technological problems, based on selected principles derived from natural sciences and on selected material technologies” (152). New paradigms represent discontinuities in trajectories of progress as defined within earlier paradigms. They tend to redefine the very meaning of progress, and point technologists toward new classes of problems as the targets of ensuing normal technology development. The question examined by Dosi—how new technologies are selected and retained—is closely related to the question of why firms succeed or fail as beneficiaries of such changes.

7. Value network, as presented here, draws heavily on ideas I developed jointly with Professor Richard S. Rosenbloom and which are summarized in two journal articles: Clayton M. Christensen and Richard S. Rosenbloom, “Explaining the Attacker’s Advantage: The Technological Paradigms, Organizational Dynamics, and the Value Network,” Research Policy (24), 1995, 233–257; and Richard S. Rosenbloom and Clayton M. Christensen, “Technological Discontinuities, Organizational Capabilities, and Strategic Commitments,” Industrial and Corporate Change (3), 1994, 655–685. I am heavily indebted to Professor Rosenbloom for his contributions to the development of these perspectives.

8. See D. L. Marples, “The Decisions of Engineering Design,” IEEE Transactions on Engineering Management EM8, 1961, 55–71; and C. Alexander, Notes on the Synthesis of Form (Cambridge, MA: Harvard University Press, 1964).

9. On this point, too, correspondence between the concept of the value network and Dosi’s concept of technological paradigms is strong. (See note 6.) The scope and boundaries of a value network are defined by the dominant technological paradigm and the corresponding technological trajectory employed at the higher levels of the network. As Dosi suggests, value can be defined as a function of the dominant technological paradigm in the ultimate system of use in the value network.

10. Michael Porter, Competitive Advantage (New York: The Free Press, 1985).

11. A more complete report of this analysis can be found in chapter 7 of Clayton M. Christensen, The Innovator’s Challenge: Understanding the Influence of Market Environment on Processes of Technology Development in the Rigid Disk Drive Industry, thesis, Harvard University Graduate School of Business Administration, 1992.

12. D. Sahal, Patterns of Technological Innovation (London: Addison Wesley, 1981).

13. The most widely read proponent of this view is Richard Foster; see, for example, his Innovation: The Attacker’s Advantage (New York: Summit Books, 1986).

14. The insights summarized here are articulated more completely in C. M. Christensen, “Exploring the Limits of the Technology S-Curve,” Production and Operations Management (1), 1992, 334–366.

15. A fuller account of similar decisions made in other firms can be found in Clayton M. Christensen, The Innovator’s Challenge: Understanding the Influence of Market Environment on Processes of Technology Development in the Rigid Disk Drive Industry, thesis, Harvard University Graduate School of Business Administration, 1992.

16. This procedure is consistent with Robert Burgelman’s observation that one of the greatest difficulties encountered by corporate entrepreneurs is in finding the right “beta test sites,” where products can be interactively developed and refined with customers. Generally, the entrée to the customer was provided by the salesperson who sold the firm’s established product lines. This helped the firm develop new products for established markets, but not identify new applications for its new technology. See Robert Burgelman and Leonard Sayles, Inside Corporate Innovation (New York: The Free Press, 1986) 76–80. Professor Rebecca Henderson pointed out to me that this tendency always to take new technologies to mainstream customers reflects a rather narrow marketing competence—that although many scholars tend to frame the issue as one of technological competence, such inability to find new markets for new technologies may be a firm’s most serious handicap in innovation.

17. Voice coil motors were more expensive than the stepper motors that Seagate had previously used. While not new to the market, they were new to Seagate.

18. This is consistent with the findings reported by Arnold Cooper and Dan Schendel in “Strategic Responses to Technological Threats,” Business Horizons (19), February, 1976, 61–69.

19. Ultimately, nearly all North American disk drive manufacturers can trace their founders’ genealogy to IBM’s San Jose division, which developed and manufactured its magnetic recording products. See Clayton M. Christensen,

“The Rigid Disk Drive Industry: A History of Commercial and Technological Turbulence,” Business History Review (67), Winter, 1993, 531–588.

20. In general, these component technologies were developed within the largest of the established firms that dominated the established markets above these entrants. This is because new components generally (but not always) have a sustaining impact on technology trajectories. These high-end, established firms typically were engaged in the hottest pursuit of sustaining innovations.

21. The research of Eric von Hippel, frequently cited as evidence of the value of listening to customers, indicates that customers originate a large majority of new product ideas (see Eric von Hippel, The Sources of Innovation [New York: Oxford University Press, 1988]). One fruitful avenue for future research would be to revisit von Hippel’s data in light of the framework presented here. The value network framework would predict that the innovations toward which the customers in von Hippel’s study led their suppliers would have been sustaining innovations. We would expect disruptive innovations to have come from other sources.

22. Henderson saw similar potential danger for being misled by customers in her study of photolithographic aligner equipment manufacturers. See Rebecca M. Henderson, “Keeping Too Close to Your Customers,” Massachusetts Institute of Technology Sloan School of Management working paper, 1993.

23. Many industry observers have noted that there seems to be a floor on the cost of making a disk drive, somewhere around $120 per device, below which even the best manufacturers cannot plunge. This is the basic cost of designing, producing, and assembling the requisite components. Drive makers keep reducing costs per megabyte by continuously increasing the number of megabytes available in that basic $120 box. The effect of this floor on the competition between disk drives and flash cards may be profound. It means that in low-capacity applications, as the price of flash memory falls, flash will become cost-competitive with disk memory. The frontier above which magnetic disk drives have lower costs per megabyte than flash will keep moving upmarket, in a manner perfectly analogous to the upmarket movement of larger disk drive architectures. Experts predicted, in fact, that by 1997, a 40 MB flash card would be priced comparably to a 40 MB disk drive.

24. Lewis H. Young, “Samsung Banks on Tiny Flash Cell,” Electronic Business Buyer (21), July, 1995, 28.

25. Richard Tedlow, New and Improved: A History of Mass Marketing in America (Boston: Harvard Business School Press, 1994).

CHAPTER THREE

Disruptive Technological Change in the Mechanical Excavator Industry

Excavators and their steam shovel predecessors are huge pieces of capital equipment sold to excavation contractors. While few observers consider this a fast-moving, technologically dynamic industry, it has points in common with the disk drive industry: Over its history, leading firms have successfully adopted a series of sustaining innovations, both incremental and radical, in components and architecture, but almost the entire population of mechanical shovel manufacturers was wiped out by a disruptive technology—hydraulics—that the leaders’ customers and their economic structure had caused them initially to ignore. Although in disk drives such invasions of established markets occurred within a few years of the initial emergence of each disruptive technology, the triumph of hydraulic excavators took twenty years. Yet the disruptive invasion proved just as decisive and difficult to counter in excavators as those in the disk drive industry. [1]

LEADERSHIP IN SUSTAINING TECHNOLOGICAL CHANGE

From William Smith Otis’ invention of the steam shovel in 1837 through the early 1920s, mechanical earthmoving equipment was steam-powered. A central boiler sent steam through pipes to small steam engines at each point where power was required in the machine. Through a system of pulleys, drums, and cables, these engines manipulated frontward-scooping buckets, as illustrated in Figure 3.1. Originally, steam shovels were mounted on rails and used to excavate earth in railway and canal construction. American excavator manufacturers were tightly clustered in northern Ohio and near Milwaukee.

In the early 1920s, when there were more than thirty-two steam shovel manufacturers based in the United States, the industry faced a major technological upheaval, as gasoline-powered engines were substituted for steam power. [2] This transition to gasoline power falls into the category that Henderson and Clark label radical technological transition. The fundamental technological concept in a key component (the engine) changed from steam to internal combustion, and the basic architecture of the product changed. Where steam shovels used steam pressure to power a set of steam engines to extend and retract the cables that actuated their buckets, gasoline shovels used a single engine and a very different system of gearing, clutches, drums, and brakes to wind and unwind the cable. Despite the radical nature of the technological change, however, gasoline technology had a sustaining impact on the mechanical excavator industry. Gasoline engines were powerful enough to enable contractors to move earth faster, more reliably, and at lower cost than any but the very largest steam shovels.

Figure 3.1 Cable-Actuated Mechanical Shovel Manufactured by Osgood General

Source: Osgood General photo in Herbert L. Nichols, Jr., Moving the Earth: The Workbook of Excavation (Greenwich, CT: North Castle, 1955).

The leading innovators in gasoline engine technology were the industry’s dominant firms, such as Bucyrus, Thew, and Marion. Twenty-three of the twenty-five largest makers of steam shovels successfully negotiated the transition to gasoline power. [3] As Figure 3.2 shows, there were a few entrant firms among the gasoline technology leaders in the 1920s, but the established firms dominated this transition.

Beginning in about 1928, the established manufacturers of gasoline-powered shovels initiated the next major, but less radical, sustaining technological transition—to shovels powered by diesel engines and electric motors. A further transition, made after World War II, introduced the arched boom design, which allowed longer reach, bigger buckets, and better down-reaching flexibility. The established firms continued to embrace and succeed with each of these innovations.

Figure 3.2 Manufacturers of Gasoline-Powered Cable Shovels, 1920–1934

Source: Data are from the Historical Construction Equipment Association and from The Thomas Register, various years.

Excavation contractors themselves actually pioneered a number of other important sustaining innovations, first modifying their own equipment in the field to make it perform better and then manufacturing excavators incorporating those features to sell to the broader market. [4]

THE IMPACT OF DISRUPTIVE HYDRAULICS TECHNOLOGY

The next major technological change precipitated widespread failure in the industry. Beginning shortly after World War II and continuing through the late 1960s, while the dominant source of power remained the diesel engine, a new mechanism emerged for extending and lifting the bucket: hydraulically actuated systems replaced the cable-actuated systems. Only four of the thirty or so established manufacturers of cable-actuated equipment in business in the 1950s (Insley, Koehring, Little Giant, and Link Belt) had successfully transformed themselves into sustainable hydraulic excavator manufacturers by the 1970s. A few others survived by withdrawing into making such equipment as huge, cable-actuated draglines for strip mining and dredging. [5] Most of the others failed. The firms that overran the excavation equipment industry at this point were all entrants into the hydraulics generation: J. I. Case, John Deere, Drott, Ford, J. C. Bamford, Poclain, International Harvester, Caterpillar, O & K, Demag, Leibherr, Komatsu, and Hitachi. [6] Why did this happen?

Performance Demanded in the Mechanical Excavator Market

Excavators are one of many types of earthmoving equipment. Some equipment, such as bulldozers, loaders, graders, and scrapers, essentially push, smooth, and lift earth. Excavators [7] have been used to dig holes and trenches, primarily in three markets: first and largest, the general excavation market, composed of contractors who dig holes for basements or civil engineering projects such as canal construction; second, sewer and piping contractors, who generally dig long trenches; and third, open pit or strip mining. In each of these markets, contractors have tended to measure the functionality of mechanical excavators by their reach or extension distance and by the cubic yards of earth lifted in a single scoop. [8]

In 1945, sewer and piping contractors used machines whose bucket capacity averaged about 1 cubic yard (best for digging relatively narrow trenches), while the average general excavation contractor used excavators that hefted 2^1_2 cubic yards per scoop and mining contractors used shovels holding about 5 cubic yards. The average bucket capacity used in each of these markets increased at about 4 percent per year, a rate of increase constrained by other factors in the broader system-of-use. The logistical problems of transporting large machines into and out of typical construction sites, for example, helped limit the rate of increase demanded by contractors.

The Emergence and Trajectory of Improvement of Hydraulic Excavation

The first hydraulic excavator was developed by a British company, J. C. Bamford, in 1947. Similar products then emerged simultaneously in several American companies in the late 1940s, among them, the Henry Company, of Topeka, Kansas, and Sherman Products, Inc., of Royal Oak, Michigan. The approach was labeled “Hydraulically Operated Power Take-Off,” yielding an acronym that became the name of the third entrant to hydraulic excavating in the late 1940s, HOPTO. [9]

Their machines were called backhoes because they were mounted on the back of industrial or farm tractors. Backhoes excavated by extending the shovel out, pushing it down into the earth, [10] curling or articulating the shovel under the slice of earth, and lifting it up out of the hole. Limited by the power and strength of available hydraulic pumps’ seals, the capacity of these early machines was a mere 1_4 cubic yard, as graphed in Figure 3.3. Their reach was also limited to about six feet. Whereas the best cable excavators could rotate a full 360 degrees on their track base, the most flexible backhoes could rotate only 180 degrees.

Because their capacity was so small and their reach so short, hydraulic excavators were of no use to mining, general excavation, or sewer contractors, who were demanding machines with buckets that held 1 to 4 cubic yards. As a result, the entrant firms had to develop a new application for their products. They began to sell their excavators as attachments for the back of small industrial and farm tractors made by Ford, J. I. Case, John Deere, International Harvester, and Massey Ferguson. Small residential contractors purchased these units to dig narrow ditches from water and sewer lines in the street to the foundations of houses under construction. These very small jobs had never warranted the expense or time required to bring in a big, imprecise, cable-actuated, track-driven shovel, so the trenches had always been dug by hand. Hydraulic backhoes attached to highly mobile tractors could do these jobs in less than an hour per house, and they became extremely popular with contractors building large tract subdivisions during the housing booms that followed World War II and the Korean War. These early backhoes were sold through tractor and implement dealerships accustomed to dealing with small customers.

Figure 3.3 Disruptive Impact of Hydraulics Technology in the Mechanical Excavator Market

Source: Data are from the Historical Construction Equipment Association.

The early users of hydraulic excavators were, in a word, very different from the mainstream customers of the cable shovel manufacturers—in size, in needs, and in the distribution channels through which they bought. They constituted a new value network for mechanical excavation. Interestingly, just as the performance of smaller-architecture disk drives was measured in different metrics than the performance of large drives (weight, ruggedness, and power consumption versus capacity and speed), the performance of the first backhoes was measured differently from the perfor mance of cable-actuated equipment. The metrics featured most prominently in early product literature of hydraulic backhoes were shovel width (contractors wanted to dig narrow, shallow trenches) and the speed and maneuverability of the tractor. Figure 3.4, excerpted from an early product brochure from Sherman Products for its “Bobcat” hydraulic back-hoe, illustrates this. Sherman called its Bobcat a “digger,” showed it operating in tight quarters, and claimed it could travel over sod with minimum damage. The Bobcat was mounted on a Ford tractor. (Ford subsequently acquired the Sherman Bobcat line.) The featured attributes, of course, were simply irrelevant to contractors whose bread was buttered by big earthmoving projects. These differences in the rank-ordering of performance attributes defined the boundaries of the industry’s value networks.

Figure 3.4 Hydraulic Backhoe Manufactured by Sherman Products

Source: Brochure from Sherman Products, Inc., Royal Oak, Michigan, early 1950s.

The solid line in Figure 3.3 charts the rate of improvement in bucket size that hydraulics engineers were able to provide in the new excavator architecture. The maximum available bucket size had reached 3_8 cubic yard by 1955, 1_2 cubic yard by 1960, and 2 cubic yards by 1965. By 1974, the largest hydraulic excavators had the muscle to lift 10 cubic yards. This trajectory of improvement, which was far more rapid than the rate of improvement demanded in any of the excavator markets, carried this disruptive hydraulics technology upward from its original market through the large, mainstream excavation markets. The use of hydraulic excavators in general contracting markets was given a boost in 1954 when another entrant firm in Germany, Demag, introduced a track-mounted model that could rotate on its base a full 360 degrees.

THE RESPONSE TO HYDRAULICS BY THE ESTABLISHED EXCAVATOR MANUFACTURERS

Just as Seagate Technology was one of the first firms to develop prototype 3.5-inch drives, Bucyrus Erie, the leading cable shovel maker, was keenly aware of the emergence of hydraulic excavating technology. By 1950 (about two years after the first backhoe appeared) Bucyrus purchased a fledgling hydraulic backhoe company, the Milwaukee Hydraulics Corporation. Bucyrus faced precisely the same problem in marketing its hydraulic backhoe as Seagate had faced with its 3.5-inch drives: Its most powerful mainstream customers had no use for it.

Bucyrus Erie’s response was a new product, introduced in 1951, called the “Hydrohoe.” Instead of using three hydraulic cylinders, it used only two, one to curl the shovel into the earth and one to “crowd” or draw the shovel toward the cab; it used a cable mechanism to lift the shovel. The Hydrohoe was thus a hybrid of the two technologies, reminiscent of the early transoceanic steamships outfitted with sails. [11] There is no evidence, however, that the Hydrohoe’s hybrid design resulted from Bucyrus engineers’ being “stuck” in some sort of cable-based engineering paradigm. Rather, the cable lift mechanism was the only viable way at that time, based on the state of hydraulics technology, to give the Hydrohoe the bucket capacity and reach that Bucyrus marketers thought they needed to appeal to their existing customers’ needs.

Figure 3.5 presents an excerpt from an early Hydrohoe product brochure. Note the differences from Sherman’s marketing approach: Bucyrus labeled the Hydrohoe a “dragshovel,” showed it in an open field, and claimed it could “get a heaping load on every pass”—all intended to appeal to general excavation contractors. Rather than commercialize the disruptive technology in the value network in which the current attributes of hydraulics were prized, Bucyrus tried to adapt the technology to fit its own value network. Despite this attempt, the Hydrohoe was still too limited in capacity and reach and did not sell well to Bucyrus’ customers. Bucyrus kept its Hydrohoe on the market for over a decade, attempting periodically to upgrade its performance to make it acceptable to its customers, but the machine was never commercially successful. Ultimately, the company returned to the cable shovels that its customers needed.

Figure 3.5 Hydrohoe Manufactured by Bucyrus Erie

Source: Brochure from Bucyrus Erie Company, South Milwaukee, Wisconsin, 1951.

Bucyrus Erie was the only maker of cable-actuated shovels known to have launched a hydraulic excavator between 1948 and 1961: All of the other manufacturers continued serving their established customers, well and prosperously. [12] In fact, the largest makers of cable-actuated excavators, Bucyrus Erie and Northwest Engineering, logged record profits until 1966—the point at which the disruptive hydraulics technology had squarely intersected with customers’ needs in the sewer and piping segment. This is typical of industries facing a disruptive technology: The leading firms in the established technology remain financially strong until the disruptive technology is, in fact, in the midst of their mainstream market.

Between 1947 and 1965, twenty-three companies entered the mechanical excavation market with hydraulic products. Figure 3.6, which measures the total number of active entrants and established firms offering hydraulic excavators (net of the companies that had exited), shows how completely the entrants dominated the hydraulic excavator market.

In the 1960s, some of the strongest cable shovel makers introduced shovels with hydraulics. Almost all of these models were hybrids, however, like Bucyrus Erie’s Hydrohoe, generally employing a hydraulic cylinder to articulate or curl the bucket and using cables to extend the bucket out and to lift the boom. When used in this way in the 1960s, hydraulics had a sustaining impact on the established manufacturers’ products, improving their performance in the mainstream value networks. Some of the methods that engineers found to use hydraulics on the cable excavators were truly ingenious. All of this innovative energy, however, was targeted at existing customers.

The strategies employed by the excavator manufacturers during this period highlight an important choice that confronts companies encountering disruptive technological change. In general, the successful entrants accepted the capabilities of hydraulics technology in the 1940s and 1950s as a given and cultivated new market applications in which the technology, as it existed, could create value. And as a general rule, the established firms saw the situation the other way around: They took the market’s needs as the given. They consequently sought to adapt or improve the technology in ways that would allow them to market the new technology to their existing customers as a sustaining improvement. The established firms steadfastly focused their innovative investments on their customers. Subsequent chapters will show that this strategic choice is present in most instances of disruptive innovation. Consistently, established firms attempt to push the technology into their established markets, while the successful entrants find a new market that values the technology.

Figure 3.6 Manufacturers of Hydraulic Excavators, 1948–1965

Source: Data are from the Historical Construction Equipment Association.

Hydraulics technology ultimately did progress to the point where it could address the needs of mainstream excavation contractors. That progress was achieved, however, by the entrant companies, who had first found a market for the initial capabilities of the technology, accumulated design and manufacturing experience in that market, and then used that commercial platform to attack the value networks above them. The established firms lost this contest. Only four cable excavator companies—Insley, Koehring, Little Giant, and Link Belt—remained as viable suppliers to excavation contractors by successfully but belatedly introducing lines of hydraulic excavators to defend their markets. [13]

Aside from these, however, the other leading manufacturers of big cable machines in the mainstream excavation markets never introduced a commercially successful hydraulic excavator. Although some had employed hydraulics to a modest degree as a bucket-curling mechanism, they lacked the design expertise and volume-based manufacturing cost position to compete as hydraulics invaded the mainstream. By the early 1970s, all of these firms had been driven from the sewer, piping, and general excavation markets by the entrants, most of which had refined their technological capabilities initially in the small-contractor market. [14]

This contrast in strategies for profiting from change characterizes the approaches employed by entrant and established firms in many of the other industries affected by disruptive technologies—particularly disk drives, steel, computers, and electric cars.

THE CHOICE BETWEEN CABLE AND HYDRAULICS

In the trajectory map of Figure 3.3, when hydraulics technology became capable of addressing the bucket-size needs of sewer and piping contractors (and a similar trajectory could be sketched for arm-reach), the competitive dynamics in the industry changed, and the mainstream excavation contractors changed the criteria by which they purchased their equipment. Even today, the cable-actuated architecture can attain much longer reach and greater lift than can hydraulic excavators: They have roughly parallel technology trajectories. But once both cable-and hydraulics-actuated systems could satisfy mainstream market requirements, excavation contractors could no longer base their choice of equipment on which had longer reach and greater bucket capacity. Both were good enough, and the fact that cable was better ceased to have competitive relevance.

Contractors found, however, that hydraulic machines were much less prone to breakdowns than cable-actuated excavators. In particular, those who had experienced the life-threatening snap of a cable while hefting a heavy bucket embraced reliable hydraulics quickly, as soon as it was capable of doing the job. Once both technologies were good enough in the basic capabilities demanded, therefore, the basis of product choice in the market shifted to reliability. Sewer and piping contractors began adopting hydraulic equipment rapidly beginning in the early 1960s, and general excavation contractors followed later in the decade.

CONSEQUENCES AND IMPLICATIONS OF THE HYDRAULICS ERUPTION

What went wrong within the companies that made cable-actuated excavators? Clearly, with the benefit of hindsight, they should have invested in hydraulics machines and embedded that piece of their organizations charged with making hydraulic products in the value network that needed them. But the dilemma in managing the disruptive technology in the heat of the battle is that nothing went wrong inside these companies. Hydraulics was a technology that their customers didn’t need—indeed, couldn’t use. Each cable shovel manufacturer was one of at least twenty manufacturers doing everything they could to steal each other’s customers: If they took their eyes off their customers’ next-generation needs, existing business would have been put at risk. Moreover, developing bigger, better, and faster cable excavators to steal share from existing competitors constituted a much more obvious opportunity for profitable growth than did a venture into hydraulic backhoes, given how small the backhoe market was when it appeared in the 1950s. So, as we have seen before, these companies did not fail because the technology wasn’t available. They did not fail because they lacked information about hydraulics or how to use it; indeed, the best of them used it as soon as it could help their customers. They did not fail because management was sleepy or arrogant. They failed because hydraulics didn’t make sense—until it was too late.

The patterns of success and failure we see among firms faced with sustaining and disruptive technology change are a natural or systematic result of good managerial decisions. That is, in fact, why disruptive technologies confront innovators with such a dilemma. Working harder, being smarter, investing more aggressively, and listening more astutely to customers are all solutions to the problems posed by new sustaining technologies. But these paradigms of sound management are useless—even counterproductive, in many instances—when dealing with disruptive technology.

NOTES

1. A summary of how this same mechanism might have affected a broader range of industries can be found in Richard S. Rosenbloom and Clayton M. Christensen, “Technological Discontinuities, Organizational Capabilities, and Strategic Commitments,” Industrial and Corporate Change (3), 1994, 655–686.

2. This information and the data used to calculate the graphs in this section were provided by Dimitrie Toth, Jr., and Keith Haddock, both National Directors of the Historical Construction Equipment Association. The association has a wealth of information about the earthmoving equipment industry in its archives, and Toth and Haddock were most gracious in sharing their knowledge and information with me. I am also indebted to them for their helpful comments on an earlier draft of this chapter. Other useful sources of information are Peter Grimshaw, Excavators (Poole, England: Blandford Press, 1985); The Olyslager Organisation, Inc., Earthmoving Vehicles (London: Frederick Warne & Co., Ltd., 1972); Harold F. Williamson and Kenneth H. Myers, Designed for Digging: The First 75 Years of Bucyrus Erie Company (Evanston, IL: Northwestern University Press, 1955); and J. L. Allhands, Tools of the Earthmover (Huntsville, TX: Sam Houston College Press, 1951).

3. Interestingly, the high success rate was only amongst the industry’s twenty-five largest firms. Only one of the seven smallest steam shovel manufacturers survived this sustaining technology change to internal gasoline combustion. Almost no information is available about these companies other than what is provided by their product brochures. I suspect, however, that the fact that the large and mid-sized firms cruised through this transition while the small ones were killed indicates that resources played a part in the story, a conclusion that complements the theoretical perspectives summarized in chapter 2 above. Some sustaining technologies clearly are so expensive to develop and implement or so dependent on proprietary or scarce expertise that some companies simply cannot successfully manage the transition. I am indebted to Professor Richard Rosenbloom for sharing his perspective on this issue.

4. An example of this is the development of the first dragline, by Page, a Chicago area contractor. Page dug Chicago’s system of canals, and invented the drag-line in 1903 to do that job more effectively. Page draglines were later used extensively in digging the Panama Canal, alongside steam shovels made by Bucyrus Erie and Marion. This finding that customers were significant sources of sustaining innovations is consistent with Professor Eric von Hippel’s findings; see The Sources of Innovation (New York: Oxford University Press, 1988).

5. The companies that survived the invasion of hydraulics in this way found safe haven in a particular high-end market. Bucyrus Erie and Marion, for example, became the dominant makers of the huge stripping shovels used in strip mines. Marion’s model 6360 stripping shovel was the largest frontward-scooping shovel ever built, able to heft 180 cubic yards in its bucket. (An advertisement showing Paul Bunyan standing aside the 6360 is one of the most stunning pieces of advertising art I have seen.) Harnischfeger is the world’s largest maker of electric mining shovels, while Unit found a niche making the huge pedestal cranes used on offshore oil rigs. For a time, Northwest survived by making draglines for dredging ocean shipping lanes. P & H and Lorain made huge cranes and draglines (all cable-actuated).

6. As the hydraulic excavator has matured, these companies have met with varying degrees of subsequent success. In 1996, the world’s highest-volume excavator companies, Demag and O & K, were based in Germany.

7. Technically, excavators that scoop their buckets forward are power shovels. This was the dominant design from 1837 through the early 1900s, and persisted as a major market segment through much of this century. Excavators that pull earth backward toward the cab are backhoes. As the hydraulic excavator became the dominant design during the 1970s, both types came to be called excavators. Until hydraulic actuation required the booms to be permanently attached to the unit, contractors could attach different booms or arms to their basic power units so that the same unit could work as a shovel, backhoe, or crane. Similarly, different buckets, sometimes called dippers, could be attached to move different types of material.

8. The true measure of performance in excavation was the number of cubic yards of earth that could be moved per minute. This measure was so dependent upon operator skill and upon the type of earth being dug, however, that contractors adopted bucket size as the more robust, verifiable metric.

9. These British and American pioneers were followed by several European manufacturers, each of which was also an entrant to the excavator industry, including France’s Poclain and Italy’s Bruneri Brothers.

10. The ability to push the shovel into the earth was a major advantage to the hydraulics approach. The cable-actuated excavators that pulled earth toward the operator all had to rely on gravity to drive the teeth of the heavy shovel into the earth.

11. Makers of early hybrid ocean transports, which were steam-powered but still outfitted with sails, used the same rationale for their design as did the Bucyrus Erie engineers: Steam power still was not reliable enough for the transoceanic market, so steam power plants had to be backed up by conventional technology. The advent of steam-powered ships and their substitution for wind-powered ships in the transoceanic business is itself a classic study of disruptive technology. When Robert Fulton sailed the first steamship up the Hudson River in 1819, it underperformed transoceanic sailing ships on nearly every dimension of performance: It cost more per mile to operate; it was slower; and it was prone to frequent breakdowns. Hence, it could not be used in the transoceanic value network and could only be applied in a different value network, inland waterways, in which product performance was measured very differently. In rivers and lakes, the ability to move against the wind or in the absence of a wind was the attribute most highly valued by ship captains, and along that dimension, steam outperformed sail. Some scholars (see, for example, Richard Foster, in Innovation: The Attacker’s Advantage [New York: Summit Books, 1986]) have marveled at how myopic were the makers of sailing ships, who stayed with their aging technology until the bitter end, in the early 1900s, completely ignoring steam power. Indeed, not a single maker of sailing ships survived the industry’s transition to steam power. The value network framework offers a perspective on this problem that these scholars seem to have ignored, however. It was not a problem of knowing about steam power or of having access to technology. The problem was that the customers of the sailing ship manufacturers, who were transoceanic shippers, could not use steam-powered ships until the turn of the century. To cultivate a position in steamship building, the makers of sailing ships would have had to engineer a major strategic reorientation into the inland waterway market, because that was the only value network where steam-powered vessels were valued throughout most of the 1800s. Hence, it was these firms’ reluctance or inability to change strategy, rather than their inability to change technology, that lay at the root of their failure in the face of steam-powered vessels.

12. An exception to this is an unusual product introduced by Koehring in 1957: the Skooper combined cables and hydraulics to dig earth away from a facing wall; it did not dig down into the earth.

13. Bucyrus Erie does not fit easily into either of these groups. It introduced a large hydraulic excavator in the 1950s, but subsequently withdrew it from the market. In the late 1960s, it acquired the “Dynahoe” line of hydraulic loader-backhoes from Hy-Dynamic Corporation and sold them as utility machines to its general excavation customers, but, again, dropped this product line as well.

14. Caterpillar was a very late (but successful) entrant into the hydraulic excavation equipment industry, introducing its first model in 1972. Excavators were an extension of its line of dozers, scrapers, and graders. Caterpillar never participated in the excavation machine market when cable actuation was the dominant design.

CHAPTER FOUR

What Goes Up, Can’t Go Down

It is clear from the histories of the disk drive and excavator industries that the boundaries of value networks do not completely imprison the companies within them: There is considerable upward mobility into other networks. It is in restraining downward mobility into the markets enabled by disruptive technologies that the value networks exercise such unusual power. In this chapter we will explore these questions: Why could leading companies migrate so readily toward high-end markets, and why does moving downmarket appear to have been so difficult? Rational managers, as we shall see, can rarely build a cogent case for entering small, poorly defined low-end markets that offer only lower profitability. In fact, the prospects for growth and improved profitability in upmarket value networks often appear to be so much more attractive than the prospect of staying within the current value network, that it is not unusual to see well-managed companies leaving (or becoming uncompetitive with) their original customers as they search for customers at higher price points. In good companies, resources and energy coalesce most readily behind proposals to attack upmarket into higher-performance products that can earn higher margins.

Indeed, the prospects for improving financial performance by moving toward upmarket value networks are so strong that one senses a huge magnet in the northeast corner of the disk drive and excavator trajectory maps. This chapter examines the power of this “northeastern pull” by looking at evidence from the history of the disk drive industry. It then generalizes this framework by exploring the same phenomenon in the battle between minimill and integrated steel makers.

THE GREAT NORTHEAST MIGRATION IN DISK DRIVES

Figure 4.1 plots in more detail the upmarket movement of Seagate Technology, whose strategy was typical of most disk drive manufacturers. Recall that Seagate had spawned, and then grew to dominate, the value network for desktop computing. Its product position relative to capacity demanded in its market is mapped by vertical lines which span from the lowest-to the highest-capacity drives in its product line, in each of the years shown. The black rectangle on the line measuring each year’s capacity span shows the median capacity of the drives Seagate introduced in each of those years.

Figure 4.1 Upmarket Migration of Seagate Products

Source: Data are from various issues of Disk/Trend Report.

Between 1983 and 1985, the center of gravity of Seagate’s product line was positioned squarely on the average capacity demanded in the desktop segment. It was between 1987 and 1989 that the disruptive 3.5-inch form invaded the desktop market from below. Seagate responded to that attack, not by fighting the disruptive technology head-on, but by retreating up-market. It continued to offer models in the capacity ranges the desktop PC market demanded, but by 1993 the focus of its energy had clearly shifted to the market for mid-range computers, such as file servers and engineering workstations.

Indeed, disruptive technologies have such a devastating impact because the firms that first commercialized each generation of disruptive disk drives chose not to remain contained within their initial value network. Rather, they reached as far upmarket as they could in each new product generation, until their drives packed the capacity to appeal to the value networks above them. It is this upward mobility that makes disruptive technologies so dangerous to established firms—and so attractive to entrants.

VALUE NETWORKS AND CHARACTERISTIC COST STRUCTURES

What lies behind this asymmetric mobility? As we have already seen, it is driven by resource allocation processes that direct resources toward new product proposals that promise higher margins and larger markets. These are almost always better in the northeast portions of trajectory maps (such as Figures 1.7 and 3.3) than in the southeast. The disk drive manufacturers migrated to the northeast corner of the product-market map because the resource allocation processes they employed took them there.

As we saw in chapter 2, a characteristic of each value network is a particular cost structure that firms within it must create if they are to provide the products and services in the priority their customers demand. Thus, as the disk drive makers became large and successful within their “home” value network, they developed a very specific economic character: tuning their levels of effort and expenses in research, development, sales, marketing, and administration to the needs of their customers and the challenges of their competitors. Gross margins tended to evolve in each value network to levels that enabled the better disk drive makers to make money, given these costs of doing business.

In turn, this gave these companies a very specific model for improving profitability. Generally, they found it difficult to improve profitability by hacking out cost while steadfastly standing in their mainstream market: The research, development, marketing, and administrative costs they were incurring were all critical to remaining competitive in their mainstream business. Moving upmarket toward higher-performance products that promised higher gross margins was usually a more straightforward path to profit improvement. Moving downmarket was anathema to that objective.

The obviousness of the path toward profit improvement is shown in Figure 4.2. The three bars on the left depict the size of the desktop, minicomputer, and mainframe computer value networks in 1981 and are labeled with the characteristic margins enjoyed by disk drive makers in each of those networks. Gross margins are clearly higher in higher-end markets, compensating manufacturers for the higher levels of overhead characteristic of those businesses.

The differences in the size of these markets and the characteristic cost structures across these value networks created serious asymmetries in the combat among these firms. Firms making 8-inch drives for the minicomputer market, for example, had cost structures requiring gross margins of 40 percent. Aggressively moving downmarket would have pitted them against foes who had honed their cost structures to make money at 25 percent gross margins. On the other hand, moving upmarket enabled them to take a relatively lower-cost structure into a market that was accustomed to giving its suppliers 60 percent gross margins. Which direction made sense? A similar asymmetry faced the makers of 5.25-inch drives in 1986, as they decided whether to spend their resources building a position in the emerging market for 3.5-inch drives in portable computers or to move up toward the minicomputer and mainframe companies.

Committing development resources to launch higher-performance products that could garner higher gross margins generally both offered greater returns and caused less pain. As their managers were making repeated decisions about which new product development proposals they should fund and which they should shelve, proposals to develop higher-performance products targeted at the larger, higher-margin markets immediately above them always got the resources. In other words, sensible resource allocation processes were at the root of companies’ upward mobility and downmarket immobility across the boundaries of the value networks in the disk drive industry.

The hedonic regression analysis summarized in chapter 2 showed that higher-end markets consistently paid significantly higher prices for incremental megabytes of capacity. Why would anyone opt to sell a megabyte for less when it could be sold for more? The disk drive companies’ migration to the northeast was, as such, highly rational.

Figure 4.2 Views Upmarket and Downmarket for Established Disk Drive

Source: Data are from various issues of Disk/Trend Report, corporate annual reports, and data provided in personal interviews.

Note: Percentages above each bar indicate typical gross margins in each value network.

Other scholars have found evidence in other industries that as companies leave their disruptive roots in search of greater profitability in the market tiers above them, they gradually come to acquire the cost structures required to compete in those upper market tiers. [1] This exacerbates their problem of downward immobility.

RESOURCE ALLOCATION AND UPWARD MIGRATION

Further insight into this asymmetric mobility across value networks comes from comparing two different descriptive models of how resources are allocated. The first model describes resource allocation as a rational, top-down decision-making process in which senior managers weigh alternative proposals for investment in innovation and put money into those projects that they find to be consistent with firm strategy and to offer the highest return on investment. Proposals that don’t clear these hurdles are killed.

The second model of resource allocation, first articulated by Joseph Bower, [2] characterizes resource allocation decisions much differently. Bower notes that most proposals to innovate are generated from deep within the organization not from the top. As these ideas bubble up from the bottom, the organization’s middle managers play a critical but invisible role in screening these projects. These managers can’t package and throw their weight behind every idea that passes by; they need to decide which are the best, which are most likely to succeed, and which are most likely to be approved, given the corporate financial, competitive, and strategic climate.

In most organizations, managers’ careers receive a big boost when they play a key sponsorship role in very successful projects—and their careers can be permanently derailed if they have the bad judgment or misfortune to back projects that fail. Middle managers aren’t penalized for all failures, of course. Projects that fail because the technologists couldn’t deliver, for example, often are not (necessarily) regarded as failures at all, because a lot is learned from the effort and because technology development is generally regarded as an unpredictable, probabilistic endeavor. But projects that fail because the market wasn’t there have far more serious implications for managers’ careers. These tend to be much more expensive and public failures. They generally occur after the company has made full investments in product design, manufacturing, engineering, marketing, and distribution. Hence, middle managers—acting in both their own and the company’s interest—tend to back those projects for which market demand seems most assured. They then work to package the proposals for their chosen projects in ways geared to win senior management approval. As such, while senior managers may think they’re making the resource allocation decisions, many of the really critical resource allocation decisions have actually been made long before senior management gets involved: Middle managers have made their decisions about which projects they’ll back and carry to senior management—and which they will allow to languish.

Consider the implications of this for a successful firm’s downward and upward mobility from its initial value network in this hypothetical example. In the same week, two respected employees, one from marketing, the other from engineering, run two very different ideas for new products past their common manager two levels above them in the organization. The marketer comes first, with an idea for a higher-capacity, higher-speed model. The two-levels-up manager starts her interrogation:

“Who’s going to buy it?”

“Well, there’s a whole segment in the workstation industry—they buy over $600 million in drives each year—that we’ve just never been able to reach because our capacity points just don’t reach that high. I think this product just might get us there.”

“Have you run this idea past any potential customers?”

“Yeah, I was in California last week. They all said they wanted prototypes as soon as they could get them. There’s a design window opening up in nine months. They’ve been working with their current supplier [competitor X] to get something ready, but someone we just hired from competitor X said they’re having lots of trouble meeting the specs. I really think we can do it.”

“But does engineering think we can do it?”

“They say it’ll be a stretch, but you know them. They always say that.” “What kind of margins are we looking at up there?”

“That’s what really excites me about this. If we can build it in our current factory, given the price per megabyte competitor X has been getting, I think we can get close to 35 percent.”

Compare that conversation to the manager’s interchange with the engineer whose idea is for a cheaper, smaller, slower, lower-capacity disruptive disk drive.

“Who’s going to buy it?”

“Well, I’m not sure, but there’s got to be a market out there somewhere for it. People are always wanting things smaller and less expensive. I could see them using it in fax machines, printers, maybe.”

“Have you run this idea past any potential customers?”

“Yeah, when I was at the last trade show I sketched the idea out for one of our current customers. He said he was interested, but couldn’t see how they could really use it. Today you really need 270 MB to run everything, and there’s just no way we could get that kind of capacity on this thing—at least not for a while. His response doesn’t surprise me, really.”

“How about the guys who make fax machines? What do they think?”

“Well, they say they don’t know. Again, it’s an intriguing idea, but they already have their product plans pretty well set, and none of them use disk drives.”

“You think we could make money on this project?”

“Well, I think so, but that depends on how we could price it, of course.”

Which of the two projects will the two-levels-up manager back? In the tug-of-war for development resources, projects targeted at the explicit needs of current customers or at the needs of existing users that a supplier has not yet been able to reach will always win over proposals to develop products for markets that do not exist. This is because, in fact, the best resource allocation systems are designed precisely to weed out ideas that are unlikely to find large, profitable, receptive markets. Any company that doesn’t have a systematic way of targeting its development resources toward customers’ needs, in fact, will fail. [3]

The most vexing managerial aspect of this problem of asymmetry, where the easiest path to growth and profit is up, and the most deadly attacks come from below, is that “good” management—working harder and smarter and being more visionary—doesn’t solve the problem. The resource allocation process involves thousands of decisions, some subtle and some explicit, made every day by hundreds of people, about how their time and the company’s money ought to be spent. Even when a senior manager decides to pursue a disruptive technology, the people in the organization are likely to ignore it or, at best, cooperate reluctantly if it doesn’t fit their model of what it takes to succeed as an organization and as individuals within an organization. Well-run companies are not populated by yes-people who have been taught to carry out mindlessly the directives of management. Rather, their employees have been trained to understand what is good for the company and what it takes to build a successful career within the company. Employees of great companies exercise initiative to serve customers and meet budgeted sales and profits. It is very difficult for a manager to motivate competent people to energetically and persistently pursue a course of action that they think makes no sense. An example from the history of the disk drive industry illustrates the impact of such employee behavior.

THE CASE OF THE 1.8-INCH DISK DRIVE

Managers in disk drive companies were very generous in helping me conduct the research reported in this book, and, as the results began emerging in 1992, I began feeding back the published papers that summarized what I was learning. I was particularly interested in whether the framework summarized in Figure 1.7 would have an impact on their decisions regarding the 1.8-inch drive, which was just then emerging as the industry’s most recent disruptive technology. For industry outsiders, of course, the conclusion was obvious: “How many times does this have to happen before these guys learn?! Of course they’ve got to do it.” The guys did, in fact, learn. By the end of 1993, each of the leading drive makers had developed 1.8-inch models and had them ready for introduction if and when the market developed.

In August 1994, I was visiting the CEO of one of the largest disk drive companies and asked him what his firm was doing about the 1.8-inch drive. This clearly touched a hot button. He pointed to a shelf in his office where a sample 1.8-inch drive was perched. “You see that?” he demanded. “That’s the fourth generation of 1.8-inch drives we’ve developed—each one with more capacity than the last. But we haven’t sold any. We want to be ready when the market is there, but there just isn’t a market for them yet.”

I countered by reminding him that Disk/Trend Report, a highly regarded market research publication that was the source of much of the data used in my study, had measured the 1993 market at $40 million, was projecting 1994 sales to be $80 million, and forecast 1995 volume at $140 million.

“I know that’s what they think,” he responded. “But they’re wrong. There isn’t a market. We’ve had that drive in our catalog for 18 months. Everyone knows we’ve got it, but nobody wants it. The market just isn’t there. We just got way ahead of the market.” I had no other basis for pressing my point with this manager, who is one of the most astute managers I’ve ever met. Our conversation moved to other issues.

About a month later I was leading a case discussion in the Harvard MBA program’s technology and operations management course about the development of a new engine at Honda. One of the students in the class had previously worked in Honda’s research and development organization, so I asked him to take a few minutes to tell the class what it was like working there. It turned out that he had been working on dashboard mapping and navigation systems. I couldn’t resist interrupting his talk by asking, “How do you store all that data for the maps?”

Said the student: “We found a little 1.8-inch disk drive and put it in there. It’s really neat—almost a solid-state device, with very few moving parts. Really rugged.”

“Who do you buy them from?” I pressed.

“It’s kind of funny,” he replied. “You can’t buy them from any of the big disk drive companies. We get them from a little startup company somewhere in Colorado—I can’t remember the name.”

I have since reflected on why the head of this company would insist so stubbornly that there was no market for 1.8-inch drives, even while there was, and why my student would say the big drive makers didn’t sell these drives, even though they were trying. The answer lies in the northeast-southeast problem, and in the role that the hundreds of well-trained decision makers in a good company play in funneling resources and energy into those projects they perceive will bring the company the greatest growth and profit. The CEO had decided that the company was going to catch this next disruptive wave early and had shepherded the project through to a successful, economical design. But among the employees, there was nothing about an $80 million, low-end market that solved the growth and profit problems of a multibillion dollar company—especially when capable competitors were doing all they could to steal away the customers providing those billions. (The revenue figure is disguised.) And way at the other end of the company, there was nothing about supplying prototype quantities of 1.8-inch drives to an automaker that solved the problem of meeting the 1994 quotas of salespeople whose contacts and expertise were based so solidly in the computer industry.

For an organization to accomplish a task as complex as launching a new product, logic, energy, and impetus must all coalesce behind the effort. Hence, it is not just the customers of an established firm that hold it captive to their needs. Established firms are also captive to the financial structure and organizational culture inherent in the value network in which they compete—a captivity that can block any rationale for timely investment in the next wave of disruptive technology.

VALUE NETWORKS AND MARKET VISIBILITY

The impetus to drift upmarket can be particularly powerful when a firm’s customers themselves are migrating upmarket. In such circumstances, suppliers of an intermediate component such as a disk drive may not sense their northeasterly migration because they are embedded among competitors and customers experiencing a similar drift.

In this light, we can see how easy it would have been for the leading 8-inch disk drive makers—Priam, Quantum, and Shugart—to miss the 5.25-inch generation of drives. Not a single one of their core customers, for example, Digital Equipment, Prime Computer, Data General, Wang Laboratories, and Nixdorf, successfully introduced a desktop computer. Instead, each was moving upmarket itself toward ever higher performance segments of their markets, trying to win the business of customers who historically had used mainframes. Similarly, not a single one of the customers of the 14-inch drive makers—mainframe makers such as Univac, Burroughs, NCR, ICL, Siemens, and Amdahl—ever made a bold enough move downmarket into minicomputers to become a significant player there.

Three factors—the promise of upmarket margins, the simultaneous upmarket movement of many of a company’s customers, and the difficulty of cutting costs to move downmarket profitably—together create powerful barriers to downward mobility. In the internal debates about resource allocation for new product development, therefore, proposals to pursue disruptive technologies generally lose out to proposals to move upmarket. In fact, cultivating a systematic approach to weeding out new product development initiatives that would likely lower profits is one of the most important achievements of any well-managed company.

An important strategic implication of this rational pattern of upmarket movement is that it can create vacuum in low-end value networks that draws in entrants with technologies and cost structures better suited to competition. One of these powerful downmarket voids occurred in the steel industry, for example, when entrant companies employing disruptive minimill process technology entered through low-end beachheads; they have attacked relentlessly upmarket ever since.

THE NORTHEASTERLY MIGRATION OF INTEGRATED STEEL

Minimill steel making first became commercially viable in the mid-1960s. Employing widely available and familiar technology and equipment, mini-mills melt scrap steel in electric arc furnaces, continuously cast it into intermediate shapes called billets, and then roll those into products such as bars, rods, beams, or sheets. They are called minimills because the scale at which they produce cost-competitive molten steel from scrap is less than one-tenth of the scale required for an integrated mill to produce cost-competitive molten steel from iron ore in blast and basic oxygen furnaces. (Integrated mills take their name from the integrated process of transforming iron ore, coal, and limestone into final steel shapes.) Integrated mills and minimills look much the same in their processes of continuous casting and rolling operations. Scale is the only difference: The output of efficiently sized blast furnaces requires that integrated mills’ casting and rolling operations must be much greater than those of the minimills.

North America’s steel minimills are the most efficient, lowest-cost steel makers in the world. In 1995, the most efficient minimill required 0.6 labor-hours per ton of steel produced; the best integrated mill required 2.3 labor-hours. In the product categories in which they compete, the average minimill can make product of equivalent quality, on a fully costed basis, at about a 15 percent lower cost than the average integrated mill. In 1995, it cost about $400 million to build a cost-competitive steel minimill and about $6 billion to build a cost-competitive integrated mill. [4] In terms of capital cost per ton of steel making capacity, integrated mills are more than four times as costly to build. [5] As a result, minimills’ share of the North American market has grown from nothing in 1965 to 19 percent in 1975, 32 percent in 1985, and 40 percent in 1995. Experts predict they will account for half of all steel production by the turn of the century. [6] Minimills virtually dominate the North American markets for rods, bars, and structural beams.

Yet not a single one of the world’s major integrated steel companies to date has built a mill employing minimill technology. Why would none of them do something that makes so much sense? The explanation forwarded most frequently by the business press, especially in the United States, is that the managers of the integrated companies are conservative, backward-looking, risk-averse, and incompetent. Consider these indictments.

Last year, U.S. Steel Corp. closed fifteen of its facilities, claiming they had become “noncompetitive.” Three years ago, Bethlehem Steel Corp. shuttered major portions of its plants in Johnstown, PA, and Lackawanna, NY…. The closing of these major steel complexes is the final dramatic concession from today’s chief executives that management has not been doing its job. It represents decades of maximizing profits to look good for the short term. [7]

If the U.S. steel industry were as productive in tons per man-hour as it is in rhetoric per problem, it would be a top-notch performer. [8]

Surely there is some credibility to such accusations. But managerial incompetence cannot be a complete answer for the failure of North American integrated mills to counter the conquest by minimills of vast portions of the steel industry. None of what most experts regard as the best-managed and most successful of the world’s integrated steel makers— including Nippon, Kawasaki, and NKK in Japan; British Steel and Hoogovens in Europe; and Pohang Steel in Korea—has invested in minimill technology even though it is demonstrably the lowest-cost technology in the world.

At the same time, in the last decade the management teams at integrated mills have taken aggressive steps to increase mill efficiency. USX, for example, improved the efficiency of its steel making operations from more than nine labor-hours per ton of steel produced in 1980 to just under three hours per ton in 1991. It accomplished this by ferociously attacking the size of its workforce, paring it from more than 93,000 in 1980 to fewer than 23,000 in 1991, and by investing more than $2 billion in modernizing its plant and equipment. Yet all of this managerial aggressiveness was targeted at conventional ways of making steel. How can this be?

Minimill steelmaking is a disruptive technology. When it emerged in the 1960s, because it used scrap steel, it produced steel of marginal quality. The properties of its products varied according to the metallurgical composition and impurities of the scrap. Hence, about the only market that minimill producers could address was that for steel reinforcing bars (rebars)—right at the bottom of the market in terms of quality, cost, and margins. This market was the least attractive of those served by established steel makers. And not only were margins low, but customers were the least loyal: They would switch suppliers at will, dealing with whoever offered the lowest price. The integrated steel makers were almost relieved to be rid of the rebar business.

The minimills, however, saw the rebar market quite differently. They had very different cost structures than those of the integrated mills: little depreciation and no research and development costs, low sales expenses (mostly telephone bills), and minimal general managerial overhead. They could sell by telephone virtually all the steel they could make—and sell it profitably.

Once they had established themselves in the rebar market, the most aggressive minimills, especially Nucor and Chaparral, developed a very different view of the overall steel market than the view that the integrated mills held. Whereas the downmarket rebar territory they seized had looked singularly unattractive to their integrated competitors, the minimills’ view upmarket showed that opportunities for greater profits and expanded sales were all above them. With such incentive, they worked to improve the metallurgical quality and consistency of their products and invested in equipment to make larger shapes.

As the trajectory map in Figure 4.3 indicates, the minimills next attacked the markets for larger bars, rods, and angle irons immediately above them. By 1980, they had captured 90 percent of the rebar market and held about 30 percent of the markets for bars, rods, and angle irons. At the time of the minimills’ attack, the bar, rod, and angle iron shapes brought the lowest margins in the integrated mills’ product lines. As a consequence, the integrated steel makers were, again, almost relieved to be rid of the business, and by the mid-1980s this market belonged to the minimills.

Once their position in the market for bars, rods, and angle irons seemed secure, the minimills continued their march upmarket, this time toward structural beams. Nucor did so from a new minimill plant in Arkansas, and Chaparral launched its attack from a new mill adjacent to its first one in Texas. The integrated mills were driven from this market by the minimills as well. In 1992, USX closed its South Chicago structural steel mill, leaving Bethlehem as the only integrated North American structural steel maker. Bethlehem closed its last structural beam plant in 1995, leaving the field to the minimills.

Figure 4.3 The Progress of Disruptive Minimill Steel Technology

An important part of this story is that, throughout the 1980s, as they were ceding the bar and beam business to the minimills, the integrated steel makers experienced dramatically improving profit. Not only were these firms attacking cost, they were forsaking their lowest-margin products and focusing increasingly on high-quality rolled sheet steel, where quality-sensitive manufacturers of cans, cars, and appliances paid premium prices for metallurgically consistent steel with defect-free surfaces. Indeed, the lion’s share of integrated mills’ investments in the 1980s had been targeted at improving their ability to provide the most demanding customers in these three markets with the highest-quality product and to do so profitably. Sheet steel markets were an attractive haven for the integrated producers in part because they were protected from minimill competition. It cost about $2 billion to build a state-of-the-art, cost-competitive sheet steel rolling mill, and this capital outlay simply had been too much for even the largest of the minimills.

Targeting the premium end of the market pleased the integrated mills’ investors: For example, Bethlehem Steel’s market value had leapt from $175 million in 1986 to $2.4 billion in 1989. This represented a very attractive return on the $1.3 billion the company invested in R&D and plant and equipment during this period. The business press generously acknowledged these aggressive, well-placed investments.

Walter Williams (Bethlehem’s CEO) has worked wonders. Over the past three years he mounted a highly personal campaign to improve the quality and productivity of Bethlehem’s basic steel business. Bethlehem’s metamorphosis has outclassed even its major U.S. competitors—which as a whole are now producing at lower costs than their Japanese rivals and are fast closing the quality gap. Customers notice the difference. “It’s nothing short of miraculous,” says a top purchaser of sheet steel at Campbell Soup. [Italics added.] [9]

Another analyst made similar observations.

While almost no one was looking, a near miracle occurred: Big Steel is making a quiet comeback. Gary Works (US Steel) is back in the black … pouring out a glowing river of molten iron at the rate of 3 million tons per year—a North American record. Union-management problem-solving teams are everywhere. Instead of making steel in all shapes and sizes, Gary has focused almost entirely on higher-value flat-rolled steel. [Italics added.] [10]

Almost all of us would agree that these remarkable recoveries were the fruits of good management. But where will good management in this genre lead these firms?

MINIMILL THIN-SLAB CASTING FOR SHEET STEEL

While integrated steel makers were busy engineering their recoveries, more disruptive clouds began gathering on the horizon. In 1987, a German supplier of equipment for the steel industry, Schloemann-Siemag AG, announced that it had developed what it called “continuous thin-slab casting” technology—a way for steel to be continuously cast from its molten state into long, thin slabs that could be transported directly, without cooling, into a rolling mill. Rolling the white-hot, already thin slab of steel to the final thickness of coiled sheet steel was much simpler than the traditional task mastered by the integrated mills of reheating and rolling sheet from thick ingots or slabs. Most important, a cost-competitive continuous thin-slab casting and rolling mill could be built for less than $250 million—one-tenth the capital cost of a traditional sheet mill and a relatively manageable investment for a minimill steel maker. At this scale, an electric arc furnace could easily supply the required quantity of molten steel. Moreover, thin-slab casting promised at least a 20 percent reduction in the total cost of making sheet steel.

Because of its promise, thin-slab casting was carefully evaluated by every major player in the steel industry. Some integrated mills, such as USX, worked very hard to justify installation of a thin-slab facility. [11] In the end, however, it was minimill Nucor Steel, rather than the integrated mills, that made the bold move into thin-slab casting. Why?

At the outset, thin-slab casting technology could not offer the smooth, defect-free surface finish required by the integrated mills’ mainstream customers (makers of cans, cars, and appliances). The only markets were those such as construction decking and corrugated steel for culverts, pipes, and Quonset huts, in which users were more sensitive to price than to surface blemishes. Thin-slab casting was a disruptive technology. Furthermore, large, capable, and hungry integrated competitors were busy trying to rob each other’s most profitable business with the large auto, appliance, and can companies. It made no sense for them to target capital investment at thin-slab casting, positioned as it was in the least-profitable, most price-competitive and commodity-like end of their business. Indeed, after seriously considering between 1987 and 1988 whether to invest in thin-slab casting at an amount then projected to be about $150 million, both Bethlehem and USX elected instead to invest in conventional thick-slab continuous casters at a cost of $250 million to protect and enhance the profitability of the business with their mainstream customers.

Not surprisingly, Nucor saw the situation another way. Unencumbered by the demands of profitable customers in the sheet steel business and benefiting from a cost structure forged at the bottom of the industry, Nucor fired up the world’s first continuous thin-slab casting facility in Crawfordsville, Indiana, in 1989, and constructed a second mill in Hickman, Arkansas, in 1992. It increased its capacity at both sites by 80 percent in 1995. Analysts estimate that Nucor had captured 7 percent of the massive North American sheet market by 1996—hardly enough to concern the integrated mills, because Nucor’s success has been limited to the commoditized, least-profitable end of their product line. Of course, in its effort to win higher-margin business with higher-quality products from these mills, Nucor has already improved the surface quality of its sheet steel substantially.

Thus, the integrated steel companies’ march to the profitable northeast corner of the steel industry is a story of aggressive investment, rational decision making, close attention to the needs of mainstream customers, and record profits. It is the same innovator’s dilemma that confounded the leading providers of disk drives and mechanical excavators: Sound managerial decisions are at the very root of their impending fall from industry leadership.

NOTES

1. This process of moving to higher tiers of the market and then adding the costs to support business at that level was described by Professor Malcom P. McNair, of the Harvard Business School, in a way that strikingly parallels the disk drive story. Writing in a history of retailing, McNair describes how successive waves of retailers entered the field with disruptive technologies (though he does not use the term):

The wheel always revolves, sometimes slowly, sometimes more rapidly, but it does not stand still. The cycle frequently begins with the bold new concept, the innovation. Somebody gets a bright new idea. There is a John Wanamaker, a George Hartford (A&P), a Frank Woolworth, a W. T. Grant, a General Wood (Sears), a Michael Cullen (supermarkets), a Eugene Ferkauf. Such an innovator has an idea for a new kind of distributive enterprise. At the outset he is in bad odor, ridiculed, scorned, condemned as “illegitimate.” Bankers and investors are leery of him. But he attracts the public on the basis of the price appeal made possible by the low operating costs inherent in his innovation. As he goes along he trades up, improves the quality of his merchandise, improves the appearance and standing of his store, attains greater respectability….

During this process of growth the institution rapidly becomes respectable in the eyes of both consumers and investors, but at the same time its capital investment increases and its operating costs tend to rise. Then the institution enters the stage of maturity…. The maturity phase soon tends to be followed by topheaviness … and eventual vulnerability. Vulnerability to what? Vulnerability to the next fellow who has a bright idea and who starts his business on a low-cost basis, slipping in under the umbrella that the old-line institutions have hoisted.

See Malcom P. McNair, “Significant Trends and Developments in the Post-War Period,” in Albert B. Smith, ed., Competitive Distribution in a Free High-Level Economy and Its Implications for the University (Pittsburgh: University of Pittsburgh Press, 1958) 17–18. In other words, the very costs required to become competitive in higher-end markets restrict downward mobility and create further incentive to move upmarket.

2. Joseph Bower, Managing the Resource Allocation Process (Homewood, IL: Richard D. Irwin, 1970).

3. The use of the term systematic in this sentence is important, because most resource allocation systems work in a systematic way—whether the system is formal or informal. It will be shown later in this book that a key to managers’ ability to confront disruptive technology successfully is their ability to intervene and make resource allocation decisions personally and persistently. Allocation systems are designed to weed out just such proposals as disruptive technologies. An excellent description of this dilemma can be found in Roger Martin, “Changing the Mind of the Corporation,” Harvard Business Review, November–December 1993, 81–94.

4. Because of slow growth in steel demand in many of the world’s markets, fewer large integrated steel mills are being built in the 1990s. Those integrated mills that are being built these days are in high-growth, rapidly developing countries such as Korea, Mexico, and Brazil.

5. Professor Thomas Eagar of the Department of Materials Science at the Massachusetts Institute of Technology provided these estimates.

6. “The U.S. Steel Industry: An Historical Overview,” Goldman Sachs U.S. Research Report, 1995.

7. “What Caused the Decline,” Business Week, June 30, 1980, 74.

8. Donald B. Thompson, “Are Steel’s Woes Just Short-term,” Industry Week, February 22, 1982, 31.

9. Gregory L. Miles, “Forging the New Bethlehem,” Business Week, June 5, 1989, 108–110.

10. Seth Lubove and James R. Norman, “New Lease on Life,” Forbes, May 9, 1994, 87.

11. The experience of the team at U.S. Steel charged with evaluating continuous thin-slab casting technology is chronicled in the Harvard Business School teaching case “Continuous Casting Investments at USX Corporation,” No. 697-020.

Part Two

MANAGING DISRUPTIVE

TECHNOLOGICAL CHANGE

In the search for reasons why so many strong companies in three very different industries stumbled or failed, the research summarized in the preceding chapters casts doubt on several conventional explanations other researchers have offered. It wasn’t the case that the leading companies’ engineers tended to get stuck in a particular technological paradigm or ignored innovations that were “not invented here.” The cause of failure could not be solely attributed to established firms’ inadequate competence in new technological fields or their inability to stay atop their industry’s “technological mudslide.” Of course, these problems do afflict some companies. But as a general rule, the evidence is very strong that as long as the new technology was required to address the needs of their customers, established firms were able to muster the expertise, capital, suppliers, energy, and rationale to develop and implement the requisite technology both competitively and effectively. This has been true for incremental as well as radical advances; for projects that consumed months as well as those lasting more than a decade; in fast-paced disk drives, in the slower-paced mechanical excavator industry, and in the process-intensive steel industry.

Probably the most important outcome of this attempt to define the problem is that it ruled out poor management as a root cause. Again, this is not to say that good and bad management aren’t key factors affecting the fortunes of firms. But as a general explanation, the managers of the companies studied here had a great track record in understanding customers’ future needs, identifying which technologies could best address those needs, and in investing to develop and implement them. It was only when confronted with disruptive technology that they failed. There had, therefore, to be a reason why good managers consistently made wrong decisions when faced with disruptive technological change.

The reason is that good management itself was the root cause. Managers played the game the way it was supposed to be played. The very decision-making and resource-allocation processes that are key to the success of established companies are the very processes that reject disruptive technologies: listening carefully to customers; tracking competitors’ actions carefully; and investing resources to design and build higher-performance, higher-quality products that will yield greater profit. These are the reasons why great firms stumbled or failed when confronted with disruptive technological change.

Successful companies want their resources to be focused on activities that address customers’ needs, that promise higher profits, that are technologically feasible, and that help them play in substantial markets. Yet, to expect the processes that accomplish these things also to do something like nurturing disruptive technologies—to focus resources on proposals that customers reject, that offer lower profit, that underperform existing technologies and can only be sold in insignificant markets—is akin to flapping one’s arms with wings strapped to them in an attempt to fly. Such expectations involve fighting some fundamental tendencies about the way successful organizations work and about how their performance is evaluated.

Part Two of this book is built upon detailed case studies of a few companies that succeeded, and many more that failed, when faced with disruptive technological change. Just as in our analogy to man’s finally learning to fly when aviators ultimately came to understand and either harness or accommodate some fundamental laws of nature, these case studies show that those executives who succeeded tended to manage by a very different set of rules than those that failed. There were, in fact, five fundamental principles of organizational nature that managers in the successful firms consistently recognized and harnessed. The firms that lost their battles with disruptive technologies chose to ignore or fight them. These principles are:

1. Resource dependence: Customers effectively control the patterns of resource allocation in well-run companies.

2. Small markets don’t solve the growth needs of large companies.

3. The ultimate uses or applications for disruptive technologies are unknowable in advance. Failure is an intrinsic step toward success.

4. Organizations have capabilities that exist independently of the capabilities of the people who work within them. Organizations’ capabilities reside in their processes and their values—and the very processes and values that constitute their core capabilities within the current business model also define their disabilities when confronted with disruption.

5. Technology supply may not equal market demand. The attributes that make disruptive technologies unattractive in established markets often are the very ones that constitute their greatest value in emerging markets.

How did the successful managers harness these principles to their advantage?

1. They embedded projects to develop and commercialize disruptive technologies within an organization whose customers needed them. When managers aligned a disruptive innovation with the “right” customers, customer demand increased the probability that the innovation would get the resources it needed.

2. They placed projects to develop disruptive technologies in organizations small enough to get excited about small opportunities and small wins.

3. They planned to fail early and inexpensively in the search for the market for a disruptive technology. They found that their markets generally coalesced through an iterative process of trial, learning, and trial again.

4. They utilized some of the resources of the mainstream organization to address the disruption, but they were careful not to leverage its processes and values. They created different ways of working within an organization whose values and cost structure were turned to the disruptive task at hand.

5. When commercializing disruptive technologies, they found or developed new markets that valued the attributes of the disruptive products, rather than search for a technological breakthrough so that the disruptive product could compete as a sustaining technology in mainstream markets.

Chapters 5 through 9 in Part Two describe in more detail how managers can address and harness these four principles. Each chapter starts by examining how harnessing or ignoring these principles affected the fortunes of disk drive companies when disruptive technologies were emerging.[1] Each chapter then branches into an industry with very different characteristics, to show how the same principles drove the success and failure of firms confronted with disruptive technologies there.

The sum of these studies is that while disruptive technology can change the dynamics of industries with widely varying characteristics, the drivers of success or failure when confronted by such technology are consistent across industries.

Chapter 10 shows how these principles can be used by illustrating how managers might apply them in a case study of a particularly vexing technology—the electric vehicle. Chapter 11 then reviews the principal findings of the book.

NOTES

1. The notion that we exercise power most effectively when we understand the physical and psychological laws that define the way the world works and then position or align ourselves in harmony with those laws, is of course not new to this book. At a light-hearted level, Stanford Professor Robert Burgelman, whose work is extensively cited in ths book, once dropped his pen onto the floor in a lecture. He muttered as he stooped to pick it up, “I hate gravity.” Then, as he walked to the blackboard to continue his line of thought, he added, “But do you know what? Gravity doesn’t care! It will always pull things down, and I may as well plan on it.”

At a more serious level, the desirability of aligning our actions with the amore powerful laws of nature, society, and psychology, in order to lead a productive life, is a central theme in many works, particularly the ancient Chinese classic, Tao te Ching.

CHAPTER FIVE

Give Responsibility for Disruptive Technologies to Organizations Whose Customers Need Them

Most executives would like to believe that they’re in charge of their organizations, that they make the crucial decisions and that when they decide that something should be done everyone snaps to and executes. This chapter expands on the view already introduced: that in practice, it is a company’s customers who effectively control what it can and cannot do. As we have seen in the disk drive industry, companies were willing to bet enormous amounts on technologically risky projects when it was clear that their customers needed the resulting products. But they were unable to muster the wherewithal to execute much simpler disruptive projects if existing, profitable customers didn’t need the products.

This observation supports a somewhat controversial theory called resource dependence, propounded by a minority of management scholars, [1] which posits that companies’ freedom of action is limited to satisfying the needs of those entities outside the firm (customers and investors, primarily) that give it the resources it needs to survive. Drawing heavily upon concepts from biological evolution, resource dependence theorists assert that organizations will survive and prosper only if their staffs and systems serve the needs of customers and investors by providing them with the products, services, and profit they require. Organizations that do not will ultimately die off, starved of the revenues they need to survive. [2] Hence, through this survival-of-the-fittest mechanism, those firms that rise to prominence in their industries generally will be those whose people and processes are most keenly tuned to giving their customers what they want. The controversy with this theory arises when its proponents conclude that managers are powerless to change the courses of their firms against the dictates of their customers. Even if a manager has a bold vision to take her or his company in a very different direction, the power of the customer-focused people and processes in any company well-adapted to survival in its competitive environment will reject the manager’s attempts to change direction. Therefore, because they provide the resources upon which the firm is dependent, it is the customers, rather than the managers, who really determine what a firm will do. It is forces outside the organization, rather than the managers within it, that dictate the company’s course. Resource dependence theorists conclude that the real role of managers in companies whose people and systems are well-adapted to survival is, therefore, only a symbolic one.

For those of us who have managed companies, consulted for management, or taught future managers, this is a most disquieting thought. We are there to manage, to make a difference, to formulate and implement strategy, to accelerate growth and improve profits. Resource dependence violates our very reason for being. Nonetheless, the findings reported in this book provide rather stunning support for the theory of resource dependence—especially for the notion that the customer-focused resource allocation and decision-making processes of successful companies are far more powerful in directing investments than are executives’ decisions.

Clearly, customers wield enormous power in directing a firm’s investments. What, then, should managers do when faced with a disruptive technology that the company’s customers explicitly do not want? One option is to convince everyone in the firm that the company should pursue it anyway, that it has long-term strategic importance despite rejection by the customers who pay the bills and despite lower profitability than the upmarket alternatives. The other option would be to create an independent organization and embed it among emerging customers that do need the technology. Which works best?

Managers who choose the first option essentially are picking a fight with a powerful tendency of organizational nature—that customers, not managers, essentially control the investment patterns of a company. By contrast, managers who choose the second option align themselves with this tendency, harnessing rather than fighting its power. The cases presented in this chapter provide strong evidence that the second option offers far higher probabilities of success than the first.

INNOVATION AND RESOURCE ALLOCATION

The mechanism through which customers control the investments of a firm is the resource allocation process—the process that determines which initiatives get staff and money and which don’t. Resource allocation and innovation are two sides of the same coin: Only those new product development projects that do get adequate funding, staffing, and management attention have a chance to succeed; those that are starved of resources will languish. Hence, the patterns of innovation in a company will mirror quite closely the patterns in which resources are allocated.

Good resource allocation processes are designed to weed out proposals that customers don’t want. When these decision-making processes work well, if customers don’t want a product, it won’t get funded; if they do want it, it will. This is how things must work in great companies. They must invest in things customers want—and the better they become at doing this, the more successful they will be.

As we saw in chapter 4, resource allocation is not simply a matter of top-down decision making followed by implementation. Typically, senior managers are asked to decide whether to fund a project only after many others at lower levels in the organization have already decided which types of project proposals they want to package and send on to senior management for approval and which they don’t think are worth the effort. Senior managers typically see only a well-screened subset of the innovative ideas generated. [3]

And even after senior management has endorsed funding for a particular project, it is rarely a “done deal.” Many crucial resource allocation decisions are made after project approval—indeed, after product launch—by mid-level managers who set priorities when multiple projects and products compete for the time of the same people, equipment, and vendors. As management scholar Chester Barnard has noted:

From the point of view of the relative importance of specific decisions, those of executives properly call for first attention. But from the point of view of aggregate importance, it is not decisions of executives, but of non-executive participants in organizations which should enlist major interest. [Italics added.] [4]

So how do non-executive participants make their resource allocation decisions? They decide which projects they will propose to senior management and which they will give priority to, based upon their understanding of what types of customers and products are most profitable to the company. Tightly coupled with this is their view of how their sponsorship of different proposals will affect their own career trajectories within the company, a view that is formed heavily by their understanding of what customers want and what types of products the company needs to sell more of in order to be more profitable. Individuals’ career trajectories can soar when they sponsor highly profitable innovation programs. It is through these mechanisms of seeking corporate profit and personal success, therefore, that customers exert a profound influence on the process of resource allocation, and hence on the patterns of innovation, in most companies.

SUCCESS IN DISRUPTIVE DISK DRIVE TECHNOLOGY

It is possible to break out of this system of customer control, however. Three cases in the history of the disk drive industry demonstrate how managers can develop strong market positions in a disruptive technology. In two cases, managers harnessed, rather than fought, the forces of resource dependence: They spun out independent companies to commercialize the disruptive technology. In the third, the manager chose to fight these forces, and survived the project, exhausted.

Quantum and Plus Development

As we have seen, Quantum Corporation, a leading maker of 8-inch drives sold in the minicomputer market in the early 1980s, completely missed the advent of 5.25-inch drives: It introduced its first versions nearly four years after those drives first appeared in the market. As the 5.25-inch pioneers began to invade the minicomputer market from below, for all the reasons already described, Quantum’s sales began to sag.

In 1984 several Quantum employees saw a potential market for a thin 3.5-inch drive plugged into an expansion slot in IBM XT-and AT-class desktop computers—drives that would be sold to personal computer users rather than the OEM minicomputer manufacturers that had accounted for all of Quantum’s revenue. They determined to leave Quantum and start a new firm to commercialize their idea.

Rather than let them leave unencumbered, however, Quantum’s executives financed and retained 80 percent ownership of this spinoff venture, called Plus Development Corporation, and set the company up in different facilities. It was a completely self-sufficient organization, with its own executive staff and all of the functional capabilities required in an independent company. Plus was extremely successful. It designed and marketed its drives but had them manufactured under contract by Matsushita Kotobuki Electronics (MKE) in Japan.

As sales of Quantum’s line of 8-inch drives began to evaporate in the mid-1980s, they were offset by Plus’s growing “Hardcard” revenues. By 1987, sales of Quantum’s 8-and 5.25-inch products had largely disappeared. Quantum then purchased the remaining 20 percent of Plus, essentially closed down the old corporation, and installed Plus’s executives in Quantum’s most senior positions. They then reconfigured Plus’s 3.5-inch products to appeal to OEM desktop computer makers, such as Apple, just as the capacity vector for 3.5-inch drives was invading the desktop market, as shown in the disk drive trajectory map in Figure 1.7. Quantum, thus reconstituted as a 3.5-inch drive maker, has aggressively adopted sustaining component technology innovations, moving upmarket toward engineering workstations, and has also successfully negotiated the sustaining architectural innovation into 2.5-inch drives. By 1994 the new Quantum had become the largest unit-volume producer of disk drives in the world. [5]

Control Data in Oklahoma

Control Data Corporation (CDC) effected the same self-reconstitution— once. CDC was the dominant manufacturer of 14-inch drives sold into the OEM market between 1965 and 1982; its market share fluctuated between 55 and 62 percent. When the 8-inch architecture emerged in the late 1970s, however, CDC missed it—by three years. The company never captured more than a fraction of the 8-inch market, and those 8-inch drives that it did sell were sold almost exclusively to defend its established customer base of mainframe computer manufacturers. The reason was resources and managerial emphasis: Engineers and marketers at the company’s principal Minneapolis facility kept getting pulled off the 8-inch program to resolve problems in the launch of next-generation 14-inch products for CDC’s mainstream customers.

CDC launched its first 5.25-inch model two years after Seagate’s pioneering product appeared in 1980. This time, however, CDC located its 5.25-inch effort in Oklahoma City. This was done, according to one manager, “not to escape CDC’s Minneapolis engineering culture, but to isolate the [5.25-inch product] group from the company’s mainstream customers.” Although it was late in the market and never regained its former dominant position, CDC’s foray into 5.25-inch drives was profitable, and at times the firm commanded a 20 percent share of higher-capacity 5.25-inch drives.

Micropolis: Transition by Managerial Force

Micropolis Corporation, an early disk drive leader founded in 1978 to make 8-inch drives, was the only other industry player to successfully make the transition to a disruptive platform. It did not use the spin-out strategy that had worked for Quantum and Control Data, however, choosing instead to manage the change from within the mainstream company. But even this exception supports the rule that customers exert exceptionally powerful influence over the investments that firms can undertake successfully.

Micropolis began to change in 1982, when founder and CEO Stuart Mabon intuitively perceived the trajectories of market demand and technology supply mapped in Figure 1.7 and decided that the firm should become primarily a maker of 5.25-inch drives. While initially hoping to keep adequate resources focused on developing its next generation of 8-inch drives so that Micropolis could straddle both markets, [6] he assigned the company’s premier engineers to the 5.25-inch program. Mabon recalls that it took “100 percent of my time and energy for eighteen months” to keep adequate resources focused on the 5.25-inch program, because the organization’s own mechanisms allocated resources to where the customers were—8-inch drives.

By 1984, Micropolis had failed to keep pace with competition in the minicomputer market for disk drives and withdrew its remaining 8-inch models. With Herculean effort, however, it did succeed in its 5.25-inch programs. Figure 5.1 shows why this struggle occurred: In making the transition, Micropolis assumed a position on a very different technological trajectory. It had to walk away from every one of its major customers and replace the lost revenues with sales of the new product line to an entirely different group of desktop computer makers. Mabon remembers the experience as the most exhausting of his life.

Figure 5.1 Technology Transition and Market Position at Micropolis Corporation

Source: Data are from various issues of Disk/Trend Report.

Micropolis finally introduced a 3.5-inch product in 1993. That was the point at which the product had progressed to pack more than 1 gigabyte in the 3.5-inch platform. At that level, Micropolis could sell the 3.5-inch drive to its existing customers.

DISRUPTIVE TECHNOLOGIES AND THE THEORY OF RESOURCE DEPENDENCE

The struggles recounted earlier of Seagate Technology’s attempts to sell 3.5-inch drives and of Bucyrus Erie’s failed attempt to sell its early Hydrohoe only to its mainstream customers illustrate how the theory of resource dependence can be applied to cases of disruptive technologies. In both instances, Seagate and Bucyrus were among the first in their industries to develop these disruptive products. But despite senior managers’ decisions to introduce them, the impetus or organizational energy required to launch the products aggressively into the appropriate value networks simply did not coalesce—until customers needed them.

Should we then accept the corollary stipulated by resource-dependence theorists that managers are merely powerless individuals? Hardly. In the Introduction, exploring the image of how people learned to fly, I noted that all attempts had ended in failure as long as they consisted of fighting fundamental laws of nature. But once laws such as gravity, Bernoulli’s principle, and the notions of lift, drag and resistance began to be understood, and flying machines were designed that accounted for or harnessed those laws, people flew quite successfully. By analogy, this is what Quantum and Control Data did. By embedding independent organizations within an entirely different value network, where they were dependent upon the appropriate set of customers for survival, those managers harnessed the powerful forces of resource dependence. The CEO of Micro-polis fought them, but he won a rare and costly victory.

Disruptive technologies have had deadly impact in many industries besides disk drives, mechanical excavators, and steel. [7] The following pages summarize the effect of disruptive technologies in three other industries— computers, retailing, and printers—to highlight how the only companies in those industries that established strong market positions in the disruptive technologies were those which, like Quantum and Control Data, harnessed rather than fought the forces of resource dependence.

DEC, IBM, AND THE PERSONAL COMPUTER

Quite naturally, the computer industry and the disk drive industry have parallel histories, because value networks of the latter are embedded in those of the former. In fact, if the axes and intersecting trajectories depicted on the disk drive trajectory map in Figure 1.7 were relabeled with computer-relevant terms, it would summarize equally well the failure of leading computer industry firms. IBM, the industry’s first leader, sold its mainframe computers to the central accounting and data processing departments of large organizations. The emergence of the minicomputer represented a disruptive technology to IBM and its competitors. Their customers had no use for it; it promised lower, not higher, margins; and the market initially was significantly smaller. As a result, the makers of mainframes ignored the minicomputer for years, allowing a set of entrants—Digital Equipment, Data General, Prime, Wang, and Nixdorf—to create and dominate that market. IBM ultimately introduced its own line of minicomputers, but it did so primarily as a defensive measure, when the capabilities of minicomputers had advanced to the point that they were performance-competitive with the computing needs of some of IBM’s customers.

Similarly, none of the makers of minicomputers became a significant factor in the desktop personal computer market, because to them the desktop computer was a disruptive technology. The PC market was created by another set of entrants, including Apple, Commodore, Tandy, and IBM. The minicomputer makers were exceptionally prosperous and highly regarded by investors, the business press, and students of good management—until the late 1980s, when the technological trajectory of the desktop computer intersected with the performance demanded by those who had previously bought minicomputers. The missile-like attack of the desktop computer from below severely wounded every minicomputer maker. Several of them failed. None established a viable position in the desktop personal computer value network.

A similar sequence of events characterized the emergence of the portable computer, where the market was created and dominated by a set of entrants like Toshiba, Sharp, and Zenith. Apple and IBM, the leading desktop makers, did not introduce portable models until the portables’ performance trajectory intersected with the computing needs of their customers.

Probably none of these firms has been so deeply wounded by disruptive technology as Digital Equipment. DEC fell from fortune to folly in just a few years, as stand-alone workstations and networked desktop computers obviated most customers’ needs for minicomputers almost overnight.

DEC didn’t stumble for lack of trying, of course. Four times between 1983 and 1995 it introduced lines of personal computers targeted at consumers, products that were technologically much simpler than DEC’s minicomputers. But four times it failed to build businesses in this value network that were perceived within the company as profitable. Four times it withdrew from the personal computer market. Why? DEC launched all four forays from within the mainstream company. [8] For all of the reasons so far recounted, even though executive-level decisions lay behind the move into the PC business, those who made the day-to-day resource allocation decisions in the company never saw the sense in investing the necessary money, time, and energy in low-margin products that their customers didn’t want. Higher-performance initiatives that promised up-scale margins, such as DEC’s super-fast Alpha microprocessor and its adventure into mainframe computers, captured the resources instead.

In trying to enter the desktop personal computing business from within its mainstream organization, DEC was forced to straddle the two different cost structures intrinsic to two different value networks. It simply couldn’t hack away enough overhead cost to be competitive in low-end personal computers because it needed those costs to remain competitive in its higher-performance products.

Yet IBM’s success in the first five years of the personal computing industry stands in stark contrast to the failure of the other leading mainframe and minicomputer makers to catch the disruptive desktop computing wave. How did IBM do it? It created an autonomous organization in Florida, far away from its New York state headquarters, that was free to procure components from any source, to sell through its own channels, and to forge a cost structure appropriate to the technological and competitive requirements of the personal computing market. The organization was free to succeed along metrics of success that were relevant to the personal computing market. In fact, some have argued that IBM’s subsequent decision to link its personal computer division much more closely to its mainstream organization was an important factor in IBM’s difficulties in maintaining its profitability and market share in the personal computer industry. It seems to be very difficult to manage the peaceful, unambiguous coexistence of two cost structures, and two models for how to make money, within a single company.

The conclusion that a single organization might simply be incapable of competently pursuing disruptive technology, while remaining competitive in mainstream markets, bothers some “can-do” managers—and, in fact, most managers try to do exactly what Micropolis and DEC did: maintain their competitive intensity in the mainstream, while simultaneously trying to pursue disruptive technology. The evidence is strong that such efforts rarely succeed; position in one market will suffer unless two separate organizations, embedded within the appropriate value networks, pursue their separate customers.

KRESGE, WOOLWORTH, AND DISCOUNT RETAILING

In few industries has the impact of disruptive technology been felt so pervasively as in retailing, where discounters seized dominance from traditional department and variety stores. The technology of discount retailing was disruptive to traditional operations because the quality of service and selection offered by discounters played havoc with the accustomed metrics of quality retailing. Moreover, the cost structure required to compete profitably in discount retailing was fundamentally different than that which department stores had developed to compete within their value networks.

The first discount store was Korvette’s, which began operating a number of outlets in New York in the mid-1950s. Korvette’s and its imitators operated at the very low end of retailing’s product line, selling nationally known brands of standard hard goods at 20 to 40 percent below department store prices. They focused on products that “sold themselves” because customers already knew how to use them. Relying on national brand image to establish the value and quality of their products, these discounters eliminated the need for knowledgeable salespeople; they also focused on the group of customers least attractive to mainstream retailers: “young wives of blue collar workers with young children.” [9] This was counter to the upscale formulas department stores historically had used to define quality retailing and to improve profits.

Discounters didn’t accept lower profits than those of traditional retailers, however; they just earned their profits through a different formula. In the simplest terms, retailers cover their costs through the gross margin, or markup, they charge over the cost of the merchandise they sell. Traditional department stores historically marked merchandise up by 40 percent and turned their inventory over four times in a year—that is, they earned 40 percent on the amount they invested in inventory, four times during the year, for a total return on inventory investment of 160 percent. Variety stores earned somewhat lower profits through a formula similar to that used by the department stores. Discount retailers earned a return on inventory investment similar to that of department stores, but through a different model: low gross margins and high inventory turns. Table 5.1 summarizes the three positions.

The history of discount retailing vividly recalls the history of minimill steel making. Just like the minimills, discounters took advantage of their cost structure to move upmarket and seize share from competing traditional retailers at a stunning rate: first at the low end, in brand-name hard goods such as hardware, small appliances, and luggage, and later in territory further to the northeast such as home furnishings and clothing. Figure 5.2 illustrates how stunning the discounters’ invasion was: Their share of retailing revenues in the categories of goods they sold rose from 10 percent in 1960 to nearly 40 percent a scant six years later.

Table 5.1 Different Pathways to Profits

Retailer Type

Company Example

Typical Gross Margins

Typical Inventory Tums

Return on Inventory Investment *

Department stores

R. H. Macy

40%

4x

160%

Variety stores

F. W. Woolworth

36%

4x

144%

Discount retailers

Kmart

20%

8x

160%

* Calculated as Margins x Turns, in other words, the total of the margins earned through successive turnovers each year. Source: Annual corporate reports of many companies in each category for various years.

Figure 5.2 Gains in Discount Retailers’ Market Share, 1960–1966

Source: Data are from various issues of Discount Merchandiser.

Just as in disk drives and excavators, a few of the leading traditional retailers—notably S. S. Kresge, F. W. Woolworth, and Dayton Hudson— saw the disruptive approach coming and invested early. None of the other major retail chains, including Sears, Montgomery Ward, J. C. Penney, and R. H. Macy, made a significant attempt to create a business in discount retailing. Kresge (with its Kmart chain) and Dayton Hudson (with the Target chain) succeeded. [10] They both created focused discount retailing organizations that were independent from their traditional business. They recognized and harnessed the forces of resource dependence. By contrast, Woolworth failed in its venture (Woolco), trying to launch it from within the F. W. Woolworth variety store company. A detailed comparison of the approaches of Kresge and Woolworth, which started from very similar positions, lends additional insight into why establishing independent organizations to pursue disruptive technology seems to be a necessary condition for success.

S. S. Kresge, then the world’s second largest variety store chain, began studying discount retailing in 1957, while discounting was still in its infancy. By 1961, both Kresge and its rival F. W. Woolworth (the world’s largest variety store operator) had announced initiatives to enter discount retailing. Both firms opened stores in 1962, within three months of each other. The performance of the Woolco and Kmart ventures they launched, however, subsequently differed dramatically. A decade later, Kmart’s sales approached $3.5 billion while Woolco’s sales were languishing unprofitably at $0.9 billion. [11]

In making its commitment to discount retailing, Kresge decided to exit the variety store business entirely: In 1959 it hired a new CEO, Harry Cunningham, whose sole mission was to convert Kresge into a discounting powerhouse. Cunningham, in turn, brought in an entirely new management team, so that by 1961 there “was not a single operating vice president, regional manager, assistant regional manager, or regional merchandise manager who was not new on the job.” [12] In 1961 Cunningham stopped opening any new variety stores, embarking instead on a program of closing about 10 percent of Kresge’s existing variety operations each year. This represented a wholesale refocusing of the company on discount retailing.

Woolworth, on the other hand, attempted to support a program of sustaining improvements in technology, capacity, and facilities in its core variety store businesses while simultaneously investing in disruptive discounting. The managers charged with improving the performance of Woolworth’s variety stores were also charged with building “the largest chain of discount houses in America.” CEO Robert Kirkwood asserted that Woolco “would not conflict with the company’s plans for growth and expansion in the regular variety store operations,” and that no existing stores would be converted to a discount format. [13] Indeed, as discount retailing hit its most frenzied expansion phase in the 1960s, Woolworth was opening new variety stores at the pace it had set in the 1950s.

Unfortunately (but predictably), Woolworth proved unable to sustain within a single organization the two different cultures, and two different models of how to make a profit, that were required to be successful in variety and discount retailing. By 1967 it had dropped the term “discount” from all Woolco advertising, adopting the term “promotional department store” instead. Although initially Woolworth had set up a separate administrative staff for its Woolco operation, by 1971 more rational, cost-conscious heads had prevailed.

In a move designed to increase sales per square foot in both Woolco and Woolworth divisions, the two subsidiaries have been consolidated operationally on a regional basis. Company officials say the consolidation—which involves buying offices, distribution facilities and management personnel at the regional level—will help both to develop better merchandise and more efficient stores. Woolco will gain the benefits of Woolworth’s buying resources, distribution facilities and additional expertise in developing specialty departments. In return, Woolworth will gain Woolco’s knowhow in locating, designing, promoting and operating large stores over 100,000 sq. ft. [14]

What was the impact of this cost-saving consolidation? It provided more evidence that two models for how to make money cannot peacefully coexist within a single organization. Within a year of this consolidation, Woolco had increased its markups such that its gross margins were the highest in the discount industry—about 33 percent. In the process, its inventory turns fell from the 7x it originally had achieved to 4x. The formula for profit that had long sustained F. W. Woolworth (35 percent margins for four inventory turns or 140 percent return on inventory investment) was ultimately demanded of Woolco as well. (See Figure 5.3.) Woolco was no longer a discounter—in name or in fact. Not surprisingly, Woolworth’s venture into discount retailing failed: It closed its last Woolco store in 1982.

Woolworth’s organizational strategy for succeeding in disruptive discount retailing was the same as Digital Equipment’s strategy for launching its personal computer business. Both founded new ventures within the mainstream organization that had to earn money by mainstream rules, and neither could achieve the cost structure and profit model required to succeed in the mainstream value network.

Figure 5.3 Impact of the Integration of Woolco, and F. W. Woolworth on the Way

Source: Data are from various annual reports of F. W. Woolworth Company and from various issues of Discount Merchandiser.

SURVIVAL BY SUICIDE: HEWLETT-PACKARD’S LASER JET AND INK-JET PRINTERS

Hewlett-Packard’s experience in the personal computer printer business illustrates how a company’s pursuit of a disruptive technology by spinning out an independent organization might entail, in the end, killing another of its business units.

Hewlett-Packard’s storied success in manufacturing printers for personal computers becomes even more remarkable when one considers its management of the emergence of bubble-jet or ink-jet technology. Beginning in the mid-1980s, HP began building a huge and successful business around laser jet printing technology. The laser jet was a discontinuous improvement over dot-matrix printing, the previously dominant personal computer printing technology, and HP built a commanding market lead.

When an alternative way of translating digital signals into images on paper (ink-jet technology) first appeared, there were vigorous debates about whether laser jet or ink jet would emerge as the dominant design in personal printing. Experts lined up on both sides of the question, offering HP extensive advice on which technology would ultimately become the printer of choice on the world’s desktops. [15]

Although it was never framed as such in the debates of the time, inkjet printing was a disruptive technology. It was slower than the laser jet, its resolution was worse, and its cost per printed page was higher. But the printer itself was smaller and potentially much less expensive than the laser jet. At these lower prices, it promised lower gross margin dollars per unit than the laser jet. Thus, the ink-jet printer was a classic disruptive product, relative to the laser jet business.

Rather than place its bet exclusively with one or the other, and rather than attempt to commercialize the disruptive ink-jet from within the existing printer division in Boise, Idaho, HP created a completely autonomous organizational unit, located in Vancouver, Washington, with responsibility for making the ink-jet printer a success. It then let the two businesses compete against each other. Each has behaved classically. As shown in Figure 5.4, the laser jet division has moved sharply upmarket, in a strategy reminiscent of 14-inch drives, mainframe computers, and integrated steel mills. HP’s laser jet printers can print at high speeds with exceptional resolution; handle hundreds of fonts and complicated graphics; print on two sides of the page; and serve multiple users on a network. They have also gotten larger physically.

The ink-jet printer isn’t as good as the laser jet and may never be. But the critical question is whether the ink jet could ever be as good a printer as the personal desktop computing market demands. The answer appears to be yes. The resolution and speed of ink-jet printers, while still inferior to those of laser jets, are now clearly good enough for many students, professionals, and other un-networked users of desktop computers.

HP’s ink-jet printer business is now capturing many of those who would formerly have been laser jet users. Ultimately, the number of users at the highest-performance end of the market, toward which the laser jet division is headed, will probably become small. One of HP’s businesses may, in the end, have killed another. But had HP not set up its ink-jet business as a separate organization, the ink-jet technology would probably have languished within the mainstream laser jet business, leaving one of the other companies now actively competing in the ink-jet printer business, such as Canon, as a serious threat to HP’s printer business. And by staying in the laser business, as well, HP has joined IBM’s mainframe business and the integrated steel companies in making a lot of money while executing an upmarket retreat. [16]

Figure 5.4 Speed Improvement in InkJet and LaserJet Printers

Source: Hewlett-Packard product brochures, various years.

NOTES

1. The theory of resource dependence has been most thoroughly argued by Jeffrey Pfeffer and Gerald R. Salancik in The External Control of Organizations: A Resource Dependence Perspective (New York: Harper & Row, 1978).

2. This implies that, in managing business under both normal conditions and conditions of assault by a disruptive technology, the choice of which customers the firm will serve has enormous strategic consequences.

3. Joseph L. Bower, in Managing the Resource Allocation Process (Homewood, IL: Richard D. Irwin, 1972), presents an elegant and compelling picture of the resource allocation process.

4. Chester Barnard, The Functions of the Executive (Cambridge, MA: Harvard University Press, 1938), 190–191.

5. Quantum’s spin-out of the Hardcard effort and its subsequent strategic reorientation is an example of the processes of strategy change described by Robert Burgelman, in “Intraorganizational Ecology of Strategy-Making and Organizational Adaptation: Theory and Field Research,” Organization Science (2), 1991, 239–262, as essentially a process of natural selection through which suboptimal strategic initiatives lose out to optimal ones in the internal competition for corporate resources.

6. The failure of Micropolis to maintain simultaneous competitive commitments to both its established technology and the new 5.25-inch technology is consistent with the technological histories recounted by James Utterback, in Mastering the Dynamics of Innovation (Boston: Harvard Business School Press, 1994). Utterback found that firms that attempted to develop radically new technology almost always tried to maintain simultaneous commitment to the old and that they almost always failed.

7. A set of industries in which disruptive technologies are believed to have played a role in toppling leading firms is presented by Richard S. Rosenbloom and Clayton M. Christensen in “Technological Discontinuities, Organizational Capabilities, and Strategic Commitments,” Industrial and Corporate Change (3), 1994, 655–685.

8. In the 1990s, DEC finally set up a Personal Computer Division in its attempt to build a significant personal computer business. It was not as autonomous from DEC’s mainstream business; however, the Quantum and Control Data spin-outs were. Although DEC set up specific performance metrics for the PC division, it was still held, de facto, to corporate standards for gross margins and revenue growth.

9. “Harvard Study on Discount Shoppers,” Discount Merchandiser, September, 1963, 71.

10. When this book was being written, Kmart was a crippled company, having been beaten in a game of strategy and operational excellence by WalMart. Nonetheless, during the preceding two decades, Kmart had been a highly successful retailer, creating extraordinary value for Kresge shareholders. Kmart’s present competitive struggles are unrelated to Kresge’s strategy in meeting the original disruptive threat of discounting.

11. A detailed contrast between the Woolworth and Kresge approaches to discount retailing can be found in the Harvard Business School teaching case. “The Discount Retailing Revolution in America,” No. 695-081.

12. See Robert Drew-Bear, “S. S. Kresge’s Kmarts,” Mass Merchandising: Revolution and Evolution (New York: Fairchild Publications, 1970), 218.

13. F. W. Woolworth Company Annual Report, 1981, p. 8.

14. “Woolco Gets Lion’s Share of New Space,” Chain Store Age, November, 1972, E27. This was an extraordinarily elegant, rational argument for the consolidation, clearly crafted by a corporate spin-doctor extraordinaire. Never mind that no Woolworth stores approached 100,000 square feet in size!

15. See, for example, “The Desktop Printer Industry in 1990,” Harvard Business School, Case No. 9-390-173.

16. Business historian Richard Tedlow noted that the same dilemma had confronted A&P’s executives as they deliberated whether to adopt the disruptive supermarket retailing format:

The supermarket entrepreneurs competed against A&P not by doing better what A&P was the best company in the world at doing, but by doing something that A&P did not want to do at all. The greatest entrepreneurial failure in this story is Kroger. This company was second in the market, and one of its own employees (who left to found the world’s first supermarket) knew how to make it first. Kroger executives did not listen. Perhaps it was lack of imagination or perhaps, like the executives at A&P, those at Kroger also had too much invested in the standard way of doing business. If the executives at A&P endorsed the supermarket revolution, they were ruining their own distribution system. That is why they sat by paralyzed, unable to act until it was almost too late. In the end, A&P had little choice. The company could ruin its own system, or see others do it.

See Richard Tedlow, New and Improved: The Story of Mass Marketing in America (Boston: Harvard Business School Press, 1996).

CHAPTER SIX

Match the Size of the Organization to the Size of the Market

Managers who confront disruptive technological change must be leaders, not followers, in commercializing disruptive technologies. Doing so requires implanting the projects that are to develop such technologies in commercial organizations that match in size the market they are to address. These assertions are based on two key findings of this study: that leadership is more crucial in coping with disruptive technologies than with sustaining ones, and that small, emerging markets cannot solve the near-term growth and profit requirements of large companies.

The evidence from the disk drive industry shows that creating new markets is significantly less risky and more rewarding than entering established markets against entrenched competition. But as companies become larger and more successful, it becomes even more difficult to enter emerging markets early enough. Because growing companies need to add increasingly large chunks of new revenue each year just to maintain their desired rate of growth, it becomes less and less possible that small markets can be viable as vehicles through which to find these chunks of revenue. As we shall see, the most straightforward way of confronting this difficulty is to implant projects aimed at commercializing disruptive technologies in organizations small enough to get excited about small-market opportunities, and to do so on a regular basis even while the mainstream company is growing.

ARE THE PIONEERS REALLY THE ONES WITH ARROWS IN THEIR BACKS?

A crucial strategic decision in the management of innovation is whether it is important to be a leader or acceptable to be a follower. Volumes have been written on first-mover advantages, and an offsetting amount on the wisdom of waiting until the innovation’s major risks have been resolved by the pioneering firms. “You can always tell who the pioneers were,” an old management adage goes. “They’re the ones with the arrows in their backs.” As with most disagreements in management theory, neither position is always right. Indeed, some findings from the study of the disk drive industry give some insight into when leadership is critical and when followership makes better sense.

Leadership in Sustaining Technologies May Not Be Essential

One of the watershed technologies affecting the pace at which disk drive makers have increased the recording density of their drives was the thin-film read/write head. We saw in chapter 1 that despite the radically different, competence-destroying character of the technology, the $100 million and five-to-fifteen year expense of developing it, the firms that led in this technology were the leading, established disk drive manufacturers.

Because of the risk involved in the technology’s development and its potential importance to the industry, the trade press began speculating in the late 1970s about which competitor would lead with thin-film heads. How far might conventional ferrite head technology be pushed? Would any drive makers get squeezed out of the industry race because they placed a late or wrong bet on the new head technology? Yet, it turned out, whether a firm led or followed in this innovation did not make a substantial difference in its competitive position. This is illustrated in Figures 6.1 and 6.2.

Figure 6.1 shows when each of the leading firms introduced its first model employing thin-film head technology. The vertical axis measures the recording density of the drive. The bottom end of the line for each firm denotes the maximum recording density it had achieved before it introduced a model with a thin-film head. The top end of each line indicates the density of the first model each company introduced with a thin-film head. Notice the wide disparity in the points at which the firms felt it was important to introduce the new technology. IBM led the industry, introducing its new head when it had achieved 3 megabits (Mb) per square inch. Memorex and Storage Technology similarly took a leadership posture with respect to this technology. At the other end, Fujitsu and Hitachi pushed the performance of conventional ferrite heads nearly ten times beyond the point where IBM first introduced the technology, choosing to be followers, rather than leaders, in thin-film technology.

Figure 6.1 Points at Which Thin-Film Technology Was Adopted by Leading Manufacturers, Relative to the Capabilities of Ferrite/Oxide Technology at the Time of the Switch

Source: Data are from various issues of Disk/Trend Report.

What benefit, if any, did leadership in this technology give to the pioneers? There is no evidence that the leaders gained any significant competitive advantage over the followers; none of the firms that pioneered thin-film technology gained significant market share on that account. In addition, pioneering firms appear not to have developed any sort of learning advantage enabling them to leverage their early lead to attain higher levels of density than did followers. Evidence of this is displayed in Figure 6.2. The horizontal axis shows the order in which the firms adopted thin-film heads. Hence, IBM was the first, Memorex, the second, and Fujitsu the fifteenth. The vertical axis gives the rank ordering of the recording density of the most advanced model marketed by each firm in 1989. If the early adopters of thin-film heads enjoyed some sort of experience-based advantage over the late adopters, then we would expect the points in the chart to slope generally from the upper left toward the lower right. The chart shows instead that there is no relationship between leadership and followership in thin-film heads and any subsequent technological edge. [1]

Each of the other sustaining technologies in the industry’s history present a similar picture. There is no evidence that any of the leaders in developing and adopting sustaining technologies developed a discernible competitive advantage over the followers. [2]

Leadership in Disruptive Technologies Creates Enormous Value

In contrast to the evidence that leadership in sustaining technologies has historically conferred little advantage on the pioneering disk drive firms, there is strong evidence that leadership in disruptive technology has been very important. The companies that entered the new value networks enabled by disruptive generations of disk drives within the first two years after those drives appeared were six times more likely to succeed than those that entered later.

Eighty-three companies entered the U.S. disk drive industry between 1976 and 1993. Thirty-five of these were diversified concerns, such as Memorex, Ampex, 3M, and Xerox, that made other computer peripheral equipment or other magnetic recording products. Forty-eight were independent startup companies, many being financed by venture capital and headed by people who previously had worked for other firms in the industry. These numbers represent the complete census of all firms that ever were incorporated and/or were known to have announced the design of a hard drive, whether or not they actually sold any. It is not a statistical sample of firms that might be biased in favor or against any type of firm.

Figure 6.2 Relationship between Order of Adoption of Thin-Film Technology and Areal Density of Highest-Performance 1989 Model

Source: Clayton M. Christensen, “Exploring the Limits of the Technology S-Curve. Part I: Component Technologies,” Production and Operations Management 1, no. 4 (Fall 1992): 347. Reprinted by permission.

The entry strategies employed by each of these firms can be characterized along the two axes in Table 6.1. The vertical axis describes technology strategies, with firms at the bottom using only proven technologies in their initial products and those at the top using one or more new component technologies. [3] The horizontal axis charts market strategies, with firms at the left having entered already established value networks and those at the right having entered emerging value networks. [4] Another way to characterize this matrix is to note that companies that were agressive at entry in developing and adopting sustaining innovations appear in the two top boxes, left and right, while companies that led at entry in creating new value networks appear in the two right-hand boxes, top and bottom. The companies in the right boxes include all companies that attempted to create new value networks, even those networks that did not materialize into substantial markets (such as removable hard drives).

Table 6.1 Disk Drive Companies Achieving $100 Million in Annual Revenues in at Least One Year Between 1976 and 1994

Source: Data are from various issues of Disk/Trend Report.

Note: S indicates success, F indicates failure, N indicates no, T indicates total.

Each quadrant displays the number of companies that entered using the strategy represented. Under the S (for “success”) are the number of firms that successfully generated $100 million in revenues in at least one year, even if the firm subsequently failed; F (for “failure”) shows the number of firms that failed ever to reach the $100 million revenue threshold and that have subsequently exited the industry; N (for “no”) indicates the number of firms for which there is as yet no verdict because, while still operating in 1994, they had not yet reached $100 million in sales; and T (for “total”) lists the total number of firms that entered in each category. [5] The column labeled “% Success” indicates the percentage of the total number of firms that reached $100 million in sales. Finally, beneath the matrix are the sums of the data in the two quadrants above.

The numbers beneath the matrix show that only three of the fifty-one firms (6 percent) that entered established markets ever reached the $100 million revenue benchmark. In contrast, 37 percent of the firms that led in disruptive technological innovation—those entering markets that were less than two years old—surpassed the $100 million level, as shown on the right side of Table 6.1. Whether a firm was a start-up or a diversified firm had little impact on its success rate. What mattered appears not to have been its organizational form, but whether it was a leader in introducing disruptive products and creating the markets in which they were sold. [6]

Only 13 percent of the firms that entered attempting to lead in sustaining component technologies (the top half of the matrix) succeeded, while 20 percent of the firms that followed were successful. Clearly, the lower-right quadrant offered the most fertile ground for success.

The cumulative sales numbers in the right-most columns in each quadrant show the total, cumulative revenues logged by all firms pursuing each of the strategies; these are summarized below the matrix. The result is quite stunning. The firms that led in launching disruptive products together logged a cumulative total of $62 billion dollars in revenues between 1976 and 1994. [7] Those that followed into the markets later, after those markets had become established, logged only $3.3 billion in total revenue. It is, indeed, an innovator’s dilemma. Firms that sought growth by entering small, emerging markets logged twenty times the revenues of the firms pursuing growth in larger markets. The difference in revenues per firm is even more striking: The firms that followed late into the markets enabled by disruptive technology, on the left half of the matrix, generated an average cumulative total of $64.5 million per firm. The average company that led in disruptive technology generated $1.9 billion in revenues. The firms on the left side seem to have made a sour bargain. They exchanged a market risk, the risk that an emerging market for the disruptive technology might not develop after all, for a competitive risk, the risk of entering markets against entrenched competition. [8]

COMPANY SIZE AND LEADERSHIP IN DISRUPTIVE TECHNOLOGIES

Despite evidence that leadership in disruptive innovation pays such huge dividends, established firms, as shown in the first four chapters of this book, often fail to take the lead. Customers of established firms can hold the organizations captive, working through rational, well-functioning resource allocation processes to keep them from commercializing disruptive technologies. One cruel additional disabling factor that afflicts established firms as they work to maintain their growth rate is that the larger and more successful they become, the more difficult it is to muster the rationale for entering an emerging market in its early stages, when the evidence above shows that entry is so crucial.

Good managers are driven to keep their organizations growing for many reasons. One is that growth rates have a strong effect on share prices. To the extent that a company’s stock price represents the discounted present value of some consensus forecast of its future earnings stream, then the level of the stock price—whether it goes up or down—is driven by changes in the projected rate of growth in earnings. [9] In other words, if a company’s current share price is predicated on a consensus growth forecast of 20 percent, and the market’s consensus for growth is subsequently revised downward to 15 percent growth, then the company’s share price will likely fall—even though its revenues and earnings will still be growing at a healthy rate. A strong and increasing stock price, of course, gives a company access to capital on favorable terms; happy investors are a great asset to a company.

Rising share prices make stock option plans an inexpensive way to provide incentive to and to reward valuable employees. When share prices stagnate or fall, options lose their value. In addition, company growth creates room at the top for high-performing employees to expand the scope of their responsibilities. When companies stop growing, they begin losing many of their most promising future leaders, who see less opportunity for advancement.

Finally, there is substantial evidence that growing companies find it much easier to justify investments in new product and process technologies than do companies whose growth has stopped. [10]

Unfortunately, companies that become large and successful find that maintaining growth becomes progressively more difficult. The math is simple: A $40 million company that needs to grow profitably at 20 percent to sustain its stock price and organizational vitality needs an additional $8 million in revenues the first year, $9.6 million the following year, and so on; a $400 million company with a 20 percent targeted growth rate needs new business worth $80 million in the first year, $96 million in the next, and so on; and a $4 billion company with a 20 percent goal needs to find $800 million, $960 million, and so on, in each successive year.

This problem is particularly vexing for big companies confronting disruptive technologies. Disruptive technologies facilitate the emergence of new markets, and there are no $800 million emerging markets. But it is precisely when emerging markets are small—when they are least attractive to large companies in search of big chunks of new revenue—that entry into them is so critical.

How can a manager of a large, successful company deal with these realities of size and growth when confronted by disruptive change? I have observed three approaches in my study of this problem:

1. Try to affect the growth rate of the emerging market, so that it becomes big enough, fast enough, to make a meaningful dent on the trajectory of profit and revenue growth of a large company.

2. Wait until the market has emerged and become better defined, and then enter after it “has become large enough to be interesting.”

3. Place responsibility to commercialize disruptive technologies in organizations small enough that their performance will be meaningfully affected by the revenues, profits, and small orders flowing from the disruptive business in its earliest years.

As the following case studies show, the first two approaches are fraught with problems. The third has its share of drawbacks too, but offers more evidence of promise.

CASE STUDY: PUSHING THE GROWTH RATE OF AN EMERGING MARKET

The history of Apple Computer’s early entry into the hand-held computer, or personal digital assistant (PDA), market helps to clarify the difficulties confronting large companies in small markets.

Apple Computer introduced its Apple I in 1976. It was at best a preliminary product with limited functionality, and the company sold a total of 200 units at $666 each before withdrawing it from the market. But the Apple I wasn’t a financial disaster. Apple had spent modestly on its development, and both Apple and its customers learned a lot about how desktop personal computers might be used. Apple incorporated this learning into its Apple II computer, introduced in 1977, which was highly successful. Apple sold 43,000 Apple II computers in the first two years they were on the market, [11] and the product’s success positioned the company as the leader in the personal computer industry. On the basis of the Apple II’s success Apple went public in 1980.

A decade after the release of the Apple II, Apple Computer had grown into a $5 billion company, and like all large and successful companies, it found itself having to add large chunks of revenue each year to preserve its equity value and organizational vitality. In the early 1990s, the emerging market for hand-held PDAs presented itself as a potential vehicle for achieving that needed growth. In many ways, this opportunity, analogous to that in 1978 when the Apple II computer helped shape its industry, was a great fit for Apple. Apple’s distinctive design expertise was in user-friendly products, and user-friendliness and convenience were the basis of the PDA concept.

How did Apple approach this opportunity? Aggressively. It invested scores of millions of dollars to develop its product, dubbed the “Newton.” The Newton’s features were defined through one of the most thoroughly executed market research efforts in corporate history; focus groups and surveys of every type were used to determine what features consumers would want. The PDA had many of the characteristics of a disruptive computing technology, and recognizing the potential problems, Apple CEO John Sculley made the Newton’s development a personal priority, promoting the product widely, and ensuring that the effort got the technical and financial resources it needed.

Apple sold 140,000 Newtons in 1993 and 1994, its first two years on the market. Most observers, of course, viewed the Newton as a big flop. Technically, its handwriting recognition capabilities were disappointing, and its wireless communications technologies had made it expensive. But what was most damning was that while Sculley had publicly positioned the Newton as a key product to sustain the company’s growth, its first-year sales amounted to about 1 percent of Apple’s revenues. Despite all the effort, the Newton made hardly a dent in Apple’s need for new growth.

But was the Newton a failure? The timing of Newton’s entry into the handheld market was akin to the timing of the Apple II into the desktop market. It was a market-creating, disruptive product targeted at an undefinable set of users whose needs were unknown to either themselves or Apple. On that basis, Newton’s sales should have been a pleasant surprise to Apple’s executives: It outsold the Apple II in its first two years by a factor of more than three to one. But while selling 43,000 units was viewed as an IPO-qualifying triumph in the smaller Apple of 1979, selling 140,000 Newtons was viewed as a failure in the giant Apple of 1994.

As chapter 7 will show, disruptive technologies often enable something to be done that previously had been deemed impossible. Because of this, when they initially emerge, neither manufacturers nor customers know how or why the products will be used, and hence do not know what specific features of the product will and will not ultimately be valued. Building such markets entails a process of mutual discovery by customers and manufacturers—and this simply takes time. In Apple’s development of the desktop computer, for example, the Apple I failed, the first Apple II was lackluster, and the Apple II[h31501] succeeded. The Apple III was a market failure because of quality problems, and the Lisa was a failure. The first two generations of the Macintosh computer also stumbled. It wasn’t until the third iteration of the Macintosh that Apple and its customers finally found “it”: the standard for convenient, user-friendly computing to which the rest of the industry ultimately had to conform. [12]

In launching the Newton, however, Apple was desperate to short-circuit this coalescent process for defining the ultimate product and market. It assumed that its customers knew what they wanted and spent very aggressively to find out what this was. (As the next chapter will show, this is impossible.) Then to give customers what they thought they wanted, Apple had to assume the precarious role of a sustaining technology leader in an emerging industry. It spent enormous sums to push mobile data communications and handwriting recognition technologies beyond the state of the art. And finally, it spent aggressively to convince people to buy what it had designed.

Because emerging markets are small by definition, the organizations competing in them must be able to become profitable at small scale. This is crucial because organizations or projects that are perceived as being profitable and successful can continue to attract financial and human resources both from their corporate parents and from capital markets. Initiatives perceived as failures have a difficult time attracting either. Unfortunately, the scale of the investments Apple made in its Newton in order to hasten the emergence of the PDA market made it very difficult to earn an attractive return. Hence, the Newton came to be broadly viewed as a flop.

As with most business disappointments, hindsight reveals the faults in Apple’s Newton project. But I believe that the root cause of Apple’s struggle was not inappropriate management. The executives’ actions were a symptom of a deeper problem: Small markets cannot satisfy the near-term growth requirements of big organizations.

CASE STUDY: WAITING UNTIL A MARKET IS LARGE ENOUGH TO BE INTERESTING

A second way that many large companies have responded to the disruptive technology trap is to wait for emerging markets to “get large enough to be interesting” before they enter. Sometimes this works, as IBM’s well-timed 1981 entry into the desktop PC business demonstrated. But it is a seductive logic that can backfire, because the firms creating new markets often forge capabilities that are closely attuned to the requirements of those markets and that later entrants find difficult to replicate. Two examples from the disk drive industry illustrate this problem.

Priam Corporation, which ascended to leadership of the market for 8-inch drives sold to minicomputer makers after its entry in 1978, had built the capability in that market to develop its drives on a two-year rhythm. This pace of new product introduction was consistent with the rhythm by which its customers, minicomputer makers, introduced their new products into the market.

Seagate’s first 5.25-inch drive, introduced to the emerging desktop market in 1980, was disruptively slow compared to the performance of Priam’s drives in the minicomputer market. But by 1983, Seagate and the other firms that led in implementing the disruptive 5.25-inch technology had developed a one-year product introduction rhythm in their market. Because Seagate and Priam achieved similar percentage improvements in speed with each new product generation, Seagate, by introducing new generations on a one-year rhythm, quickly began to converge on Priam’s performance advantage.

Priam introduced its first 5.25-inch drive in 1982. But the rhythm by which it introduced its subsequent 5.25-inch models was the two-year capability it had honed in the minicomputer market—not the one-year cycle required to compete in the desktop marketplace. As a consequence, it was never able to secure a single major OEM order from a desktop computer manufacturer: It just couldn’t hit their design windows with its new products. And Seagate, by taking many more steps forward than did Priam, was able to close the performance gap between them. Priam closed its doors in 1990.

The second example occurred in the next disruptive generation. Seagate Technology was the second in the industry to develop a 3.5-inch drive in 1984. Analysts at one point had speculated that Seagate might ship 3.5-inch drives as early as 1985; and indeed, Seagate showed a 10 MB model at the fall 1985 Comdex Show. When Seagate still had not shipped a 3.5-inch drive by late 1986, CEO Al Shugart explained, “So far, there just isn’t a big enough market for it, as yet.” [13] In 1987, when the 3.5-inch market at $1.6 billion had gotten “big enough to be interesting,” Seagate finally launched its offering. By 1991, however, even though Seagate had by then built substantial volume in 3.5-inch drives, it had not yet succeeded in selling a single drive to a maker of portable computers: Its models were all sold into the desktop market, defensively cannibalizing its sales of 5.25-inch drives. Why?

One likely reason for this phenomenon is that Conner Peripherals, which pioneered and maintained the lead in selling 3.5-inch drives to portable computer makers, fundamentally changed the way drive makers had to approach the portables market. As one Conner executive described it,

From the beginning of the OEM disk drive industry, product development had proceeded in three sequential steps. First you designed the drive; then you made it; and then you sold it. We changed all that. We first sell the drives; then we design them; and then we build them. [14]

In other words, Conner set a pattern whereby drives for the portable computer market were custom-designed for major customers. And it refined a set of capabilities in its marketing, engineering, and manufacturing processes that were tailored to that pattern. [15] Said another Conner executive, “Seagate was never able to figure out how to sell drives in the portable market. They just never got it.” [16]

CASE STUDY: GIVING SMALL OPPORTUNITIES TO SMALL ORGANIZATIONS

Every innovation is difficult. That difficulty is compounded immeasurably, however, when a project is embedded in an organization in which most people are continually questioning why the project is being done at all. Projects make sense to people if they address the needs of important customers, if they positively impact the organization’s needs for profit and growth, and if participating in the project enhances the career opportunities of talented employees. When a project doesn’t have these characteristics, its manager spends much time and energy justifying why it merits resources and cannot manage the project as effectively. Frequently in such circumstances, the best people do not want to be associated with the project—and when things get tight, projects viewed as nonessential are the first to be canceled or postponed.

Executives can give an enormous boost to a project’s probability of success, therefore, when they ensure that it is being executed in an environment in which everyone involved views the endeavor as crucial to the organization’s future growth and profitability. Under these conditions, when the inevitable disappointments, unforeseen problems, and schedule slippages occur, the organization will be more likely to find ways to muster whatever is required to solve the problem.

As we have seen, a project to commercialize a disruptive technology in a small, emerging market is very unlikely to be considered essential to success in a large company; small markets don’t solve the growth problems of big companies. Rather than continually working to convince and remind everyone that the small, disruptive technology might someday be significant or that it is at least strategically important, large companies should seek to embed the project in an organization that is small enough to be motivated by the opportunity offered by a disruptive technology in its early years. This can be done either by spinning out an independent organization or by acquiring an appropriately small company. Expecting achievement-driven employees in a large organization to devote a critical mass of resources, attention, and energy to a disruptive project targeted at a small and poorly defined market is equivalent to flapping one’s arms in an effort to fly: It denies an important tendency in the way organizations work. [17]

There are many success stories to the credit of this approach. Control Data, for example, which had essentially missed the 8-inch disk drive generation, sent a group to Oklahoma City to commercialize its 5.25-inch drive. In addition to CDC’s need to escape the power of its mainstream customers, the firm explicitly wanted to create an organization whose size matched the opportunity. “We needed an organization,” reflected one manager, “that could get excited about a $50,000 order. In Minneapolis [which derived nearly $1 billion from the sale of 14-inch drives in the mainframe market] you needed a million-dollar order just to turn anyone’s head.” CDC’s Oklahoma City venture proved to be a significant success.

Another way of matching the size of an organization to the size of the opportunity is to acquire a small company within which to incubate the disruptive technology. This is how Allen Bradley negotiated its very successful disruptive transition from mechanical to electronic motor controls.

For decades the Allen Bradley Company (AB) in Milwaukee has been the undisputed leader in the motor controls industry, making heavy-duty, sophisticated switches that turn large electric motors off and on and protect them from overloads and surges in current. AB’s customers were makers of machine tools and cranes as well as contractors who installed fans and pumps for industrial and commercial heating, ventilating, and air conditioning (HVAC) systems. Motor controls were electromechanical devices that operated on the same principle as residential light switches, although on a larger scale. In sophisticated machine tools and HVAC systems, electric motors and their controls were often linked, through systems of electromechanical relay switches, to turn on and off in particular sequences and under particular conditions. Because of the value of the equipment they controlled and the high cost of equipment downtime, controls were required to be rugged, capable of turning on and off millions of times and of withstanding the vibrations and dirt that characterized the environments in which they were used.

In 1968, a startup company, Modicon, began selling electronic programmable motor controls—a disruptive technology from the point of view of mainstream users of electromechanical controls. Texas Instruments (TI) entered the fray shortly thereafter with its own electronic controller. Because early electronic controllers lacked the real and perceived ruggedness and robustness for harsh environments of the hefty AB-type controllers, Modicon and TI were unable to sell their products to mainstream machine tool makers and HVAC contractors. As performance was measured in the mainstream markets, electronic products underperformed conventional controllers, and few mainstream customers needed the programmable flexibility offered by electronic controllers.

As a consequence, Modicon and TI were forced to cultivate an emerging market for programmable controllers: the market for factory automation. Customers in this emerging market were not equipment manufacturers, but equipment users, such as Ford and General Motors, who were just beginning their attempt to integrate pieces of automatic manufacturing equipment.

Of the five leading manufacturers of electromechanical motor controls—Allen Bradley, Square D, Cutler Hammer, General Electric, and Westinghouse—only Allen Bradley retained a strong market position as programmable electronic controls improved in ruggedness and began to invade the core motor control markets. Allen Bradley entered the electronic controller market just two years after Modicon and built a market-leading position in the new technology within a few years, even as it kept its strength in its old electromechanical products. It subsequently transformed itself into a major supplier of electronic controllers for factory automation. The other four companies, by contrast, introduced electronic controllers much later and subsequently either exited the controller business or were reduced to weak positions. From a capabilities perspective this is a surprising outcome, because General Electric and Westinghouse had much deeper expertise in microelectronics technologies at that time than did Allen Bradley, which had no institutional experience in the technology.

What did Allen Bradley do differently? In 1969, just one year after Modicon entered the market, AB executives bought a 25 percent interest in Information Instruments, Inc., a fledgling programmable controller start-up based in Ann Arbor, Michigan. The following year it purchased outright a nascent division of Bunker Ramo, which was focused on programmable electronic controls and their emerging markets. AB combined these acquisitions into a single unit and maintained it as a business separate from its mainstream electromechanical products operation in Milwaukee. Over time, the electronics products have significantly eaten into the electromechanical controller business, as one AB division attacked the other. [18] By contrast, each of the other four companies tried to manage its electronic controller businesses from within its mainstream electromechanical divisions, whose customers did not initially need or want electronic controls. Each failed to develop a viable position in the new technology.

Johnson & Johnson has with great success followed a strategy similar to Allen Bradley’s in dealing with disruptive technologies such as endoscopic surgical equipment and disposable contact lenses. Though its total revenues amount to more than $20 billion, J&J comprises 160 autonomously operating companies, which range from its huge MacNeil and Janssen pharmaceuticals companies to small companies with annual revenues of less than $20 million. Johnson & Johnson’s strategy is to launch products of disruptive technologies through very small companies acquired for that purpose.

SUMMARY

It is not crucial for managers pursuing growth and competitive advantage to be leaders in every element of their business. In sustaining technologies, in fact, evidence strongly suggests that companies which focus on extending the performance of conventional technologies, and choose to be followers in adopting new ones, can remain strong and competitive. This is not the case with disruptive technologies, however. There are enormous returns and significant first-mover advantages associated with early entry into the emerging markets in which disruptive technologies are initially used. Disk drive manufacturers that led in commercializing disruptive technology grew at vastly greater rates than did companies that were disruptive technology followers.

Despite the evidence that leadership in commercializing disruptive technologies is crucial, large, successful innovators encounter a significant dilemma in the pursuit of such leadership. In addition to dealing with the power of present customers as discussed in the last chapter, large, growth-oriented companies face the problem that small markets don’t solve the near-term growth needs of large companies. The markets whose emergence is enabled by disruptive technologies all began as small ones. The first orders that the pioneering companies received in those markets were small ones. And the companies that cultivated those markets had to develop cost structures enabling them to become profitable at small scale. Each of these factors argues for a policy of implanting projects to commercialize disruptive innovations in small organizations that will view the projects as being on their critical path to growth and success, rather than as being distractions from the main business of the company.

This recommendation is not new, of course; a host of other management scholars have also argued that smallness and independence confer certain advantages in innovation. It is my hope that chapters 5 and 6 provide deeper insight about why and under what circumstances this strategy is appropriate.

NOTES

1. The benefits of persistently pursuing incremental improvements versus taking big strategic leaps have been capably argued by Robert Hayes in “Strategic Planning: Forward in Reverse?” Harvard Business Review, November– December, 1985, 190–197.

I believe that there are some specific situations in which leadership in sustaining technology is crucial, however. In a private conversation, Professor Kim Clark characterized these situations as those affecting knife-edge businesses, that is, businesses in which the basis of competition is simple and unidimensional and there is little room for error. An example of such a knife-edge industry is the photolithographic aligner (PLA) industry, studied by Rebecca M. Henderson and Kim B. Clark, in “Architectural Innovation: The Reconfiguration of Existing Systems and the Failure of Established Firms,” Administrative Science Quarterly (35), March, 1990, 9–30. In this case, aligner manufacturers failed when they fell behind technologically in the face of sustaining architectural changes. This is because the basis of competition in the PLA industry was quite straightforward even though the products themselves were very complex: products either made the narrowest line width on silicon wafers of any in the industry or no one bought them. This is because PLA customers, makers of integrated circuits, simply had to have the fastest and most capable photolithographic alignment equipment or they could not remain competitive in their own markets. The knife-edge existed because product functionality was the only basis of competition: PLA manufacturers would either fall off one side to rapid success or off the other side to failure. Clearly, such knife-edge situations make leadership in sustaining technology very important.

In most other sustaining situations, however, leadership is not crucial. This far more common situation is the subject of Richard S. Rosenbloom’s study of the transition by National Cash Register from electro-mechanical to electronic technology. (See Richard S. Rosenbloom, “From Gears to Chips: The Transformation of NCR and Harris in the Digital Era,” Working paper, Harvard Business School Business History Seminar, 1988). In this case, NCR was very late in its industry in developing and launching a line of electronic cash registers. So late was NCR with this technology, in fact, that its sales of new cash registers dropped essentially to zero for an entire year in the early 1980s. Nonetheless, the company had such a strong field service capability that it survived by serving its installed base for the year it took to develop and launch its electronic cash registers. NCR then leveraged the strength of its brand name and field sales presence to quickly recapture its share of the market.

Even though a cash register is a simpler machine than a photolithographic aligner, I would characterize its market as complex, in that there are multiple bases of competition, and hence multiple ways to survive. As a general rule, the more complex a market, the less important is leadership in sustaining technological innovations. It is in dealing with knife-edge markets or with disruptive technologies that leadership appears to be crucial. I am indebted to Professors Kim B. Clark and Robert Hayes for their contributions to my thinking on this topic.

2. This is not to say that firms whose product performance or product cost consistently lagged behind the competition were able to prosper. I assert that there is no evidence that leadership in sustaining technological innovation confers a discernible and enduring competitive advantage over companies that have adopted a follower strategy because there are numerous ways to “skin the cat” in improving the performance of a complex product such as a disk drive. Developing and adopting new component technologies, such as thin-film and magneto-resistive heads, is one way to improve performance, but there are innumerable other avenues for extending the performance of conventional technologies while waiting for new approaches to become better understood and more reliable. This argument is presented more fully in Clayton M. Christensen, “Exploring the Limits of the Technology S-Curve,” Production and Operations Management (1), 1992, 334–366.

3. For the purposes of this analysis, a technology was classed as “new or unproven” if less than two years had elapsed from the time it had first appeared in a product that was manufactured and sold by a company somewhere in the world or if, even though it had been in the market for more than two years, less than 20 percent of the disk drive makers had used the technology in one of their products.

4. In this analysis, emerging markets or value networks were those in which two years or less had elapsed since the first rigid disk drive had been used with that class of computers; established markets or value networks were those in which more than two years had elapsed since the first drive was used.

5. Entry by acquisition was a rare route of entry in the disk drive industry. Xerox followed this strategy, acquiring Diablo, Century Data, and Shugart Associates. The performance of these companies after acquisition was so poor that few other companies followed Xerox’s lead. The only other example of entry by acquisition was the acquisition of Tandon by Western Digital, a manufacturer of controllers. In the case of Xerox and Western Digital, the entry strategy of the firms they acquired is recorded in Table 6.1. Similarly, the start-up of Plus Development Corporation, a spin-out of Quantum, appears in Table 6.1 as a separate company.

6. The evidence summarized in this matrix may be of some use to venture capital investors, as a general way to frame the riskiness of proposed investments. It suggests that start-ups which propose to commercialize a breakthrough technology that is essentially sustaining in character have a far lower likelihood of success than start-ups whose vision is to use proven technology to disrupt an established industry with something that is simpler, more reliable, and more convenient. The established firms in an industry have every incentive to catch up with a supposed sustaining technological breakthrough, while they have strong disincentives to pursue disruptive initiatives.

7. Not all of the small, emerging markets actually became large ones. The market for removable drive modules, for example, remained a small niche for more than a decade, only beginning to grow to significant size in the mid-1990s. The conclusion in the text that emerging markets offer a higher probability for success reflects the average, not an invariant result.

8. The notions that one ought not accept the risks of innovating simultaneously along both market and technology dimensions are often discussed among venture capitalists. It is also a focus of chapter 5 in Lowell W. Steele, Managing Technology (New York: McGraw Hill, 1989). The study reported here of the posterior probabilities of success for different innovation strategies builds upon the concepts of Steele and Lyle Ochs (whom Steele cites). I was also stimulated by ideas presented in Allan N. Afuah and Nik Bahram, “The Hypercube of Innovation,” Research Policy (21), 1992.

9. The simplest equation used by financial analysts to determine share price is P [h21505] D/(C-G), where P [h21505] price per share, D [h21505] dividends per share, C [h21505] the company’s cost of capital, and G [h21505] projected long-term growth rate.

10. This evidence is summarized by Clayton M. Christensen in “Is Growth an Enabler of Good Management, or the Result of It?” Harvard Business School working paper, 1996.

11. Scott Lewis, “Apple Computer, Inc.,” in Adele Hast, ed., International Directory of Company Histories (Chicago: St. James Press, 1991), 115–116.

12. An insightful history of the emergence of the personal computer industry appears in Paul Frieberger and Michael Swaine, Fire in the Valley: The Making of the Personal Computer (Berkeley, CA: Osborne-McGraw Hill, 1984).

13. “Can 3.5[h21033] Drives Displace 5.25s in Personal Computing?” Electronic Business, 1 August, 1986, 81–84.

14. Personal interview with Mr. William Schroeder, Vice Chairman, Conner Peripherals Corporation, November 19, 1991.

15. An insightful study on the linkage among a company’s historical experience, its capabilities, and what it consequently can and cannot do, appears in Dorothy Leonard-Barton, “Core Capabilities and Core Rigidities: A Paradox in Managing New Product Development,” Strategic Management Journal (13), 1992, 111–125.

16. Personal interview with Mr. John Squires, cofounder and Executive Vice President, Conner Peripherals Corporation, April 27, 1992.

17. See, for example, George Gilder, “The Revitalization of Everything: The Law of the Microcosm,” Harvard Business Review, March–April, 1988, 49–62.

18. Much of this information about Allen Bradley has been taken from John Gurda, The Bradley Legacy (Milwaukee: The Lynde and Harry Bradley Foundation, 1992).

CHAPTER SEVEN

Discovering New and Emerging Markets

Markets that do not exist cannot be analyzed: Suppliers and customers must discover them together. Not only are the market applications for disruptive technologies unknown at the time of their development, they are unknowable. The strategies and plans that managers formulate for confronting disruptive technological change, therefore, should be plans for learning and discovery rather than plans for execution. This is an important point to understand, because managers who believe they know a market’s future will plan and invest very differently from those who recognize the uncertainties of a developing market.

Most managers learn about innovation in a sustaining technology context because most technologies developed by established companies are sustaining in character. Such innovations are, by definition, targeted at known markets in which customer needs are understood. In this environment, a planned, researched approach to evaluating, developing, and marketing innovative products is not only possible, it is critical to success.

What this means, however, is that much of what the best executives in successful companies have learned about managing innovation is not relevant to disruptive technologies. Most marketers, for example, have been schooled extensively, at universities and on the job, in the important art of listening to their customers, but few have any theoretical or practical training in how to discover markets that do not yet exist. The problem with this lopsided experience base is that when the same analytical and decision-making processes learned in the school of sustaining innovation are applied to enabling or disruptive technologies, the effect on the company can be paralyzing. These processes demand crisply quantified information when none exists, accurate estimates of financial returns when neither revenues nor costs can be known, and management according to detailed plans and budgets that cannot be formulated. Applying inappropriate marketing, investment, and management processes can render good companies incapable of creating the new markets in which enabling or disruptive technologies are first used.

In this chapter we shall see how experts in the disk drive industry were able to forecast the markets for sustaining technologies with stunning accuracy but had great difficulty in spotting the advent and predicting the size of new markets for disruptive innovations. Additional case histories in the motorcycle and microprocessor industries further demonstrate the uncertainty about emerging market applications for disruptive or enabling technologies, even those that, in retrospect, appear obvious.

FORECASTING MARKETS FOR SUSTAINING VERSUS DISRUPTIVE TECHNOLOGIES

An unusual amount of market information has been available about the disk drive industry from its earliest days—a major reason why studying it has yielded such rich insights. The primary source of data, Disk/Trend Report, published annually by Disk/Trend, Inc., of Mountain View, California, lists every model of disk drive that has ever been offered for sale by any company in the world, for each of the years from 1975 to the present. It shows the month and year in which each model was first shipped, lists the performance specifications of the drive, and details the component technologies used. In addition, every manufacturer in the world shares with Disk/Trend its sales by product type, with information about what types of customers bought which drive. Editors at Disk/Trend then aggregate this data to derive the size of each narrowly defined market segment and publish a listing of the major competitors’ shares, carefully guarding all proprietary data. Manufacturers in the industry find the reports so valuable that they all continue to share their proprietary data with Disk/Trend.

In each edition, Disk/Trend publishes the actual unit volumes and dollar sales in each market segment for the year just past and offers its forecasts for each of the next four years in each category. Given its unparalleled access to industry data spanning two decades, this publication offers an unusual chance to test through unfolding market history the accuracy of past predictions. Over all, Disk/Trend has a remarkable track record in forecasting the future of established markets, but it has struggled to estimate accurately the size of new markets enabled by disruptive disk drive technologies.

The evidence is summarized in Figure 7.1, which compares the total unit volumes that Disk/Trend Report had forecast would be shipped in the first four years after commercial shipments of each new disk drive architecture began, to the total volumes that were actually shipped over that four-year period. To facilitate comparison, the heights of the bars measuring forecast shipments were normalized to a value of 100, and the volumes actually shipped were scaled as a percentage of the forecast. Of the five new architectures for which Disk/Trend’s forecasts were available, the 14-inch Winchester and the 2.5-inch generation were sustaining innovations, which were sold into the same value networks as the preceding generation of drives. The other three, 5.25-, 3.5-, and 1.8-inch drives, were disruptive innovations that facilitated the emergence of new value networks. (Disk/Trend did not publish separate forecasts for 8-inch drives.)

Figure 7.1 The Four Years after the First Commercial Shipments: Sustaining versus Disruptive Technologies

Source: Data are from various issues of Disk/Trend Report.

Notice that Disk/Trend’s forecasts for the sustaining 2.5-inch and 14-inch Winchester technologies were within 8 percent and 7 percent, respectively, of what the industry actually shipped. But its estimates were off by 265 percent for 5.25-inch drives, 35 percent for 3.5-inch drives (really quite close), and 550 percent for 1.8-inch drives. Notably, the 1.8-inch drive, the forecast of which Disk/Trend missed so badly, was the first generation of drives with a primarily non-computer market.

The Disk/Trend staff used the same methods to generate the forecasts for sustaining architectures as they did for disruptive ones: interviewing leading customers and industry experts, trend analysis, economic modeling, and so on. The techniques that worked so extraordinarily well when applied to sustaining technologies, however, clearly failed badly when applied to markets or applications that did not yet exist.

IDENTIFYING THE MARKET FOR THE HP 1.3-INCH KITTYHAWK DRIVE

Differences in the forecastablity of sustaining versus disruptive technologies profoundly affected Hewlett-Packard’s efforts to forge a market for its revolutionary, disruptive 1.3-inch Kittyhawk disk drive. [1] In 1991, Hewlett-Packard’s Disk Memory Division (DMD), based in Boise, Idaho, generated about $600 million in disk drive revenues for its $20 billion parent company. That year a group of DMD employees conceived of a tiny, 1.3-inch 20 MB drive, which they code-named Kittyhawk. This was indeed a radical program for HP: The smallest drive previously made by DMD had been 3.5-inches, and DMD had been one of the last in the industry to introduce one. The 1.3-inch Kittyhawk represented a significant leapfrog for the company—and, most notably, was HP’s first attempt to lead in a disruptive technology.

For the project to make sense in a large organization with ambitious growth plans, HP executives mandated that Kittyhawk’s revenues had to ramp to $150 million within three years. Fortunately for Kittyhawk’s proponents, however, a significant market for this tiny drive loomed on the horizon: hand-held palm-top computers, or personal digital assistants (PDAs). Kittyhawk’s sponsors, after studying projections for this market, decided that they could scale the revenue ramp that had been set for them. They consulted a market research firm, which confirmed HP’s belief that the market for Kittyhawk would indeed be substantial.

HP’s marketers developed deep relationships with senior executives at major companies in the computer industry, for example, Motorola, ATT, IBM, Apple, Microsoft, Intel, NCR, and Hewlett-Packard itself, as well as at a host of lesser-known startup companies. All had placed substantial product development bets on the PDA market. Many of their products were designed with Kittyhawk’s features in mind, and Kittyhawk’s design in turn reflected these customers’ well-researched needs.

The Kittyhawk team concluded that developing a drive that met these customers’ requirements would be a demanding but feasible technological stretch, and they launched an aggressive twelve-month effort to develop the tiny device. The result, shown in Figure 7.2, was impressive. The first version packed 20 MB, and a second model, introduced a year later, stored 40 MB. To meet the ruggedness demanded in its target market of PDAs and electronic notebooks, Kittyhawk was equipped with an impact sensor similar to those used in automobile airbag crash sensors and could withstand a three-foot drop onto concrete without data loss. It was designed to sell initially at $250 per unit.

Although Kittyhawk’s technical development went according to plan, the development of applications for it did not. The PDA market failed to materialize substantially, as sales of Apple’s Newton and competing devices fell far short of aspirations. This surprised many of the computer industry experts whose opinions HP’s marketers had worked so hard to synthesize. During its first two years on the market, Kittyhawk logged just a fraction of the sales that had been forecast. The sales achieved might have initially satisfied startup companies and venture capitalists, but for HP’s management, the volumes were far below expectations and far too small to satisfy DMD’s need to grow and gain overall market share. Even more surprising, the applications that contributed most significantly to Kittyhawk’s sales were not in computers at all. They were Japanese-language portable word processors, miniature cash registers, electronic cameras, and industrial scanners, none of which had figured in Kittyhawk’s original marketing plans.

Figure 7.2 Hewlett-Packard’s Kittyhawk Drive

Source: Hewlett Packard Company. Used by permission.

Even more frustrating, as the second anniversary of Kittyhawk’s launch approached, were the inquiries received by HP marketers from companies making mass-market video game systems to buy very large volumes of Kittyhawk—if HP could make a version available at a lower price point. These companies had been aware of Kittyhawk for two years, but they reported that it had taken some time for them to see what could be done with a storage device so small.

To a significant extent, HP had designed Kittyhawk to be a sustaining technology for mobile computing. Along many of the metrics of value in that application—small size, low weight and power consumption, and ruggedness—Kittyhawk constituted a discontinuous sustaining improvement relative to 2.5-and 1.8-inch drives. Only in capacity (which HP had pushed as far as possible) was Kittyhawk deficient. The large inquiries and orders that finally began arriving for the Kittyhawk, however, were for a truly disruptive product: something priced at $50 per unit and with limited functionality. For these applications, a capacity of 10 MB would have been perfectly adequate.

Unfortunately, because HP had positioned the drive with the expensive features needed for the PDA market rather than designing it as a truly disruptive product, it simply could not meet the price required by home video game manufacturers. Having invested so aggressively to hit its original targets as defined by the PDA application, management had little patience and no money to redesign a simpler, defeatured 1.3-inch drive that fit the market applications that had finally become clear. HP withdrew Kittyhawk from the market in late 1994.

The HP project managers concede in retrospect that their most serious mistake in managing the Kittyhawk initiative was to act as if their forecasts about the market were right, rather than as if they were wrong. They had invested aggressively in manufacturing capacity for producing the volumes forecast for the PDA market and had incorporated design features, such as the shock sensor, that were crucial to acceptance in the PDA market they had so carefully researched. Such planning and investment is crucial to success in a sustaining technology, but, the managers reflected, it was not right for a disruptive product like Kittyhawk. If they had the opportunity to launch Kittyhawk all over again, they would assume that neither they nor anyone else knew for sure what kinds of customers would want it or in what volumes. This would lead them toward a much more exploratory, flexible approach toward product design and investment in manufacturing capacity; they would, given another chance, feel their way into the market, leaving enough resources to redirect their program if necessary and building upon what they learned on the way.

Hewlett-Packard’s disk drive makers are not the only ones, of course, who behaved as if they knew what the market for a disruptive technology would be. They are in stellar company, as the following case histories show.

HONDA’S INVASION OF THE NORTH AMERICAN MOTORCYCLE INDUSTRY

Honda’s success in attacking and dominating the North American and European motorcycle markets has been cited as a superb example of clear strategic thinking coupled with aggressive and coherent execution. According to these accounts, Honda employed a deliberate manufacturing strategy based on an experience curve in which it cut prices, built volume, aggressively reduced costs, cut prices some more, reduced costs further, and built an unassailable volume-based low-cost manufacturing position in the motorcycle market. Honda then used that base to move upmarket and ultimately blew all established motorcycle manufacturers out of the market except for Harley-Davidson and BMW, which barely survived. [2] Honda combined this manufacturing triumph with a clever product design, catchy advertising, and a convenient, broad-based distributor/retailer network tailored to the informal cyclists who constituted Honda’s core customer base. Told in this manner, Honda’s history is a tale of strategic brilliance and operational excellence that all managers dream will be told about them someday. The reality of Honda’s achievement, as recounted by the Honda employees who were managing the business at the time, however, is quite different. [3]

During Japan’s years of post-war reconstruction and poverty, Honda had emerged as a supplier of small, rugged motorized bicycles that were used by distributors and retailers in congested urban areas to make small deliveries to local customers. Honda developed considerable expertise in designing small, efficient engines for these bikes. Its Japanese market sales grew from an initial annual volume of 1,200 units in 1949 to 285,000 units in 1959.

Honda’s executives were eager to exploit the company’s low labor costs to export motorbikes to North America, but there was no equivalent market there for its popular Japanese “Supercub” delivery bike. Honda’s research showed that Americans used motorcyles primarily for over-the-road distance driving in which size, power, and speed were the most highly valued product attributes. Accordingly, Honda engineers designed a fast, powerful motorcycle specifically for the American market, and in 1959 Honda dispatched three employees to Los Angeles to begin marketing efforts. To save living expenses, the three shared an apartment, and each brought with him a Supercub bike to provide cheap transportation around the city.

The venture was a frustrating experience from the beginning. Honda’s products offered no advantage to prospective customers other than cost, and most motorcycle dealers refused to accept the unproven product line. When the team finally succeeded in finding some dealers and selling a few hundred units, the results were disastrous. Honda’s understanding of engine design turned out not to be transferable to highway applications, in which bikes were driven at high speeds for extended periods: The engines sprung oil leaks and the clutches wore out. Honda’s expenses in air-freighting the warrantied replacement motorcycles between Japan and Los Angeles nearly sunk the company.

Meanwhile, one Saturday, Kihachiro Kawashima, the Honda executive in charge of the North American venture, decided to vent his frustrations by taking his Supercub into the hills east of Los Angeles. It helped: He felt better after zipping around in the dirt. A few weeks later he sought relief dirt-biking again. Eventually he invited his two colleagues to join him on their Supercubs. Their neighbors and others who saw them zipping around the hills began inquiring where they could buy those cute little bikes, and the trio obliged by special-ordering Supercub models for them from Japan. This private use of what became known as off-road dirt bikes continued for a couple of years. At one point a Sears buyer tried to order Supercubs for the company’s outdoor power equipment departments, but Honda ignored the opportunity, preferring to focus on selling large, powerful, over-the-road cycles, a strategy that continued to be unsuccessful.

Finally, as more and more people clamored for their own little Honda Supercubs to join their dirt-biking friends, the potential for a very different market dawned on Honda’s U.S. team: Maybe there was an undeveloped off-the-road recreational motorbike market in North America for which— quite by accident—the company’s little 50cc Supercub was nicely suited. Although it took much arguing and arm-twisting, the Los Angeles team ultimately convinced corporate management in Japan that while the company’s large bike strategy was doomed to failure, another quite different opportunity to create a totally new market segment merited pursuit.

Once the small-bike strategy was formally adopted, the team found that securing dealers for the Supercub was an even more vexing challenge than it had been for its big bikes. There just weren’t any retailers selling that class of product. Ultimately, Honda persuaded a few sporting goods dealers to take on its line of motorbikes, and as they began to promote the bikes successfully, Honda’s innovative distribution strategy was born.

Honda had no money for a sophisticated advertising campaign. But a UCLA student who had gone dirt-biking with his friends came up with the advertising slogan, “You meet the nicest people on a Honda,” for a paper he wrote in an advertising course. Encouraged by his teacher, he sold the idea to an advertising agency, which then convinced Honda to use it in what became an award-winning advertising campaign. These serendipitous events were, of course, followed by truly world-class design engineering and manufacturing execution, which enabled Honda to repeatedly lower its prices as it improved its product quality and increased its production volumes.

Honda’s 50cc motorbike was a disruptive technology in the North American market. The rank-ordering of product attributes that Honda’s customers employed in their product decision making defined for Honda a very different value network than the established network in which Harley-Davidson, BMW, and other traditional motorcycle makers had competed.

From its low-cost manufacturing base for reliable motorbikes, using a strategy reminiscent of the upmarket invasions described earlier in disk drives, steel, excavators, and retailing, Honda turned its sights upmarket, introducing between 1970 and 1988 a series of bikes with progressively more powerful engines.

For a time in the late 1960s and early 1970s, Harley attempted to compete head-on with Honda and to capitalize on the expanding lowend market by producing a line of small-engine (150 to 300 cc) bikes acquired from the Italian motorcycle maker Aeromecchania. Harley attempted to sell the bikes through its North American dealer network. Although Honda’s manufacturing prowess clearly disadvantaged Harley in this effort, a primary cause of Harley’s failure to establish a strong presence in the small-bike value network was the opposition of its dealer network. Their profit margins were far greater on high-end bikes, and many of them felt the small machines compromised Harley-Davidson’s image with their core customers.

Recall from chapter 2 the finding that within a given value network, the disk drive companies and their computer-manufacturing customers had developed very similar economic models or cost structures, which determined the sorts of business that appeared profitable to them. We see the same phenomenon here. Within their value network, the economics of Harley’s dealers drove them to favor the same type of business that Harley had come to favor. Their coexistence within the value network made it difficult for either Harley or its dealers to exit the network through its bottom. In the late 1970s Harley gave in and repositioned itself at the very high end of the motorcycle market—a strategy reminiscent of Seagate’s repositioning in disk drives, and of the upmarket retreats of the cable excavator companies and the integrated steel mills.

Interestingly, Honda proved just as inaccurate in estimating how large the potential North American motorcycle market was as it had been in understanding what it was. Its initial aspirations upon entry in 1959 had been to capture 10 percent of a market estimated at 550,000 units per year with annual growth of 5 percent. By 1975 the market had grown 16 percent per year to 5,000,000 annual units—units that came largely from an application that Honda could not have foreseen. [4]

INTEL’S DISCOVERY OF THE MICROPROCESSOR MARKET

Intel Corporation, whose founders launched the company in 1969 based on their pioneering development of metal-on-silicon (MOS) technology to produce the world’s first dynamic random access memory (DRAM) integrated circuits, had become by 1995 one of the world’s most profitable major companies. Its storied success is even more remarkable because, when its initial leadership position in the DRAM market began crumbling between 1978 and 1986 under the onslaught of Japanese semiconductor manufacturers, Intel transformed itself from a second-tier DRAM company into the world’s dominant microprocessor manufacturer. How did Intel do it?

Intel developed the original microprocessor under a contract development arrangement with a Japanese calculator manufacturer. When the project was over, Intel’s engineering team persuaded company executives to purchase the microprocessor patent from the calculator maker, which owned it under the terms of its contract with Intel. Intel had no explicit strategy for building a market for this new microprocessor; the company simply sold the chip to whoever seemed to be able to use it.

Mainstream as they seem today, microprocessors were disruptive technologies when they first emerged. They were capable only of limited functionality, compared to the complex logic circuits that constituted the central processing units of large computers in the 1960s. But they were small and simple, and they enabled affordable logic and computation in applications where this previously had not been feasible.

Through the 1970s, as competition in the DRAM market intensified, margins began to decline on Intel’s DRAM revenues while margins on its microprocessor product line, where there was less competition, stayed robust. Intel’s system for allocating production capacity operated according to a formula whereby capacity was committed in proportion to the gross margins earned by each product line. The system therefore imperceptibly began diverting investment capital and manufacturing capacity away from the DRAM business and into microprocessors—without an explicit management decision to do so. [5] In fact, Intel senior management continued to focus most of its own attention and energy on DRAM, even while the company’s resource allocation processes were gradually implementing an exit from that business.

This de facto strategy shift, driven by Intel’s autonomously operating resource allocation process, was fortuitous. Because so little was known of the microprocessor market at that time, explicit analysis would have provided little justification for a bold move into microprocessors. Gordon Moore, Intel co-founder and chairman, for example, recalled that IBM’s choice of the Intel 8088 microprocessor as the “brain” of its new personal computer was viewed within Intel as a “small design win.” [6] Even after IBM’s stunning success with its personal computers, Intel’s internal forecast of the potential applications for the company’s next-generation 286 chip did not include personal computers in its list of the fifty highest-volume applications. [7]

In retrospect, the application of microprocessors to personal computers is an obvious match. But in the heat of the battle, of the many applications in which microprocessors might have been used, even a management team as astute as Intel’s could not know which would emerge as the most important and what volumes and profits it would yield.

UNPREDICTABILITY AND DOWNWARD IMMOBILITY IN ESTABLISHED FIRMS

The reaction of some managers to the difficulty of correctly planning the markets for disruptive technologies is to work harder and plan smarter. While this approach works for sustaining innovations, it denies the evidence about the nature of disruptive ones. Amid all the uncertainty surrounding disruptive technologies, managers can always count on one anchor: Experts’ forecasts will always be wrong. It is simply impossible to predict with any useful degree of precision how disruptive products will be used or how large their markets will be. An important corollary is that, because markets for disruptive technologies are unpredictable, companies’ initial strategies for entering these markets will generally be wrong.

How does this statement square with the findings presented in Table 6.1, which showed a stunning difference in the posterior probabilities of success between firms that entered new, emerging value networks (37 percent) and those that entered existing value networks (6 percent)? If markets cannot be predicted in advance, how can firms that target them be more successful? Indeed, when I have shown the matrix in Table 6.1 to managerial audiences, they are quite astonished by the differences in the magnitudes and probabilities of success. But it is clear that the managers don’t believe that the results can be generalized to their own situations. The findings violate their intuitive sense that creating new markets is a genuinely risky business. [8]

Failed Ideas versus Failed Businesses

The case studies reviewed in this chapter suggest a resolution to this puzzle. There is a big difference between the failure of an idea and the failure of a firm. Many of the ideas prevailing at Intel about where the disruptive microprocessor could be used were wrong; fortunately, Intel had not expended all of its resources implementing wrong-headed marketing plans while the right market direction was still unknowable. As a company, Intel survived many false starts in its search for the major market for microprocessors. Similarly, Honda’s idea about how to enter the North American motorcycle market was wrong, but the company didn’t deplete its resources pursuing its big-bike strategy and was able to invest aggressively in the winning strategy after it had emerged. Hewlett-Packard’s Kittyhawk team was not as fortunate. Believing they had identified the winning strategy, its managers spent their budget on a product design and the manufacturing capacity for a market application that never emerged. When the ultimate applications for the tiny drive ultimately began to coalesce, the Kittyhawk team had no resources left to pursue them.

Research has shown, in fact, that the vast majority of successful new business ventures abandoned their original business strategies when they began implementing their initial plans and learned what would and would not work in the market. [9] The dominant difference between successful ventures and failed ones, generally, is not the astuteness of their original strategy. Guessing the right strategy at the outset isn’t nearly as important to success as conserving enough resources (or having the relationships with trusting backers or investors) so that new business initiatives get a second or third stab at getting it right. Those that run out of resources or credibility before they can iterate toward a viable strategy are the ones that fail.

Failed Ideas and Failed Managers

In most companies, however, individual managers don’t have the luxury of surviving a string of trials and errors in pursuit of the strategy that works. Rightly or wrongly, individual managers in most organizations believe that they cannot fail: If they champion a project that fails because the initial marketing plan was wrong, it will constitute a blotch on their track record, blocking their rise through the organization. Because failure is intrinsic to the process of finding new markets for disruptive technologies, the inability or unwillingness of individual managers to put their careers at risk acts as a powerful deterrent to the movement of established firms into the value networks created by those technologies. As Joseph Bower observed in his classic study of the resource allocation process at a major chemical company, “Pressure from the market reduces both the probability and the cost of being wrong. [10]

Bower’s observation is consistent with the findings in this book about the disk drive industry. When demand for an innovation was assured, as was the case with sustaining technologies, the industry’s established leaders were capable of placing huge, long, and risky bets to develop whatever technology was required. When demand was not assured, as was the case in disruptive technologies, the established firms could not even make the technologically straightforward bets required to commercialize such innovations. That is why 65 percent of the companies entering the disk drive industry attempted to do so in an established, rather than emerging market. Discovering markets for emerging technologies inherently involves failure, and most individual decision makers find it very difficult to risk backing a project that might fail because the market is not there.

Plans to Learn versus Plans to Execute

Because failure is intrinsic to the search for initial market applications for disruptive technologies, managers need an approach very different from what they would take toward a sustaining technology. In general, for sustaining technologies, plans must be made before action is taken, forecasts can be accurate, and customer inputs can be reasonably reliable. Careful planning, followed by aggressive execution, is the right formula for success in sustaining technology.

But in disruptive situations, action must be taken before careful plans are made. Because much less can be known about what markets need or how large they can become, plans must serve a very different purpose: They must be plans for learning rather than plans for implementation. By approaching a disruptive business with the mindset that they can’t know where the market is, managers would identify what critical information about new markets is most necessary and in what sequence that information is needed. Project and business plans would mirror those priorities, so that key pieces of information would be created, or important uncertainties resolved, before expensive commitments of capital, time, and money were required.

Discovery-driven planning, which requires managers to identify the assumptions upon which their business plans or aspirations are based, [11] works well in addressing disruptive technologies. In the case of Hewlett-Packard’s Kittyhawk disk drive, for example, HP invested significant sums with its manufacturing partner, the Citizen Watch Company, in building and tooling a highly automated production line. This commitment was based on an assumption that the volumes forecast for the drive, built around forecasts by HP customers of PDA sales, were accurate. Had HP’s managers instead assumed that nobody knew in what volume PDAs would sell, they might have built small modules of production capacity rather than a single, high-volume line. They could then have held to capacity or added or reduced capacity as key events confirmed or disproved their assumptions.

Similarly, the Kittyhawk product development plan was based on an assumption that the dominant application for the little drive was in PDAs, which demanded high ruggedness. Based on this assumption, the Kittyhawk team committed to components and a product architecture that made the product too expensive to be sold to the price-sensitive video game makers at the emerging low end of the market. Discovery-driven planning would have forced the team to test its market assumptions before making commitments that were expensive to reverse—in this case, possibly by creating a modularized design that easily could be reconfigured or defeatured to address different markets and price points, as events in the marketplace clarified the validity of their assumptions.

Philosophies such as management by objective and management by exception often impede the discovery of new markets because of where they focus management attention. Typically, when performance falls short of plan, these systems encourage management to close the gap between what was planned and what happened. That is, they focus on unanticipated failures. But as Honda’s experience in the North American motorcycle market illustrates, markets for disruptive technologies often emerge from unanticipated successes, on which many planning systems do not focus the attention of senior management. [12] Such discoveries often come by watching how people use products, rather than by listening to what they say.

I have come to call this approach to discovering the emerging markets for disruptive technologies agnostic marketing, by which I mean marketing under an explicit assumption that no one—not us, not our customers—can know whether, how, or in what quantities a disruptive product can or will be used before they have experience using it. Some managers, faced with such uncertainty, prefer to wait until others have defined the market. Given the powerful first-mover advantages at stake, however, managers confronting disruptive technologies need to get out of their laboratories and focus groups and directly create knowledge about new customers and new applications through discovery-driven expeditions into the marketplace.

NOTES

1. What follows is a summary of the fuller history recounted in “Hewlett-Packard: The Flight of the Kittyhawk,” Harvard Business School, Case No. 9-697-060, 1996.

2. Examples of such histories of Honda’s success include the Harvard Business School case study, “A Note on the Motorcycle Industry—1975,” No. 9-578-210, and a report published by The Boston Consulting Group, “Strategy Alternatives for the British Motorcycle Industry,” 1975.

3. Richard Pascale and E. Tatum Christiansen, “Honda (A),” Harvard Business School Teaching, Case No. 9-384-049, 1984, and “Honda (B),” Harvard Business School, Teaching Case No. 9-384-050, 1984.

4. Statistical Abstract of the United States (Washington, D.C.: United States Bureau of the Census, 1980), 648.

5. Intel’s exit from the DRAM business and entry into microprocessors has been chronicled by Robert A. Burgelman in “Fading Memories: A Process Theory of Strategic Business Exit in Dynamic Environments,” Administrative Science Quarterly (39), 1994, 24–56. This thoroughly researched and compellingly written study of the process of strategy evolution is well worth reading.

6. George W. Cogan and Robert A. Burgelman, “Intel Corporation (A): The DRAM Decision,” Stanford Business School, Case PS-BP-256.

7. Robert A. Burgelman, “Fading Memories: A Process Theory of Strategic Business Exit in Dynamic Environments,” Administrative Science Quarterly (39) 1994.

8. Studies of how managers define and perceive risk can shed significant light on this puzzle. Amos Tversky and Daniel Kahneman, for example, have shown that people tend to regard propositions that they do not understand as more risky, regardless of their intrinsic risk, and to regard things they do understand as less risky, again without regard to intrinsic risk. (Amos Tversky and Daniel Kahneman, “Judgment Under Uncertainty: Heuristics and Biases,” Science [185], 1974, 1124–1131.) Managers, therefore, may view creation of new markets as risky propositions, in the face of contrary evidence, because they do not understand non-existent markets; similarly, they may regard investment in sustaining technologies, even those with high intrinsic risk, as safe because they understand the market need.

9. Among the excellent studies in this tradition are Myra M. Hart, Founding Resource Choices: Influences and Effects, DBA thesis, Harvard University Graduate School of Business Administration, 1995; Amar Bhide, “How Entrepreneurs Craft Strategies that Work,” Harvard Business Review, March–April, 1994, 150–163; Amar Bhide, “Bootstrap Finance: The Art of Start-Ups,” Harvard Business Review, November–December 1992, 109–118; “Hewlett-Packard’s Kittyhawk,” Harvard Business School, Case No. 9-697-060; and “Vallourec’s Venture into Metal Injection Molding,” Harvard Business School, Case No. 9-697-001.

10. Joseph Bower, Managing the Resource Allocation Process (Homewood, IL: Richard D. Irwin, 1970), 254.

11. Rita G. McGrath and Ian C. MacMillan, “Discovery-Driven Planning,” Harvard Business Review, July–August, 1995, 4–12.

12. This point is persuasively argued in Peter F. Drucker, Innovation and Entrepreneurship (New York: Harper & Row, 1985). Below, in chapter 9, I recount how software maker Intuit discovered that many of the people buying its Quicken personal financial management software were, in fact, using it to keep the books of their small businesses. Intuit had not anticipated this application, but it consequently adapted the product more closely to small business needs and launched Quickbooks, which captured more than 70 percent of the small business accounting software market within two years.

CHAPTER EIGHT

How to Appraise Your Organization’s Capabilities and Disabilities

When managers assign employees to tackle a critical innovation, they instinctively work to match the requirements of the job with the capabilities of the individuals whom they charge to do it. In evaluating whether an employee is capable of successfully executing a job, managers will assess whether he or she has the requisite knowledge, judgment, skill, perspective, and energy. Managers will also assess the employee’s values—the criteria by which he or she tends to decide what should and shouldn’t be done. Indeed, the hallmark of a great manager is the ability to identify the right person for the right job, and to train his or her employees so that they have the capabilities to succeed at the jobs they are given.

Unfortunately, some managers don’t think as rigorously about whether their organizations have the capability to successfully execute jobs that may be given to them. Frequently, they assume that if the people working on a project individually have the requisite capabilities to get the job done well, then the organization in which they work will also have the same capability to succeed. This often is not the case. One could take two sets of identically capable people and put them to work in two different organizations, and what they accomplish would likely be significantly different. This is because organizations themselves, independent of the people and other resources in them, have capabilities. To succeed consistently, good managers need to be skilled not just in choosing, training, and motivating the right people for the right job, but in choosing, building, and preparing the right organization for the job as well.

The purpose of this chapter is to describe the theory that lies behind the empirical observations made in chapters 5, 6, and 7—in particular, the observation that the only companies that succeeded in addressing disruptive technology were those that created independent organizations whose size matched the size of the opportunity. The notion that organizations have “core competencies” has been a popular one for much of the last decade. [1] In practice, however, most managers have found that the concept is sufficiently vague that some supposed “competence” can be cited in support of a bewildering variety of innovation proposals. This chapter brings greater precision to the core competence concept, by presenting a framework to help managers understand, when they are confronted with a necessary change, whether the organizations over which they preside are competent or incompetent of tackling the challenges that lie ahead.

AN ORGANIZATIONAL CAPABILITIES FRAMEWORK

Three classes of factors affect what an organization can and cannot do: its resources, its processes, and its values. When asking what sorts of innovations their organizations are and are not likely to be able to implement successfully, managers can learn a lot about capabilities by disaggregating their answers into these three categories. [2]

Resources

Resources are the most visible of the factors that contribute to what an organization can and cannot do. Resources include people, equipment, technology, product designs, brands, information, cash, and relationships with suppliers, distributors, and customers. Resources are usually things, or assets—they can be hired and fired, bought and sold, depreciated or enhanced. They often can be transferred across the boundaries of organizations much more readily than can processes and values. Without doubt, access to abundant and high-quality resources enhances an organization’s chances of coping with change.

Resources are the things that managers most instinctively identify when assessing whether their organizations can successfully implement changes that confront them. Yet resource analysis clearly does not tell a sufficient story about capabilities. Indeed, we could deal identical sets of resources to two different organizations, and what they created from those resources would likely be very different—because the capabilities to transform inputs into goods and services of greater value reside in the organization’s processes and values.

Processes

Organizations create value as employees transform inputs of resources— people, equipment, technology, product designs, brands, information, energy, and cash—into products and services of greater worth. The patterns of interaction, coordination, communication, and decision-making through which they accomplish these transformations are processes. [3] Processes include not just manufacturing processes, but those by which product development, procurement, market research, budgeting, planning, employee development and compensation, and resource allocation are accomplished.

Processes differ not only in their purpose, but also in their visibility. Some processes are “formal,” in the sense that they are explicitly defined, visibly documented, and consciously followed. Other processes are “informal,” in that they are habitual routines or ways of working that have evolved over time, which people follow simply because they work—or because “That’s the way we do things around here.” Still other methods of working and interacting have proven so effective for so long that people unconsciously follow them—they constitute the culture of the organization. Whether they are formal, informal, or cultural, however, processes define how an organization transforms the sorts of inputs listed above into things of greater value.

Processes are defined or evolve de facto to address specific tasks. This means that when managers use a process to execute the tasks for which it was designed, it is likely to perform efficiently. But when the same, seemingly efficient process is employed to tackle a very different task, it is likely to seem slow, bureaucratic, and inefficient. In other words, a process that defines a capability in executing a certain task concurrently defines disabilities in executing other tasks. [4] The reason good managers strive for focus in their organizations is that processes and tasks can be readily aligned. [5]

One of the dilemmas of management is that, by their very nature, processes are established so that employees perform recurrent tasks in a consistent way, time after time. To ensure consistency, they are meant not to change—or if they must change, to change through tightly controlled procedures. This means that the very mechanisms through which organizations create value are intrinsically inimical to change.

Some of the most crucial processes to examine as capabilities or disabilities aren’t the obvious value-adding processes involved in logistics, development, manufacturing, and customer service. Rather, they are the enabling or background processes that support investment decision-making. As we saw in chapter 7, the processes that render good companies incapable of responding to change are often those that define how market research is habitually done; how such analysis is translated into financial projections; how plans and budgets are negotiated and how those numbers are delivered; and so on. These typically inflexible processes are where many organizations’ most serious disabilities in coping with change reside.

Values

The third class of factors that affect what an organization can or cannot accomplish is its values. The values of an organization are the criteria by which decisions about priorities are made. Some corporate values are ethical in tone, such as those that guide decisions to ensure patient well-being at Johnson & Johnson or that guide decisions about plant safety at Alcoa. But within the Resources-Processes-Values (RPV) framework, values have a broader meaning. An organization’s values are the standards by which employees make prioritization decisions—by which they judge whether an order is attractive or unattractive; whether a customer is more important or less important; whether an idea for a new product is attractive or marginal; and so on. Prioritization decisions are made by employees at every level. At the executive tiers, they often take the form of decisions to invest or not invest in new products, services, and processes. Among salespeople, they consist of on-the-spot, day-to-day decisions about which products to push with customers and which not to emphasize.

The larger and more complex a company becomes, the more important it is for senior managers to train employees at every level to make independent decisions about priorities that are consistent with the strategic direction and the business model of the company. A key metric of good management, in fact, is whether such clear and consistent values have permeated the organization. [6]

Clear, consistent, and broadly understood values, however, also define what an organization cannot do. A company’s values, by necessity, must reflect its cost structure or its business model, because these define the rules its employees must follow in order for the company to make money. If, for example, the structure of a company’s overhead costs requires it to achieve gross profit margins of 40 percent, a powerful value or decision rule will have evolved that encourages middle managers to kill ideas that promise gross margins below 40 percent. This means that such an organization would be incapable of successfully commercializing projects targeting low-margin markets. At the same time, another organization’s values, driven by a very different cost structure, might enable or facilitate the success of the very same project.

The values of successful firms tend to evolve in a predictable fashion in at least two dimensions. The first relates to acceptable gross margins. As companies add features and functionality to their products and services in order to capture more attractive customers in premium tiers of their markets, they often add overhead cost. As a result, gross margins that at one point were quite attractive, at a later point seem unattractive. Their values change. For example, Toyota entered the North American market with its Corona model—a product targeting the lowest-priced tiers of the market. As the entry tier of the market became crowded with look-alike models from Nissan, Honda, and Mazda, competition among equally low-cost competitors drove down profit margins. Toyota developed more sophisticated cars targeted at higher tiers of the market in order to improve its margins. Its Corolla, Camry, Previa, Avalon, and Lexus families of cars have been introduced in response to the same competitive pressures—it kept its margins healthy by migrating up-market. In the process, Toyota has had to add costs to its operation to design, build, and support cars of this caliber. It progressively deemphasized the entry-level tiers of the market, having found the margins it could earn there to be unattractive, given its changed cost structure.

Nucor Steel, the leading minimill that led the up-market charge against the integrated mills that was recounted in chapter 4, likewise has experienced a change in values. As it has managed the center of gravity in its product line up-market from re-bar to angle iron to structural beams and finally to sheet steel, it has begun to decidedly deemphasize re-bar—the product that had been its bread and butter in its earlier years.

The second dimension along which values predictably change relates to how big a business has to be in order to be interesting. Because a company’s stock price represents the discounted present value of its projected earnings stream, most managers typically feel compelled not just to maintain growth, but to maintain a constant rate of growth. In order for a $40 million company to grow 25 percent, it needs to find $10 million in new business the next year. For a $40 billion company to grow 25 percent, it needs to find $10 billion in new business the next year. The size of market opportunity that will solve each of these companies’ needs for growth is very different. As noted in chapter 6, an opportunity that excites a small organization isn’t big enough to be interesting to a very large one. One of the bittersweet rewards of success is, in fact, that as companies become large, they literally lose the capability to enter small emerging markets. This disability is not because of a change in the resources within the companies—their resources typically are vast. Rather, it is because their values change.

Executives and Wall Street financiers who engineer megamergers among already huge companies in order to achieve cost savings need to account for the impact of these actions on the resultant companies’ values. Although their merged organizations might have more resources to throw at innovation problems, their commercial organizations tend to lose their appetites for all but the biggest blockbuster opportunities. Huge size constitutes a very real disability in managing innovation. In many ways, Hewlett-Packard’s recent decision to split itself into two companies is rooted in its recognition of this problem.

THE RELATIONSHIP BETWEEN PROCESSES AND VALUES, AND SUCCESS IN ADDRESSING SUSTAINING VS. DISRUPTIVE TECHNOLOGIES

The resources-processes-values (RPV) framework has been a useful tool for me to understand the findings from my research relating to the differences in companies’ track records in sustaining and disruptive technologies. Recall that we identified 116 new technologies that were introduced in the industry’s history. Of these, 111 were sustaining technologies, in that their impact was to improve the performance of disk drives. Some of these were incremental improvements while others, such as magneto-resistive heads, represented discontinuous leaps forward in performance. In all 111 cases of sustaining technology, the companies that led in developing and introducing the new technology were the companies that had led in the old technology. The success rate of the established firms in developing and adopting sustaining technologies was 100 percent.

The other five of these 116 technologies were disruptive innovations—in each case, smaller disk drives that were slower and had lower capacity than those used in the mainstream market. There was no new technology involved in these disruptive products. Yet none of the industry’s leading companies remained atop the industry after these disruptive innovations entered the market—their batting average was zero.

Why such markedly different batting averages when playing the sustaining versus disruptive games? The answer lies in the RPV framework of organizational capabilities. The industry leaders developed and introduced sustaining technologies over and over again. Month after month, year after year, as they introduced new and improved products in order to gain an edge over the competition, the leading companies developed processes for evaluating the technological potential and assessing their customers’ needs for alternative sustaining technologies. In the parlance of this chapter, the organizations developed a capability for doing these things, which resided in their processes. Sustaining technology investments also fit the values of the leading companies, in that they promised higher margins from better products sold to their leading-edge customers.

On the other hand, the disruptive innovations occurred so intermittently that no company had a routinized process for handling them. Furthermore, because the disruptive products promised lower profit margins per unit sold and could not be used by their best customers, these innovations were inconsistent with the leading companies’ values. The leading disk drive companies had the resources—the people, money, and technology—required to succeed at both sustaining and disruptive technologies. But their processes and values constituted disabilities in their efforts to succeed at disruptive technologies.

Large companies often surrender emerging growth markets because smaller, disruptive companies are actually more capable of pursuing them. Though start-ups lack resources, it doesn’t matter. Their values can embrace small markets, and their cost structures can accommodate lower margins. Their market research and resource allocation processes allow managers to proceed intuitively rather than having to be backed up by careful research and analysis, presented in PowerPoint. All of these advantages add up to enormous opportunity or looming disaster—depending upon your perspective.

Managers who face the need to change or innovate, therefore, need to do more than assign the right resources to the problem. They need to be sure that the organization in which those resources will be working is itself capable of succeeding—and in making that assessment, managers must scrutinize whether the organization’s processes and values fit the problem.

THE MIGRATION OF CAPABILITIES

In the start-up stages of an organization, much of what gets done is attributable to its resources—its people. The addition or departure of a few key people can have a profound influence on its success. Over time, however, the locus of the organization’s capabilities shifts toward its processes and values. As people work together successfully to address recurrent tasks, processes become defined. And as the business model takes shape and it becomes clear which types of business need to be accorded highest priority, values coalesce. In fact, one reason that many soaring young companies flame out after they go public based upon a hot initial product is that whereas their initial success was grounded in resources— the founding group of engineers—they fail to create processes that can create a sequence of hot products.

An example of such flame out is the story of Avid Technology, a producer of digital editing systems for television. Avid’s technology removed tedium from the video editing process. Customers loved it, and on the back of its star product, Avid stock rose from $16 at its 1993 IPO to $49 in mid-1995. However, the strains of being a one-trick pony soon surfaced as Avid was faced with a saturated market, rising inventories and receivables, and increased competition. Customers loved the product, but Avid’s lack of effective processes to consistently develop new products and to control quality, delivery, and service ultimately tripped the company and sent its stock back down.

In contrast, at highly successful firms such as McKinsey and Company, the processes and values have become so powerful that it almost doesn’t matter which people get assigned to which project teams. Hundreds of new MBAs join the firm every year, and almost as many leave. But the company is able to crank out high-quality work year after year because its core capabilities are rooted in its processes and values rather than in its resources. I sense, however, that these capabilities of McKinsey also constitute its disabilities. The rigorously analytical, data-driven processes that help it create value for its clients in existing, relatively stable markets render it much less capable of building a strong client base among the rapidly growing companies in dynamic technology markets.

In the formative stages of a company’s processes and values, the actions and attitudes of the company’s founder have a profound impact. The founder often has strong opinions about the way employees ought to work together to reach decisions and get things done. Founders similarly impose their views of what the organization’s priorities need to be. If the founder’s methods are flawed, of course, the company will likely fail. But if those methods are useful, employees will collectively experience for themselves the validity of the founder’s problem-solving methodologies and criteria for decision-making. As they successfully use those methods of working together to address recurrent tasks, processes become defined. Likewise, if the company becomes financially successful by prioritizing various uses of its resources according to criteria that reflect the founder’s priorities, the company’s values begin to coalesce.

As successful companies mature, employees gradually come to assume that the priorities they have learned to accept, and the ways of doing things and methods of making decisions that they have employed so successfully, are the right way to work. Once members of the organization begin to adopt ways of working and criteria for making decisions by assumption, rather than by conscious decision, then those processes and values come to constitute the organization’s culture. [7] As companies grow from a few employees to hundreds and thousands, the challenge of getting all employees to agree on what needs to be done and how it should be done so that the right jobs are done repeatedly and consistently can be daunting for even the best managers. Culture is a powerful management tool in these situations. Culture enables employees to act autonomously and causes them to act consistently.

Hence, the location of the most powerful factors that define the capabilities and disabilities of organizations migrates over time —from resources toward visible, conscious processes and values, and then toward culture. As long as the organization continues to face the same sorts of problems that its processes and values were designed to address, managing the organization is relatively straightforward. But because these factors also define what an organization cannot do, they constitute disabilities when the problems facing the company change. When the organization’s capabilities reside primarily in its people, changing to address new problems is relatively simple. But when the capabilities have come to reside in processes and values and especially when they have become embedded in culture, change can become extraordinarily difficult.

A case in point: Did Digital Equipment have the capability to succeed in personal computers?

Digital Equipment Corporation (DEC) was a spectacularly successful maker of minicomputers from the 1960s through the 1980s. One might have been tempted to assert, when the personal computer market began to coalesce in the early 1980s, that DEC’s “core competence” was in building computers. But if computers were DEC’s competence, why did the company stumble?

Clearly, DEC had the resources to succeed in personal computers. Its engineers were routinely designing far more sophisticated computers than PCs. DEC had plenty of cash, a great brand, and strong technology. But did DEC have the processes to succeed in the personal computer business? No. The processes for designing and manufacturing minicomputers involved designing many of the key components of the computer internally and then integrating the components into proprietary configurations. The design process itself consumed two to three years for a new product model. DEC’s manufacturing processes entailed making most components and assembling them in a batch mode. It sold direct to corporate engineering organizations. These processes worked extremely well in the minicomputer business.

The personal computer business, in contrast, required processes through which the most cost-effective components were outsourced from the best suppliers around the globe. New computer designs, comprised of modular components, had to be completed in six-to twelve-month cycles. The computers were manufactured in high-volume assembly lines, and sold through retailers to consumers and businesses. None of these processes required to compete successfully in the personal computer business existed within DEC. In other words, although the people working at DEC, as individuals, had the abilities to design, build, and sell personal computers profitably, they were working in an organization that was incapable of doing this because its processes had been designed and had evolved to do other tasks well. The very processes that made the company capable of succeeding in one business rendered it incapable of succeeding in another.

And what about DEC’s values? Because of the overhead costs that were required to succeed in the minicomputer business, DEC had to adopt a set of values that essentially dictated, “If it generates 50 percent gross margins or more, it’s good business. If it generates less than 40 percent margins, it’s not worth doing.” Management had to ensure that all employees prioritized projects according to this criterion, or the company couldn’t make money. Because personal computers generated lower margins, they did not “fit” with DEC’s values. The company’s criteria for prioritization placed higher-performance minicomputers ahead of personal computers in the resource allocation process. And any attempts that the company made to enter the personal computer business had to target the highest-margin tiers of that market—because the financial results that might be earned in those tiers were the only ones that the company’s values would tolerate. But because of the patterns noted in chapter 4—the strong tendency for competitors with low-overhead business models to migrate upmarket—Digital’s values rendered it incapable of pursuing a winning strategy.

As we saw in chapter 5, Digital Equipment could have owned another organization whose processes and values were tailored to those required to play in the personal computer game. But the particular organization in Maynard, Massachusetts, whose extraordinary capabilities had carried the company to such success in the minicomputer business, was simply incapable of succeeding in the personal computer world.

CREATING CAPABILITIES TO COPE WITH CHANGE

If a manager determined that an employee was incapable of succeeding at a task, he or she would either find someone else to do the job or carefully train the employee to be able to succeed. Training often works, because individuals can become skilled at multiple tasks.

Despite beliefs spawned by popular change-management and reengineering programs, processes are not nearly as flexible or “trainable” as are resources—and values are even less so. The processes that make an organization good at outsourcing components cannot simultaneously make it good at developing and manufacturing components in-house. Values that focus an organization’s priorities on high-margin products cannot simultaneously focus priorities on low-margin products. This is why focused organizations perform so much better than unfocused ones: their processes and values are matched carefully with the set of tasks that need to be done.

For these reasons, managers who determine that an organization’s capabilities aren’t suited for a new task, are faced with three options through which to create new capabilities. They can:

- Acquire a different organization whose processes and values are a close match with the new task

- Try to change the processes and values of the current organization

- Separate out an independent organization and develop within it the new processes and values that are required to solve the new problem

Creating Capabilities Through Acquisitions

Managers often sense that acquiring rather than developing a set of capabilities makes competitive and financial sense. The RPV model can be a useful way to frame the challenge of integrating acquired organizations. Acquiring managers need to begin by asking, “What is it that really created the value that I just paid so dearly for? Did I justify the price because of its resources—its people, products, technology, market position, and so on? Or, was a substantial portion of its worth created by processes and values—unique ways of working and decision-making that have enabled the company to understand and satisfy customers, and develop, make, and deliver new products and services in a timely way?

If the acquired company’s processes and values are the real driver of its success, then the last thing the acquiring manager wants to do is to integrate the company into the new parent organization. Integration will vaporize many of the processes and values of the acquired firm as its managers are required to adopt the buyer’s way of doing business and have their proposals to innovate evaluated according to the decision criteria of the acquiring company. If the acquiree’s processes and values were the reason for its historical success, a better strategy is to let the business stand alone, and for the parent to infuse its resources into the acquired firm’s processes and values. This strategy, in essence, truly constitutes the acquisition of new capabilities.

If, on the other hand, the company’s resources were the primary rationale for the acquisition, then integrating the firm into the parent can make a lot of sense—essentially plugging the acquired people, products, technology, and customers into the parent’s processes, as a way of leveraging the parent’s existing capabilities.

The perils of the DaimlerChrysler merger that began in the late 1990s, for example, can be better understood through the RPV model. Chrysler had few resources that could be considered unique in comparison to its competitors. Its success in the market of the 1990s was rooted in its processes—particularly in its rapid, creative product design processes, and in its processes of integrating the efforts of its subsystem suppliers. What would be the best way for Daimler to leverage the capabilities that Chrysler brought to the table? Wall Street exerted nearly inexorable pressure on management to consolidate the two organizations in order to cut costs. However, integrating the two companies would likely vaporize the key processes that made Chrysler such an attractive acquisition in the first place.

This situation is reminiscent of IBM’s 1984 acquisition of Rolm. There wasn’t anything in Rolm’s pool of resources that IBM didn’t already have. It was Rolm’s processes for developing PBX products and for finding new markets for them that was really responsible for its success. In 1987 IBM decided to fully integrate the company into its corporate structure. Trying to push Rolm’s resources—its products and its customers—through the same processes that were honed in its large computer business, caused the Rolm business to stumble badly. And inviting executives of a computer company whose values had been whetted on operating profit margins of 18 percent to get excited about prioritizing products with operating margins below 10 percent was impossible. IBM’s decision to integrate Rolm actually destroyed the very source of the original worth of the deal. As this chapter is being written in February 2000, DaimlerChrysler, bowing to the investment community’s drumbeat for efficiency savings, now stands on the edge of the same precipice.

Often, it seems, financial analysts have a better intuition for the value of resources than for processes.

In contrast, Cisco Systems’ acquisitions process has worked well— because its managers seem to have kept resources, processes, and values in the right perspective. Between 1993 and 1997 it acquired primarily small companies that were less than two years old: early-stage organizations whose market value was built primarily upon their resources— particularly engineers and products. Cisco has a well-defined, deliberate process by which it essentially plugs these resources into the parent’s processes and systems, and it has a carefully cultivated method of keeping the engineers of the acquired company happily on the Cisco payroll. In the process of integration, Cisco throws away whatever nascent processes and values came with the acquisition—because those weren’t what Cisco paid for. On a couple of occasions when the company acquired a larger, more mature organization—notably its 1996 acquisition of StrataCom— Cisco did not integrate. Rather, it let StrataCom stand alone, and infused its substantial resources into the organization to help it grow at a more rapid rate. [8]

On at least three occasions, Johnson & Johnson has used acquisitions to establish a position in an important wave of disruptive technology. Its businesses in disposable contact lenses, endoscopic surgery, and diabetes blood glucose meters were all acquired when they were small, were allowed to stand alone, and were infused with resources. Each has become a billion-dollar business. Lucent Technologies and Nortel followed a similar strategy for catching the wave of routers, based upon packet-switching technology, that were disrupting their traditional circuit-switching equipment. But they made these acquisitions late and the firms they acquired, Ascend Communications and Bay Networks, respectively, were extraordinarily expensive because they had already created the new market application, data networks, along with the much larger Cisco Systems—and they were right on the verge of attacking the voice network.

Creating New Capabilities Internally

Companies that have tried to develop new capabilities within established organizational units also have a spotty track record, unfortunately. Assembling a beefed-up set of resources as a means of changing what an existing organization can do is relatively straightforward. People with new skills can be hired, technology can be licensed, capital can be raised, and product lines, brands, and information can be acquired. Too often, however, resources such as these are then plugged into fundamentally unchanged processes—and little change results. For example, through the 1970s and 1980s Toyota upended the world automobile industry through its innovation in development, manufacturing, and supply-chain processes— without investing aggressively in resources such as advanced manufacturing or information-processing technology. General Motors responded by investing nearly $60 billion in manufacturing resources—computer-automated equipment that was designed to reduce cost and improve quality. Using state-of-the-art resources in antiquated processes, however, made little difference in General Motors’ performance, because it is in its processes and values that the organization’s most fundamental capabilities lie. Processes and values define how resources—many of which can be bought and sold, hired and fired—are combined to create value.

Unfortunately, processes are very hard to change—for two reasons. The first is that organizational boundaries are often drawn to facilitate the operation of present processes. Those boundaries can impede the creation of new processes that cut across those boundaries. When new challenges require different people or groups to interact differently than they habitually have done—addressing different challenges with different timing than historically had been required—managers need to pull the relevant people out of the existing organization and draw a new boundary around a new group. New team boundaries enable or facilitate new patterns of working together that ultimately can coalesce as new processes—new capabilities for transforming inputs into outputs. Professors Steven C. Wheelwright and Kim B. Clark have called these structures heavyweight teams. [9]

The second reason new process capabilities are hard to develop is that, in some cases, managers don’t want to throw the existing processes out—the methods work perfectly well in doing what they were designed to do. As noted above, while resources tend to be flexible and can be used in a variety of situations, processes and values are by their very nature inflexible. Their very raison d’e^tre is to cause the same thing to be done consistently, over and over again. Processes are meant not to change.

When disruptive change appears on the horizon, managers need to assemble the capabilities to confront the change before it has affected the mainstream business. In other words, they need an organization that is geared toward the new challenge before the old one, whose processes are tuned to the existing business model, has reached a crisis that demands fundamental change.

Because of its task-specific nature, it is impossible to ask one process to do two fundamentally different things. Consider the examples presented in chapter 7, for instance. The market research and planning processes that are appropriate for the launch of new products into existing markets simply aren’t capable of guiding a company into emerging, poorly defined markets. And the processes by which a company would experimentally and intuitively feel its way into emerging markets would constitute suicide if employed in a well-defined existing business. If a company needs to do both types of tasks simultaneously, then it needs two very different processes. And it is very difficult for a single organizational unit to employ fundamentally different, opposing processes. As shown below, this is why managers need to create different teams, within which different processes to address new problems can be defined and refined.

Creating Capabilities Through a Spin-out Organization

The third mechanism for new capability creation—spawning them within spin-out ventures—is currently en vogue among many managers as they wrestle with how to address the Internet. When are spin-outs a crucial step in building new capabilities to exploit change, and what are the guidelines by which they should be managed? A separate organization is required when the mainstream organization’s values would render it incapable of focusing resources on the innovation project. Large organizations cannot be expected to allocate freely the critical financial and human resources needed to build a strong position in small, emerging markets. And it is very difficult for a company whose cost structure is tailored to compete in high-end markets to be profitable in low-end markets as well. When a threatening disruptive technology requires a different cost structure in order to be profitable and competitive, or when the current size of the opportunity is insignificant relative to the growth needs of the mainstream organization, then—and only then—is a spin-out organization a required part of the solution.

How separate does the effort need to be? The primary requirement is that the project cannot be forced to compete with projects in the mainstream organization for resources. Because values are the criteria by which prioritization decisions are made, projects that are inconsistent with a company’s mainstream values will naturally be accorded lowest priority. Whether the independent organization is physically separate is less important than is its independence from the normal resource allocation process.

In our studies of this challenge, we have never seen a company succeed in addressing a change that disrupts its mainstream values absent the personal, attentive oversight of the CEO—precisely because of the power of processes and values and particularly the logic of the normal resource allocation process. Only the CEO can ensure that the new organization gets the required resources and is free to create processes and values that are appropriate to the new challenge. CEOs who view spin-outs as a tool to get disruptive threats off of their personal agendas are almost certain to meet with failure. We have seen no exceptions to this rule.

The framework summarized in Figure 8.1 can help managers exploit the capabilities that reside in their current processes and values when that is possible, and to create new ones, when the present organization is incapable. The left axis in Figure 8.1 measures the extent to which the existing processes—the patterns of interaction, communication, coordination, and decision-making currently used in the organization—are the ones that will get the new job done effectively. If the answer is yes (toward the lower end of the scale), the project manager can exploit the organization’s existing processes and organizational structure to succeed. As depicted in the corresponding position on the right axis, functional or lightweight teams, as described by Clark and Wheelwright, [10] are useful structures for exploiting existing capabilities. In such teams, the role of the project manager is to facilitate and coordinate work that is largely done within functional organizations.

Figure 8.1 Fitting an Innovation’s Requirements with the Organization’s Capabilities

Note: The left and bottom axes reflect the questions the manager needs to ask about the existing situation. The notes at the right side represent the appropriate response to the situation on the left axis. The notes at the top represent the appropriate response to the manager’s answer to the bottom axis.

On the other hand, if the ways of getting work done and of decision-making in the mainstream business would impede rather than facilitate the work of the new team—because different people need to interact with different people about different subjects and with different timing than has habitually been necessary—then a heavyweight team structure is necessary. Heavyweight teams are tools to create new processes—new ways of working together that constitute new capabilities. In these teams, members do not simply represent the interests and skills of their function. They are charged to act like general managers, and reach decisions and make trade-offs for the good of the project. They typically are dedicated and colocated.

The horizontal axis of Figure 8.1 asks managers to assess whether the organization’s values will allocate to the new initiative the resources it will need in order to become successful. If there is a poor, disruptive fit, then the mainstream organization’s values will accord low priority to the project. Therefore, setting up an autonomous organization within which development and commercialization can occur will be absolutely essential to success. At the other extreme, however, if there is a strong, sustaining fit, then the manager can expect that the energy and resources of the mainstream organization will coalesce behind it. There is no reason for a skunk works or a spin-out in such cases.

Region A in Figure 8.1 depicts a situation in which a manager is faced with a breakthrough but sustaining technological change—it fits the organization’s values. But it presents the organization with different types of problems to solve and therefore requires new types of interaction and coordination among groups and individuals. The manager needs a heavyweight development team to tackle the new task, but the project can be executed within the mainstream company. This is how Chrysler, Eli Lilly, and Medtronic accelerated their product development cycles so dramatically. [11] Heavyweight teams are the organizational mechanism that the managers of IBM’s disk drive division used to learn how to integrate components more effectively in their product designs, in order to wring 50 percent higher performance out of the components they used. Microsoft’s project to develop and launch its Internet browser was located in the Region A corner of this framework. It represented an extraordinary, difficult managerial achievement that required different people to work together in patterns different than any ever used before within Microsoft. But it was a sustaining technology to the company. Its customers wanted the product, and it strengthened the company’s integral business model. There was, therefore, no need to spin the project out into a completely different organization.

When in Region B, where the project fits the company’s processes and values, a lightweight development team can be successful. In such teams coordination across functional boundaries occurs within the mainstream organization.

Region C denotes an area in which a manager is faced with a disruptive technological change that doesn’t fit the organization’s existing processes and values. To ensure success in such instances, managers should create an autonomous organization and commission a heavyweight development team to tackle the challenge. In addition to the examples cited in chapters 5, 6, and 7, many companies’ efforts to address the distribution channel conflicts created by the Internet should be managed in this manner. In 1999 Compaq Computer, for example, launched a business to market its computers direct to customers over the Internet, so that it could compete more effectively with Dell Computer. Within a few weeks its retailers had protested so loudly that Compaq had to back away from the strategy. This was very disruptive to the values, or profit model, of the company and its retailers. The only way it could manage this conflict would be to launch the direct business through an independent company. It might even need a different brand in order to manage the tension.

Some have suggested that Wal-Mart’s strategy of managing its on-line retailing operation through an independent organization in Silicon Valley is foolhardy, because the spin-out organization can’t leverage Wal-Mart’s extraordinary logistics management processes and infrastructure. I believe the spin-out was wise, however, based upon Figure 8.1. The on-line venture actually needs very different logistics processes than those of its bricks-and-mortar operations. Those operations transport goods by the truck-load. On-line retailers need to pick individual items from inventory and ship small packages to diverse locations. The venture is not only disruptive to Wal-Mart’s values, but it needs to create its own logistics processes as well. It needed to be spun out separately.

Region D typifies projects in which products or services similar to those in the mainstream need to be sold within a fundamentally lower overhead cost business model. Wal-Mart’s Sam’s Clubs would fit in this region. These, in fact, can leverage similar logistics management processes as the main company; but budgeting, management, and P&L responsibility needs to be different.

Functional and lightweight teams are appropriate vehicles for exploiting established capabilities, whereas heavyweight teams are tools for creating new ones. Spin-out organizations, similarly, are tools for forging new values. Unfortunately, most companies employ a one-size-fits-all organizing strategy, using lightweight teams for programs of every size and character. Among those few firms that have accepted the “heavyweight gospel,” many have attempted to organize all of their development teams in a heavyweight fashion. Ideally, each company should tailor the team structure and organizational location to the process and values required by each project.

In many ways, the disruptive technologies model is a theory of relativity, because what is disruptive to one company might have a sustaining impact on another. For example, Dell Computer began by selling computers over the telephone. For Dell, the initiative to begin selling and accepting orders over the Internet was a sustaining innovation. It helped it make more money in the way it was already structured. For Compaq, Hewlett-Packard, and IBM, however, marketing direct to customers over the Internet would have a powerfully disruptive impact. The same is true in stock brokerage. For discount brokers such as Ameritrade and Charles Schwab, which accepted most of their orders by telephone, trading securities on-line simply helped them discount more cost-effectively—and even offer enhanced service relative to their former capabilities. For full-service firms with commissioned brokers such as Merrill Lynch, however, on-line trading represents a powerful disruptive threat.

SUMMARY

Managers whose organizations are confronting change must first determine that they have the resources required to succeed. They then need to ask a separate question: does the organization have the processes and values to succeed? Asking this second question is not as instinctive for most managers because the processes by which work is done and the values by which employees make their decisions have served them well. What I hope this framework adds to managers’ thinking, however, is that the very capabilities of their organizations also define their disabilities. A little time spent soul-searching for honest answers to this issue will pay off handsomely. Are the processes by which work habitually gets done in the organization appropriate for this new problem? And will the values of the organization cause this initiative to get high priority, or to languish?

If the answer to these questions is no, it’s okay. Understanding problems is the most crucial step in solving them. Wishful thinking about this issue can set teams charged with developing and implementing an innovation on a course fraught with roadblocks, second-guessing, and frustration. The reasons why innovation often seems to be so difficult for established firms is that they employ highly capable people, and then set them to work within processes and values that weren’t designed to facilitate success with the task at hand. Ensuring that capable people are ensconced in capable organizations is a major management responsibility in an age such as ours, when the ability to cope with accelerating change has become so critical.

NOTES

1. See C. K. Prahalad, and Gary Hamel, “The Core Competence of the Corporation,” Harvard Business Review, 1990.

2. Many of these ideas emerged from wonderful, stimulating discussions with doctoral students in the Business Policy seminar at the Harvard Business School between 1993 and 1999. I wish to thank all of those students, but in particular Don Sull, Tom Eisenmann, Tomoyoshi Noda, Michael Raynor, Michael Roberto, Deborah Sole, Clark Gilbert, and Michael Overdorf for their contributions to these ideas.

3. The most logical, comprehensive characterization of processes that we have seen is in David Garvin, “The Processes of Organization and Management,” Sloan Management Review, Summer, 1998. When we use the term “processes,” we mean for it to include all of the types of processes that Garvin has defined.

4. See Dorothy Leonard-Barton, “Core Capabilities and Core Rigidities: A Paradox in Managing New Product Development,” Strategic Management Journal (13), 1992, 111–12

5. Professor Leonardi’s work on this topic, in my opinion, constitutes the fundamental paradigm upon which much subsequent research is being built. 5. See Wickham Skinner, “The Focused Factory,” Harvard Business Review, 1974.

6. See, for example, Thomas Peters and Robert Waterman, In Search of Excellence (New York: Harper & Row Publishers, 1982).

7. See Edgar Schein, Organizational Culture and Leadership (San Francisco: Jossey-Bass Publishers, 1988). This description of the development of an organization’s culture draws heavily from Schein’s research.

8. See Nicole Tempest, “Cisco Systems, Inc. Post-Acquisition Manufacturing Integration,” a teaching case published jointly by the Stanford University Graduate School of Business and the Harvard Business School, 1998.

9. Steven C. Wheelwright and Kim B. Clark, Revolutionizing Product Development (New York: The Free Press, 1992).

10. See Kim B. Clark and Steven C. Wheelwright, “Organizing and Leading Heavyweight Development Teams,” California Management Review (34), Spring, 1992, 9–28. The concepts described in this article are extremely important. We highly recommend that managers interested in these problems study it thoughtfully. They define a heavyweight team as one in which team members typically are dedicated and colocated. The charge of each team member is not to represent their functional group on the team, but to act as a general manager—to assume responsibility for the success of the entire project, and to be actively involved in the decisions and work of members who come from each functional area. As they work together to complete their project, they will work out new ways of interacting, coordinating, and decision-making that will come to comprise the new processes, or new capabilities, that will be needed to succeed in the new enterprise on an ongoing basis. These ways of getting work done then get institutionalized as the new business or product line grows.

11. See Jeff Dyer, “How Chrysler Created an American Keiretsu,” Harvard Business Review, July-August, 1996, 42–56; Clayton M. Christensen, “We’ve Got Rhythm! Medtronic Corporation’s Cardiac Pacemaker Business,” Harvard Business School, Case No. 698-004; and Steven C. Wheelwright, “Eli Lilly: The Evista Project,” Harvard Business School, Case No. 699-016.

CHAPTER NINE

Performance Provided, Market Demand, and the Product Life Cycle

The graphs in this book showing the intersecting technology and market trajectories have proven useful in explaining how leading firms can stumble from positions of industry leadership. In each of the several industries explored, technologists were able to provide rates of performance improvement that have exceeded the rates of performance improvement that the market has needed or was able to absorb. Historically, when this performance oversupply occurs, it creates an opportunity for a disruptive technology to emerge and subsequently to invade established markets from below.

As it creates this threat or opportunity for a disruptive technology, performance oversupply also triggers a fundamental change in the basis of competition in the product’s market: The rank-ordering of the criteria by which customers choose one product or service over another will change, signaling a transition from one phase (variously defined by management theorists) to the next of the product life cycle. In other words, the intersecting trajectories of performance supplied and performance demanded are fundamental triggers behind the phases in the product life cycle. Because of this, trajectory maps such as those used in this book usefully characterize how an industry’s competitive dynamics and its basis of competition are likely to change over time.

As with past chapters, this discussion begins with an analysis from the disk drive industry of what can happen when the performance supplied exceeds the market’s demands. After seeing the same phenomenon played out in the markets for accounting software and for diabetes care products, the link between this pattern and the phases of the product life cycle will be clear.

PERFORMANCE OVERSUPPLY AND CHANGING BASES OF COMPETITION

The phenomenon of performance oversupply is charted in Figure 9.1, an extract from Figure 1.7. It shows that by 1988, the capacity of the average 3.5-inch drive had finally increased to equal the capacity demanded in the mainstream desktop personal computer market, and that the capacity of the average 5.25-inch drive had by that time surpassed what the mainstream desktop market demanded by nearly 300 percent. At this point, for the first time since the desktop market emerged, computer makers had a choice of drives to buy: The 5.25-and 3.5-inch drives both provided perfectly adequate capacity.

What was the result? The desktop personal computer makers began switching to 3.5-inch drives in droves. Figure 9.2 illustrates this, using a substitution curve format in which the vertical axis measures the ratio of new-to old-technology units sold. In 1985 this measure was .007, meaning that less than 1 percent (.0069) of the desktop market had switched to the 3.5-inch format. By 1987, the ratio had advanced 0.20, meaning that 16.7 percent of the units sold into this market that year were 3.5-inch drives. By 1989, the measure was 1.5, that is, only four years after the 3.5-inch product had appeared as a faint blip on the radar screen of the market, it accounted for 60 percent of drive sales.

Why did the 3.5-inch drive so decisively conquer the desktop PC market? A standard economic guess might be that the 3.5-inch format represented a more cost-effective architecture: If there were no longer any meaningful differentiation between two types of products (both had adequate capacity), price competition would intensify. This was not the case here, however. Indeed, computer makers had to pay, on average, 20 percent more per megabyte to use 3.5-inch drives, and yet they still flocked to the product. Moreover, computer manufacturers opted for the costlier drive while facing fierce price competition in their own product markets. Why?

Performance oversupply triggered a change in the basis of competition. Once the demand for capacity was satiated, other attributes, whose performance had not yet satisfied market demands, came to be more highly valued and to constitute the dimensions along which drive makers sought to differentiate their products. In concept, this meant that the most important attribute measured on the vertical axis of figures such as 8.1 changed, and that new trajectories of product performance, compared to market demands, took shape.

Figure 9.1 Intersecting Trajectories of Capacity Demanded versus Capacity Supplied in Rigid Disk Drives

Source: Data are from various issues of Disk/Trend Report.

Figure 9.2 Substitution of 8-, 5.25-, and 3.5-Inch Drives of 30 to 100 MB

Source: Data are from various issues of Disk/Trend Report.

Specifically, in the desktop personal computer marketplace between 1986 and 1988, the smallness of the drive began to matter more than other features. The smaller 3.5-inch drive allowed computer manufacturers to reduce the size, or desktop footprint, of their machines. At IBM, for example, the large XT/AT box gave way to the much smaller PS1/PS2 generation machines.

For a time, when the availability of small drives did not satisfy market demands, desktop computer makers continued to pay a hefty premium for 3.5-inch drives. In fact, using the hedonic regression analysis described in chapter 4, the 1986 shadow price for a one-cubic-inch reduction in the volume of a disk drive was $4.72. But once the computer makers had configured their new generations of desktop machines to use the smaller drive, their demand for even more smallness was satiated. As a result, the 1989 shadow price, or the price premium accorded to smaller drives, diminished to $0.06 for a one-cubic-inch reduction.

Generally, once the performance level demanded of a particular attribute has been achieved, customers indicate their satiation by being less willing to pay a premium price for continued improvement in that attribute. Hence, performance oversupply triggers a shift in the basis of competition, and the criteria used by customers to choose one product over another changes to attributes for which market demands are not yet satisfied.

Figure 9.3 summarizes what seems to have happened in the desktop PC market: The attribute measured on the vertical axis repeatedly changed. Performance oversupply in capacity triggered the first redefinition of the vertical axis, from capacity to physical size. When performance on this new dimension satisfied market needs, the definition of performance on the vertical axis changed once more, to reflect demand for reliability. For a time, products offering competitively superior shock resistance and mean time between failure (MTBF) were accorded a significant price premium, compared to competitive offerings. But as MTBF values approached one million hours, [1] the shadow price accorded to an increment of one hundred hours MTBF approached zero, suggesting performance oversupply on that dimension of product performance. The subsequent and current phase is an intense price-based competition, with gross margins tumbling below 12 percent in some instances.

WHEN DOES A PRODUCT BECOME A COMMODITY?

The process of commoditization of disk drives was defined by the interplay between the trajectories of what the market demanded and what the technology supplied. The 5.25-inch drive had become a price-driven commodity in the desktop market by about 1988, when the 3.5-inch drive was still at a premium price. The 5.25-inch drive, in addition, even though priced as a commodity in desktop applications, was at the same time, relative to 8-inch drives, achieving substantial price premiums in higher-tier markets. As described in chapter 4, this explains the aggressive moves upmarket made by established companies.

A product becomes a commodity within a specific market segment when the repeated changes in the basis of competition, as described above, completely play themselves out, that is, when market needs on each attribute or dimension of performance have been fully satisfied by more than one available product. The performance oversupply framework may help consultants, managers, and researchers to understand the frustrated comments they regularly hear from salespeople beaten down in price negotiations with customers: “Those stupid guys are just treating our product like it was a commodity. Can’t they see how much better our product is than the competition’s?” It may, in fact, be the case that the product offerings of competitors in a market continue to be differentiated from each other. But differentiation loses its meaning when the features and functionality have exceeded what the market demands.

Figure 9.3 Changes in the Basis of Competition in the Disk Drive Industry

PERFORMANCE OVERSUPPLY AND THE EVOLUTION OF PRODUCT COMPETITION

The marketing literature provides numerous descriptions of the product life cycle and of the ways in which the characteristics of products within given categories evolve over time. [2] The findings in this book suggest that, for many of these models, performance oversupply is an important factor driving the transition from one phase of the cycle to the next.

Consider, for example, the product evolution model, called the buying hierarchy by its creators, Windermere Associates of San Francisco, California, which describes as typical the following four phases: functionality, reliability, convenience, and price. Initially, when no available product satisfies the functionality requirements the market, the basis of competition, or the criteria by which product choice is made, tends to be product functionality. (Sometimes, as in disk drives, a market may cycle through several different functionality dimensions.) Once two or more products credibly satisfy the market’s demand for functionality, however, customers can no longer base their choice of products on functionality, but tend to choose a product and vendor based on reliability. As long as market demand for reliability exceeds what vendors are able to provide, customers choose products on this basis—and the most reliable vendors of the most reliable products earn a premium for it.

But when two or more vendors improve to the point that they more than satisfy the reliability demanded by the market, the basis of competition shifts to convenience. Customers will prefer those products that are the most convenient to use and those vendors that are most convenient to deal with. Again, as long as the market demand for convenience exceeds what vendors are able to provide, customers choose products on this basis and reward vendors with premium prices for the convenience they offer. Finally, when multiple vendors offer a package of convenient products and services that fully satisfies market demand, the basis of competition shifts to price. The factor driving the transition from one phase of the buying hierarchy to the next is performance oversupply.

Another useful conception of industry evolution, formulated by Geoffrey Moore in his book Crossing the Chasm, [3] has a similar underlying logic, but articulates the stages in terms of the user rather than the product. Moore suggests that products are initially used by innovators and early adopters in an industry—customers who base their choice solely on the product’s functionality. During this phase the top-performing products command significant price premiums. Moore observes that markets then expand dramatically after the demand for functionality in the mainstream market has been met, and vendors begin to address the need for reliability among what he terms early majority customers. A third wave of growth occurs when product and vendor reliability issues have been resolved, and the basis of innovation and competition shifts to convenience, thus pulling in the late majority customers. Underlying Moore’s model is the notion that technology can improve to the point that market demand for a given dimension of performance can be satiated.

This evolving pattern in the basis of competition—from functionality, to reliability and convenience, and finally to price—has been seen in many of the markets so far discussed. In fact, a key characteristic of a disruptive technology is that it heralds a change in the basis of competition.

OTHER CONSISTENT CHARACTERISTICS OF DISRUPTIVE TECHNOLOGIES

Two additional important characteristics of disruptive technologies consistently affect product life cycles and competitive dynamics: First, the attributes that make disruptive products worthless in mainstream markets typically become their strongest selling points in emerging markets; and second, disruptive products tend to be simpler, cheaper, and more reliable and convenient than established products. Managers must understand these characteristics to effectively chart their own strategies for designing, building, and selling disruptive products. Even though the specific market applications for disruptive technologies cannot be known in advance, managers can bet on these two regularities.

1. The Weaknesses of Disruptive Technologies Are Their Strengths

The relation between disruptive technologies and the basis of competition in an industry is complex. In the interplay among performance oversupply, the product life cycle, and the emergence of disruptive technologies, it is often the very attributes that render disruptive technologies useless in mainstream markets that constitute their value in new markets.

In general, companies that have succeeded in disruptive innovation initially took the characteristics and capabilities of the technology for granted and sought to find or create a new market that would value or accept those attributes. Thus, Conner Peripherals created a market for small drives in portable computers, where smallness was valued; J. C. Bamford and J. I. Case built a market for excavators among residential contractors, where small buckets and tractor mobility actually created value; and Nucor found a market that didn’t mind the surface blemishes on its thin-slab-cast sheet steel.

The companies toppled by these disruptive technologies, in contrast, each took the established market’s needs as given, and did not attempt to market the technology until they felt it was good enough to be valued in the mainstream market. Thus, Seagate’s marketers took the firm’s early 3.5-inch drives to IBM for evaluation, rather than asking, “Where is the market that would actually value a smaller, lower-capacity drive?” When Bucyrus Erie acquired its Hydrohoe hydraulic excavator line in 1951, its managers apparently did not ask, “Where is the market that actually wants a mobile excavator that can only dig narrow trenches?” They assumed instead that the market needed the largest possible bucket size and the longest possible reach; they jury-rigged the Hydrohoe with cables, pulleys, clutches, and winches and attempted to sell it to general excavation contractors. When U.S. Steel was evaluating continuous thin-slab casting, they did not ask, “Where is the market for low-priced sheet steel with poor surface appearance?” Rather, they took it for granted that the market needed the highest-possible quality of surface finish and invested more capital in a conventional caster. They applied to a disruptive innovation a way of thinking appropriate to a sustaining technology.

In the instances studied in this book, established firms confronted with disruptive technology typically viewed their primary development challenge as a technological one: to improve the disruptive technology enough that it suits known markets. In contrast, the firms that were most successful in commercializing a disruptive technology were those framing their primary development challenge as a marketing one: to build or find a market where product competition occurred along dimensions that favored the disruptive attributes of the product. [4]

It is critical that managers confronting disruptive technology observe this principle. If history is any guide, companies that keep disruptive technologies bottled up in their labs, working to improve them until they suit mainstream markets, will not be nearly as successful as firms that find markets that embrace the attributes of disruptive technologies as they initially stand. These latter firms, by creating a commercial base and then moving upmarket, will ultimately address the mainstream market much more effectively than will firms that have framed disruptive technology as a laboratory, rather than a marketing, challenge.

2. Disruptive Technologies Are Typically Simpler, Cheaper, and More Reliable and Convenient than Established Technologies

When performance oversupply has occurred and a disruptive technology attacks the underbelly of a mainstream market, the disruptive technology often succeeds both because it satisfies the market’s need for functionality, in terms of the buying hierarchy, and because it is simpler, cheaper, and more reliable and convenient than mainstream products. Recall, for example, the attack of hydraulic excavation technology into the mainstream sewer and general excavation markets recounted in chapter 3. Once hydraulically powered excavators had the strength to handle buckets of 2 to 4 cubic yards of earth (surpassing the performance demanded in mainstream markets), contractors rapidly switched to these products even though the cable-actuated machines were capable of moving even more earth per scoop. Because both technologies provided adequate bucket capacity for their needs, contractors opted for the technology that was most reliable: hydraulics.

Because established companies are so prone to push for high-performance, high-profit products and markets, they find it very difficult not to overload their first disruptive products with features and functionality. Hewlett-Packard’s experience in designing its 1.3-inch Kittyhawk disk drive teaches just this lesson. Unable to design a product that was truly simple and cheap, Kittyhawk’s champions pushed its capacity to the limits of technology and gave it levels of shock resistance and power consumption that would make it competitive as a sustaining product. When very high volume applications for a cheap, simple, single-function, 10 MB drive began to emerge, HP’s product was not disruptive enough to catch that wave. Apple committed a similar error in stretching the functionality of its Newton, instead of initially targeting simplicity and reliability.

PERFORMANCE OVERSUPPLY IN THE ACCOUNTING SOFTWARE MARKET

Intuit, the maker of financial management software, is known primarily for its extraordinarily successful personal financial software package, Quicken. Quicken dominates its market because it is easy and convenient. Its makers pride themselves on the fact that the vast majority of Quicken customers simply buy the program, boot it up on their computers, and begin using it without having to read the instruction manual. Its developers made it so convenient to use, and continue to make it simpler and more convenient, by watching how customers use the product, not by listening to what they or the “experts” say they need. By watching for small hints of where the product might be difficult or confusing to use, the developers direct their energies toward a progressively simpler, more convenient product that provides adequate, rather than superior, functionality. [5]

Less well known is Intuit’s commanding 70 percent share of the North American small business accounting software market. [6] Intuit captured that share as a late entrant when it launched Quickbooks, a product based on three simple insights. First, previously available small business accounting packages had been created under the close guidance of certified public accountants and required users to have a basic knowledge of accounting (debits and credits, assets and liabilities, and so on) and to make every journal entry twice (thus providing an audit trail for each transaction). Second, most existing packages offered a comprehensive and sophisticated array of reports and analyses, an array that grew ever more complicated and specialized with each new release as developers sought to differentiate their products by offering greater functionality. And third, 85 percent of all companies in the United States were too small to employ an accountant: The books were kept by the proprietors or by family members, who had no need for or understanding of most of the entries and reports available from mainstream accounting software. They did not know what an audit trail was, let alone sense a need to use one.

Scott Cook, Intuit’s founder, surmised that most of these small companies were run by proprietors who relied more on their intuition and direct knowledge of the business than on the information contained in accounting reports. In other words, Cook decided that the makers of accounting software for small businesses had overshot the functionality required by that market, thus creating an opportunity for a disruptive software technology that provided adequate, not superior functionality and was simple and more convenient to use. Intuit’s disruptive Quickbooks changed the basis of product competition from functionality to convenience and captured 70 percent of its market within two years of its introduction. [7] In fact, by 1995 Quickbooks accounted for a larger share of Intuit’s revenues than did Quicken.

The response of established makers of small business accounting software to Intuit’s invasion, quite predictably, has been to move upmarket, continuing to release packages loaded with greater functionality; these focus on specific market subsegments, targeted at sophisticated users of information systems at loftier tiers of the market. Of the three leading suppliers of small business accounting software (each of which claimed about 30 percent of the market in 1992), one has disappeared and one is languishing. The third has introduced a simplified product to counter the success of Quickbooks, but it has claimed only a tiny portion of the market.

PERFORMANCE OVERSUPPLY IN THE PRODUCT LIFE CYCLE OF INSULIN

Another case of performance oversupply and disruptive technology precipitating a change in the basis of competition—and threatening a change in industry leadership—is found in the worldwide insulin business. In 1922, four researchers in Toronto first successfully extracted insulin from the pancreases of animals and injected it, with miraculous results, into humans with diabetes. Because insulin was extracted from the ground-up pancreases of cows and pigs, improving the purity of insulin (measured in impure parts per million, or ppm) constituted a critical trajectory of performance improvement. Impurities dropped from 50,000 ppm in 1925 to 10,000 ppm in 1950 to 10 ppm in 1980, primarily as the result of persistent investment and effort by the world’s leading insulin manufacturer, Eli Lilly and Company.

Despite this improvement, animal insulins, which are slightly different from human insulin, caused a fraction of a percent of diabetic patients to build up resistance in their immune systems. Thus, in 1978, Eli Lilly contracted with Genentech to create genetically altered bacteria that could produce insulin proteins that were the structural equivalent of human insulin proteins and 100 percent pure. The project was technically successful, and in the early 1980s, after a nearly $1 billion investment, Lilly introduced its Humulin-brand insulin to the market. Priced at a 25 percent premium over insulins of animal extraction, because of its human equivalence and its purity, Humulin was the first commercial-scale product for human consumption to emerge from the biotechnology industry.

The market’s response to this technological miracle, however, was tepid. Lilly found it very difficult to sustain a premium price over animal insulin, and the growth in the sales volume of Humulin was disappointingly slow. “In retrospect,” noted a Lilly researcher, “the market was not terribly dissatisfied with pork insulin. In fact, it was pretty happy with it.” [8] Lilly had spent enormous capital and organizational energy overshooting the market’s demand for product purity. Once again, this was a differentiated product to which the market did not accord a price premium because the performance it provided exceeded what the market demanded.

Meanwhile, Novo, a much smaller Danish insulin maker, was busy developing a line of insulin pens, a more convenient way for taking insulin. Conventionally, people with diabetes carried a separate syringe, inserted its needle into one glass insulin vial, pulled its plunger out to draw slightly more than the desired amount of insulin into the syringe, and held up the needle and flicked the syringe several times to dislodge any air bubbles that clung to the cylinder walls. They generally then had to repeat this process with a second, slower acting type of insulin. Only after squeezing the plunger slightly to force any remaining bubbles—and, inevitably, some insulin—out of the syringe could they inject themselves with the insulin. This process typically took one to two minutes.

Novo’s pen, in contrast, held a cartridge containing a couple of weeks’ supply of insulin, usually mixtures of both the fast-acting and the gradually released types. People using the Novo pen simply had to turn a small dial to the amount of insulin they needed to inject, poke the pen’s needle under the skin, and press a button. The procedure took less than ten seconds. In contrast to Lilly’s struggle to command a premium price for Humulin, Novo’s convenient pens easily sustained a 30 percent price premium per unit of insulin. Through the 1980s, propelled largely by the success of its line of pens and pre-mixed cartridges, Novo increased its share of the worldwide insulin market substantially—and profitably. Lilly’s and Novo’s experiences offer further proof that a product whose performance exceeds market demands suffers commodity-like pricing, while disruptive products that redefine the basis of competition command a premium.

Teaching the Harvard Business School case to executives and MBA students about Lilly overshooting the market demand for insulin purity has been one of my most interesting professional experiences. In every class, the majority of students quickly pounce on Lilly for having missed something so obvious—that only a fraction of a percent of people with diabetes develop insulin resistance—and that the differentiation between highly purified pork insulin at 10 ppm and perfectly pure Humulin was not significant. Surely, they assert, a few simple focus groups in which patients and doctors were asked whether they wanted purer insulin would have given Lilly adequate guidance.

In every discussion, however, more thoughtful students soon begin to sway class opinion toward the view that (as we have seen over and over) what is obvious in retrospect might not be at all obvious in the thick of battle. Of all the physicians to whom Lilly’s marketers listened, for example, which ones tended to carry the most credibility? Endocrinologists whose practices focused on diabetes care, the leading customers in this business. What sorts of patients are most likely to consume the professional interests of these specialists? Those with the most advanced and intractable problems, among which insulin resistance was prominent. What, therefore, were these leading customers likely to tell Lilly’s marketers when they asked what should be done to improve the next-generation insulin product? Indeed, the power and influence of leading customers is a major reason why companies’ product development trajectories overshoot the demands of mainstream markets.

Furthermore, thoughtful students observe that it would not even occur to most marketing managers to ask the question of whether a 100 percent pure human insulin might exceed market needs. For more than fifty years in a very successful company with a very strong culture, greater purity was the very definition of a better product. Coming up with purer insulins had always been the formula for staying ahead of the competition. Greater purity had always been a catching story that the salesforce could use to attract the time and attention of busy physicians. What in the company’s history would cause its culture-based assumptions suddenly to change and its executives to begin asking questions that never before had needed to be answered? [9]

CONTROLLING THE EVOLUTION OF PRODUCT COMPETITION

Figure 9.4 summarizes the model of performance oversupply, depicting a multi-tiered market in which the trajectory of performance improvement demanded by the market is shallower than the trajectory of improvement supplied by technologists. Hence, each tier of the market progresses through an evolutionary cycle marked by a shifting basis for product choice. Although other terms for product life cycles would yield similar results, this diagram uses the buying hierarchy devised by Windermere Associates, in which competition centers first on functionality, followed by reliability, convenience, and, finally, price. In each of the cases reviewed in this chapter, the products heralding shifts in the basis of competition and progression to the next product life cycle phase were disruptive technologies.

Figure 9.4 Managing Changes in the Basis of Competition

The figure shows the strategic alternatives available to companies facing performance oversupply and the consequent likelihood that disruptive approaches will change the nature of competition in their industry. The first general option, labeled strategy 1 and the one most commonly pursued in the industries explored in this book, is to ascend the trajectory of sustaining technologies into ever-higher tiers of the market, ultimately abandoning lower-tier customers when simpler, more convenient, or less costly disruptive approaches emerge.

A second alternative, labeled strategy 2, is to march in lock-step with the needs of customers in a given tier of the market, catching successive waves of change in the basis of competition. Historically, this appears to have been difficult to do, for all of the reasons described in earlier chapters. In the personal computer industry, for example, as the functionality of desktop machines came to satiate the demands of the lower tiers of the market, new entrants such as Dell and Gateway 2000 entered with value propositions centered on convenience of purchase and use. In the face of this, Compaq responded by actively pursuing this second approach, aggressively fighting any upmarket drift by producing a line of computers with low prices and modest functionality targeted to the needs of the lower tiers of the market.

The third strategic option for dealing with these dynamics is to use marketing initiatives to steepen the slopes of the market trajectories so that customers demand the performance improvements that the technologists provide. Since a necessary condition for the playing out of these dynamics is that the slope of the technology trajectory be steeper than the market’s trajectory, when the two slopes are parallel, performance oversupply—and the progression from one stage of the product life cycle to the next—does not occur or is at least postponed.

Some computer industry observers believe that Microsoft, Intel, and the disk drive companies have pursued this last strategy very effectively. Microsoft has used its industry dominance to create and successfully market software packages that consume massive amounts of disk memory and require ever-faster microprocessors to execute. It has, essentially, increased the slopes of the trajectories of improvement in functionality demanded by their customers to parallel the slope of improvement provided by their technologists. The effect of this strategy is described in Figure 9.5, depicting recent events in the disk drive industry. (This chart updates through 1996 the disk drive trajectory map in Figure 1.7.) Notice how the trajectories of capacity demanded in the mid-range, desktop, and notebook computer segments kinked upward in the 1990s along a path that essentially paralleled the capacity path blazed by the makers of 3.5-inch and 2.5-inch disk drives. Because of this, these markets have not experienced performance oversupply in recent years. The 2.5-inch drive remains locked within the notebook computer market because capacity demanded on the desktop is increasing at too brisk a pace. The 3.5-inch drive remains solidly ensconced in the desktop market, and the 1.8-inch drive has penetrated few notebook computers, for the same reasons. In this situation, the companies whose products are positioned closest to the top of the market, such as Seagate and IBM, have been the most profitable, because in the absence of technology oversupply, a shift in the stages of the product life cycle at the high end of the market has been held at bay.

Figure 9.5 Changed Performance Demand Trajectories and the Deferred Impact of Disruptive Technologies

Source: An earlier version of this figure was published in Clayton M. Christensen, “The Rigid Disk Drive Industry: A History of Commercial and Technological Turbulence,” Business History Review 67, no. 4 (Winter 1993): 559.

It is unclear how long the marketers at Microsoft, Intel, and Seagate can succeed in creating demand for whatever functionality their technologists can supply. Microsoft’s Excel spreadsheet software, for example, required 1.2 MB of disk storage capacity in its version 1.2, released in 1987. Its version 5.0, released in 1995, required 32 MB of disk storage capacity. Some industry observers believe that if a team of developers were to watch typical users, they would find that functionality has substantially overshot mainstream market demands. If true, this could create an opportunity for a disruptive technology—applets picked off the internet and used in simple internet appliances rather than in full-function computers, for example—to invade this market from below.

RIGHT AND WRONG STRATEGIES

Which of the strategies illustrated in Figure 9.4 is best? This study finds clear evidence that there is no one best strategy. Any of the three, consciously pursued, can be successful. Hewlett-Packard’s pursuit of the first strategy in its laser jet printer business has been enormously profitable. In this instance, it has been a safe strategy as well, because HP is attacking its own position with disruptive ink-jet technology. Compaq Computer and the trinity of Intel, Microsoft, and the disk drive makers have success-fully—at least to date—implemented the second and third strategies, respectively.

These successful practitioners have in common their apparent under-standing—whether explicit or intuitive—of both their customers’ trajectories of need and their own technologists’ trajectories of supply. Understanding these trajectories is the key to their success thus far. But the list of firms that have consistently done this is disturbingly short. Most well-run companies migrate unconsciously to the northeast, setting themselves up to be caught by a change in the basis of competition and an attack from below by disruptive technology.

NOTES

1. In disk drive industry convention, a mean time between failure measure of one million hours means that if one million disk drives were turned on simultaneously and operated continuously for one hour, one of those drives would fail within the first hour.

2. Three of the earliest and most influential papers that proposed the existence of product life cycles were Jay W. Forrester, “Industrial Dynamics,” Harvard Business Review, July–August, 1958, 9–14; Arch Patton, “Stretch Your Products’ Earning Years—Top Management’s Stake in the Product Life Cycle,” Management Review (38), June, 1959, 67–79; and William E. Cox, “Product Life Cycles as Marketing Models,” Journal of Business (40), October, 1967, 375. Papers summarizing the conceptual and empirical problems surrounding the product life cycle concept include Nariman K. Dhalla and Sonia Yuspeh, “Forget the Product Life Cycle Concept!” Harvard Business Review, January–February, 1976, 102–112; David R. Rink and John E. Swan, “Product Life Cycle Research: A Literature Review,” Journal of Business Research, 1979, 219; and George S. Day, “The Product Life Cycle: Analysis and Applications Issues,” Journal of Marketing (45), Fall, 1981, 60–67. A paper by Gerard J. Tellis and C. Merle Crawford, “An Evolutionary Approach to Product Growth Theory,” Journal of Marketing (45), Fall, 1981, 125–132, contains a cogent critique of the product life cycle concept, and presents a theory of product evolution that presages many of the ideas presented in this section.

3. Geoffrey A. Moore, Crossing the Chasm (New York: HarperBusiness, 1991).

4. The same behavior characterized the emergence of portable radios. In the early 1950s, Akio Morita, the chairman of Sony, took up residence in an inexpensive New York City hotel in order to negotiate a license to AT&T’s patented transistor technology, which its scientists had invented in 1947. Morita found AT&T to be a less-than-willing negotiator and had to visit the company repeatedly badgering AT&T to grant the license. Finally AT&T relented. After the meeting ended in which the licensing documents were signed, an AT&T official asked Morita what Sony planned to do with the license. “We will build small radios,” Morita replied. “Why would anyone care about smaller radios?” the official queried. “We’ll see,” was Morita’s answer. Several months later Sony introduced to the U.S. market the first portable transistor radio. According to the dominant metrics of radio performance in the mainstream market, these early transistor radios were really bad, offering far lower fidelity and much more static than the vacuum tube–based tabletop radios that were the dominant design of the time. But rather than work in his labs until his transistor radios were performance-competitive in the major market (which is what most of the leading electronics companies did with transistor technology), Morita instead found a market that valued the attributes of the technology as it existed at the time—the portable personal radio. Not surprisingly, none of the leading makers of table-top radios became a leading producer of portable radios, and all were subsequently driven from the radio market. (This story was recounted to me by Dr. Sheldon Weinig, retired vice chairman for manufacturing and technology of Sony Corporation.)

5. John Case, “Customer Service: The Last Word,” Inc. Magazine, April, 1991, 1–5.

6. This information in this section was given to the author by Scott Cook, the founder and chairman of Intuit Corporation, and by Jay O’Connor, marketing manager for Quickbooks.

7. Cook recounts that in the process of designing a simple and convenient accounting software package, Intuit’s developers arrived at a profound insight. The double-entry accounting system originally developed by Venetian merchants to catch arithmetical mistakes continued to be used in every available package of accounting software—even though computers typically do not make mistakes in addition and subtraction. Intuit was able to greatly simplify its product by eliminating this unneeded dimension of product functionality.

8. See “Eli Lilly & Co.: Innovation in Diabetes Care,” Harvard Business School, Case No. 9-696-077. This case notes that although Lilly was not able to achieve premium pricing for its Humulin insulin, it benefited from the investment. Humulin protected Lilly against a possible shortfall in the pancreas supply, threatened by declining red meat consumption, and it gave Lilly a very valuable experience and asset base in the volume manufacturing of bioengineered drugs.

9. Once such minority opinions have been raised in class, many students then begin to see that institutions widely regarded as among the best-managed and most successful in the world may have overshot what their mainstream markets demand. Intel, for example, has always measured the speed of its microprocessors on the vertical axis of its performance graphs. It has always assumed that the market demands ever-faster microprocessors, and evidence to the tune of billions of dollars in profit has certainly confirmed that belief. Certainly some leading-edge customers need chips that process instructions at rates of 200, 400, and 800 MHz. But what about the mainstream market? Is it possible that sometime soon the speed and cost of Intel’s new microprocessors might overshoot market demands? And if technology oversupply is possible, how will thousands of Intel employees be able to recognize when this has occurred, accepting the change with enough conviction to completely alter the trajectory of their development efforts? Discerning technology oversupply is difficult. Doing something about it is even more so.

CHAPTER TEN

Managing Disruptive Technological Change: A Case Study

As we approach the end of this book, we should better understand why great companies can stumble. Incompetence, bureaucracy, arrogance, tired executive blood, poor planning, and short-term investment horizons obviously have played leading roles in toppling many companies. But we have learned here that even the best managers are subject to certain laws that make disruptive innovation difficult. It is when great managers haven’t understood or have attempted to fight these forces that their companies have stumbled.

This chapter uses the forces and principles described in earlier chapters to illustrate how managers can succeed when faced with disruptive technology change. To do so, I employ a case study format, using a personal voice, to suggest how I, as a hypothetical employee of a major automaker, might manage a program to develop and commercialize one of the most vexing innovations of our day: the electric vehicle. My purpose here is explicitly not to offer any so-called right answer to this particular challenge, nor to predict whether or how electric vehicles may become commercially successful. Rather, it is to suggest in a familiar but challenging context how managers might structure their thinking about a similar problem by proposing a sequence of questions that, if asked, can lead to a sound and useful answer.

HOW CAN WE KNOW IF A TECHNOLOGY IS DISRUPTIVE?

Electric-powered vehicles have hovered at the fringe of legitimacy since the early 1900s, when they lost the contest for the dominant vehicle design to gasoline power. Research on these vehicles accelerated during the 1970s, however, as policy makers increasingly looked to them as a way to reduce urban air pollution. The California Air Resources Board (CARB) forced an unprecedented infusion of resources into the effort in the early 1990s when it mandated that, starting in 1998, no automobile manufacturer would be allowed to sell any cars in California if electric vehicles did not constitute at least 2 percent of its unit sales in the state. [1]

In my hypothetical responsibility for managing an automaker’s program, my first step would be to ask a series of questions: How much do we need to worry about electric cars? That is, aside from California’s mandate, does the electric car pose a legitimate disruptive threat to companies making gasoline-powered automobiles? Does it constitute an opportunity for profitable growth?

To answer these questions, I would graph the trajectories of performance improvement demanded in the market versus the performance improvement supplied by the technology; in other words, I would create for electric vehicles a trajectory map similar to those in Figures 1.7 or 9.5. Such charts are the best method I know for identifying disruptive technologies.

The first step in making this chart involves defining current mainstream market needs and comparing them with the current capacity of electric vehicles. To measure market needs, I would watch carefully what customers do, not simply listen to what they say. Watching how customers actually use a product provides much more reliable information than can be gleaned from a verbal interview or a focus group. [2] Thus, observations indicate that auto users today require a minimum cruising range (that is, the distance that can be driven without refueling) of about 125 to 150 miles; most electric vehicles only offer a minimum cruising range of 50 to 80 miles. Similarly, drivers seem to require cars that accelerate from 0 to 60 miles per hour in less than 10 seconds (necessary primarily to merge safely into high-speed traffic from freeway entrance ramps); most electric vehicles take nearly 20 seconds to get there. And, finally, buyers in the mainstream market demand a wide array of options, but it would be impossible for electric vehicle manufacturers to offer a similar variety within the small initial unit volumes that will characterize that business. [3] According to almost any definition of functionality used for the vertical axis of our proposed chart, the electric vehicle will be deficient compared to a gasoline-powered car.

This information is not sufficient to characterize electric vehicles as disruptive, however. They will only be disruptive if we find that they are also on a trajectory of improvement that might someday make them competitive in parts of the mainstream market. To assess this possibility, we need to project trajectories measuring the performance improvement demanded in the market versus the performance improvement that electric vehicle technology may provide. If these trajectories are parallel, then electric vehicles are unlikely to become factors in the mainstream market; but if the technology will progress faster than the pace of improvement demanded in the market, then the threat of disruption is real.

Figure 10.1 shows that the trajectories of performance improvement demanded in the market—whether measured in terms of required acceleration, cruising range, or top cruising speed—are relatively flat. This is because traffic laws impose a limit on the usefulness of ever-more-powerful cars, and demographic, economic, and geographic considerations limit the increase in commuting miles for the average driver to less than 1 percent per year. [4] At the same time, the performance of electric vehicles is improving at a faster rate—between 2 and 4 percent per year— suggesting that sustaining technological advances might indeed carry electric vehicles from their position today, where they cannot compete in mainstream markets, to a position in the future where they might. [5]

In other words, as an automotive company executive, I would worry about the electric vehicle, not just because it is politically correct to be investing in environmentally friendly technologies, but because electric vehicles have the smell of a disruptive technology. They can’t be used in mainstream markets; they offer a set of attributes that is orthogonal to those that command attention in the gasoline-powered value network; and the technology is moving ahead at a faster rate than the market’s trajectory of need.

Because electric vehicles are not sustaining innovations, however, mainstream automakers naturally doubt that there is a market for them— another symptom of a disruptive innovation. Consider this statement by the director of Ford’s electric vehicle program: “The electric Ranger will sell at approximately $30,000 and have a lead-acid battery that will give it a range of 50 miles …. The 1998 electric vehicle will be a difficult sell. The products that will be available will not meet customer expectations in terms of range, cost or utility.” [6] Indeed, given their present performance along these parameters, it will be about as easy to sell electric vehicles into the mainstream car market as it was to sell 5.25-inch disk drives to mainframe computer makers in 1980.

Figure 10.1 The Electric Car

Source: Data are from Dr. Paul J. Miller, Senior Energy Fellow, W. Alton Jones Foundation and from numerous articles about electric vehicles.

In evaluating these trajectories, I would be careful to keep asking the right question: Will the trajectory of electric vehicle performance ever intersect the trajectory of market demands (as revealed in the way customers use cars)? Industry experts may contend that electric vehicles will never perform as well as gasoline-powered cars, in effect comparing the trajectories of the two technologies. They are probably correct. But, recalling the experience of their counterparts in the disk drive industry, they will have the right answer to the wrong question. I also would note, but not be deterred by, the mountain of expert opinion averring that without a major technological breakthrough in battery technology, there will never be a substantial market for electric vehicles. The reason? If electric vehicles are viewed as a sustaining technology for established market value networks, they are clearly right. But because the track records of experts predicting the nature and size of markets for disruptive technologies is very poor, I would be particularly skeptical of the experts’ skepticism, even as I remain uncertain about my own conclusions.

WHERE IS THE MARKET FOR ELECTRIC VEHICLES?

Having decided that electric vehicles are a potentially disruptive technology, my next challenge would be to define a marketing strategy that could lead my company to a legitimate, unsubsidized market in which electric cars might first be used. In formulating this marketing strategy, I would apply three findings from earlier chapters in this book.

First, I would acknowledge that, by definition, electric vehicles cannot initially be used in mainstream applications because they do not satisfy the basic performance requirements of that market. I would therefore be sure that everybody having anything to do with my program understands this point: Although we don’t have a clue about where the market is, the one thing we know for certain is that it isn’t in an established automobile market segment. Ironically, I would expect most automakers to focus precisely and myopically on the mainstream market because of the principle of resource dependence and the principle that small markets don’t solve the growth and profit needs of big companies. I would not, therefore, follow the lead of other automakers in my search for customers, because I would recognize that their instincts and capabilities are likely to be trained on the wrong target. [7]

Nonetheless, my task is to find a market in which the vehicles can be used, because the early entrants into disruptive technology markets develop capabilities that constitute strong advantages over later entrants. They’re the ones that, from a profitable business base in this beachhead market, will most successfully throw impetus behind the sustaining innovations required to move the disruptive technology upmarket, toward the mainstream. Holding back from the market, waiting for laboratory researchers to develop a breakthrough battery technology, for example, is the path of least resistance for managers. But this strategy has rarely proven to be a viable route to success with a disruptive innovation.

Historically, as we have seen, the very attributes that make disruptive technologies uncompetitive in mainstream markets actually count as positive attributes in their emerging value network. In disk drives, the smallness of 5.25-inch models made them unusable in large computers but very useful on the desktop. While the small bucket capacity and short reach of early hydraulic excavators made them useless in general excavation, their ability to dig precise, narrow trenches made them useful in residential construction. Odd as it sounds, therefore, I would direct my marketers to focus on uncovering somewhere a group of buyers who have an undiscovered need for a vehicle that accelerates relatively slowly and can’t be driven farther than 100 miles!

The second point on which I would base my marketing approach is that no one can learn from market research what the early market(s) for electric vehicles will be. I can hire consultants, but the only thing I can know for sure is that their findings will be wrong. Nor can customers tell me whether or how they might use electric vehicles, because they will discover how they might use the products at the same time as we discover it—just as Honda’s Supercub opened an unforeseen new application for motorbiking. The only useful information about the market will be what I create through expeditions into the market, through testing and probing, trial and error, by selling real products to real people who pay real money. [8] Government mandates, incidentally, are likely to distort rather than solve the problem of finding a market. I would, therefore, force my organization to live by its wits rather than to rely on capricious subsidies or noneconomic–based California regulation to fuel my business.

The third point is that my business plan must be a plan for learning, not one for executing a preconceived strategy. Although I will do my best to hit the right market with the right product and the right strategy the first time out, there is a high probability that a better direction will emerge as the business heads toward its initial target. I must therefore plan to be wrong and to learn what is right as fast as possible. [9] I cannot spend all of my resources or all of my organizational credibility on an all-or-nothing first-time bet, as Apple did with its Newton or Hewlett-Packard did with its Kittyhawk. I need to conserve resources to get it right on the second or third try.

These three concepts would constitute the foundation of my marketing strategy.

Potential Markets: Some Speculation

What might emerge as the initial value network for electric vehicles? Again, though it is impossible to predict, it almost surely will be one in which the weaknesses of the electric vehicle will be seen as strengths. One of my students has suggested that the parents of high school students, who buy their children cars for basic transportation to and from school, friends’ homes, and school events, might constitute a fertile market for electric vehicles. [10] Given the option, these parents might see the product simplicity, slow acceleration, and limited driving range of electric vehicles as very desirable attributes for their teenagers’ cars—especially if they were styled with teenagers in mind. Given the right marketing approach, who knows what might happen? An earlier generation met a lot of nice people on their Hondas.

Another possible early market might be taxis or small-parcel delivery vehicles destined for the growing, crowded, noisy, polluted cities of Southeast Asia. Vehicles can sit on Bangkok’s roads all day, mostly idling in traffic jams and never accelerating above 30 miles per hour. Electric motors would not need to run and hence would not drain the battery while idling. The maneuverability and ease of parking of these small vehicles would be additional attractions.

These or similar market ideas, whether or not they ultimately prove viable, are at least consistent with the way disruptive technologies develop and emerge.

How Are Today’s Automobile Companies Marketing Electric Vehicles?

The strategy proposed here for finding and defining the initial market for electric vehicles stands in stark contrast to the marketing approaches being used by today’s major automakers, each of which is struggling to sell electric vehicles into its mainstream market in the time-honored tradition of established firms mishandling disruptive technologies. Consider this statement made in 1995 by William Glaub, Chrysler general sales manager, discussing his company’s planned offering for 1998. [11]

Chrysler Corporation is preparing to provide an electric powered version of our slick new minivan in time for the 1998 model year. After an in-depth study of the option between a purpose-built vehicle and modification of an existing platform, the choice of the minivan to use as an electric powered platform, in retrospect, is an obvious best choice for us. Our experience shows that fleets will likely be the best opportunity to move any number of these vehicles …. The problem that we face is not in creating an attractive package. The new minivan is an attractive package. The problem is that sufficient energy storage capacity is not available on board the vehicle. [12]

To position its offering in the mainstream market, Chrysler has had to pack its minivan with 1,600 pounds of batteries. This, of course, makes its acceleration much slower, its driving range shorter, and its braking distance longer than other available gasoline-powered automobiles. Because of the way Chrysler has positioned its electric vehicle, industry analysts naturally compare it to gasoline-powered minivans, using the metrics paramount in the mainstream value network. At an estimated cost of $100,000 (compared with $22,000 for the gasoline-powered model), nobody in their right mind would consider buying Chrysler’s product.

Chrysler’s marketers are, naturally enough, very pessimistic about their ability to sell any electric minivans in California, despite the government’s mandate that they do so. William Glaub, for example, continued the remarks cited above with the following observation:

Markets are developed with fine products that customers desire to own. No salesman can take marginal product into the marketplace and have any hope of establishing a sustainable consumer base. Consumers will not be forced into a purchase that they do not want. Mandates will not work in a consumer-driven, free market economy. For electric vehicles to find a place in the market, respectable products comparable to today’s gasoline-powered cars must be available. [13]

Chrysler’s conclusion is absolutely correct, given the way its marketers have framed their challenge. [14] Mainstream customers can never use a disruptive technology at its outset.

WHAT SHOULD BE OUR PRODUCT, TECHNOLOGY, AND DISTRIBUTION STRATEGIES?

Product Development for Disruptive Innovations

Guiding my engineers in designing our initial electric vehicle will be a challenge, because of the classic chicken-and-egg problem: Without a market, there is no obvious or reliable source of customer input; without a product that addresses customers’ needs, there can be no market. How can we design a product in such a vacuum? Fortunately, the principles described in this book give us some help.

The most valuable guidance comes from chapter 9, which indicated that the basis of competition will change over a product’s life cycle and that the cycle of evolution itself is driven by the phenomenon of performance oversupply, that is, the condition in which the performance provided by a technology exceeds the actual needs of the market. Historically, performance oversupply opens the door for simpler, less expensive, and more convenient—and almost always disruptive—technologies to enter.

Performance oversupply indeed seems to have occurred in autos. There are practical limits to the size of auto bodies and engines, to the value of going from 0 to 60 in fewer seconds, and to the consumer’s ability to cope with overchoice in available options. Thus, we can safely predict that the basis of product competition and customer choice will shift away from these measures of functionality toward other attributes, such as reliability and convenience. This is borne out by the nature of the most successful entrants into the North American market during the past thirty years; they have succeeded not because they introduced products with superior functionality, but because they competed on the basis of reliability and convenience.

Toyota, for example, entered the U.S. market with its simple, reliable Corona, establishing a low-end market position. Then, consistent with the inexorable attraction to migrate upmarket, Toyota introduced models, such as Camry, Previa, and Lexus, with added features and functionality, creating a vacuum at the low end of the market into which entrants such as Saturn and Hyundai have entered. Saturn’s strategy has been to characterize the customer’s entire experience of buying and owning the vehicle as reliable and convenient, but it, too, judging by recent reports, [15] will soon take its turn moving upmarket, creating a new vacuum at the low end for even simpler, more convenient transportation.

In all likelihood, therefore, the winning design in the first stages of the electric vehicle race will be characterized by simplicity and convenience and will be incubated in an emerging value network in which these attributes are important measures of value. Each of the disruptive technologies studied in this book has been smaller, simpler, and more convenient than preceding products. Each was initially used in a new value network in which simplicity and convenience were valued. This was true for smaller, simpler disk drives; desktop and portable computers; hydraulic backhoes; steel minimills as opposed to integrated mills; insulin-injecting pens as opposed to syringes. [16]

Using these qualities as my guiding principles, I would instruct my design engineers to proceed according to the following three criteria.

First, this vehicle must be simple, reliable, and convenient. That probably means, for example, that figuring out a way to recharge its batteries quickly, using the commonly available electrical service, would be an immutable technological objective.

Second, because no one knows the ultimate market for the product or how it will ultimately be used, we must design a product platform in which feature, function, and styling changes can be made quickly and at low cost. Assuming, for example, that the initial customers for electric vehicles will be parents who buy them for their teenaged children to drive to and from school, friends’ homes, and activities, the first model would have features and styling appropriate and appealing to teenagers. But, although we may target this market first, there’s a high probability that our initial concept will prove wrong. So we’ve got to get the first models done fast and on a shoestring—leaving ample budget to get it right once feedback from the market starts coming in. [17]

Third, we must hit a low price point. Disruptive technologies typically have a lower sticker price per unit than products that are used in the mainstream, even though their cost in use is often higher. What enabled the use of disk drives in desktop computers was not just their smaller size; it was their low unit price, which fit within the overall price points that personal computer makers needed to hit. The price per megabyte of the smaller disk drives was always higher than for the larger drives. Similarly, in excavators the price per excavator was lower for the early hydraulic models than for the established cable-actuated ones, but their total cost per cubic yard of earth moved per hour was much higher. Accordingly, our electric vehicle must have a lower sticker price than the prevailing price for gasoline-powered cars, even if the operating cost per mile driven is higher. Customers have a long track record of paying price premiums for convenience.

Technology Strategy for Disruptive Innovations

Our technology plan cannot call for any technological breakthroughs on the path critical for the project’s success. Historically, disruptive technologies involve no new technologies; rather, they consist of components built around proven technologies and put together in a novel product architecture that offers the customer a set of attributes never before available.

The major automakers engaged in electric vehicle development today all maintain that a breakthrough in battery technology is absolutely essential before electric vehicles can be commercially viable. John R. Wallace, of Ford, for example, has stated the following:

The dilemma is that today’s batteries cannot satisfy these consumer needs. As anybody who is familiar with today’s battery technology will tell you, electric vehicles are not ready for prime time. All of the batteries expected to be available in 1998 fall short of the 100-mile range [required by consumers]. The only solution for the problems of range and cost is improved battery technology. To ensure a commercially successful electric vehicle market, the focus of our resources should be on the development of battery technology. Industry efforts such as those through the U.S. Advanced Battery consortium, along with cooperative efforts among all electric vehicle stakeholders—such as utilities, battery companies, environmentalists, regulators and converters— are the most effective way to ensure the marketability of electric vehicles. [18]

William Glaub, of Chrysler, takes a similar position: “The advanced lead-acid batteries that will be used will provide less than the fuel storage equivalent of two gallons of gasoline. This is like leaving home every day with the ‘low fuel’ light on. In other words, the battery technology is simply not ready.” [19]

The reason these companies view a breakthrough in battery technology as the critical bottleneck to the commercial success of electric vehicles, of course, is that their executives have positioned their minds and their products in the mainstream market. For Chrysler, this means an electric minivan; for Ford, an electric Ranger. Given this position, they must deliver a sustaining technological impact from what is inherently a disruptive technology. They need a breakthrough in battery technology because they made the choice to somehow position electric vehicles as a sustaining technology. A battery breakthrough is not likely to be required of companies whose executives choose to harness or account for the basic laws of disruptive technology by creating a market in which the weaknesses of the electric vehicle become its strengths.

Where will advances in battery technology eventually come from? Looking at the historical record, we can assert the following. The companies that ultimately achieve the advances in battery technology required to power cars for 150-mile cruises (if they are ever developed) will be those that pioneer the creation of a new value network using proven technology and then develop the sustaining technologies needed to carry them upward into more attractive markets. [20] Our finding that well-managed companies are generally upwardly mobile and downwardly immobile, therefore, suggests that the impetus to find the battery breakthrough will indeed be strongest among the disruptive innovators, which will have built a lowend market for electric vehicles before trying to move upmarket toward the larger, more profitable mainstream.

Distribution Strategy for Disruptive Innovations

It has almost always been the case that disruptive products redefine the dominant distribution channels, because dealers’ economics—their models for how to make money—are powerfully shaped by the mainstream value network, just as the manufacturer’s are. Sony’s disruptive introduction of convenient and reliable portable transistorized radios and televisions shifted the dominant retail channel from appliance and department stores with expensive sales support and field service networks (required for sets built with vacuum tubes) to volume-oriented, low-overhead discount retailers. Honda’s disruptive motorbikes were rejected by mainstream motorcycle dealers, forcing the company to create a new channel among sporting goods retailers. We saw, in fact, that a major reason why Harley-Davidson’s small-bike initiative failed is that its dealers rejected it: The image and economics of the small Italian bikes Harley had acquired did not fit its dealer network.

The reason disruptive technologies and new distribution channels frequently go hand-in-hand is, in fact, an economic one. Retailers and distributors tend to have very clear formulas for making money, as the histories of Kresge and Woolworth in chapter 4 showed. Some make money by selling low volumes of big-ticket products at high margins; others make money by selling large volumes at razor-thin margins that cover minimal operating overheads; still others make their money servicing products already sold. Just as disruptive technologies don’t fit the models of established firms for improving profits, they often don’t fit the models of their distributors, either.

My electric vehicle program would, therefore, have as a basic strategic premise the need to find or create new distribution channels for electric vehicles. Unless proven otherwise, I’d bet that mainstream dealers of gasoline-powered automobiles would not view the sorts of disruptive electric vehicles we have in mind as critical to their success.

WHAT ORGANIZATION BEST SERVES DISRUPTIVE INNOVATIONS?

After identifying the electric vehicle as a potentially disruptive technology; setting realistic bearings for finding its potential markets; and establishing strategic parameters for the product’s design, technology, and distribution network, as program manager I would next turn to organization. Creating an organizational context in which this effort can prosper will be crucial, because rational resource allocation processes in established companies consistently deny disruptive technologies the resources they need to survive, regardless of the commitment senior management may ostensibly have made to the program.

Spinning Off an Independent Organization

As we saw in the discussion of resource dependence in chapter 5, established firms that successfully built a strong market position in a disruptive technology were those that spun off from the mainstream company an independent, autonomously operated organization. Quantum, Control Data, IBM’s PC Division, Allen Bradley, and Hewlett-Packard’s desk-jet initiative all succeeded because they created organizations whose survival was predicated upon successful commercialization of the disruptive technology: These firms embedded a dedicated organization squarely within the emerging value network.

As program manager, therefore, I would strongly urge corporate management to create an independent organization to commercialize electric vehicle technology, either an autonomous business unit, such as GM’s Saturn Division or the IBM PC Division, or an independent company whose stock is largely owned by the corporation. In an independent organization, my best employees would be able to focus on electric vehicles without being repeatedly withdrawn from the project to solve pressing problems for customers who pay the present bills. Demands from our own customers, on the other hand, would help us to focus on and lend impetus and excitement to our program.

An independent organization would not only make resource dependence work for us rather than against us, but it would also address the principle that small markets cannot solve the growth or profit problems of large companies. For many years into the future, the market for electric vehicles will be so small that this business is unlikely to contribute significantly to the top or bottom lines of a major automaker’s income statement. Thus, since senior managers at these companies cannot be expected to focus either their priority attention or their priority resources on electric vehicles, the most talented managers and engineers would be unlikely to want to be associated with our project, which must inevitably be seen as a financially insignificant effort: To secure their own futures within the company, they naturally will want to work on mainstream programs, not peripheral ones.

In the early years of this new business, orders are likely to be denominated in hundreds, not tens of thousands. If we are lucky enough to get a few wins, they almost surely will be small ones. In a small, independent organization, these small wins will generate energy and enthusiasm. In the mainstream, they would generate skepticism about whether we should even be in the business. I want my organization’s customers to answer the question of whether we should be in the business. I don’t want to spend my precious managerial energy constantly defending our existence to efficiency analysts in the mainstream.

Innovations are fraught with difficulties and uncertainties. Because of this, I want always to be sure that the projects that I manage are positioned directly on the path everyone believes the organization must take to achieve higher growth and greater profitability. If my program is widely viewed as being on that path, then I have confidence that when the inevitable problems arise, somehow the organization will work with me to muster whatever it takes to solve them and succeed. If, on the other hand, my program is viewed by key people as nonessential to the organization’s growth and profitability, or even worse, is viewed as an idea that might erode profits, then even if the technology is simple, the project will fail.

I can address this challenge in one of two ways: I could convince everyone in the mainstream (in their heads and their guts) that the disruptive technology is profitable, or I could create an organization that is small enough, with an appropriate cost structure, that my program can be viewed as being on its critical path to success. The latter alternative is a far more tractable management challenge.

In a small, independent organization I will more likely be able to create an appropriate attitude toward failure. Our initial stab into the market is not likely to be successful. We will, therefore, need the flexibility to fail, but to fail on a small scale, so that we can try again without having destroyed our credibility. Again, there are two ways to create the proper tolerance toward failure: change the values and culture of the mainstream organization or create a new organization. The problem with asking the mainstream organization to be more tolerant of risk-taking and failure is that, in general, we don’t want to tolerate marketing failure when, as is most often the case, we are investing in sustaining technology change. The mainstream organization is involved in taking sustaining technological innovations into existing markets populated by known customers with researchable needs. Getting it wrong the first time is not an intrinsic part of these processes: Such innovations are amenable to careful planning and coordinated execution.

Finally, I don’t want my organization to have pockets that are too deep. While I don’t want my people to feel pressure to generate significant profit for the mainstream company (this would force us into a fruitless search for an instant large market), I want them to feel constant pressure to find some way—some set of customers somewhere—to make our small organization cash-positive as fast as possible. We need a strong motivation to accelerate through the trials and errors inherent in cultivating a new market.

Of course, the danger in making this unequivocal call for spinning out an independent company is that some managers might apply this remedy indiscriminately, viewing skunkworks and spinoffs as a blanket solution—an industrial-strength aspirin that cures all sorts of problems. In reality, spinning out is an appropriate step only when confronting disruptive innovation. The evidence is very strong that large, mainstream organizations can be extremely creative in developing and implementing sustaining innovations. [21] In other words, the degree of disruptiveness inherent in an innovation provides a fairly clear indication of when a mainstream organization might be capable of succeeding with it and when it might be expected to fail.

In terms of the framework presented in Figure 5.6, the electric vehicle is not only a disruptive innovation, but it involves massive architectural reconfiguration as well, a reconfiguration that must occur not only within the product itself but across the entire value chain. From procurement through distribution, functional groups will have to interface differently than they have ever before. Hence, my project would need to be managed as a heavyweight team in an organization independent of the mainstream company. This organizational structure cannot guarantee the success of our electric vehicle program, but it would at least allow my team to work in an environment that accounts for, rather than fights, the principles of disruptive innovation.

NOTES

1. In 1996, the state government delayed implementation of this requirement until the year 2002, in response to motor vehicle manufacturers’ protests that, given the performance and cost of the vehicles they had been able to design, there was no demand for electric vehicles.

2. An excellent study on this subject is summarized in Dorothy Leonard-Barton, Wellsprings of Knowledge (Boston: Harvard Business School Press, 1995).

3. This information was taken from an October 1994 survey conducted by The Dohring Company and quoted by the Toyota Motor Sales Company at the CARB (California Air Resources Board) Workshop on Electric Vehicle Consumer Marketability held in El Monte, California, on June 28, 1995.

4. This information was provided by Dr. Paul J. Miller, Senior Energy Fellow, W. Alton Jones Foundation, Inc., Charlottesville, Virginia. It was augmented with information from the following sources: Frank Keith, Paul Norton, and Dana Sue Potestio, Electric Vehicles: Promise and Reality (California State Legislative Report [19], No. 10, July, 1994); W. P. Egan, Electric Cars (Can-berra, Australia: Bureau of Transport Economics, 1974); Daniel Sperling, Future Drive: Electric Vehicles and Sustainable Transportation (Washington, D.C.: Island Press, 1995); and William Hamilton, Electric Automobiles (New York: McGraw Hill Company, 1980).

5. Based on the graphs in Figure 10.1, it will take a long time for disruptive electric vehicle technology to become competitive in mainstream markets if future rates of improvement resemble those of the past. The historical rate of performance improvement is, of course, no guarantee that the future rate can be maintained. Technologists very well might run into insurmountable technological barriers. What we can say for sure, however, is that the incentive of disruptive technologists to find some way to engineer around such barriers will be just as strong as the disincentive that established car makers will feel to move down-market. If present rates of improvement continue, however, we would expect the cruising range of electric cars, for example, to intersect with the average range demanded in the mainstream market by 2015, and electric vehicle acceleration to intersect with mainstream demands by 2020. Clearly, as will be discussed below, it will be crucial for electric vehicle innovators to find markets that value the attributes of the technology as it currently is capable, rather than waiting until the technology improves to the point that it can be used in the mainstream market.

6. This statement was made by John R. Wallace, Director of Electric Vehicle Programs, Ford Motor Company, at the CARB Workshop on Electric Vehicle Consumer Marketability held at El Monte, California, on June 28, 1995.

7. It is remarkable how instinctively and consistently good companies try to force innovations toward their existing base of customers, regardless of whether they are sustaining or disruptive in character. We have seen this several times in this book: for example, in mechanical excavators, where Bucyrus Erie tried with its “Hydrohoe” to make hydraulic excavation technology work for mainstream excavation contractors; in motorcycles, where Harley-Davidson tried to launch low-end brand name bikes through its dealer network; and in the electric vehicle case described here, in which Chrysler packed nearly a ton of batteries into a minivan. Charles Ferguson and Charles Morris, in their book Computer Wars, recount a similar story about IBM’s efforts to commercialize Reduced Instruction Set Computing (RISC) microprocessor technology. RISC was invented at IBM, and its inventors built computers with RISC chips that were “screamingly fast.” IBM subsequently spent massive amounts of time, money, and manpower trying to make the RISC chip work in its main line of minicomputers. This required so many design compromises, however, that the program was never successful. Several key members of IBM’s RISC team left in frustration, subsequently playing key roles in establishing the RISC chipmaker MIPS and Hewlett-Packard’s RISC chip business. These efforts were successful because, having accepted the attributes of the product for what they were, they found a market, in engineering workstations, that valued those attributes. IBM failed because it tried to force the technology into a market it had already found. Interestingly, IBM ultimately built a successful business around a RISC-architecture chip when it launched its own engineering workstation. See Charles Ferguson and Charles Morris, Computer Wars (New York: Time Books, 1994).

8. The notion that non-existent markets are best researched through action, rather than through passive observation, is explored in Gary Hamel and C. K. Prahalad, “Corporate Imagination and Expeditionary Marketing,” Harvard Business Review, July-August, 1991, 81–92.

9. The concept that business plans dealing with disruptive innovations should be plans for learning rather than plans for executing a preconceived strategy is taught clearly by Rita G. McGrath and Ian MacMillan in “Discovery-Driven Planning,” Harvard Business Review, July-August, 1995, 44–54.

10. Jeffrey Thoresen Severts, “Managing Innovation: Electric Vehicle Development at Chrysler,” Harvard Business School MBA student paper, 1996. A copy of this paper is available on request from Clayton Christensen, Harvard Business School.

11. Glaub’s remarks were made in the context of the California Air Resources Board mandate that by 1998 all companies selling gasoline-powered vehicles in the state must, in order to sell any cars at all, sell enough electric-powered vehicles to constitute 2 percent of their total vehicle unit sales in the state. As already noted, the state government, in 1996, delayed implementation of that requirement until 2002.

12. This statement was made by William Glaub, General Sales Manager, Field Sales Operations, Chrysler Corporation, at the CARB Workshop on Electric Vehicle Consumer Marketability held in El Monte, California, on June 28, 1995; see p. 5 of the company’s press release about the workshop.

13. Ibid.

14. It is important to note that these statistics for Chrysler’s offering were determined by Chrysler’s efforts to commercialize the disruptive technology; they are not intrinsic to electrically powered vehicles per se. Electric vehicles designed for different, lighter-duty applications, such as one by General Motors, have driving ranges of up to 100 miles. (See Jeffrey Thoresen Severts, “Managing Innovation: Electric Vehicle Development at Chrysler,” Harvard Business School student paper, 1996.)

15. See, for example, Gabriella Stern and Rebecca Blumenstein, “GM Is Expected to Back Proposal for Midsize Version of Saturn Car,” The Wall Street Journal, May 24, 1996, B4.

16. This list of smaller, simpler, more convenient disruptive technologies could be extended to include a host of others whose histories could not be squeezed into this book: tabletop photocopiers; surgical staplers; portable, transistorized radios and televisions; helican scan VCRs; microwave ovens; bubble jet printers. Each of these disruptive technologies has grown to dominate both its initial and its mainstream markets, having begun with simplicity and convenience as their primary value propositions.

17. The notion that it takes time, experimentation, and trial and error to achieve a dominant product design, a very common pattern with disruptive technologies, is discussed later in this chapter.

18. This statement was made by John R. Wallace, of Ford, at the CARB Workshop on Electric Vehicle Consumer Marketability held in El Monte, California, on June 28, 1995; see p. 5 of the company’s press release.

19. Glaub, statement made at the CARB Workshop.

20. Two excellent articles in which the relative roles of product development and incremental versus radical technology development are researched and discussed are Ralph E. Gomory, “From the ‘Ladder of Science’ to the Product Development Cycle,” Harvard Business Review, November-December, 1989, 99–105, and Lowell Steele, “Managers’ Misconceptions About Technology,” Harvard Business Review, 1983, 733–740.

21. In addition to the findings from the disk drive study summarized in chapters 1 and 2 that established firms were able to muster the wherewithal to lead in extraordinarily complex and risky sustaining innovations, there is similar evidence from other industries; see, for example, Marco Iansiti, “Technology Integration: Managing Technological Evolution in a Complex Environment,” Research Policy 24, 1995, 521–542.

CHAPTER ELEVEN

The Dilemmas of Innovation: A Summary

One of the most gratifying outcomes of the research reported in this book is the finding that managing better, working harder, and not making so many dumb mistakes is not the answer to the innovator’s dilemma. This discovery is gratifying because I have never met a group of people who are smarter or work harder or are as right so often as the managers I know. If finding better people than these were the answer to the problems posed by disruptive technologies, the dilemma would indeed be intractable.

We have learned in this book that in their straightforward search for profit and growth, some very capable executives in some extraordinarily successful companies, using the best managerial techniques, have led their firms toward failure. Yet companies must not throw out the capabilities, organizational structures, and decision-making processes that have made them successful in their mainstream markets just because they don’t work in the face of disruptive technological change. The vast majority of the innovation challenges they will face are sustaining in character, and these are just the sorts of innovations that these capabilities are designed to tackle. Managers of these companies simply need to recognize that these capabilities, cultures, and practices are valuable only in certain conditions.

I have found that many of life’s most useful insights are often quite simple. In retrospect, many of the findings of this book fit that mold: Initially they seemed somewhat counterintuitive, but as I came to understand them, the insights were revealed as simple and sensible. I review them here, in the hope that they will prove useful to those readers who may be wrestling with the innovator’s dilemmas.

First, the pace of progress that markets demand or can absorb may be different from the progress offered by technology. This means that products that do not appear to be useful to our customers today (that is, disruptive technologies) may squarely address their needs tomorrow. Recognizing this possibility, we cannot expect our customers to lead us toward innovations that they do not now need. Therefore, while keeping close to our customers is an important management paradigm for handling sustaining innovations, it may provide misleading data for handling disruptive ones. Trajectory maps can help to analyze conditions and to reveal which situation a company faces.

Second, managing innovation mirrors the resource allocation process: Innovation proposals that get the funding and manpower they require may succeed; those given lower priority, whether formally or de facto, will starve for lack of resources and have little chance of success. One major reason for the difficulty of managing innovation is the complexity of managing the resource allocation process. A company’s executives may seem to make resource allocation decisions, but the implementation of those decisions is in the hands of a staff whose wisdom and intuition have been forged in the company’s mainstream value network: They understand what the company should do to improve profitability. Keeping a company successful requires that employees continue to hone and exercise that wisdom and intuition. This means, however, that until other alternatives that appear to be financially more attractive have disappeared or been eliminated, managers will find it extraordinarily difficult to keep resources focused on the pursuit of a disruptive technology.

Third, just as there is a resource allocation side to every innovation problem, matching the market to the technology is another. Successful companies have a practiced capability in taking sustaining technologies to market, routinely giving their customers more and better versions of what they say they want. This is a valued capability for handling sustaining innovation, but it will not serve the purpose when handling disruptive technologies. If, as most successful companies try to do, a company stretches or forces a disruptive technology to fit the needs of current, mainstream customers—as we saw happen in the disk drive, excavator, and electric vehicle industries—it is almost sure to fail. Historically, the more successful approach has been to find a new market that values the current characteristics of the disruptive technology. Disruptive technology should be framed as a marketing challenge, not a technological one.

Fourth, the capabilities of most organizations are far more specialized and context-specific than most managers are inclined to believe. This is because capabilities are forged within value networks. Hence, organizations have capabilities to take certain new technologies into certain markets. They have disabilities in taking technology to market in other ways. Organizations have the capability to tolerate failure along some dimensions, and an incapacity to tolerate other types of failure. They have the capability to make money when gross margins are at one level, and an inability to make money when margins are at another. They may have the capability to manufacture profitably at particular ranges of volume and order size, and be unable to make money with different volumes or sizes of customers. Typically, their product development cycle times and the steepness of the ramp to production that they can negotiate are set in the context of their value network.

All of these capabilities—of organizations and of individuals—are defined and refined by the types of problems tackled in the past, the nature of which has also been shaped by the characteristics of the value networks in which the organizations and individuals have historically competed. Very often, the new markets enabled by disruptive technologies require very different capabilities along each of these dimensions.

Fifth, in many instances, the information required to make large and decisive investments in the face of disruptive technology simply does not exist. It needs to be created through fast, inexpensive, and flexible forays into the market and the product. The risk is very high that any particular idea about the product attributes or market applications of a disruptive technology may not prove to be viable. Failure and interative learning are, therefore, intrinsic to the search for success with a disruptive technology. Successful organizations, which ought not and cannot tolerate failure in sustaining innovations, find it difficult simultaneously to tolerate failure in disruptive ones.

Although the mortality rate for ideas about disruptive technologies is high, the overall business of creating new markets for disruptive technologies need not be inordinately risky. Managers who don’t bet the farm on their first idea, who leave room to try, fail, learn quickly, and try again, can succeed at developing the understanding of customers, markets, and technology needed to commercialize disruptive innovations.

Sixth, it is not wise to adopt a blanket technology strategy to be always a leader or always a follower. Companies need to take distinctly different postures depending on whether they are addressing a disruptive or a sustaining technology. Disruptive innovations entail significant first-mover advantages: Leadership is important. Sustaining situations, however, very often do not. The evidence is quite strong that companies whose strategy is to extend the performance of conventional technologies through consistent incremental improvements do about as well as companies whose strategy is to take big, industry-leading technological leaps.

Seventh, and last, the research summarized in this book suggests that there are powerful barriers to entry and mobility that differ significantly from the types defined and historically focused on by economists. Economists have extensively described barriers to entry and mobility and how they work. A characteristic of almost all of these formulations, however, is that they relate to things, such as assets or resources, that are difficult to obtain or replicate. [1] Perhaps the most powerful protection that small entrant firms enjoy as they build the emerging markets for disruptive technologies is that they are doing something that it simply does not make sense for the established leaders to do. Despite their endowments in technology, brand names, manufacturing prowess, management experience, distribution muscle, and just plain cash, successful companies populated by good managers have a genuinely hard time doing what does not fit their model for how to make money. Because disruptive technologies rarely make sense during the years when investing in them is most important, conventional managerial wisdom at established firms constitutes an entry and mobility barrier that entrepreneurs and investors can bank on. It is powerful and pervasive.

Established companies can surmount this barrier, however. The dilemmas posed to innovators by the conflicting demands of sustaining and disruptive technologies can be resolved. Managers must first understand what these intrinsic conflicts are. They then need to create a context in which each organization’s market position, economic structure, developmental capabilities, and values are sufficiently aligned with the power of their customers that they assist, rather than impede, the very different work of sustaining and disruptive innovators. I hope this book helps them in this effort.

NOTES

1. By things I mean barriers such as proprietary technology; ownership of expensive manufacturing plants with large minimum efficient manufacturing scales; pre-emption of the most powerful distributors in major markets; exclusive control of key raw materials or unique human resources; the credibility and reputation that comes from strong brand names; cumulative production experience and/or the presence of steep economies of scale; and so on. The seminal work on entry barriers from an economist’s perspective is Joseph Bain, Barriers to New Competition (Cambridge, MA: Harvard University Press, 1956); see also Richard Caves and Michael Porter, “From Entry Barriers to Mobility Barriers,” Quarterly Journal of Economics (91), May, 1977, 241–261.

The Innovator’s Dilemma Book Group Guide

The summary and questions in this guide are designed to stimulate thinking and discussion about The Innovator’s Dilemma, how its findings are manifest in many industries today, and the implications of those findings for the future.

Thesis of the Book

In The Innovator’s Dilemma, Professor Clayton Christensen asks the question: Why do well-managed companies fail? He concludes that they often fail because the very management practices that have allowed them to become industry leaders also make it extremely difficult for them to develop the disruptive technologies that ultimately steal away their markets.

Well-managed companies are excellent at developing the sustaining technologies that improve the performance of their products in the ways that matter to their customers. This is because their management practices are biased toward:

Listening to customers

Investing aggressively in technologies that give those customers what they say they want

Seeking higher margins

Targeting larger markets rather than smaller ones

Disruptive technologies, however, are distinctly different from sustaining technologies. Disruptive technologies change the value proposition in a market. When they first appear, they almost always offer lower performance in terms of the attributes that mainstream customers care about. In computer disk drives, for example, disruptive technologies have always had less capacity than the old technologies. But disruptive technologies have other attributes that a few fringe (generally new) customers value. They are typically cheaper, smaller, simpler, and frequently more convenient to use. Therefore, they open new markets. Further, because with experience and sufficient investment, the developers of disruptive technologies will always improve their products’ performance, they eventually are able to take over the older markets. This is because they are able to deliver sufficient performance on the old attributers, and they add some new ones.

The Innovator’s Dilemma describes both the processes through which disruptive technologies supplant older technologies and the powerful forces within well-managed companies that make them unlikely to develop those technologies themselves. Professor Christensen offers a framework of four Principles of Disruptive Technology to explain why the management practices that are the most productive for exploiting existing technologies are antiproductive when it comes to developing disruptive ones. And, finally, he suggests ways that managers can harness these principles so that their companies can become more effective at developing for themselves the new technologies that are going to capture their markets in the future.

Principles of Disruptive Technology

1. Companies Depend on Customers and Investors for Resources In order to survive, companies must provide customers and investors with the products, services, and profits that they require. The highest performing companies, therefore, have well-developed systems for killing ideas that their customers don’t want. As a result, these companies find it very difficult to invest adequate resources in disruptive technologies—lower-margin opportunities that their customers don’t want—until their customers want them. And by then, it is too late.

2. Small Markets Don’t Solve the Growth Needs of Large Companies To maintain their share prices and create internal opportunities for their employees, successful companies need to grow. It isn’t necessary that they increase their growth rates, but they must maintain them. And as they get larger, they need increasing amounts of new revenue just to maintain the same growth rate. Therefore, it becomes progressively more difficult for them to enter the newer, smaller markets that are destined to become the large markets of the future. To maintain their growth rates, they must focus on large markets.

3. Markets That Don’t Exist Can’t Be Analyzed Sound market research and good planning followed by execution according to plan are the hallmarks of good management. But companies whose investment processes demand quantification of market size and financial returns before they can enter a market get paralyzed when faced with disruptive technologies because they demand data on markets that don’t yet exist.

4. Technology Supply May Not Equal Market Demand Although disruptive technologies can initially be used only in small markets, they eventually become competitive in mainstream markets. This is because the pace of technological progress often exceeds the rate of improvement that mainstream customers want or can absorb. As a result, the products that are currently in the mainstream eventually will overshoot the performance that mainstream markets demand, while the disruptive technologies that underperform relative to customer expectations in the mainstream market today may become directly competitive tomorrow. Once two or more products are offering adequate performance, customers will find other criteria for choosing. These criteria tend to move toward reliability, convenience, and price, all of which are areas in which the newer technologies often have advantages.

A big mistake that managers make in dealing with new technologies is that they try to fight or overcome the Principles of Disruptive Technology. Applying the traditional management practices that lead to success with sustaining technologies always leads to failure with disruptive technologies, says Professor Christensen. The more productive route, which often leads to success, he says, is to understand the natural laws that apply to disruptive technologies and to use them to create new markets and new products. Only by recognizing the dynamics of how disruptive technologies develop can managers respond effectively to the opportunities that they present.

Specifically, he advises managers faced with disruptive technologies to:

1. Give responsibility for disruptive technologies to organizations whose customers need them so that resources will flow to them.

2. Set up a separate organization small enough to get excited by small gains.

3. Plan for failure. Don’t bet all your resources on being right the first time. Think of your initial efforts at commercializing a disruptive technology as learning opportunities. Make revisions as you gather data.

4. Don’t count on breakthroughs. Move ahead early and find the market for the current attributes of the technology. You will find it outside the current mainstream market. You will also find that the attributes that make disruptive technologies unattractive to mainstream markets are the attributes on which the new markets will be built.

Questions for Discussion

1. The characteristics of a disruptive technology are:
They are simpler and cheaper and lower performing.

They generally promise lower margins, not higher profits.

Leading firms’ most profitable customers generally can’t use and don’t want them.

They are first commercialized in emerging or insignificant markets.

The Innovator’s Dilemma discusses disruptive innovations in the disk-drive, excavator, steel, and auto industries. Looking back through history, can you identify some disruptive technologies that eventually replaced older products and industries? Can you think of others that are emerging today, maybe even ones that could threaten your business?

2. There is a tendency in all markets for companies to move upmarket toward more complicated products with higher prices. Why is it difficult for companies to enter markets for simpler, cheaper products? Can you think of companies that have upscaled themselves out of business? How might they have avoided that?

3. The same tendency for companies to move upmarket that can be fatal for established companies also accounts for the eventual development of emerging markets into mainstream markets. Besides the examples in the book, can you think of companies that have upscaled themselves to success?

4. In attempting to commercialize a disruptive technology, why is it important to begin investing on the assumption that your expectations will be wrong? Besides the motorcycle, excavator, and disk-drive examples in the book, can you think of other examples in which a company began marketing a product for one application but the big market turned out to be for another application?

5. One of the hallmarks of disruptive technologies is that initially they underperform the current technology on the attributes that matter most to mainstream customers. The companies that succeed in commercializing them, therefore, must find different customers for whom the new technology’s attributes are most valuable. Can you think of any markets that are emerging today based on attributes or qualities that seemed unimportant to the mainstream markets when they were introduced? What older, mainstream products or companies are threatened?

6. When two or more products meet the minimum specifications for the functionality of a product, customers begin to look for other deciding factors. According to a Windermere Associates study cited in the book, the progression usually is from functionality to reliability to convenience to price. What are some current markets that have recently moved one or more steps along this progression?

7. Most people think that senior executives make the important decisions about where a company will go and how it will invest its resources, but the real power lies with the people deeper in the organization who decide which proposals will be presented to senior management. What are the corporate factors that lead midlevel employees to ignore or kill disruptive technologies? Should well-managed companies change these practices and policies?

8. What are the personal career considerations that lead ambitious employees in large corporations to ignore or kill disruptive technologies? Should well-managed companies change the policies that encourage employees to think this way?

9. What do the findings in this book suggest about how companies will be organized in the future? Should large organizations with structures created around functionalities redesign themselves into interconnected teams, as some management theorists currently believe? Or, recognizing that different technologies and different markets have differing needs, should they try to have distinct organizational structures and management practices for different circumstances? Is this realistically possible?

10. The CEO of a disk-drive maker is quoted in chapter 4 as saying that “We got way ahead of the market” in explaining why his company failed to commercialize a 1.8-inch disk drive that it had developed. At the time, however, there was a burgeoning market for 1.8-inch drives among new users that his company hadn’t discovered. Professor Christensen argues that “disruptive technology should be framed as a marketing challenge, not a technological one.” Do you think there is a market somewhere for all technologies? If not, how would you as a manager go about figuring out which technologies to shelve and which ones to pursue aggressively?

11. Similarly, Professor Christensen argues that companies should not wait for new breakthroughs to improve a technology’s performance. Instead, they need to find customers who value the very attributes that others consider to be shortcomings. As a manager, how do you decide when a technology—or idea—needs more development and when it’s time to aggressively put it on the market?

12. The primary thesis of The Innovator’s Dilemma is that the management practices that allow companies to be leaders in mainstream markets are the same practices that cause them to miss the opportunities offered by disruptive technologies. In other words, well-managed companies fail because they are well managed. Do you think that the definition of what constitutes “good management” is changing? In the future, will listening to customers, investing aggressively in producing what those customers say they want, and carefully analyzing markets become “bad management”? What kind of system might combine the best of both worlds?

About the Author

Clayton M. Christensen is an associate professor of business administration at the Harvard Business School, where he holds a joint appointment with the Technology and Operations Management and General Management faculty groups. His research and writing focus on the management of technological innovation, the problems in finding new markets for new technologies, and the identification and development of organizational capabilities. Prior to joining the Harvard Business School faculty, Professor Christensen served as chairman and president of Ceramics Process Systems Corporation, a firm he co-founded in 1984 with several MIT professors. He also served as a White House Fellow and as a member of the staff of the Boston Consulting Group. He is the author or co-author of numerous articles in journals such as Research Policy, Strategic Management Journal, Industrial and Corporate Change, the Business History Review, and the Harvard Business Review.

The Innovator's Solution:

Creating and Sustaining Successful Growth

Clayton M. Christensen

Michael E. Raynor

Harvard Business School Press

Boston, Massachusetts

Copyright

Copyright 2003 Harvard Business School Publishing Corporation

All rights reserved.

No part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording, or otherwise), without the prior permission of the publisher. Requests for permission should be directed to permissions@hbsp.harvard.edu, or mailed to Permissions, Harvard Business School Publishing, 60 Harvard Way, Boston, Massachusetts 02163.

First eBook Edition: January 2004

ISBN: 978-1-57851-852-4

Contents

Copyright

In Gratitude

1. The Growth Imperative

2. How Can We Beat Our Most Powerful Competitors?

3. What Products Will Customers Want to Buy?

4. Who Are The Best Customers for Our Products?

5. Getting The Scope of the Business Right

6. How to Avoid Commoditization

7. Is Your Organization Capable of Disruptive Growth?

8. Managing the Strategy Development Process

9. There Is Good Money and There Is Bad Money

10. The Role of Senior Executives in Leading New Growth

Epilogue: Passing the Baton

About The Authors

IN GRATITUDE

I have spent much of the past decade puzzling over two questions. The first: It is easy to explain why poorly run companies fail; but many of history’s most successful and best-run firms have lost their positions of leadership, too. Why is it so hard to sustain success? The Innovator’s Dilemma summarized what I learned about this puzzle. It’s not just management mistakes that cause failure. Certain practices that are essential to a company’s success—like catering to the needs of your best customers and focusing investments where profitability is most attractive—can cause failure too.

The second centered on the opportunity in the dilemma: If I wanted to start a company that could become significant and successful and ultimately topple the firms that now lead an industry, how could I do it? If indeed there are predictable reasons why businesses stumble, we might then help managers avoid those causes of failure and help them make decisions that predictably lead to successful growth. This is The Innovator’s Solution.

The challenge of this research quickly outstripped my abilities; and I have relied upon some extraordinary people to help me complete it. Michael Raynor, who has tutored me from the day he arrived as a doctoral student at Harvard, has been an exceptional colleague. To describe Michael’s integrated grasp of arts, letters, philosophical discourse, and history as “incisive” would understate his intellect. Confident that I could expose and rectify the gaps in my evidence and logic by examining my rough ideas through the lenses of the varied academic disciplines that Michael’s mind has mastered, I asked him to join me as coauthor. Michael has balanced this work with his duties as a husband, father, and director of research at Deloitte Consulting, all the while shuttling between Toronto and Boston. I deeply appreciate his selfless, humble, and persistent hammering to get these ideas shaped right. He has become a great friend.

Scott Anthony, Mark Johnson, and Matt Eyring each have forsaken or postponed far more lucrative careers to join me in this effort. As my primary research associate, Scott has managed our staff of researchers, written crucial case studies, helped me teach and explain complicated concepts, and reviewed and refined every draft of this book. Mark and Matt, through our firm Innosight, have translated these concepts into practical tools and processes to help managers build businesses that will be significant and successful—and in so doing have taught me how our findings can interface with managerial reality. My office manager, Christine Gaze, and research partners Sally Aaron, Mick Bass, Will Clark, Jeremy Dann, Tara Donovan, Taddy Hall, John Kenagy, Michael and Amy Overdorf, Nate Redmond, Erik Roth, and David Sundahl each have helped me stay atop the huge volume of interesting ideas, opportunities for inquiry and authorship, and requests for assistance that flow into and out of my office. They have painstakingly helped us get the data, logic, and language right for every purpose.

I have a profound debt to Harvard Business School and my colleagues here. The insightful research of Professors Clark Gilbert and Steve Spear has been exceptionally valuable. Other faculty, including Kent Bowen, Joseph Bower, Hank Chesbrough, Kim Clark, Tom Eisenmann, Lee Fleming, Frances Frei, Alan MacCormack, Gary Pisano, Richard Rosenbloom, Bill Sahlman, Don Sull, Richard Tedlow, Stefan Thomke, Michael Tushman, and Steve Wheelwright have also shaped what we have come to understand—as have Professors Rebecca Henderson, Paul Carlile, James Utterback, and Eric von Hippel of MIT, Robert Burgelman of Stanford, and Stuart Hart of UNC. The extraordinary benefit of Harvard’s case method of teaching is that the teachers can carry issues they don’t understand into the classroom, ask questions of the students in the context of a case, and then listen to and learn from some of the brightest people in the world. I express my love and my gratitude to my students for preparing so hard every day to teach each other and their teacher in so many ways. It is a learning system without parallel.

I also have sought the advice of some the most capable business thinkers and executives in the world. Matt Verlinden and Steve King of Integral, Geoffrey Moore of the Chasm Group, Tony Ulwick of Strategyn, Crawford del Prete of IDC, Andy Grove of Intel, Ken Dobler of Johnson & Johnson, Dan Carp and Willy Shih of Kodak, Dennis Hunter of Applied Materials, Michael Putz of Cisco, Chris Rowen of Tensilica, Bill George of Medtronic, Meir Weinstein of EMC, Michael Packer and Kelly Martin of Merrill Lynch, Mark Ross of Cypress Semiconductor, and Ron Dollens, Ginger Graham, and Rod Nash of Guidant have all tutored me.

I owe the deepest debt to my family. My children, Matthew, Ann, Michael, Spencer, and Katie, each have discussed, used, and bettered my understanding through their own work and schooling. My wife, Christine, is the smartest person I have known. Her standards for clarity and completeness are uncompromising, and her language and intellect are imprinted on every concept in this book—which is remarkable, given that much of her advice came at the end of long days that were filled with the pressures of motherhood and her selfless service to others. She brings love and light to me and everyone she meets, every day.

Academia for some can be an enterprise of solitary pursuits. I am blessed in contrast to work within a community of selfless, humble, smart, and intellectually courageous men and women who as a group have made the substantial progress that is summarized in this book. I am grateful to have been able to play my role in this effort.

Clayton M. Christensen

Boston, Massachusetts

Like Clayton, I offer my thanks to the many people who have shared their experiences and talents with us. Without their willingness to be part of our learning processes, neither this book nor our respective careers would be possible.

The latitude I have enjoyed within Deloitte Research is, as far as I know, unparalleled in the consulting industry. The firm has gone beyond simply tolerating my idiosyncratic undertakings—of which this book is certainly one—to actively encouraging them, making possible the exploration of a different way to create and share knowledge. I am especially grateful to Ann Baxter, the head of Deloitte Research, and Larry Scott, global leader of Deloitte Consulting’s Strategy and Operations practice, for making it possible for the ball to start rolling, and to innumerable others in Deloitte Consulting and Deloitte & Touche for their enthusiasm and support that has maintained and accelerated that momentum.

These few sentences are one of the few opportunities I shall have to acknowledge for posterity my intellectual debt to Clayton. My first contact with Clayton’s work was as a doctoral student at Harvard Business School. In his writings I found a rare combination of theoretical elegance, intellectual rigor, creative data analysis, and managerial relevance. When I read The Innovator’s Dilemma, I, like so many others, felt that a mote had been removed from my eye, and that what I had previously seen only dimly, if at all, was suddenly brought into the light. Clayton’s work has become for me a standard to which I continue to aspire, and so it is truly a privilege to have had the opportunity to contribute to and be part of the continued development and elaboration of those ideas. During the course of my doctoral studies, I was lucky enough to have Clayton as a teacher. In the course of our work together on this book, he has become a mentor, colleague, and friend.

I save for last the one to whom I owe the most: my wife, Annabel. Her love and support have been unconditional through the years of doctoral studies, through the inevitable absences attendant to a career in consulting, through my preoccupation with this and other projects (but mostly this one!), and through the various other challenges resulting from the somewhat oddball path I have chosen. Without her, I could not pursue my dreams. Without her, and without our daughter, Charlotte, I wouldn’t have any worth pursuing.

Michael E. Raynor

Mississauga, Ontario

CHAPTER ONE

THE GROWTH IMPERATIVE

Financial markets relentlessly pressure executives to grow and keep growing faster and faster. Is it possible to succeed with this mandate? Don’t the innovations that can satisfy investors’ demands for growth require taking risks that are unacceptable to those same investors? Is there a way out of this dilemma?

This is a book about how to create new growth in business. Growth is important because companies create shareholder value through profitable growth. Yet there is powerful evidence that once a company’s core business has matured, the pursuit of new platforms for growth entails daunting risk. Roughly one company in ten is able to sustain the kind of growth that translates into an above-average increase in shareholder returns over more than a few years.[1] Too often the very attempt to grow causes the entire corporation to crash. Consequently, most executives are in a no-win situation: equity markets demand that they grow, but it’s hard to know how to grow. Pursuing growth the wrong way can be worse than no growth at all.

Consider AT&T. In the wake of the government-mandated divestiture of its local telephony services in 1984, AT&T became primarily a long distance telecommunications services provider. The break-up agreement freed the company to invest in new businesses, so management almost immediately began seeking avenues for growth and the shareholder value that growth creates.

The first such attempt arose from a widely shared view that computer systems and telephone networks were going to converge. AT&T first tried to build its own computer division in order to position itself at that intersection, but was able to do no better than annual losses of $200 million. Rather than retreat from a business that had proved to be unassailable from the outside, the company decided in 1991 to bet bigger still, acquiring NCR, at the time the world’s fifth-largest computer maker, for $7.4 billion. That proved only to be a down payment: AT&T lost another $2 billion trying to make the acquisition work. AT&T finally abandoned this growth vision in 1996, selling NCR for $3.4 billion, about a third of what it had invested in the opportunity.

But the company had to grow. So even as the NCR acquisition was failing, AT&T was seeking growth opportunities in technologies closer to its core. In light of the success of the wireless services that several of its spun-off local telephone companies had achieved, in 1994 the company bought McCaw Cellular, at the time the largest national wireless carrier in the United States, for $11.6 billion, eventually spending $15 billion in total on its own wireless business. When Wall Street analysts subsequently complained that they were unable to properly value the combined higher-growth wireless business within the lower-growth wireline company, AT&T decided to create a separately traded stock for the wireless business in 2000. This valued the business at $10.6 billion, about two-thirds of the investment AT&T had made in the venture.

But that move left the AT&T wireline stock right where it had started, and the company had to grow. So in 1998 it embarked upon a strategy to enter and reinvent the local telephony business with broadband technology. Acquiring TCI and MediaOne for a combined price of $112 billion made AT&T Broadband the largest cable operator in the United States. Then, more quickly than anyone could have foreseen, the difficulties in implementation and integration proved insurmountable. In 2000, AT&T agreed to sell its cable assets to Com-cast for $72 billion.[2]

In the space of a little over ten years, AT&T had wasted about $50 billion and destroyed even more in shareholder value—all in the hope of creating shareholder value through growth.

The bad news is that AT&T is not a special case. Consider Cabot Corporation, the world’s major producer of carbon black, a compound that imparts to products such as tires many of their most important properties. This business has long been very strong, but the core markets haven’t grown rapidly. To create the growth that builds shareholder value, Cabot’s executives in the early 1980s launched several aggressive growth initiatives in advanced materials, acquiring a set of promising specialty metals and high-tech ceramics businesses. These constituted operating platforms into which the company would infuse new process and materials technology that was emerging from its own research laboratories and work it had sponsored at MIT.

Wall Street greeted these investments to accelerate Cabot’s growth trajectory with enthusiasm and drove the company’s share price to triple the level at which it had languished prior to these initiatives. But as the losses created by Cabot’s investments in these businesses began to drag the entire corporation’s earnings down, Wall Street hammered the stock. While the overall market appreciated at a robust rate between 1988 and 1991, Cabot’s shares dropped by more than half. In the early 1990s, feeling pressure to boost earnings, Cabot’s board brought in new management whose mandate was to shut down the new businesses and refocus on the core. As Cabot’s profitability rebounded, Wall Street enthusiastically doubled the company’s share price. The problem, of course, was that this turnaround left the new management team no better off than their predecessors: desperately seeking growth opportunities for mature businesses with limited prospects.[3]

We could cite many cases of companies’ similar attempts to create new-growth platforms after the core business had matured. They follow an all-too-similar pattern. When the core business approaches maturity and investors demand new growth, executives develop seemingly sensible strategies to generate it. Although they invest aggressively, their plans fail to create the needed growth fast enough; investors hammer the stock; management is sacked; and Wall Street rewards the new executive team for simply restoring the status quo ante: a profitable but low-growth core business.[4]

Even expanding firms face a variant of the growth imperative. No matter how fast the growth treadmill is going, it is not fast enough. The reason: Investors have a pesky tendency to discount into the present value of a company’s stock price whatever rate of growth they foresee the company achieving. Thus, even if a company’s core business is growing vigorously, the only way its managers can deliver a rate of return to shareholders in the future that exceeds the risk-adjusted market average is to grow faster than shareholders expect. Changes in stock prices are driven not by simply the direction of growth, but largely by unexpected changes in the rate of change in a company’s earnings and cash flows. Hence, one company that is projected to grow at 5 percent and in fact keeps growing at 5 percent and another company that is projected to grow at 25 percent and delivers 25 percent growth will both produce for future investors a market-average risk-adjusted rate of return in the future. [5] A company must deliver the rate of growth that the market is projecting just to keep its stock price from falling. It must exceed the consensus forecast rate of growth in order to boost its share price. This is a heavy, omnipresent burden on every executive who is sensitive to enhancing shareholder value. [6]

It’s actually even harder than this. That canny horde of investors not only discounts the expected rate of growth of a company’s existing businesses into the present value of its stock price, but also discounts the growth from new, yet-to-be-established lines of business that they expect the management team to be able to create in the future. The magnitude of the market’s bet on growth from unknown sources is, in general, based on the company’s track record. If the market has been impressed with a company’s historical ability to leverage its strengths to generate new lines of business, then the component of its stock price based on growth from unknown sources will be large. If a company’s past efforts to create new-growth businesses have not borne fruit, then its market valuation will be dominated by the projected cash flow from known, established businesses.

Table 1-1 presents one consulting firm’s analysis of the share prices of a select number of Fortune 500 companies, showing the proportion of each firm’s share price on August 21, 2002, that was attributable to cash generated by existing assets, versus cash that investors expected to be generated by new investments.[7] Of this sample, the company that was on the hook at that time to generate the largest percentage of its total growth from future investments was Dell Computer. Only 22 percent of its share price of $28.05 was justified by cash thrown off by the company’s present assets, whereas 78 percent of Dell’s valuation reflected investors’ confidence that the company would be able to invest in new assets that would generate whopping amounts of cash. Sixty-six percent of Johnson & Johnson’s market valuation and 37 percent of Home Depot’s valuation were grounded in expectations of growth from yet-to-be-made investments. These companies were on the hook for big numbers. On the other hand, only 5 percent of General Motors’s stock price on that date was predicated on future investments. Although that’s a chilling reflection of the track record of GM’s former management in creating new-growth businesses, it means that if the present management team does a better job, the company’s share price could respond handsomely.

Probably the most daunting challenge in delivering growth is that if you fail once to deliver it, the odds that you ever will be able to deliver in the future are very low. This is the conclusion of a remarkable study, Stall Points, that the Corporate Strategy Board published in 1998.[8] It examined the 172 companies that had spent time on Fortune’s list of the 50 largest companies between 1955 and 1995. Only 5 percent of these companies were able to sustain a real, inflation-adjusted growth rate of more than 6 percent across their entire tenure in this group. The other 95 percent reached a point at which their growth simply stalled, to rates at or below the rate of growth of the gross national product (GNP). Stalling is understandable, given our expectations that all growth markets become saturated and mature. What is scary is that of all these companies whose growth had stalled, only 4 percent were able to successfully reignite their growth even to a rate of 1 percent above GNP growth. Once growth had stalled, in other words, it proved nearly impossible to restart it.

The equity markets brutally punished those companies that allowed their growth to stall. Twenty-eight percent of them lost more than 75 percent of their market capitalization. Forty-one percent of the companies saw their market value drop by between 50 and 75 percent when they stalled, and 26 percent of the firms lost between 25 and 50 percent of their value. The remaining 5 percent lost less than 25 percent of their market capitalization. This, of course, increased pressure on management to regenerate growth, and to do so quickly—which made it all the more difficult to succeed. Managers cannot escape the mandate to grow.[9] Yet the odds of success, if history is any guide, are frighteningly low.

TABLE 1 - 1

Portion of Selected Firms’ Market Value That Was Based on Expected Returns from New Investments on August 21, 2002

Percent of Valuation

That Was Based on:

Fortune

500 rank

Company Name

Share

Price

New Investments

Existing Assets

53

Dell Computer

$28.05

78%

22%

47

Johnson & Johnson

$56.20

66%

34%

35

Procter & Gamble

$90.76

62%

38%

6

General Electric

$32.80

60%

40%

77

Lockheed Martin

$62.16

59%

41%

1

Wal-Mart Stores

$53.88

50%

50%

65

Intel

$19.15

49%

51%

49

Pfizer

$34.92

48%

52%

9

IBM

$81.93

46%

54%

24

Merck

$53.80

44%

56%

92

Cisco Systems

$15.00

42%

58%

18

Home Depot

$33.86

37%

63%

16

Boeing

$28.36

30%

70%

11

Verizon

$31.80

21%

79%

22

Kroger

$22.20

13%

87%

32

Sears Roebuck

$36.94

8%

92%

37

AOL Time Warner

$35.00

8%

92%

3

General Motors

$49.40

5%

95%

81

Phillips Petroleum

$35.00

3%

97%

Source:  CSFB/HOLT; Deloitte Consuting analysis.

Is Innovation a Black Box?

Why is achieving and sustaining growth so hard? One popular answer is to blame managers for failing to generate new growth—implying that more capable and prescient people could have succeeded. The solve-the-problem-by-finding-a-better-manager approach might have credence if failures to restart growth were isolated events. Study after study, however, concludes that about 90 percent of all publicly traded companies have proved themselves unable to sustain for more than a few years a growth trajectory that creates above-average shareholder returns.[10] Unless we believe that the pool of management talent in established firms is like some perverse Lake Wobegon, where 90 percent of managers are below average, there has to be a more fundamental explanation for why the vast majority of good managers has not been able to crack the problem of sustaining growth.

A second common explanation for once-thriving companies’ inability to sustain growth is that their managers become risk averse. But the facts refute this explanation, too. Corporate executives often bet the future of billion-dollar enterprises on an innovation. IBM bet its farm on the System 360 mainframe computer, and won. DuPont spent $400 million on a plant to make Kevlar tire cord, and lost. Corning put billions on the line to build its optical fiber business, and won big. More recently it sold off many of its other businesses in order to invest more in optical telecommunications, and has been bludgeoned. Many of the executives who have been unable to create sustained corporate growth have evidenced a strong stomach for risk.

There is a third, widely accepted explanation for why growth seems so hard to achieve repeatedly and well, which we also believe does not hold water: Creating new-growth businesses is simply unpredictable. Many believe that the odds of success are just that—odds—and that they are low. Many of the most insightful management thinkers have accepted the assumption that creating growth is risky and unpredictable, and have therefore used their talents to help executives manage this unpredictability. Recommendations about letting a thousand flowers bloom, bringing Silicon Valley inside, failing fast, and accelerating selection pressures are all ways to deal with the allegedly irreducible unpredictability of successful innovation.[11] The structure of the venture capital industry is in fact a testament to the pervasive belief that we cannot predict which new-growth businesses will succeed. The industry maxim says that for every ten investments—all made in the belief they would succeed—two will fail outright, six will survive as the walking wounded, and two will hit the home runs on which the success of the entire portfolio turns. Because of this belief that the process of business creation is unfathomable, few have sought to pry open the black box to study the process by which new-growth businesses are created.

We do not accept that most companies’ growth stalls because the odds of success for the next growth business they launch are impossibly low. The historical results may indeed seem random, but we believe it is because the process for creating new-growth businesses has not yet been well understood. In this book we intend to pry open the black box and study the processes that lead to success or failure in new-growth businesses.

To illustrate why it is important to understand the processes that create those results, consider these strings of numbers:

1, 2, 3, 4, 5, 6

75, 28, 41, 26, 38, 64

Which of these would you say is random, and which is predictable? The first string looks predictable: The next two numbers should be 7 and 8. But what if we told you that it was actually the winning numbers for a lottery, drawn from a drum of tumbling balls, whereas the second is the sequence of state and county roads one would follow on a scenic tour of the northern rim of Michigan’s Upper Peninsula on the way from Sault Ste. Marie, Ontario to Saxon, Wisconsin? Given the route implied by the first six roads, you can reliably predict the next two numbers—2 and 122—from a map. The lesson: You cannot say, just by looking at the result of the process, whether the process that created those results is capable of generating predictable output. You must understand the process itself.

The Forces That Shape Innovation

What can make the process of innovation more predictable? It does not entail learning to predict what individuals might do. Rather, it comes from understanding the forces that act upon the individuals involved in building businesses—forces that powerfully influence what managers choose and cannot choose to do.

Rarely does an idea for a new-growth business emerge fully formed from an innovative employee’s head. No matter how well articulated a concept or insight might be, it must be shaped and modified, often significantly, as it gets fleshed out into a business plan that can win funding from the corporation. Along the way, it encounters a number of highly predictable forces. Managers as individuals might indeed be idiosyncratic and unpredictable, but they all face forces that are similar in their mechanism of action, their timing, and their impact on the character of the product and business plan that the company ultimately attempts to implement.[12] Understanding and managing these forces can make innovation more predictable.

The action and impact of these forces in shaping ideas into business plans is illustrated in a case study of the Big Idea Group (BIG), a company that identifies, develops, and markets ideas for new toys.[13] After quoting a senior executive of a multibillion-dollar toy company who complained that there have been no exciting new toy ideas for years, the case then chronicles how BIG attacks this problem—or rather, this opportunity.

BIG invites mothers, children, tinkerers, and retirees who have ideas for new toys to attend “Big Idea Hunts,” which it convenes in locations across the country. These guests present their ideas to a panel of experts whose intuition BIG executives have come to trust. When the panel sees a good idea, BIG licenses it from the inventor and over the next several months shapes the idea into a business plan with a working prototype that they believe will sell. BIG then licenses the product to a toy company, which produces and markets it through its own channels. The company has been extraordinarily successful at finding, developing, and deploying into the market a sequence of truly exciting growth products.

How can there be such a flowering of high-potential new product opportunities in BIG’s system, and such a dearth of opportunities in the large toy company? In discussing the case, students often suggest that the product developers in the toy company just aren’t as creative, or that the executives of the major company are just too risk averse. If these diagnoses were true, the company would simply need to find more creative managers who could think outside the box. But a parade of people has cycled through the toy company, and none has been able to crack the apparent lack of exciting toy ideas. Why?

The answer lies in the process by which the ideas get shaped. Midlevel managers play a crucial role in every company’s innovation process, as they shepherd partially formed ideas into fully fledged business plans in an effort to win funding from senior management. It is the middle managers who must decide which of the ideas that come bubbling in or up to them they will support and carry to upper management for approval, and which ideas they will simply allow to languish. This is a key reason why companies employ middle managers in the first place. Their job is to sift the good ideas from the bad and to make good ideas so much better that they readily secure funding from senior management.

How do they sift and shape? Middle managers typically hesitate to throw their weight behind new product concepts whose market is not assured. If a market fails to materialize, the company will have wasted millions of dollars. The system therefore mandates that midlevel managers support their proposals with credible data on the size and growth potential of the markets that each idea targets. Opinions and feedback from significant customers add immeasurably to the credibility of claims that an idea has potential. Where does this evidence come from, given that the product hasn’t yet been fully developed? It typically comes from existing customers and markets for similar products that have been successful in the past.

Personal factors are at work in this shaping process, too. Managers who back ideas that flop often find their prospects for promotion effectively truncated. In fact, ambitious managers hesitate even to propose ideas that senior managers are not likely to approve. If they favor an idea that their superiors subsequently judge to be weak, their reputation for good judgment can be tarnished among the very executives they hope to impress. Furthermore, companies’ management development programs rarely leave their most talented middle managers in a position for longer than a few years—they move them to new assignments to broaden their skills and experience. What this means, however, is that middle managers who want a reputation for delivering results will be inclined to promote only those new-growth ideas that will pay off within the time that they reside in that particular job.

The process of sorting through and packaging ideas into plans that can win funding, in other words, shapes those ideas to resemble the ideas that were approved and became successful in the past. The processes have in fact evolved to weed out business proposals that target markets where demand might be small. The problem for growth-seeking managers, of course, is that the exciting growth markets of tomorrow are small today.

This is why the senior managers at the major toy company and at BIG can live in the same world and yet see such different things. In every sizable company, not just in the toy business, the set of ideas that has been processed and packaged for top management approval is very different from the population of ideas that is bubbling at the bottom.

A dearth of good ideas is rarely the core problem in a company that struggles to launch exciting new-growth businesses. The problem is in the shaping process. Potentially innovative new ideas seem inexorably to be recast into attempts to make existing customers still happier. We believe that many of the ideas that emerge from this packaging and shaping process as me-too innovations could just as readily be shaped into business plans that create truly disruptive growth. Managers who understand these forces and learn to harness them in making key decisions will develop successful new-growth businesses much more consistently than historically has seemed possible.[14]

Where Predictability Comes From: Good Theory

The quest for predictability in an endeavor as complex as innovation is not quixotic. What brings predictability to any field is a body of well-researched theory—contingent statements of what causes what and why. Executives often discount the value of management theory because it is associated with the word theoretical, which connotes impractical. But theory is consummately practical. The law of gravity, for example, actually is a theory—and it is useful. It allows us to predict that if we step off a cliff, we will fall.[15]

Even though most managers don’t think of themselves as being theory driven, they are in reality voracious consumers of theory. Every time managers make plans or take action, it is based on a mental model in the back of their heads that leads them to believe that the action being taken will lead to the desired result.[16] The problem is that managers are rarely aware of the theories they are using—and they often use the wrong theories for the situation they are in. It is the absence of conscious, trustworthy theories of cause and effect that makes success in building new businesses seem random.

To help executives to know whether and when they can trust the recommendations from management books or articles (including this one!) that they read for guidance as they build their businesses, we describe in the following sections a model of how good theories are built and used. We will repeatedly return to this model to illustrate how bad theory has caused growth builders to stumble in the past, and how the use of sound theory can remove many of the causes of failure.[17]

How Theories Are Built

The process of building solid theory has been researched in several disciplines, and scholars seem to agree that it proceeds in three stages. It begins by describing the phenomenon that we wish to understand. In physics, the phenomenon might be the behavior of high-energy particles. In the building of new businesses, the phenomena of interest are the things that innovators do in their efforts to succeed, and what the results of those actions are. Bad management theory results when researchers impatiently observe one or two success stories and then assume that they have seen enough.

After the phenomenon has been thoroughly characterized, researchers can then begin the second stage, which is to classify the phenomenon into categories. Juvenile-onset versus adult-onset diabetes is an example from medicine. Vertical and horizontal integration are categories of corporate diversification. Researchers need to categorize in order to highlight the most meaningful differences in the complex array of phenomena.

In the third stage, researchers articulate a theory that asserts what causes the phenomenon to occur, and why. The theory must also show whether and why the same causal mechanism might result in different outcomes, depending on the category or situation. The process of theory building is iterative, as researchers and managers keep cycling through these three steps, refining their ability to predict what actions will cause what results, under what circumstances.[18]

Getting the Categories Right

The middle stage in this cycle—getting the categories right—is the key to developing useful theory. To see why, imagine going to your medical doctor seeking treatment for a particular set of symptoms, and before you have a chance to describe what ails you, the physician hands you a prescription and tells you to “take two of these and call me in the morning.”

“But how do you know this will help me?” you ask. “I haven’t told you what’s wrong.”

“Why wouldn’t it work?” comes the reply. “It cured my previous two patients just fine.”

No sane patient would accept medicine like this. But academics, consultants, and managers routinely dispense and accept remedies to management problems in this manner. When something has worked for a few “excellent” companies, they readily advise all other companies that taking the same medicine will be good for them as well. One reason why the outcomes of innovation appear to be random is that many who write about strategy and management ignore categorization. They observe a few successful companies and then write a book recommending that other managers do the same things to be successful too—without regard for the possibility that there might be some circumstances in which their favorite solution is a bad idea.[19]

For example, thirty years ago many writers asserted that vertical integration was the key to IBM’s extraordinary success. But in the late 1990s we read that non-integration explained the triumph of outsourcing titans such as Cisco and Dell. The authors of “best practices” gospels such as these are no better than the doctor we introduced previously. The critical question that these researchers need to resolve is, “What are the circumstances in which being integrated is competitively critical, and when is a strategy of partnering and outsourcing more likely to lead to success?”

Because theory-building scholars struggle to define the right and relevant categorization of circumstances, they rarely can define the circumstances immediately. Early studies almost always sort researchers’ observations into categories defined by the attributes of the phenomena themselves. Their assertions about the actions or events that lead to the results at this point can only be statements about correlation between attributes and results, not about causality. This is the best they can do in early theory-building cycles.

Consider, for illustration, the history of man’s attempts to fly. Early researchers observed strong correlations between being able to fly and having feathers and wings. Possessing these attributes had a high correlation with the ability to fly, but when humans attempted to follow the “best practices” of the most successful flyers by strapping feathered wings onto their arms, jumping off cliffs, and flapping hard, they were not successful—because as strong as the correlations were, the would-be aviators had not understood the fundamental causal mechanism that enabled certain animals to fly. It was not until Bernoulli’s study of fluid mechanics helped him articulate the mechanism through which airfoils create lift that human flight began to be possible. But understanding the mechanism itself still wasn’t enough to make the ability to fly perfectly predictable. Further research, entailing careful experimentation and measurement under various conditions, was needed to identify the circumstances in which that mechanism did and did not yield the desired result.

When the mechanism did not result in successful flight, researchers had to carefully decipher why—what it was about the circumstances in which the unexpected result occurred that led to failure. Once categories could be stated in terms of the different types of circumstances in which aviators might find themselves, then aviators could predict the conditions in which flight was and was not possible. They could develop technologies and techniques for successfully flying in those circumstances where flight was viable. And they could teach aviators how to recognize when the circumstances were changing, so that they could change their methods appropriately. Understanding the mechanism (what causes what, and why) made flight possible; understanding the categories of circumstances made flight predictable.[20]

How did aviation researchers know what the salient boundaries were between these categories of circumstance? As long as a change in conditions did not require change in the way the pilot flew the plane, the boundary between those conditions didn’t matter. The circumstance boundaries that mattered were those that mandated a fundamental change in piloting techniques in order to keep the plane flying successfully.

Similar breakthroughs in management research increase the predictability of creating new-growth businesses. Getting beyond correlative assertions such as “Big companies are slow to innovate,” or “In our sample of successful companies, each was run by a CEO who had been promoted from within,” the breakthrough researcher first discovers the fundamental causal mechanism behind the phenomena of success. This allows those who are looking for “an answer” to get beyond the wings-and-feathers mind-set of copying the attributes of successful companies. The foundation for predictability only begins to be built when the researcher sees the same causal mechanism create a different outcome from what he or she expected—an anomaly. This prompts the researcher to define what it was about the circumstance or circumstances in which the anomaly occurred that caused the identical mechanism to result in a different outcome.

How can we tell what the right categorization is? As in aviation, a boundary between circumstances is salient only when executives need to use fundamentally different management techniques to succeed in the different circumstances defined by that boundary. If the same statement of cause and effect leads to the same outcome in two circumstances, then the distinction between those circumstances is not meaningful for the purposes of predictability.

To know for certain what circumstances they are in, managers also must know what circumstances they are not in. When collectively exhaustive and mutually exclusive categories of circumstances are defined, things get predictable: We can state what will cause what and why, and can predict how that statement of causality might vary by circumstance. Theories built on categories of circumstances become easy for companies to employ, because managers live and work in circumstances, not in attributes.[21]

When managers ask questions such as “Does this apply to my industry?” or “Does it apply to service businesses as well as product businesses?” they really are probing to understand the circumstances. In our studies, we have observed that industry-based or product/ service-based categorization schemes almost never constitute a useful foundation for reliable theory. The Innovator’s Dilemma, for example, described how the same mechanism that enabled entrant companies to up-end the leading established firms in disk drives and computers also toppled the leading companies in mechanical excavators, steel, retailing, motorcycles, accounting software, and motor controls.[22] The circumstances that mattered were not what industry you were in. Rather, there was a mechanism—the resource allocation process—that caused the established leaders to win the competitive fights when an innovation was financially attractive to their business model. The same mechanism disabled the established leaders when they were attacked by disruptive innovators—whose products, profit models, and customers were not attractive.

We can trust a theory only when its statement of what actions will lead to success describe how this will vary as a company’s circumstances change.[23] This is a major reason why the outcomes of innovation efforts have seemed quite random: Shoddy categorization has led to one-size-fits-all recommendations that in turn have led to the wrong results in many circumstances.[24] It is the ability to begin thinking and acting in a circumstance-contingent way that brings predictability to our lives.

We often admire the intuition that successful entrepreneurs seem to have for building growth businesses. When they exercise their intuition about what actions will lead to the desired results, they really are employing theories that give them a sense of the right thing to do in various circumstances. These theories were not there at birth: They were learned through a set of experiences and mentors earlier in life.

If some people have learned the theories that we call intuition, then it is our hope that these theories also can be taught to others. This is our aspiration for this book. We hope to help managers who are trying to create new-growth businesses use the best research we have been able to assemble to learn how to match their actions to the circumstances in order to get the results they need. As our readers use these ways of thinking over and over, we hope that the thought processes inherent in these theories can become part of their intuition as well.

We have written this book from the perspective of senior managers in established companies who have been charged to maintain the health and vitality of their firms. We believe, however, that our ideas will be just as valuable to independent entrepreneurs, start-up companies, and venture capital investors. Simply for purposes of brevity, we will use the term product in this book when we describe what a company makes or provides. We mean, however, for this to encompass product and service businesses, because the concepts in the book apply just as readily to both.

The Outline of This Book

The Innovator’s Dilemma summarized a theory that explains how, under certain circumstances, the mechanism of profit-maximizing resource allocation causes well-run companies to get killed. The Innovator’s Solution, in contrast, summarizes a set of theories that can guide managers who need to grow new businesses with predictable success—to become the disruptors rather than the disruptees—and ultimately kill the well-run, established competitors. To succeed predictably, disruptors must be good theorists. As they shape their growth business to be disruptive, they must align every critical process and decision to fit the disruptive circumstance.

Because building successful growth businesses is such a vast topic, this book focuses on nine of the most important decisions that all managers must make in creating growth—decisions that represent key actions that drive success inside the black box of innovation. Each chapter offers a specific theory that managers can use to make one of these decisions in a way that greatly improves their probability of success. Some of this theory has emerged from our own studies, but we are indebted to many other scholars for much of what follows. Those whose work we draw upon have contributed to improving the predictability of business building because their assertions of causality have been built upon circumstance-based categories. It is because of their careful work that we believe that managers can begin using these theories explicitly as they make these decisions, trusting that their predictions will be applicable and reliable, given the circumstances that they are in.

The following list summarizes the questions we address.

- Chapter 2: How can we beat our most powerful competitors? What strategies will result in the competitors killing us, and what courses of action could actually give us the upper hand?

- Chapter 3: What products should we develop? Which improvements over previous products will customers enthusiastically reward with premium prices, and which will they greet with indifference?

- Chapter 4: Which initial customers will constitute the most viable foundation upon which to build a successful business?

- Chapter 5: Which activities required to design, produce, sell, and distribute our product should our company do internally, and which should we rely upon our partners and suppliers to provide?

- Chapter 6: How can we be sure that we maintain strong competitive advantages that yield attractive profits? How can we tell when commoditization is going to occur, and what can we do to keep earning attractive returns?

- Chapter 7: What is the best organizational structure for this venture? What organizational unit(s) and which managers should contribute to and be responsible for its success?

- Chapter 8: How do we get the details of a winning strategy right? When is flexibility important, and when will flexibility cause us to fail?

- Chapter 9: Whose investment capital will help us succeed, and whose capital might be the kiss of death? What sources of money will help us most at different stages of our development?

- Chapter 10: What role should the CEO play in sustaining the growth of the business? When should CEOs keep their hands off the new business, and when should they become involved?

The issues that we tackle in these chapters are critical, but they cannot constitute an exhaustive list of the questions that should be relevant to launching a new-growth business. We can simply hope that we have addressed the most important ones, so that although we cannot make the creation of new-growth businesses perfectly risk free, we can help managers take major steps in that direction.

Notes

1.   Although we have not performed a true meta-analysis, there are four recently published studies that seem to converge on this estimate that roughly one company in ten succeeds at sustaining growth. Chris Zook and James Allen found in their 2001 study Profit from the Core (Boston: Harvard Business School Press) that only 13 percent of their sample of 1,854 companies were able to grow consistently over a ten-year period. Richard Foster and Sarah Kaplan published a study that same year, Creative Destruction (New York: Currency/Doubleday), in which they followed 1,008 companies from 1962 to 1998. They learned that only 160, or about 16 percent of these firms, were able merely to survive this time frame, and concluded that the perennially outperforming company is a chimera, something that has never existed at all. Jim Collins also published his Good to Great (New York: HarperBusiness) in 2001, in which he examined a universe of 1,435 companies over thirty years (1965–1995). Collins found only 126, or about 9 percent, that had managed to outperform equity market averages for a decade or more. The Corporate Strategy Board’s findings in Stall Points (Washington, DC: Corporate Strategy Board, 1988), which are summarized in detail in the text, show that 5 percent of companies in the Fortune 50 successfully maintained their growth, and another 4 percent were able to reignite some degree of growth after they had stalled. The studies all support our assertion that a 10 percent probability of succeeding in a quest for sustained growth is, if anything, a generous estimate.

2.   Because all of these transactions included stock, “true” measures of the value of the different deals are ambiguous. Although when a deal actually closes, a definitive value can be fixed, the implied value of the transaction at the time a deal is announced can be useful: It signals what the relevant parties were willing to pay and accept at a point in time. Stock price changes subsequent to the deal’s announcement are often a function of other, exogenous events having little to do with the deal itself. Where possible, we have used the value of the deals at announcement, rather than upon closing. Sources of data on these various transactions include the following:

NCR

“Fatal Attraction (AT&T’s Failed Merger with NCR),” The Economist, 23 March 1996.

“NCR Spinoff Completes AT&T Restructure Plan,” Bloomberg Business News, 1 January 1997.

McCaw and AT&T Wireless Sale

The Wall Street Journal, 21 September 1994.

“AT&T Splits Off AT&T Wireless,” AT&T news release, 9 July 2001.

AT&T, TCI, and MediaOne

“AT&T Plans Mailing to Sell TCI Customers Phone, Web Services,” The Wall Street Journal, 10 March 1999.

“The AT&T-Mediaone Deal: What the FCC Missed,” Business Week, 19 June 2000.

“AT&T Broadband to Merge with Comcast Corporation in $72 Billion Transaction,” AT&T news release, 19 December 2001.

“Consumer Groups Still Questioning Comcast-AT&T Cable Merger,” Associated Press Newswires, 21 October 2002.

3.   Cabot’s stock price outperformed the market between 1991 and 1995 as it refocused on its core business, for two reasons. On one side of the equation, demand for carbon black increased in Asia and North America as car sales surged, thereby increasing the demand for tires. On the supply side, two other American-based producers of carbon black exited the industry because they were unwilling to make the requisite investment in environmental controls, thereby increasing Cabot’s pricing power. Increased demand and reduced supply translated into a tremendous increase in the profitability of Cabot’s traditional carbon black operations, which was reflected in the company’s stock price. Between 1996 and 2000, however, its stock price deteriorated again, reflecting the dearth of growth prospects.

4.   An important study of companies’ tendency to make investments that fail to create growth was done by Professor Michael C. Jensen: “The Modern Industrial Revolution, Exit, and the Failure of Internal Control Systems,” Journal of Finance (July 1993): 831–880. Professor Jensen also delivered this paper as his presidential address to the American Finance Association. Interestingly, many of the firms that Jensen cites as having productively reaped growth from their investments were disruptive innovators—a key concept in this book.

Our unit of analysis in this book, as in Jensen’s work, is the individual firm, not the larger system of growth creation made manifest in a free market, capitalist economy. Works such as Joseph Schumpeter’s Theory of Economic Development (Cambridge, MA: Harvard University Press, 1934) and Capitalism, Socialism, and Democracy (New York: London, Harper & Brothers, 1942) are seminal, landmark works that address the environment in which firms function. Our assertion here is that whatever the track record of free market economies in generating growth at the macro level, the track record of individual firms is quite poor. It is the performance of firms within a competitive market to which we hope to contribute.

5.   This simple story is complicated somewhat by the market’s apparent incorporation of an expected “fade” in any company’s growth rate. Empirical analysis suggests that the market does not expect any company to grow, or even survive, forever. It therefore seems to incorporate into current prices a foreseen decline in growth rates from current levels and the eventual dissolution of the firm. This is the reason for the importance of terminal values in most valuation models. This fade period is estimated using regression analysis, and estimates vary widely. So, strictly speaking, if a company is expected to grow at 5 percent with a fade period of forty years, and five years into that forty-year period it is still growing at 5 percent, the stock price would rise at rates that generated economic returns for shareholders, because the forty-year fade period would start over. However, because this qualification applies to companies growing at 5 percent as well as those growing at 25 percent, it does not change the point we wish to make; that is, that the market is a harsh taskmaster, and merely meeting expectations does not generate meaningful reward.

6.   On average over their long histories, of course, faster-growing firms yield higher returns. However, the faster-growing firm will have produced higher returns than the slower-growing firm only for investors in the past. If markets discount efficiently, then the investors who reap above-average returns are those who were fortunate enough to have bought shares in the past when the future growth rate had not been fully discounted into the price of the stock. Those who bought when the future growth potential already had been discounted into the share price would not receive an above-market return. An excellent reference for this argument can be found in Alfred Rappaport and Michael J. Mauboussin, Expectations Investing: Reading Stock Prices for Better Returns (Boston: Harvard Business School Press, 2001). Rappaport and Mauboussin guide investors in methods to detect when a market’s expectations for a company’s growth might be incorrect.

7.   These were the closing market prices for these companies’ common shares on August 21, 2002. There is no significance to that particular date: It is simply the time when the analysis was done. HOLT Associates, a unit of Credit Suisse First Boston (CSFB), performed these calculations using proprietary methodology applied to publicly available financial data. The percent future is a measure of how much a company’s current stock price can be attributed to current cash flows and how much is due to investors’ expectations of future growth and performance. As CSFB/HOLT defines it,

The percent future is the percentage of the total market value that the market assigns to the company’s expected future investment. Percent future begins with the total market value (debt plus equity) less that portion attributed to the present value of existing assets and investments and divides this by the total market value of debt and equity.

CSFB/Holt calculates the present value of existing assets as the present value of the cash flows associated with the assets’ wind down and the release of the associated nondepreciating working capital. The HOLT CFROI valuation methodology includes a forty-year fade of returns equal to the total market’s average returns.

Percent Future = [Total Debt and Equity (market) – Present Value

Existing Assets]/[Total Debt and Equity (market)]

The companies listed in table 1-1 are not a sequential ranking of Fortune 500 companies, because some of the data required to perform these calculations were not available for some companies. The companies listed in this table were chosen only for illustrative purposes, and were not chosen in any way to suggest that any company’s share price is likely to increase or decline. For more information on the methodology that HOLT used, see <http://www.holtvalue.com>.

8.   See Stall Points (Washington, DC: Corporate Strategy Board, 1998).

9.   In the text we have focused only on the pressure that equity markets impose on companies to grow, but there are many other sources of intense pressure. We’ll mention just a couple here. First, when a company is growing, there are increased opportunities for employees to be promoted into new management positions that are opening up above them. Hence, the potential for growth in managerial responsibility and capability is much greater in a growing firm than in a stagnant one. When growth slows, managers sense that their possibilities for advancement will be constrained not by their personal talent and performance, but rather by how many years must pass before the more senior managers above them will retire. When this happens, many of the most capable employees tend to leave the company, affecting the company’s abilities to regenerate growth.

Investment in new technologies also becomes difficult. When a growing firm runs out of capacity and must build a new plant or store, it is easy to employ the latest technology. When a company has stopped growing and has excess manufacturing capacity, proposals to invest in new technology typically do not fare well, since the full capital cost and the average manufacturing cost of producing with the new technology are compared against the marginal cost of producing in a fully depreciated plant. As a result, growing firms typically have a technology edge over slow-growth competitors. But that advantage is not rooted so much in the visionary wisdom of the managers as it is in the difference in the circumstances of growth versus no growth.

10.  Detailed support for this estimate is provided in note 1.

11.  For example, see James Brian Quinn, Strategies for Change: Logical Incrementalism (Homewood, IL: R.D. Irwin, 1980). Quinn suggests that the first step that corporate executives need to take in building new businesses is to “let a thousand flowers bloom,” then tend the most promising and let the rest wither. In this view, the key to successful innovation lies in choosing the right flowers to tend—and that decision must rely on complex intuitive feelings, calibrated by experience.

More recent work by Tom Peters (Thriving on Chaos: Handbook for a Management Revolution [New York: Knopf/Random House, 1987]) urges innovating managers to “fail fast”—to pursue new business ideas on a small scale and in a way that generates quick feedback about whether an idea is viable. Advocates of this approach urge corporate executives not to punish failures because it is only through repeated attempts that successful new businesses will emerge.

Others draw on analogies with biological evolution, where mutations arise in what appear to be random ways. Evolutionary theory posits that whether a mutant organism thrives or dies depends on its fit with the “selection environment”—the conditions within which it must compete against other organisms for the resources required to thrive. Hence, believing that good and bad innovations pop up randomly, these researchers advise corporate executives to focus on creating a “selection environment” in which viable new business ideas are culled from the bad as quickly as possible. Gary Hamel, for example, advocates creating “Silicon Valley inside”—an environment in which existing structures are constantly dismantled, recombined in novel ways, and tested, in order to stumble over something that actually works. (See Gary Hamel, Leading the Revolution [Boston: Harvard Business School Press, 2001].)

We are not critical of these books. They can be very helpful, given the present state of understanding, because if the processes that create innovations were indeed random, then a context within which managers could accelerate the creation and testing of ideas would indeed help. But if the process is not intrinsically random, as we assert, then addressing only the context is treating the symptom, not the source of the problem.

To see why, consider the studies of 3M’s celebrated ability to create a stream of growth-generating innovations. A persistent highlight of these studies is 3M’s “15 percent rule”: At 3M, many employees are given 15 percent of their time to devote to developing their own ideas for new-growth businesses. This “slack” in how people spend their time is supported by a broadly dispersed capital budget that employees can tap in order to fund their would-be growth engines on a trial basis.

But what guidance does this policy give to a bench engineer at 3M? She is given 15 percent “slack” time to dedicate to creating new-growth businesses. She is also told that whatever she comes up with will be subject first to internal market selection pressures, then external market selection pressures. All this is helpful information. But none of it helps that engineer create a new idea, or decide which of the several ideas she might create are worth pursuing further. This plight generalizes to managers and executives at all levels in an organization. From bench engineer to middle manager to business unit head to CEO, it is not enough to occupy oneself only with creating a context for innovation that sorts the fruits of that context. Ultimately, every manager must create something of substance, and the success of that creation lies in the decisions managers must make.

All of these approaches create an “infinite regress.” By bringing the market “inside,” we have simply backed up the problem: How can managers decide which ideas will be developed to the point at which they can be subjected to the selection pressures of their internal market? Bringing the market still deeper inside simply creates the same conundrum. Ultimately, innovators must judge what they will work on and how they will do it—and what they should consider when making those decisions is what is in the black box. The acceptance of randomness in innovation, then, is not a stepping-stone on the way to greater understanding; it is a barrier.

Dr. Gary Hamel was one of the first scholars of this problem to raise with Professor Christensen the possibility that the management of innovation actually has the potential to yield predictable results. We express our thanks to him for his helpful thoughts.

12.  The scholars who introduced us to these forces are Professor Joseph Bower of the Harvard Business School and Professor Robert Burgelman of the Stanford Business School. We owe a deep intellectual debt to them. See Joseph L. Bower, Managing the Resource Allocation Process (Homewood, IL: Richard D. Irwin, 1970); Robert Burgelman and Leonard Sayles, Inside Corporate Innovation (New York: Free Press, 1986); and Robert Burgelman, Strategy Is Destiny (New York: Free Press, 2002).

13.  Clayton M. Christensen and Scott D. Anthony, “What’s the BIG Idea?” Case 9-602-105 (Boston: Harvard Business School, 2001).

14.  We have consciously chosen phrases such as “increase the probability of success” because business building is unlikely ever to become perfectly predictable, for at least three reasons. The first lies in the nature of competitive marketplaces. Companies whose actions were perfectly predictable would be relatively easy to defeat. Every company therefore has an interest in behaving in deeply unpredictable ways. A second reason is the computational challenge associated with any system with a large number of possible outcomes. Chess, for example, is a fully determined game: After White’s first move, Black should always simply resign. But the number of possible games is so great, and the computational challenge so overwhelming, that the outcomes of games even between supercomputers remain unpredictable. A third reason is suggested by complexity theory, which holds that even fully determined systems that do not outstrip our computational abilities can still generate deeply random outcomes. Assessing the extent to which the outcomes of innovation can be predicted, and the significance of any residual uncertainty or unpredictability, remains a profound theoretical challenge with important practical implications.

15.  The challenge of improving predictability has been addressed somewhat successfully in certain of the natural sciences. Many fields of science appear today to be cut and dried—predictable, governed by clear laws of cause and effect, for example. But it was not always so: Many happenings in the natural world seemed very random and unfathomably complex to the ancients and to early scientists. Research that adhered carefully to the scientific method brought the predictability upon which so much progress has been built. Even when our most advanced theories have convinced scientists that the world is not deterministic, at least the phenomena are predictably random.

Infectious diseases, for example, at one point just seemed to strike at random. People didn’t understand what caused them. Who survived and who did not seemed unpredictable. Although the outcome seemed random, however, the process that led to the results was not random—it just was not sufficiently understood. With many cancers today, as in the venture capitalists’ world, patients’ probabilities for survival can only be articulated in percentages. This is not because the outcomes are unpredictable, however. We just do not yet understand the process.

16.  Peter Senge calls theories mental models (see Peter Senge, The Fifth Discipline [New York: Bantam Doubleday Dell, 1990]). We considered using the term model in this book, but opted instead to use the term theory. We have done this to be provocative, to inspire practitioners to value something that is indeed of value.

17.  A full description of the process of theory building and of the ways in which business writers and academics ignore and violate the fundamental principles of this process is available in a paper that is presently under review, “The Process of Theory Building,” by Clayton Christensen, Paul Carlile, and David Sundahl. Paper or electronic copies are available from Professor Christensen’s office, cchristensen@hbs.edu. The scholars we have relied upon in synthesizing the model of theory building presented in this paper (and only very briefly summarized in this book) are, in alphabetical order, E. H. Carr, What Is History? (New York: Vintage Books, 1961); K. M. Eisenhardt, “Building Theories from Case Study Research,” Academy of Management Review 14, no. 4 (1989): 532–550; B. Glaser and A. Straus, The Discovery of Grounded Theory: Strategies of Qualitative Research (London: Wiedenfeld and Nicholson, 1967); A. Kaplan, The Conduct of Inquiry: Methodology for Behavioral Research (Scranton, PA: Chandler, 1964); R. Kaplan, “The Role for Empirical Research in Management Accounting,” Accounting, Organizations and Society 4, no. 5 (1986): 429–452; T. Kuhn, The Structure of Scientific Revolutions (Chicago: University of Chicago Press, 1962); M. Poole and A. Van de Ven, “Using Paradox to Build Management and Organization Theories,” Academy of Management Review 14, no. 4 (1989): 562–578; K. Popper, The Logic of Scientific Discovery (New York: Basic Books, 1959); F. Roethlisberger, The Elusive Phenomena (Boston: Harvard Business School Division of Research, 1977); Arthur Stinchcombe, “The Logic of Scientific Inference,” chapter 2 in Constructing Social Theories (New York: Harcourt, Brace & World, 1968); Andrew Van de Ven, “Professional Science for a Professional School,” in Breaking the Code of Change, eds. Michael Beer and Nitin Nohria (Boston: Harvard Business School Press, 2000); Karl E. Weick, “Theory Construction as Disciplined Imagination,” Academy of Management Review 14, no. 4, (1989): 516–531; and R. Yin, Case Study Research (Beverly Hills, CA: Sage Publications, 1984).

18.  What we are saying is that the success of a theory should be measured by the accuracy with which it can predict outcomes across the entire range of situations in which managers find themselves. Consequently, we are not seeking “truth” in any absolute, Platonic sense; our standard is practicality and usefulness. If we enable managers to achieve the results they seek, then we will have been successful. Measuring the success of theories based on their usefulness is a respected tradition in the philosophy of science, articulated most fully in the school of logical positivism. For example, see R. Carnap, Empiricism, Semantics and Ontology (Chicago: University of Chicago Press, 1956); W. V. O. Quine, Two Dogmas of Empiricism (Cambridge, MA: Harvard University Press, 1961); and W. V. O. Quine, Epistemology Naturalized. (New York: Columbia University Press, 1969).

19.  This is a serious deficiency of much management research. Econometricians call this practice “sampling on the dependent variable.” Many writers, and many who think of themselves as serious academics, are so eager to prove the worth of their theories that they studiously avoid the discovery of anomalies. In case study research, this is done by carefully selecting examples that support the theory. In more formal academic research, it is done by calling points of data that don’t fit the model “outliers” and finding a justification for excluding them from the statistical analysis. Both practices seriously limit the usefulness of what is written. It actually is the discovery of phenomena that the existing theory cannot explain that enables researchers to build better theory that is built upon a better classification scheme. We need to do anomaly-seeking research, not anomaly-avoiding research.

We have urged doctoral students who are seeking potentially productive research questions for their thesis research to simply ask when a “fad” theory won’t work—for example, “When is process reengineering a bad idea?” Or, “Might you ever want to outsource something that is your core competence, and do internally something that is not your core competence?” Asking questions like this almost always improves the validity of the original theory. This opportunity to improve our understanding often exists even for very well done, highly regarded pieces of research. For example, an important conclusion in Jim Collins’s extraordinary book From Good to Great (New York: HarperBusiness, 2001) is that the executives of these successful companies weren’t charismatic, flashy men and women. They were humble people who respected the opinions of others. A good opportunity to extend the validity of Collins’s research is to ask a question such as, “Are there circumstances in which you actually don’t want a humble, noncharismatic CEO?” We suspect that there are—and defining the different circumstances in which charisma and humility are virtues and vices could do a great service to boards of directors.

20.  We thank Matthew Christensen of the Boston Consulting Group for suggesting this illustration from the world of aviation as a way of explaining how getting the categories right is the foundation for bringing predictability to an endeavor. Note how important it was for researchers to discover the circumstances in which the mechanisms of lift and stabilization did not result in successful flight. It was the very search for failures that made success consistently possible. Unfortunately, many of those engaged in management research seem anxious not to spotlight instances their theory did not accurately predict. They engage in anomaly-avoiding, rather than anomaly-seeking, research and as a result contribute to the perpetuation of unpredictability. Hence, we lay much responsibility for the perceived unpredictability of business building at the feet of the very people whose business it is to study and write about these problems. We may, on occasion, succumb to the same problem. We can state that in developing and refining the theories summarized in this book, we have truly sought to discover exceptions or anomalies that the theory would not have predicted; in so doing, we have improved the theories considerably. But anomalies remain. Where we are aware of these, we have tried to note them in the text or notes of this book. If any of our readers are familiar with anomalies that these theories cannot yet explain, we invite them to teach us about them, so that together we can work to improve the predictability of business building further.

21.  In studies of how companies deal with technological change, for example, early researchers suggested attribute-based categories such as incremental versus radical change and product versus process change. Each categorization supported a theory, based on correlation, about how entrant and established companies were likely to be affected by the change, and each represented an improvement in predictive power over earlier categorization schemes. At this stage of the process there rarely is a best-by-consensus theory, because there are so many attributes of the phenomena. Scholars of this process have broadly observed that this confusion is an important but unavoidable stage in building theory. See Thomas Kuhn, The Structure of Scientific Revolutions (Chicago: University of Chicago Press, 1962). Kuhn chronicles at length the energies expended by advocates of various competing theories at this stage, prior to the advent of a paradigm.

In addition, one of the most influential handbooks for management and social science research was written by Barney G. Glaser and Anselm L. Strauss (The Discovery of Grounded Theory: Strategies of Qualitative Research [London: Wiedenfeld and Nicholson, 1967]). Although they name their key concept “grounded theory,” the book really is about categorization, because that process is so central to the building of valid theory. Their term “substantive theory” is similar to our term “attribute-based categories.” They describe how a knowledge-building community of researchers ultimately succeeds in transforming their understanding into “formal theory,” which we term “circumstance-based categories.”

22.  Clayton M. Christensen, The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail (Boston: Harvard Business School Press, 1997).

23.  Managers need to know if a theory applies in their situation, if they are to trust it. A very useful book on this topic is Robert K. Yin’s Case Study Research: Design and Methods (Beverly Hills, CA: Sage Publications, 1984). Building on Yin’s concept, we would say that the breadth of applicability of a theory, which Yin calls its external validity, is established by the soundness of its categorization scheme. There is no other way to gauge where theory applies and where it does not. To see why, consider the disruptive innovation model that emerged from the study of the disk drive industry in the early chapters of The Innovator’s Dilemma. The concern that readers of the disk drive study raised, of course, was whether the theory applied to other industries as well. The Innovator’s Dilemma tried to address these concerns by showing how the same theory that explained who succeeded and failed in disk drives also explained what happened in mechanical excavators, steel, retailing, motorcycles, accounting software, motor controls, diabetes care, and computers. The variety was chosen to establish the breadth of the theory’s applicability. But this didn’t put concerns to rest. Readers continued to ask whether the theory applied to chemicals, to database software, and so on.

Applying any theory to industry after industry cannot prove its applicability because it will always leave managers wondering if there is something different about their current circumstances that renders the theory untrust-worthy. A theory can confidently be employed in prediction only when the categories that define its contingencies are clear. Some academic researchers, in a well-intentioned effort not to overstep the validity of what they can defensibly claim and not claim, go to great pains to articulate the “boundary conditions” within which their findings can be trusted. This is all well and good. But unless they concern themselves with defining what the other circumstances are that lie beyond the “boundary conditions” of their own study, they circumscribe what they can contribute to a body of useful theory.

24.  An illustration of how important it is to get the categories right can be seen in the fascinating juxtaposition of two recent, solidly researched books by very smart students of management and competition that make compelling cases for diametrically opposite solutions to a problem. Each team of researchers addresses the same underlying problem—the challenge of delivering persistent, profitable growth. In Creative Destruction (New York: Currency/Doubleday, 2001), Richard Foster and Sarah Kaplan argue that if firms hope to create wealth sustainably and at a rate comparable to the broader market, they must be willing to explore radically new business models and visit upon themselves the tumult that characterizes the capital markets. At the same time, another well-executed study, Profit from the Core (Boston: Harvard Business School Press, 2001), by Bain consultants Chris Zook and James Allen, drew upon the same phenomenological evidence—that only a tiny minority of companies are able to sustain above-market returns for a significant time. But their book encourages companies to focus on and improve their established businesses rather than attempt to anticipate or even respond to the vagaries of equity investors by seeking to create new growth in less-related markets. Whereas Foster and Kaplan motivate their findings in terms of the historical suitability of incrementalism in a context of competitive continuity and argue for more radical change in light of today’s exigencies, Zook and Allen hold that focus is timeless and remains the key to success. Their prescriptions are mutually exclusive. Whose advice should we follow? At present, managers grappling with their own growth problems have no choice but to pick a camp based on the reputations of the authors and the endorsements on the dust jacket. The answer is that there is a great opportunity for circumstance-focused researchers to build on the valuable groundwork that both sets of authors have established. The question that now needs answering is: What are the circumstances in which focusing on or near the core will yield sustained profit and growth, and what are the circumstances in which broader, Fosteresque creative destruction is the approach that will succeed?

CHAPTER TWO

HOW CAN WE BEAT OUR

MOST POWERFUL COMPETITORS?

How can we know in advance of the battle whether we’re going to be able to beat the competition? Why has disruption proven to be such a consistently effective strategy for causing strong incumbent competitors to flee from their entrant attackers, rather than fight them? How can we shape our business idea into one of these disruptive strategies? Can we really predict the winners in a race for innovative growth? What if we could choose our competitive battles knowing we could win nearly every time? What if we knew in advance which growth strategies would succeed, and which would fail?

Managers have long sought ways to predict the outcome of competitive fights. Some have looked at the attributes of the companies involved, predicting that larger companies with more resources to throw at a problem will beat the smaller competitors. It’s interesting how often the CEOs of large, resource-rich companies base their strategies upon this theory, despite repeated evidence that the level of resources committed often bears little relationship to the outcome.

Others have considered the attributes of the change: When innovations are incremental, the established, leading firms in an industry are likely to reinforce their dominance; however, compared with entrants, they will be conservative and ineffective in exploiting breakthrough innovation.[1] We noted in the introduction that predictions based on attribute-based categories, as these are, prove frustratingly undependable.

Our ongoing study of innovation suggests another way to understand when incumbents will win, and when the entrants are likely to beat them. The Innovator’s Dilemma identified two distinct categories—sustaining and disruptive—based on the circumstances of innovation. In sustaining circumstances—when the race entails making better products that can be sold for more money to attractive customers—we found that incumbents almost always prevail. In disruptive circumstances—when the challenge is to commercialize a simpler, more convenient product that sells for less money and appeals to a new or unattractive customer set—the entrants are likely to beat the incumbents. This is the phenomenon that so frequently defeats successful companies. It implies, of course, that the best way for upstarts to attack established competitors is to disrupt them.

Few technologies or business ideas are intrinsically sustaining or disruptive in character. Rather, their disruptive impact must be molded into strategy as managers shape the idea into a plan and then implement it. Successful new-growth builders know—either intuitively or explicitly—that disruptive strategies greatly increase the odds of competitive success.

This chapter’s purpose is to review the disruptive innovation model from the perspective of both the disruptee and the disruptor in order to help growth builders shape their strategies so that they pick disruptive fights they can win. Because disruption happens whether we want it or not, this chapter will also help managers of established companies capture disruptive growth, instead of seeing their companies get killed by it.

The Disruptive Innovation Model

The Innovator’s Dilemma identified three critical elements of disruption, as depicted in figure 2-1. First, in every market there is a rate of improvement that customers can utilize or absorb, represented by the dotted line sloping gently upward across the chart. For example, the automobile companies keep giving us new and improved engines, but we can’t utilize all the performance that they make available under the hood. Factors such as traffic jams, speed limits, and safety concerns constrain how much performance we can use.

FIGURE 2 - 1

The Disruptive Innovation Model

To simplify the chart, we depict customers’ ability to utilize improvement as a single line. In reality, there is a distribution of customers around this median: There are many such lines, or tiers, in a market—a range indicated by the distribution curve at the right. Customers in the highest or most demanding tiers may never be satisfied with the best that is available, and those in the lowest or least demanding tiers can be oversatisfied with very little.[2] This dotted line represents technology that is “good enough” to serve customers’ needs.

Second, in every market there is a distinctly different trajectory of improvement that innovating companies provide as they introduce new and improved products. This pace of technological progress almost always outstrips the ability of customers in any given tier of the market to use it, as the more steeply sloping solid lines in figure 2-1 suggest. Thus, a company whose products are squarely positioned on mainstream customers’ current needs today will probably overshoot what those same customers are able to utilize in the future. This happens because companies keep striving to make better products that they can sell for higher profit margins to not-yet-satisfied customers in more demanding tiers of the market.

To visualize this, think back to 1983 when people first started using personal computers for word processing. Typists often had to stop their fingers to let the Intel 286 chip inside catch up. As depicted at the left side of figure 2-1, the technology was not good enough. But today’s processors offer much more speed than mainstream customers can use—although there are still a few unsatisfied customers in the most demanding tiers of the market who need even faster chips.

The third critical element of the model is the distinction between sustaining and disruptive innovation. A sustaining innovation targets demanding, high-end customers with better performance than what was previously available. Some sustaining innovations are the incremental year-by-year improvements that all good companies grind out. Other sustaining innovations are breakthrough, leapfrog-beyond-the-competition products. It doesn’t matter how technologically difficult the innovation is, however: The established competitors almost always win the battles of sustaining technology. Because this strategy entails making a better product that they can sell for higher profit margins to their best customers, the established competitors have powerful motivations to fight sustaining battles. And they have the resources to win.

Disruptive innovations, in contrast, don’t attempt to bring better products to established customers in existing markets. Rather, they disrupt and redefine that trajectory by introducing products and services that are not as good as currently available products. But disruptive technologies offer other benefits—typically, they are simpler, more convenient, and less expensive products that appeal to new or less-demanding customers.[3]

Once the disruptive product gains a foothold in new or low-end markets, the improvement cycle begins. And because the pace of technological progress outstrips customers’ abilities to use it, the previously not-good-enough technology eventually improves enough to intersect with the needs of more demanding customers. When that happens, the disruptors are on a path that will ultimately crush the incumbents. This distinction is important for innovators seeking to create new-growth businesses. Whereas the current leaders of the industry almost always triumph in battles of sustaining innovation, successful disruptions have been launched most often by entrant companies.[4]

Disruption has a paralyzing effect on industry leaders. With resource allocation processes designed and perfected to support sustaining innovations, they are constitutionally unable to respond. They are always motivated to go up-market, and almost never motivated to defend the new or low-end markets that the disruptors find attractive. We call this phenomenon asymmetric motivation. It is the core of the innovator’s dilemma, and the beginning of the innovator’s solution.

Disruption at Work: How Minimills Upended

Integrated Steel Companies

The disruption of integrated steel mills by minimills, whose history was partially reviewed in The Innovator’s Dilemma, offers a classic example of why established leaders are so much easier to beat if the idea for a new product or business is shaped into a disruption.

Historically, most of the world’s steel has come from massive integrated mills that do everything from reacting iron ore, coke, and limestone in blast furnaces to rolling finished products at the other end. It costs about $8 billion to build a huge new integrated mill today. Minimills, in contrast, melt scrap steel in electric arc furnaces—cylinders that are approximately twenty meters in diameter and ten meters tall. Because they can produce molten steel cost-effectively in such a small chamber, minimills don’t need the massive-scale rolling and finishing operations that are required to handle the output of efficient blast furnaces—which is why they are called minimills. Most important, though, minimills’ straightforward technology can make steel of any given quality for 20 percent lower cost than an integrated mill.

Steel is a commodity. You would think that every integrated steel company in the world would have aggressively adopted the straightforward, lower-cost minimill technology. Yet as of 2000 not a single integrated steel company had successfully invested in a minimill, even as the minimills had grown to account for nearly half of North America’s steel production and a significant share of other markets as well.[5]

We can explain why something that makes so much sense has been so difficult for the integrated mills. Minimills first became technologically viable in the mid-1960s. Because they melt scrap of uncertain and varying chemistry in their electric arc furnaces, the quality of the steel that minimills initially could produce was poor. In fact, the only market that would accept the output of minimills was the concrete reinforcing bar (rebar) market. The specifications for rebar are loose, so this was an ideal market for products of low and variable quality.

As the minimills attacked the rebar market, the integrated mills were happy to be rid of that dog-eat-dog commodity business. Because of the differences in their cost structures and the opportunities for investment that they each faced, the rebar market looked very different to the disruptee and the disruptor. For integrated producers, gross profit margins on rebar often hovered near 7 percent, and the entire product category accounted for only 4 percent of the industry’s tonnage. It was the least attractive of any tier of the market in which they might invest to grow. So as the minimills established a foothold in the rebar market, the integrated mills reconfigured their rebar lines to make more profitable products.

In contrast, with a 20 percent cost advantage, the minimills enjoyed attractive profits in competition against the integrated mills for rebar—until 1979, when the minimills finally succeeded in driving the last integrated mill out of the rebar market. Historical pricing statistics show that the price of rebar then collapsed by 20 percent. As long as the minimills could compete against higher-cost integrated mills, the game was profitable for them. But as soon as low-cost minimill was pitted against low-cost minimill in a commodity market, the reward for victory was that none of them could earn attractive profits in rebar.[6] Worse, as they all sought profitability by becoming more efficient producers, they discovered that cost reductions meant survival, but not profitability, in a commodity such as rebar.[7]

Soon, however, the minimills looked up-market, and what they saw there spelled relief. If they could just figure out how to make bigger and better steel—shapes like angle iron and thicker bars and rods—they could roll tons of money, because in that tier of the market, as suggested in figure 2-2, the integrated mills were earning gross margins of about 12 percent—nearly double the margins that they had been able to earn in rebar. That market was also twice as big as the rebar segment, accounting for about 8 percent of industry tonnage. As the minimills figured out how to make bigger and better steel and attacked that tier of the market, the integrated mills were almost relieved to be rid of the bar and rod business as well. It was a dog-eat-dog commodity compared with their higher-margin products, whereas for the minimills, it was an attractive opportunity compared with their lower-margin rebar. So as the minimills expanded their capacity to make angle iron and thicker bars and rods, the integrated mills shut their lines down or reconfigured them to make more profitable products. With a 20 percent cost advantage, the minimills enjoyed significant profits in competition against the integrated mills until 1984, when they finally succeeded in driving the last integrated mill out of the bar and rod market. Once again, the minimills reaped their reward: With low-cost minimill pitted against low-cost minimill, the price of bar and rod collapsed by 20 percent, and they could no longer earn attractive profits. What could they do?

FIGURE 2 - 2

The Up-Market Migration of Steel Minimills

Continued up-market movement into structural beams appeared to be the next obvious answer. Gross margins in that sector were a whopping 18 percent, and the market was three times as large as the bar and rod business. Most industry technologists thought minimills would be unable to roll structural beams. Many of the properties required to meet the specifications for steel used in building and bridge construction were imparted to the steel in the rolling processes of big integrated mills, and you just couldn’t get those properties in minimills’ abbreviated facilities. What the technical experts didn’t count on, however, was how desperately motivated the minimills would be to solve that problem, because it was the only way they could make attractive money. Minimills achieved extraordinarily clever innovations as they stretched from angle iron to I-beams—things such as Chaparral Steel’s dog-bone mold in its continuous caster, which no one had imagined could be done. Although you could never have predicted what the technical solution would be, you could predict with perfect certainty that the minimills were powerfully motivated to figure it out. Necessity remains the mother of invention.

At the beginning of their invasion into structural beams, the biggest that the minimills could roll were little six-inch beams of the sort that undergird mobile homes. They attacked the low end of the structural beam market, and again the integrated mills were almost relieved to be rid of it. It was a dog-eat-dog commodity compared with their other higher-margin products where focused investment might bring more attractive volume. To the minimills, in contrast, it was an attractive product compared with the margins they were earning on rebar and angle iron. So as the minimills expanded their capacity to roll structural beams, the integrated mills shut their structural beam mills down in order to focus on more profitable sheet steel products. With a 20 percent cost advantage, the minimills enjoyed significant profits as long as they could compete against the integrated mills. Then in the mid-1990s, when they finally succeeded in driving the last integrated mill out of the structural beam market, pricing again collapsed. Once again, the reward for victory was the end of profit.

The sequence repeated itself when the leading minimill, Nucor, attacked the sheet steel business. Its market capitalization now dwarfs that of the largest integrated steel company, US Steel. Bethlehem Steel is bankrupt at the time of this writing.

This is not a history of bungled steel company management. It is a story of rational managers facing the innovator’s dilemma: Should we invest to protect the least profitable end of our business, so that we can retain our least loyal, most price-sensitive customers? Or should we invest to strengthen our position in the most profitable tiers of our business, with customers who reward us with premium prices for better products?

The executives who confront this dilemma come in all varieties: timid, feisty, analytical, and action-driven. In an unstructured world their actions might be unpredictable. But as large industry incumbents, they encounter powerful and predictable forces that motivate them to flee rather than fight when attacked from below. That is why shaping a business idea into a disruption is an effective strategy for beating an established competitor. Disruption works because it is much easier to beat competitors when they are motivated to flee rather than fight.

The forces that propel well-managed companies up-market are always at work, in every company in every industry. Whether or not entrant firms have disrupted the established leaders yet, the forces are at work, leading predictably in one direction. It is not just a phenomenon of “technology companies” such as those involved in microelectronics, software, photonics, or biochemistry. Indeed, when we use the term technology in this book, it means the process that any company uses to convert inputs of labor, materials, capital, energy, and information into outputs of greater value. For the purpose of predictably creating growth, treating “high tech” as different from “low tech” is not the right way to categorize the world. Every company has technology, and each is subject to these fundamental forces.

The Role of Sustaining Innovation in Generating Growth

We must emphasize that we do not argue against the aggressive pursuit of sustaining innovation. Several other insightful books offer management techniques to help companies excel in sustaining innovations—and their contribution is important.[8] Almost always a host of similar companies enters an industry in its early years, and getting ahead of that crowd—moving up the sustaining-innovation trajectory more decisively than the others—is critical to the successful exploitation of the disruptive opportunity. But this is the source of the dilemma: Sustaining innovations are so important and attractive, relative to disruptive ones, that the very best sustaining companies systematically ignore disruptive threats and opportunities until the game is over.

Sustaining innovation essentially entails making a better mousetrap. Starting a new company with a sustaining innovation isn’t necessarily a bad idea: Focused companies sometimes can develop new products more rapidly than larger firms because of the conflicts and distractions that broad scope often creates. The theory of disruption suggests, however, that once they have developed and established the viability of their superior product, entrepreneurs who have entered on a sustaining trajectory should turn around and sell out to one of the industry leaders behind them. If executed successfully, getting ahead of the leaders on the sustaining curve and then selling out quickly can be a straightforward way to make an attractive financial return. This is common practice in the health care industry, and was the well-chronicled mechanism by which Cisco Systems “outsourced” (and financed with equity capital, rather than expense money) much of its sustaining-product development in the 1990s.

A sustaining-technology strategy is not a viable way to build new-growth businesses, however. If you create and attempt to sell a better product into an established market to capture established competitors’ best customers, the competitors will be motivated to fight rather than to flee.[9] This advice holds even when the entrant is a huge corporation with ostensibly deeper pockets than the incumbent.

For example, electronic cash registers were a radical but sustaining innovation relative to electromechanical cash registers, whose market was dominated by National Cash Register (NCR). NCR totally missed the advent of the new technology in the 1970s—so badly, in fact, that NCR’s product sales literally went to zero. Electronic registers were so superior that there was no reason to buy an electromechanical product except as an antique. Yet NCR survived on service revenues for over a year, and when it finally introduced its own electronic cash register, its extensive sales organization quickly captured the same share of the market as the company had enjoyed in the electromechanical realm.[10] The attempts that IBM and Kodak made in the 1970s and 1980s to beat Xerox in the high-speed photocopier business are another example. These companies were far bigger, and yet they failed to outmuscle Xerox in a sustaining-technology competition. The firm that beat Xerox was Canon—and that victory started with a disruptive tabletop copier strategy.

Similarly, corporate giants RCA, General Electric, and AT&T failed to outmuscle IBM on the sustaining-technology trajectory in mainframe computers. Despite the massive resources they threw at IBM, they couldn’t make a dent in IBM’s position. In the end, it was the disruptive personal computer makers, not the major corporations who picked a direct, sustaining-innovation fight, who bested IBM in computers. Airbus entered the commercial airframe industry head-on against Boeing, but doing so required massive subsidies from European governments. In the future, the most profitable growth in the airframe industry will probably come from firms with disruptive strategies, such as Embraer and Bombardier’s Canadair, whose regional jets are aggressively stretching up-market from below.[11]

Disruption Is a Relative Term

An idea that is disruptive to one business may be sustaining to another. Given the stark odds that favor the incumbents in the sustaining race but entrants in disruptive ones, we recommend a strict rule: If your idea for a product or business appears disruptive to some established companies but might represent a sustaining improvement for others, then you should go back to the drawing board. You need to define an opportunity that is disruptive relative to all the established players in the targeted market, or you should not invest in the idea. If it is a sustaining innovation relative to the business model of a significant incumbent, you are picking a fight you are very unlikely to win.

Take the Internet, for example. Throughout the late 1990s, investors poured billions into Internet-based companies, convinced of their “disruptive” potential. An important reason why many of them failed was that the Internet was a sustaining innovation relative to the business models of a host of companies. Prior to the advent of the Internet, Dell Computer, for example, sold computers directly to customers by mail and over the telephone. This business was already a low-end disruptor, moving up its trajectory. Dell’s banks of telephone salespeople had to be highly trained in order to walk their customers through the various configurations of components that were and were not feasible. They then manually entered the information into Dell’s order fulfillment systems.

For Dell, the Internet was a sustaining technology. It made Dell’s core business processes work better, and it helped Dell make more money in the way it was structured to make money. But the identical strategy of selling directly to customers over the Internet was very disruptive relative to Compaq’s business model, because that company’s cost structure and business processes were targeted at in-store retail distribution.

The theory of disruption would conclude that if Dell (and Gateway) had not existed, then start-up Internet-based computer retailers might have succeeded in disrupting competitors such as Compaq. But because the Internet was sustaining to powerful incumbents, entrant Internet computer retailers have not prospered.

A Disruptive Business Model Is a Valuable Corporate Asset

A disruptive business model that can generate attractive profits at the discount prices required to win business at the low end is an extraordinarily valuable growth asset. When its executives carry the business model up-market to make higher-performance products that sell at higher price points, much of the increment in pricing falls to the bottom line—and it continues to fall there as long as the disruptor can keep moving up, competing at the margin against the higher-cost disruptee. When a company tries to take a higher-cost business model down-market to sell products at lower price points, almost none of the incremental revenue will fall to its bottom line. It gets absorbed into overheads. This is why, as we discuss in chapter 7, established firms that hope to capture the growth created by disruption need to do so from within an autonomous business with a cost structure that offers as much headroom as possible for subsequent profitable migration up-market.

Moving up the trajectory into successively higher-margin tiers of the market and shedding less-profitable products at the low end is something that all good managers must do in order to keep their margins strong and their stock price healthy. Standing still is not an option, because firms that stop moving up find themselves in a rebaresque situation, slugging it out with hard-to-differentiate products against competitors whose costs are comparable.[12]

This ultimately means that in doing what they must do, every company prepares the way for its own disruption. This is the innovator’s dilemma. But it also is the beginning of the innovator’s solution. Disruption does not guarantee success, but it sure helps: The Innovator’s Dilemma showed that following a strategy of disruption increased the odds of creating a successful growth business from 6 percent to 37 percent.[13] Because the established company’s course of action is mandated so clearly, it is also clear what executives who seek to create new-growth businesses should do: Target products and markets that the established companies are motivated to ignore or run away from. Many of the most profitable growth trajectories in history have been initiated by disruptive innovations.

Two Types of Disruption

For the sake of simplicity, The Innovator’s Dilemma presented the disruptive innovation diagram in only two dimensions. In reality, there are two different types of disruptions, which can best be visualized by adding a third axis to the disruption diagram, as shown in figure 2-3. The vertical and horizontal axes are as before: the performance of the product on the vertical axis, with time plotted on the horizontal dimension. The third axis represents new customers and new contexts for consumption.

Our original dimensions—time and performance—define a particular market application in which customers purchase and use a product or service. In geometric terms, this application and set of customers reside in a plane of competition and consumption, which The Innovator’s Dilemma called a value network. A value network is the context within which a firm establishes a cost structure and operating processes and works with suppliers and channel partners in order to respond profitably to the common needs of a class of customers. Within a value network, each firm’s competitive strategy, and particularly its cost structure and its choices of markets and customers to serve, determines its perceptions of the economic value of an innovation. These perceptions, in turn, shape the rewards and threats that firms expect to experience through disruptive versus sustaining innovations.[14]

FIGURE 2 - 3

The Third Dimension of the Disruptive Innovation Model

The third dimension that extends toward us in the diagram represents new contexts of consumption and competition, which are new value networks. These constitute either new customers who previously lacked the money or skills to buy and use the product, or different situations in which a product can be used—enabled by improvements in simplicity, portability, and product cost. For each of these new value networks, a vertical axis can be drawn representing a product’s performance as it is defined in that context (which is a different measure from what is valued in the original value network).

Different value networks can emerge at differing distances from the original one along the third dimension of the disruption diagram. In the following discussion, we will refer to disruptions that create a new value network on the third axis as new-market disruptions. In contrast, low-end disruptions are those that attack the least-profitable and most overserved customers at the low end of the original value network.

New-Market Disruptions

We say that new-market disruptions compete with “nonconsumption” because new-market disruptive products are so much more affordable to own and simpler to use that they enable a whole new population of people to begin owning and using the product, and to do so in a more convenient setting. The personal computer and Sony’s first battery-powered transistor pocket radio were new-market disruptions, in that their initial customers were new consumers—they had not owned or used the prior generation of products and services. Canon’s desktop photocopiers were also a new-market disruption, in that they enabled people to begin conveniently making their own photocopies around the corner from their offices, rather than taking their originals to the corporate high-speed photocopy center where a technician had to run the job for them. When Canon made photocopying so convenient, people ended up making a lot more copies. New-market disruptors’ challenge is to create a new value network, where it is nonconsumption, not the incumbent, that must be overcome.

Although new-market disruptions initially compete against non-consumption in their unique value network, as their performance improves they ultimately become good enough to pull customers out of the original value network into the new one, starting with the least-demanding tier. The disruptive innovation doesn’t invade the mainstream market; rather, it pulls customers out of the mainstream value network into the new one because these customers find it more convenient to use the new product.

Because new-market disruptions compete against nonconsumption, the incumbent leaders feel no pain and little threat until the disruption is in its final stages. In fact, when the disruptors begin pulling customers out of the low end of the original value network, it actually feels good to the leading firms, because as they move up-market in their own world, for a time they are replacing the low-margin revenues that disruptors steal, with higher-margin revenues from sustaining innovations.[15]

Low-End Disruptions

We call disruptions that take root at the low end of the original or mainstream value network low-end disruptions. Disruptions such as steel minimills, discount retailing, and the Korean automakers’ entry into the North American market have been pure low-end disruptions in that they did not create new markets—they were simply low-cost business models that grew by picking off the least attractive of the established firms’ customers. Although they are different, new-market and low-end disruptions both create the same vexing dilemma for incumbents. New-market disruptions induce incumbents to ignore the attackers, and lowend disruptions motivate the incumbents to flee the attack.

Low-end disruption has occurred several times in retailing.[16] For example, full-service department stores had a business model that enabled them to turn inventories three times per year. They needed to earn 40 percent gross margins to make money within their cost structure. They therefore earned 40 percent three times each year, for a 120 percent annual return on capital invested in inventory (ROCII). In the 1960s, discount retailers such as Wal-Mart and Kmart attacked the low end of the department stores’ market—nationally branded hard goods such as paint, hardware, kitchen utensils, toys, and sporting goods—that were so familiar in use that they could sell themselves. Customers in this tier of the market were overserved by department stores, in that they did not need well-trained floor sales-people to help them get what they needed. The discounters’ business model enabled them to make money at gross margins of about 23 percent, on average. Their stocking policies and operating processes enabled them to turn inventories more than five times annually, so that they also earned about 120 percent annual ROCII. The discounters did not accept lower levels of profitability—their business model simply earned acceptable profit through a different formula.[17]

It is very hard for established firms not to flee from a low-end disruptor. Consider, for example, the choice that executives of full-service department stores had to make when the discount retailers were attacking the branded hard goods at the low end of department stores’ merchandise mix. Retailers’ critical resource allocation decision is the use of floor or shelf space. One option for department store executives was to allocate more space to even higher-margin cosmetics and high-fashion apparel, where gross margins often exceeded 50 percent. Because their business model turned inventories three times annually, this option promised 150 percent ROCII.

The alternative was to defend the branded hard goods businesses, which the discounters were attacking with prices 20 percent below those of department stores. Competing against the discounters at those levels would send margins plummeting to 20 percent, which, given the three-times inventory turns that were on average inherent in their business model, entailed a ROCII of 60 percent. It thus made perfect sense for the full-service department stores to flee—to get out of the very tiers of the market that the discounters were motivated to enter.[18]

Many disruptions are hybrids, combining new-market and lowend approaches, as depicted by the continuum of the third axis in figure 2-3. Southwest Airlines is actually a hybrid disruptor, for example. It initially targeted customers who weren’t flying—people who previously had used cars and buses. But Southwest pulled customers out of the low end of the major airlines’ value network as well. Charles Schwab is a hybrid disruptor. It stole some customers from full-service brokers with its discounted trading fees, but it also created new markets by enabling people who historically were not equity investors—such as students—to begin owning and trading stocks.[19]

Figure 2-4 shows where some of history’s more successful disruptors were positioned along the continuum of new-market to low-end disruption at their inception. The appendix to this chapter offers a brief historical explanation of each of the disruptive products or companies listed on the chart. This is not a complete census of disruptive companies, of course, and their position on the chart is only approximate. However, the array does convey our sense that disruption is a primary wellspring of growth. The prevalence of Japanese companies such as Sony, Nippon Steel, Toyota, Honda, and Canon in the period between 1960 and 1980 and the absence of disruptive Japanese companies in the 1990s, for example, explain a lot about why Japan’s economy has stagnated. Many of its most influential companies grew dramatically by disrupting others; but the structure of Japan’s economic system inhibits the creation of new waves of disruptive growth, in part because they might threaten those companies today.[20]

The chart also shows that disruption is an ongoing force that is always at work—meaning that disruptors in one generation become disruptees later. The Ford Model T, for example, created the first massive wave of disruptive growth in automobiles. Toyota, Nissan, and Honda then created the next wave, and Korean automakers Hyundai and Kia have now begun the third. AT&T’s wireline long distance business, which disrupted Western Union, is being disrupted by wireless long distance. Plastics makers such as Dow, DuPont, and General Electric continue to disrupt steel, even as their low end is being eaten away by suppliers of blended polyolefin plastics such as Himont.

FIGURE 2 - 4

Examples of Companies and Products Whose Roots Were in Disruption

Shaping Ideas to Become Disruptive: Three Litmus Tests

At the beginning of this chapter, we mentioned that few technologies or product ideas are inherently sustaining or disruptive when they emerge from the innovator’s mind. Instead, they go through a process of becoming fleshed out and shaped into a strategic plan in order to win funding. Many—but not all—of the initial ideas that get shaped into sustaining innovations could just as readily be shaped into disruptive business plans with far greater growth potential. The shaping process must be consciously managed, however, and not left to the dispersed and instinctive decisions of those who write business plans.

Executives must answer three sets of questions to determine whether an idea has disruptive potential. The first set explores whether the idea can become a new-market disruption. For this to happen, at least one and generally both of two questions must be answered affirmatively:

- Is there a large population of people who historically have not had the money, equipment, or skill to do this thing for themselves, and as a result have gone without it altogether or have needed to pay someone with more expertise to do it for them?

- To use the product or service, do customers need to go to an inconvenient, centralized location?

If the technology can be developed so that a large population of less skilled or less affluent people can begin owning and using, in a more convenient context, something that historically was available only to more skilled or more affluent people in a centralized, inconvenient location, then there is potential for shaping the idea into a new-market disruption.

The second set of questions explores the potential for a low-end disruption. This is possible if these two questions can be answered affirmatively:

- Are there customers at the low end of the market who would be happy to purchase a product with less (but good enough) performance if they could get it at a lower price?

- Can we create a business model that enables us to earn attractive profits at the discount prices required to win the business of these overserved customers at the low end?

Often, the innovations that enable low-end disruption are improvements that reduce overhead costs, enabling a company to earn attractive returns on lower gross margins, coupled with improvements in manufacturing or business processes that turn assets faster.

Once an innovation passes the new-market or low-end test, there is still a third critical question, or litmus test, to answer affirmatively:

- Is the innovation disruptive to all of the significant incumbent firms in the industry? If it appears to be sustaining to one or more significant players in the industry, then the odds will be stacked in that firm’s favor, and the entrant is unlikely to win.

If an idea fails the litmus tests, then it cannot be shaped into a disruption. It may have promise as a sustaining technology, but in that case we would expect that it could not constitute the basis of a new-growth business for an entrant company.

For summary, table 2-1 summarizes and contrasts the characteristics of the three strategies that firms might pursue in creating new-growth businesses: sustaining innovations, low-end disruptions, and new-market disruptions. It compares the targeted product performance or features, the targeted customers or markets, and the business model implications that each route entails. We hope that managers can use this as a template so that they can categorize and see the implications of different plans that might be presented to them for approval.

TABLE 2 - 1

Three Approaches to Creating New-Growth Businesses

Dimension

Sustaining

Innovations

Low-End

Disruptions

New-Market

Disruptions

Targeted

performance

of the product

or service

Performance improvement

in attributes most valued

by the industry’s most

demanding customers.

These improvements

may be incremental

or breakthrough in

character.

Performance that

is good enough

along the traditional

metrics of perform-

ance at the low end

of the mainstream

market.

Lower performance

in“traditional”

attributes, but

improved performance

in new attributes—

typically simplicity and

convenience.

Targeted

customers

or market

application

The most attractive (i.e.,

profitable) customers

in the mainstream

markets who are willing

to pay for improved

performance.

Overserved customers

in the low end of the

mainstream market.

Targets non-

consumption:

customers who

historically lacked the

money or skill to buy

and use the product.

Impact on

the required

business model

(processes and

cost structure)

Improves or maintains

profit margins by

exploiting the existing

processes and cost

structure and making

better use of current

competitive advantages.

Utilizes a new

operating or financial

operating or financial

different combination

of lower gross profit

margins and higher

asset utilization that

can earn attractive

returns at the discount

prices required to win

business at the low

end of the market.

Business model must

make money at lower

price per unit sold,

and at unit production

volumes that initially

will be small. Gross

margin dollars per unit

sold will be signifi

cantly lower.

Executives can use this categorization and the litmus tests to foresee the competitive consequences of alternative strategies as they shape an idea. To illustrate, we’ll examine three questions: whether Xerox could disrupt Hewlett-Packard’s ink-jet printing business, how to create growth in air conditioning, and whether online banking had (or has) the potential to create a disruptive new-growth business.

Could Xerox Disrupt Hewlett-Packard?

We don’t actually know if Xerox has considered the possibility of creating a new business of the sort we will examine here, and we use the companies’ names only to make the example more vivid. We’ve based this scenario solely on information from public sources. Xerox reportedly has developed outstanding ink-jet printing technology. What can it do with it? It could attempt to leapfrog Hewlett-Packard by making the best ink-jet printer on the market. Even if it could make a better printer, however, Xerox would be fighting a battle of sustaining technology against a company with superior resources and more at stake. HP would win that fight. But could Xerox craft a disruptive strategy for this technology? We’ll test the conditions for a low-end strategy first.

To determine whether this strategy is viable, Xerox’s managers should test whether customers in the lowest market tiers might be willing to buy a “good enough” printer that is cheaper than prevailing products.[21] At the highest tier of the market, customers seem willing to pay significantly more for a faster printer that produces sharper images. However, consumers in the less-demanding tiers are becoming increasingly indifferent to improvements. It is likely they would be interested in lower-cost alternatives. So the first question gets an affirmative answer.

The next question is whether Xerox could define a business model that could generate attractive returns at the discounted prices required to win business at the low end. The possibilities here don’t look good. HP and other printer companies already outsource the fabrication and assembly of components to the lowest-cost sources in the world. HP makes its money selling ink cartridges—whose fabrication also is outsourced to low-cost suppliers. Xerox could enter the market by selling ink cartridges at lower prices, but unless it could define an overhead cost structure and business processes that would allow it to turn assets faster, Xerox could not sustain a product strategy of low-end disruption.[22]

This means we’ll need to evaluate the potential for a new-market disruption—competing against nonconsumption. Is there a large, untapped population of computer owners who don’t have the money or skill to buy and use a printer? Probably not. Hewlett-Packard already competed successfully against nonconsumption when it launched its easy-to-use, inexpensive ink-jet printers.

What about enticing existing printer owners to buy more printers, by enabling consumption in a new, more convenient context? Now, this might be achievable. Documents created on notebook computers are not easy to print. Notebook users have to find a stationary printer and connect to it either over a network or a printer cable, or they must transfer the file via removable media to a computer that is connected to a printer. If Xerox incorporated a lightweight, inexpensive printer into the base or spine of a notebook computer so that people on the go could get hard copies when and where they needed them, the company could probably win customers even if the printer wasn’t as good as a stationary ink-jet printer. Only Xerox’s engineers could determine whether the idea is technologically feasible. But as a strategy, this would pass the litmus tests.[23]

If Xerox attempted this, we would expect HP to ignore this new-market disruption at the outset because the market would be much smaller than the stationary printer market. HP’s printer business is huge, and the company needs large sources of new revenue to sustain its growth. To trap Hewlett-Packard in an innovator’s dilemma, Xerox should develop a business model that’s attractive to Xerox but unattractive to the managers of HP and other leading established printer companies. This might entail pricing ink cartridges for embedded notebook printers low enough that the executives of HP’s ink jet printer business would find the market unattractive relative to investments they might make to move up-market in search of the higher profits they could find by competing against higher-cost stationary laser printers.

Conditions for Growth in Air Conditioners

The window-mounted air conditioner market is widely known to be mature, dominated by giants such as Carrier and Whirlpool. Could a company like Hitachi wallop them? We would predict defeat if Hitachi tried to enter this market with a quieter product that offered more features and better energy efficiency.[24] Is a low-end disruption viable? Our sense is that there are overserved customers at the low end of the existing market. They signal their overservedness by opting for the least-expensive models they can find, unwilling to pay premium prices for the alternative products that are available to them. Hitachi might expand its already substantial manufacturing operations in China, making air conditioners for export to developed economies. This might bring modest but temporary success, because after the established companies respond by setting up their own manufacturing operations in China, Hitachi would find itself locked in a battle with competitors whose costs are comparable and whose distribution and service infrastructure are strong, and where the targeted customers already have manifested an unwillingness to pay premium prices for better products. Employing low-cost labor constitutes a low-cost business model only until competitors avail themselves of the same option.

How about a new-market disruption, however? There are hundreds of millions of nonconsumers of residential air conditioning in China, who have been blocked from that market because the power-hungry, expensive machines that historically have been available don’t fit in the average family’s pocketbook or apartment. If Hitachi could design a $49.95 product that would easily slip into the window of a cramped Shanghai apartment and reduce the temperature and humidity in a ten-foot by ten-foot room with ten amps of current, things might get interesting—because once Hitachi had a business model that could make money at that price point, taking on the rest of the up-market world would be easy. Parenthetically, while Western executives are understandably concerned about the threat that low-cost manufacturing in China poses to them, our guess is that China’s greatest competitive asset is the unfathomable amount of nonconsumption in its markets, which makes them fertile ground for new-market disruptive companies of many sorts.

The Potential for Internet Banking

When we ask the test questions about Internet banking, we conclude that disruption using this technology is not possible. In the first place, there is not a large population of people who have been unable to open and maintain a bank account because they have lacked the money or skill. Existing banks’ penetration of this market is high. This rules out a new-market disruption for Internet banking.

Second, are there current bank customers at the low end who would be happy to accept a bank account with fewer privileges and features in order to get the service at a lower price? The prevalence of advertisements featuring no-fee accounts is a testament that such customers exist. But is it possible to design a business model that would afford a disruptive online bank attractive profits at the discount prices required to win business at the low end? This is problematic. The cost of money is similar for all banks. E*Trade Bank and Sony Bank are seeking answers to the low-cost business model question.

Because the idea likely does not satisfy the conditions for either a new-market or a low-end disruption, Internet banking is likely to be implemented as a sustaining innovation by established banks. As for the third test, there already are many banks and credit unions, with only a limited number of office locations, that transact much of their business by mail. Internet banking would have a sustaining impact on their business models.

Disruption is a theory: a conceptual model of cause and effect that makes it possible to better predict the outcomes of competitive battles in different circumstances. The asymmetries of motivation chronicled in this chapter are natural economic forces that act on all businesspeople, all the time. Historically, these forces almost always have toppled the industry leaders when an attacker has harnessed them, because disruptive strategies are predicated upon competitors doing what is in their best and most urgent interest: satisfying their most important customers and investing where profits are most attractive. In a profit-seeking world, this is a pretty good bet.

Not all innovative ideas can be shaped into disruptive strategies, however, because the necessary preconditions do not exist; in such situations, the opportunity is best licensed or left to the firms that are already established in the market. On occasion, entrant companies have simply caught the leaders asleep at the switch and have succeeded with a strategy of sustaining innovation. But this is rare. Disruption does not guarantee success: It just helps with an important element in the total formula. Those who create new-growth businesses need to get on the right side of a number of other challenges, to which we will now turn.

Appendix: A Brief Description of the

Disruptive Strategies of the Firms in Figure 2-4

Table 2-2 briefly summarizes our understanding of the disruptive roots of the success of the companies that are arrayed in figure 2-4. Because of space limitations, much important detail has been omitted. The companies are listed in alphabetical, rather than chronological, order. We do not pretend to be strong business historians, and as a consequence can only present here a partial listing of disruptive companies. Furthermore, it is often difficult to identify a specific year in which each firm’s disruptive strategy was launched. Some firms existed for a considerable period, often in other lines of business, before the disruptive strategy that led to their ultimate success was implemented. In some cases it seems easier to visualize the disruption in terms of a product category, rather than by listing the name of one company. Hence, we ask our readers to regard this information as only suggestive, rather than definitive.

TABLE 2 - 2

Disruptive Strategies and Companies

Company or Product

Description

802.11

This is a protocol for high-bandwidth wireless transfer of data. It has begun disrupting local-area wireline networks. Its present limitations are that the signals can’t travel long distances.

Amazon.com

A low-end disruption relative to traditional bookstores.

Barnes & Noble

Began as a local seller of mostly overstocked, surplus books. Evolved to become the dominant discount retailer of in-print books.

Beef processing

In the 1880s, Swift and Armour began huge, centralized beef slaughtering operations that transported large sides of beef by refrigerated railcar to local meat cutters. This disrupted local slaughtering operations.

Bell Telephone

Bell’s original telephone could only carry a signal for three miles and therefore was rejected by Western Union, whose business was long-distance telegraphy, because Western Union couldn’t use it. Bell started a new-market disruption, offering local communication, and as the technology improved, it pulled customers from telegraphy’s long-distance value network into telephony.

Black & Decker

Prior to 1960, handheld electric tools were heavy and rugged, designed for professionals—and very expensive. B&D introduced a line of plastic-encased tools with universal motors that would only last twenty-five to thirty hours of operation—which actually was more than adequate for most do-it-yourselfers who drill a few holes per month. In today’s dollars, B&D brought the cost of these tools down from $150 to $20, enabling a whole new population to own and use their own tools.

Blended plastics

These blends of inexpensive polyolefin plastics such as polypropylene, sold by firms such as Himont, create composite materials that in many ways share the best properties of their constituent materials. They are getting better at a stunning rate, disrupting markets that historically had been the province of engineering plastics made by firms such as GE Plastics.

Bloomberg L.P.

Bloomberg began by providing basic financial data to investment analysts and brokers. It has gradually improved its data offerings and analysis and subsequently moved into the financial news business. It has substantially disrupted Dow Jones and Reuters as a result. More recently it has created its own elecronic clearing network to disrupt stock exchanges. Issuers of government securities can auction their initial offerings over the Bloomberg system, disrupting investment banks.

Boxed beef

The “boxed beef” model of Iowa Beef Packers completed the disruption of local butchering operations. Instead of shipping large sides of beef to local meat cutters for further cutting, IBP cut the beef into finished or nearly finished cuts for placement directly in supermarket cases.

Canon photocopiers

Until the early 1980s, when people needed photocopies, they had to take their originals to the corporate photocopy center, where a technician ran the job for them. He had  to be a technician, because the high-speed Xerox machine there was very complicated and needed servicing frequently. When Canon and Ricoh introduced their countertop photocopiers, they were slow, produced poor-resolution copies, and didn’t enlarge or reduce or collate. But they were so inexpensive and simple to use that people could afford to put one right around the corner from their office. At the beginning people still took their high-volume jobs to the copy center. But little by little Canon improved its machines to the point that immediate, convenient access to high-quality, full-featured copying is almost a constitutional right in most workplaces today.

Catalog retailing

Sears, Roebuck and Montgomery Ward took root as catalog retailers—enabling people in rural America to buy things that historically had not been accessible. Their business model, entailing annual inventory turns of four times and gross margins of 30 percent, was disruptive relative to the model of full-service department stores, which required 40 percent gross margins because they turned inventories only three times annually. Sears and Montgomery Ward later moved up-market, building retail stores.

Charles Schwab

Started in 1975 as one of the first discount brokers. In the late 1990s Schwab created a separate organization to build an online trading business. It was so successful that the company folded its original organization into the disruptive one.

Circuit City, Best Buy

Disrupted the consumer electronics departments of full-service and discount department stores, which has sent them up-market into higher-margin clothing.

Cisco

Cisco’s router uses packet-switching technology to direct the flow of information over the telecommunications system, rather than the circuit-switching technology of the established industry leaders such as Lucent, Siemens, and Nortel. The technology divides information into virtual “envelopes” called packets and sends them out over the Internet. Each packet might take a different route to the addressed destination; when they arrive, the packets are put in the right order and “opened” for the recipient to see. Because this process entailed a few seconds’ latency delay, packet switching could not be used for voice telecommunications. But it was good enough to enable a new market to emerge—data networks. The technology has improved to the point that today, the latency delay of a packet-switched voice call is almost imperceptibly slower than that of a circuit-switched call, enabling VOIP, or voice-over-Internet-protocol telephony.

Community colleges

In some states, up to 80 percent of the graduates of reputable four-year state universities take some or all of their required general education courses at much less expensive community colleges, and then transfer those credits to the university—which (unconsciously) is becoming a provider of upper-division courses. Some community colleges have begun offering four-year degrees. Their enrollment is booming, often with nontraditional students who otherwise would not have taken these courses.

Concord School of Law

Founded by Kaplan, a unit of the Washington Post Company, this online law school has attracted a host of (primarily) nontraditional students. The school’s accreditation allows its graduates to take the California Bar exam, and its graduates’ success rate is comparable to those of many other law schools. Many of its students don’t enroll to become lawyers, however. They want to understand law to help them succeed in other careers.

Credit scoring

A formulaic method of determining creditworthiness, substituting for the subjective judgments of bank loan officers. Developed by a Minneapolis firm, Fair Isaac. Used initially to extend Sears and Penney’s in-store credit cards. As the technology improved, it was used for general credit cards, and then auto, mortgage, and now small-business loans.

Dell Computer

Dell’s direct-to-customer retailing model and its fast-throughput, high asset-turns manufacturing model allowed it to come underneath Compaq, IBM, and Hewlett-Packard as a low-end disruptor in personal computers. Clayton Christensen, the quintessential low-end consumer, wrote his doctoral thesis on a Dell notebook computer purchased in 1991 because it was the cheapest portable computer on the market. Because of Dell’s reputation for marginal quality, students needed special permission from Harvard to use doctoral stipend money to buy a Dell rather than a computer with a more reputable brand. Today Dell supplies most of the Harvard Business School’s computers.

Department stores

Department stores such as Z.C.M.I. in Salt Lake City, Marshall Field’s in Chicago, and Macy’s in New York disrupted small shopkeepers. The department stores made money by accelerating inventory turns to three times per year, which enabled them to earn attractive profit with 40 percent gross margins. Because their salespeople were much less knowledgeable about products, at the outset department stores had to start at the simplest end of the merchandise mix, with products that were so familiar in use that they sold themselves.

Digital animation

The fixed cost and skill required to make a full-length animated movie historically was so high that almost nobody could do it except Disney. Digital animation technology now enables far more companies (such as Pixar) to compete against Disney.

Digital printing

Offset printing is being disrupted by the ability of local ink- and laser-jet printers to print custom, on-demand color documents at ever-improving speeds and quality. It has initially taken root in applications such as sales brochures.

Discount department stores

Department stores such as Korvette’s in New York, and later Kmart, Wal-Mart, and Target, disrupted full-service department stores. The discount stores made money by accelerating inventory turns to five times per year, which enabled them to earn attractive profit with 23 percent gross margins. Because their salespeople were much less knowledgeable about products, at the outset the discount department stores had to start at the simplest end of the merchandise mix, with branded hard goods that were so familiar in use that they sold themselves. They subsequently have moved up-market into soft goods such as clothing.

eBay

Most of the Internet start-ups of the late 1990s attempted to use the Internet as a sustaining innovation relative to the business models of established companies. eBay was a notable exception because it pursued a new-market disruptive strategy—enabling owners of collectibles that could never turn the heads of auction house executives to sell off things that they no longer needed.

ECNs

Electronic clearing networks (ECNs) allow buyers and sellers of equities to exchange them over a computer, at a fraction of the cost of doing it on a formal stock exchange. Island, one of the leading ECNs, can handle on one workstation volume amounting to 20 percent of the NASDAQ’s volume.

E-mail

E-mail is disrupting postal services. The volume of personal communication that is done by letter is dropping precipitously, leaving postal services with magazines, bills, and junk mail.

Embraer and Canadair regional jets

The regional passenger jet business is booming, as the capacity of their jets over the past fifteen years has stretched from 30 to 50, 70, and now 106. As Boeing and Airbus struggle to make bigger, faster jets for transcontinental and transoceanic travel, their growth has stagnated; the industry has consolidated (Lockheed and McDonnell Douglas have been folded in); and the growth is at the bottom of the market.

Endoscopic surgery

Minimally invasive surgery was actively disregarded by leading surgeons because the technique could only address the simplest procedures. But it has improved to the point that even certain relatively complicated heart procedures are done through a small port. The disruptive impact has primarily been on equipment makers and hospitals.

Fidelity Management

Created “self-service” personal financial management through its easy-to-buy families of mutual funds, 401k accounts, insurance products, and so forth.

Fidelity was founded a few years after World War II, but began its disruptive movements in the 1970s, as best we can tell.

Flat-panel displays (Sharp et al.)

We normally think of disruptive technologies as being inexpensive, and many people are puzzled at how we could call flat-panel displays disruptive. Haven’t they come from the high end? Actually, no. Flat-panel LCD displays took root in digital watches and then moved to calculators, notebook computers, and small portable televisions. These were applications that historically had no electronic displays at all, and LCD displays were much  cheaper than alternative means of bringing imaging to those applications. Flat screens have now begun invading the mainstream market of computer monitors and in-home television screens, disrupting the cathode ray tube. They are able to sustain substantial premium prices because of their two-dimensional character.

Ford

Henry Ford’s Model T was so inexpensive that he enabled a much larger population of people who historically could not afford cars to own one.

Galanz

China’s Galanz captured nearly 40 percent of the world microwave oven market in the 1990s. Although the company could have followed a strategy of low-end disruption—using low-cost Chinese labor to make appliances for export—it instead chose to be a new-market disruptor, making ovens that were small enough and consumed little-enough power to be used in cramped Chinese apartments and were cheap enough for non-microwave-oven owners to afford. Once they had built a business model that could make profits at market-enabling price points for the domestic Chinese market, taking on the rest of the world was as easy as egg-drop soup.

GE Capital

Has disrupted major portions of the commercial banks’ historical markets, primarily through low-end disruptive strategies.

Google

Google and its competing Internet search engines are disrupting directories of many sorts, including the Yellow Pages.

Honda motorcycles

Honda’s Supercub, introduced in the late 1950s, disrupted makers of big, thunderous motorcycles such as Harley-Davidson, Triumph, BMW, and others. It took root as an off-road recreational motorized bicycle, and then improved. Honda was joined by Yamaha, Kawasaki, and Suzuki.

Ink-jet printers

These were a disruption to the laser jet printer and a sustaining technology relative to the dot-matrix printer. We put ink-jet printers toward the “new-market” end of the disruption spectrum because their compact size, light weight, and low initial cost enabled a whole new population of computer owners—primarily students—to individually own and use a printer. Although they were slow and produced fuzzy images at the outset, ink-jet printers are now the mainstream printer of choice, having pushed laser jets to the high end. Hewlett-Packard stayed atop this industry by setting up an autonomous inkjet business unit to compete against its laser jet printer business.

Intel microprocessor

Intel’s earliest microprocessor in 1971 could only constitute the brain of a four-function calculator. Makers of computers whose logic circuitry is based on microprocessors have disrupted firms that made mainframes and minicomputers, whose logic circuitry was based on printed wiring boards.

Intuit’s QuickBooks accounting software

Whereas the established industry leaders in accounting software enabled small-business managers to run all sorts of sophisticated reports for analytical purposes, QuickBooks, which was a derivative of Intuit’s personal finance software product Quicken, basically helped them keep track of their cash. It created a huge new market among very small business owners (most with fewer than five employees) who historically did not keep their books on computer. Within two years of launch, Intuit had seized 85 percent of the small-business accounting software market—mainly by creating new growth. The stealing of the established companies’ customers came later, as QuickBooks’ functionality improved.

Intuit’s TurboTax

PC-based accounting software is disrupting personal tax preparation services such as H&R Block.

Japanese steel makers

Firms such as Nippon Steel, Nippon Kokkan, and Kobe and Kawasaki Steel began their growth by exporting very low quality steel to Western markets starting in the late 1950s. As their customers (including disruptive Japanese automakers like Toyota) grew, the Japanese steel industry had to increase capacity dramatically, enabling it to incorporate the latest steelmaking technology such as continuous casting and basic oxygen furnaces in the new mills. This accelerated their up-market trajectory dramatically.

JetBlue

Whereas Southwest Airlines initially followed a strategy of new-market disruption, JetBlue’s approach is low-end disruption. Its long-range viability depends on the major airlines’ motivation to run away from the attack, as integrated steel mills and full-service department stores did.

Kodak

Until the late 1800s, photography was extremely complicated. Only professionals could own and operate the expensive equipment. George Eastman’s simple “point and shoot” Brownie camera allowed consumers to take their own pictures. They could then mail the roll of film to Kodak, which would develop it and return the photos by mail.

Kodak Funsaver

Kodak’s Funsaver brand single-use camera was born after painful labor within Kodak, because its profit model and gross margins were lower than Kodak could earn by selling roll film, and the quality of the images was not as good as those taken in high-quality 35mm cameras. But Kodak commercialized it through a different division, and it sold almost exclusively to people who would not have bought film anyway because they didn’t have a camera. Although it has potential to move up-market and take share against traditional cameras with a new brand, Maxx, we worry that Kodak might have stopped driving it in this direction.

Korean auto manufacturers (Hyundai and Kia)

Korean automakers, including Hyundai and Kia, gained more points of world- wide market share in the 1990s than any other country’s automakers. And yet few of the established firms are concerned, because their gains have come in what is, to the established firms, the lowest-profit portion of the market.

Linux

The disruptiveness of the Linux operating system can only be expressed relative to the alternatives now in the market. Its most successful deployment thus far is within the market for server operating systems—sandwiched between high-end UNIX systems and the Microsoft Windows NT operating system (which has been moving disruptively up-market against UNIX for some time). From its initial foothold in Internet servers, it has gained significant share against UNIX operating systems such as Sun’s Solaris. The position of Linux may actually block the further up-market movement of Microsoft NT. Linux has begun to disrupt the market for operating system software on handheld devices as well.

MBNA

We noted earlier that credit scoring is a formulaic method of determining the creditworthiness of a loan applicant. It was originally implemented in commercial banks as a sustaining technology, to reduce the costs of credit evaluation. In the 1990s, however, it was deployed in high-volume, low-cost “monoline” business models by firms such as MBNA, Capital One, and First USA, which have substantially disrupted commercial banks’ credit card business. At the time of this writing, in fact, Citibank is the only remaining major commercial bank with a substantial and profitable credit card business.

McDonald’s

The fast food industry has been a hybrid disruptor, making it so inexpensive and convenient to eat out that they created a massive wave of growth in the “eating out” industry. Their earliest victims were mom-and-pop diners. In the last decade the advent of food courts has taken fast food up-market. Expensive, romantic restaurants still thrive at the high end, of course.

MCI, Sprint

These firms were low-end disruptors relative to AT&T’s long-distance telephone business. They enjoyed a unique opportunity to do this, because AT&T’s long-distance rates were set by regulation at artificially high levels in order to subsidize local residential telephone service.

Merrill Lynch

Charles Merrill’s mantra in 1912 was to “Bring Wall Street to Main Street.” By employing salaried rather than commissioned brokers, he made it inexpensive enough to trade stocks that middle-income Americans could become equity investors. Merrill Lynch moved up-market over the next 90 years toward investors of higher net worth. Most of the brokerage firms that held seats on the New York Stock Exchange in the 1950s and 1960s have been merged out of existence because Merrill Lynch disrupted them.

Microsoft

Its operating system was inadequate versus those of mainframe and minicomputer makers, versus UNIX, and versus Apple’s system. But its migration from DOS to Windows to Windows NT is taking the firm up-market, to the point that the UNIX world is seriously threatened. Microsoft, in turn, faces a threat from Linux. See also SQL.

Minicomputers

Companies such as Digital Equipment, Prime, Wang, Data General, and Nixdorf were new-market disruptors relative to mainframe computer makers. Their relative simplicity and low price enabled departments (particularly engineering) in organizations to have their own computers, instead of having to rely on inconvenient, centralized mainframe computers that typically were optimized for generating financial reports.

Online stock- brokers

Online trading of equities is a sustaining technology relative to the business models of discount brokers such as Ameritrade and is disruptive relative to full-service brokers such as Merrill Lynch. For Schwab, which started as a bare-bones discount broker but had moved up toward the mainstream market by the mid-1990s, Internet-based trading was disruptive enough that the company had to set up a separate division.

Online travel agencies

Enabled by electronic ticketing, online travel agencies such as Expedia and Travelocity have so badly disrupted full-service, bricks-and-mortar agencies such as American Express that many airlines have dramatically cut the substantial commissions that historically they had paid to travel agencies.

Oracle

Oracle’s relational database software was disruptive relative to that of the prior leaders, Cullinet and IBM, whose hierarchical or transactional database software ran on mainframe computers and was used to generate standard financial reports. Relational databases ran on minicomputers (and then microprocessor-based computers). Users without deep programming expertise could readily create their own custom reports and analyses using Oracle’s modular, relational architecture.

Palm Pilot, RIM BlackBerry

Handheld devices are new-market disruptions relative to notebook computers.

Personal computers

Microprocessor-based computers made by firms such as Apple, IBM, and Compaq were true new-market disruptions in that for years they were sold and used in their unique value network before they began to capture sales from higher-end professional computers.

Plastics

Plastics as a category have disrupted steel and wood, in that the “quality” of plastic parts often was inferior to those of wood and steel along the metrics by which performance was measured in traditional applications. But their low cost and ease of shaping created many new applications, and plastics have pulled many applications out of the original metal and wood value networks into the plastic network. The disruption is particularly obvious if you look at where plastics were used in automobiles thirty years ago versus today.

Portable diabetes blood glucose meters

Disrupted makers of large blood glucose testing machines in hospital laboratories, enabling patients with diabetes to monitor their own glucose levels.

Salesforce.com

This company, with its inexpensive, simple, Internet-based system, is disrupting the leading providers of customer relationship management software, such as Siebel Systems.

Seiko watches

Remember when Seiko watches were those cheap, throw-away black plastic watches? Seiko, Citizen, and Texas Instruments (which subsequently exited) disrupted the American and European watch industries.

Sonosite

This firm makes a handheld ultrasound device that now enables health care professionals who historically needed the assistance of highly trained technicians with expensive equipment to look inside the bodies of patients in their care, and thereby to provide more accurate and timely diagnoses. The company floundered for a time attempting to implement its product as a sustaining innovation. But as of the time this book was being written, it seemed to have caught its disruptive stride in an impressive way.

Sony

Sony pioneered the use of transistors in consumer electronics. Its portable radios and portable televisions disrupted firms such as RCA that made large TVs and radios using vacuum tube technology. During the 1960s and 1970s, Sony launched a series of new-market disruptions, with products such as videotape players, handheld consumer video recorders, cassette tape players, the Walkman, and the 3.5-inch floppy disk drive.

Southwest Airlines

It was a hybrid disruptor because its original strategy was to compete against driving and buses and to fly in and out of nonmainstream airports. In addition, because its prices were so low, it also took business from established airlines. Just as Wal-Mart enjoys profit protection from being in small towns whose market can support only one discount store, many of Southwest’s routes offer the same protection.

SQL database software

Microsoft’s SQL database software product is disrupting Oracle, which has moved up-market into expensive, integrated enterprise systems. Microsoft’s Access product, in turn, is disrupting SQL.

Staples

With its direct competitors Office Max and Office Depot, Staples disrupted small stationery stores as well as commercial office supplies distributors.

Steel minimills

Have been disrupting integrated mills around the world since the mid-1960s, as recounted in the text.

Sun Microsystems

Sun, Apollo (HP), and Silicon Graphics, which built their systems around RISC microprocessors, took root in essentially the same value network as minicomputers, and disrupted them. These firms, in turn, are now being disrupted by CISC microprocessor-based computer makers such as Compaq and Dell.

Toyota

Entered the U.S. market with cheap subcompact cars like the Corona. These were so inexpensive that people who historically couldn’t afford a new car now could buy one, or families could acquire a second car. Toyota now makes Lexuses, you may have noticed. Nissan has migrated from its Datsun to Infiniti, and Honda has progressed from its miniature CVCC to the Acura.

Toys ‘R Us

Disrupted the toy departments of full-service and discount department stores, which has sent them up-market into higher-margin clothing.

Ultrasound

Ultrasound technology is disruptive relative to X-ray imaging. Hewlett-Packard, Accuson, and ATL created a multibillion-dollar industry by imaging soft tissues. The leading X-ray equipment makers, including General Electric, Siemens, and Philips, became leaders in the two major radical sustaining technology revolutions in imaging: CT scanning and magnetic resonance imaging (MRI). Because ultrasound was a new-market disruption, none of the X-ray companies participated in ultrasound until very recently, when they acquired major ultrasound equipment companies.

University of Phoenix

A unit of Apollo, the University of Phoenix is disrupting four-year colleges and certain professional graduate programs. It began by providing employee training courses for businesses, often de facto, but sometimes by formal contract. Its programs have expanded into a variety of open-enrollment, degree-granting programs. Today it is one of the largest educational institutions in the United States and is one of the leading providers of online education.

Unmanned aircraft

These machines took root initially as drone targets to uncover hidden anti-aircraft emplacements. They then moved up-market into surveillance roles, and in the 2001–2002 war in Afghanistan, moved for the first time into limited weapons-carrying roles.

Vanguard

Index mutual funds have been a low-end disruption relative to managed mutual funds. At the time of this writing, Vanguard’s assets had grown to rival closely those of the former undisputed mutual fund leader, Fidelity Management.

Veritas and Network Appliance

Network-attached storage and IP storage area networks are disruptive approaches to enterprise data storage, relative to the centralized storage systems supplied by companies such as EMC. Some of these distributed networked storage systems are so simple to augment that an office assistant can simply “snap” an additional storage server onto a network.

Wireless telephony

Cellular and digital wireless phones have been on a disruptive path against wireline phones for twenty-five years. Initially they were large, power-hungry car phones with spotty efficacy, but gradually they have improved to the point where, by some estimates, nearly one-fifth of mobile telephone users have chosen to “cut the cord” and do without wireline telephone service. The viability of the wireline long-distance business is now in jeopardy.

Xerox

Photocopying has been a new-market disruption relative to offset printing, enabling nonprinters to make copies in the convenience of their workplace. Xerox’s initial machines were so expensive and complicated that they were housed in corporate photocopy centers manned by technicians.

Notes

1.   We mentioned in chapter 1 that in early stages of theory building, the best that scholars can do is suggest categories that are defined by the attributes of the phenomena. Such studies are important stepping stones in the path of progress. One such important book is Richard Foster, Innovation: The Attacker’s Advantage (New York: Summit Books, 1986). Another study predicted that the leaders will fail when an innovation entails development of completely new technological competencies. See Michael L. Tushman and Philip Anderson, “Technological Discontinuities and Organizational Environments,” Administrative Science Quarterly 31 (1986). The research of MIT Professor James M. Utterback and his colleagues on dominant designs has been particularly instrumental in moving this body of theory toward circumstance-based categorization. See, for example, James M. Utterback and William J. Abernathy, “A Dynamic Model of Process and Product Innovation” Omega 33, no. 6 (1975): 639–656; and Clayton M. Christensen, Fernando F. Suarez, and James M. Utterback, “Strategies for Survival in Fast-Changing Industries,” Management Science 44, no. 12 (2001): 207–220.

2.   Demanding customers are those customers who are willing to pay for increases on some dimension of performance—faster speeds, smaller sizes, better reliability, and so on. Less-demanding or undemanding customers are those customers who would rather make a different trade-off, accepting less performance (slower speeds, larger sizes, less reliability, and so on) in exchange for commensurately lower prices. We depict these trajectories as straight lines because empirically, when charted on semi-long graph paper, they in fact are straight, suggesting that our ability to utilize improvement increases at an exponential pace—though a pace that is shallower than the trajectory of technological progress.

3.   After watching students and managers read, interpret, and talk about this distinction between sustaining and disruptive technologies, we have observed a stunningly common human tendency to take a new concept, new data, or new way of thinking and morph it so that it fits one’s existing mental models. Hence, many people have equated our use of the term sustaining innovation with their preexisting frame of “incremental” innovation, and they have equated the term disruptive technology with the words radical, breakthrough, out-of-the-box, or different. They then conclude that disruptive ideas (as they define the term) are good and merit investment. We regret that this happens, because our findings relate to a very specific definition of disruptiveness, as stated in our text here. It is for this reason that in this book we have substituted the term disruptive innovation for the term disruptive technology—to minimize the chance that readers will twist the concept to fit into what we believe is an incorrect way of categorizing the circumstances.

4.   The Innovator’s Dilemma notes that the only times that established companies succeeded in staying atop their industries when confronted by disruptive technologies were when the established firms created a completely separate organization and gave it an unfettered charter to build a completely new business with a completely new business model. Hence, IBM was able to remain atop its industry when minicomputers disrupted mainframes because it competed in the minicomputer market with a different business unit. And when the personal computer emerged, IBM addressed that disruption by creating an autonomous business unit in Florida. Hewlett-Packard remained the leader in printers for personal computing because it created a division to make and sell ink-jet printers that was completely independent from its printer division in Boise, which made and sold laser jet printers. Since publication of The Innovator’s Dilemma, a number of companies that were faced with disruption have succeeded in becoming leaders in the wave of disruption coming at them by setting up separate organizational units to address the disruption. Charles Schwab became the leading online broker; Teradyne, the maker of semiconductor test equipment, became the leader in PC-based testers; and Intel introduced its Celeron chip, which reclaimed the low end of the microprocessor market. We hope that as more established companies learn to address disruptions through independent business units when faced with disruptive opportunities, the odds that historically were overwhelmingly favorable to entrant firms and their venture capital backers will become more favorable to established leaders who seek to create new-growth opportunities.

5.   An exception to this statement is found in Japan, where a couple of integrated mills have subsequently acquired existing minimill companies.

6.   The economists’ simple notion that price is determined at the intersection of supply and demand curves explains this phenomenon. Price gravitates to the cash cost of the marginal, or highest-cost, producer whose capacity is required for supply to meet the quantity demanded. When the marginal producers were high-cost integrated mills, minimills could make money in rebar. When the marginal, highest-cost producers were minimills, then the price of rebar collapsed. The same mechanism destroyed the temporary profitability to the minimills of each subsequent tier of the market, as described in the text that follows.

7.   That cost reduction rarely creates competitive advantage is argued persuasively in Michael Porter, “What Is Strategy?” Harvard Business Review, November–December 1996, 61–78.

8.   We recommend in particular Steven C. Wheelwright and Kim B. Clark, Revolutionizing New Product Development (New York: The Free Press, 1992); Stefan Thomke, Experimentation Matters: Unlocking the Potential of New Technologies for Innovation (Boston: Harvard Business School Press, 2003); Stefan Thomke and Eric von Hippel, “Customers as Innovators: A New Way to Create Value,” Harvard Business Review, April 2002, 74–81; and Eric von Hippel, The Sources of Innovation (New York: Oxford University Press, 1988).

9.   This model explains quite clearly why the major airline companies in the United States are so chronically unprofitable. Southwest Airlines entered as a new-market disruptor (a concept defined in chapter 3), competing within Texas for customers who otherwise would not have flown at all, but would have used automobiles and buses. The airline has grown carefully into non-major airports, staying away from head-on competition against the majors. It is the low-end disruptors to this industry—airlines with names such as Jet-Blue, AirTran, People Express, Florida Air, Reno Air, Midway, Spirit, Presidential, and many others—that create the chronic unprofitability.

When leaders in most other industries get attacked by low-end disruptors, they can run away up-market and remain profitable (and often improve profitability) for some time. The integrated steel companies fled up-market away from the minimills. The full-service department stores fled up-market into clothing, home furnishings, and cosmetics when the discount department stores attacked branded hard goods such as hardware, paint, toys, sporting goods, and kitchen utensils at the low-margin end of the merchandise mix. Today, the discount department stores such as Target and Wal-Mart are fleeing up-market into clothing, home furnishings, and cosmetics as hard goods discounters such as Circuit City, Toys ‘R Us, Staples, Home Depot, and Kitchens Etc. attack the low end; and so on.

The problem in airlines is that the majors cannot flee up-market. Their high fixed-cost structure makes it impossible to abandon the low end. Hence, low-end disruptors easily enter and attack; once one of them gets big enough, however, the major airlines declare that enough is enough, and they turn around and fight. This is why no low-end disruptor to date has survived for longer than a few years. But because low-end disruption by new companies is so easy to start, the majors can never raise low-end pricing up to levels of attractive profitability.

10.  This history is recounted in a marvelous paper by Richard S. Rosenbloom, “From Gears to Chips: The Transformation of NCR and Harris in the Digital Era,” working paper, Harvard Business School Business History Seminar, Boston, 1988.

11.  We would be foolish to claim that it is impossible to create new-growth companies with a sustaining, leap-beyond-the-competition strategy. It is more accurate to say that the odds of success are very, very low. But some sustaining entrants have succeeded. For example, EMC Corporation took the high-end data storage business away from IBM in the 1990s with a different product architecture than IBM’s. But as best we can tell, EMC’s products were better than IBM’s in the very applications that IBM served. Hewlett-Packard’s laser jet printer business was a sustaining technology relative to the dot-matrix printer, a market dominated by Epson. Yet Epson missed it. The jet engine was a radical but sustaining innovation relative to the piston aircraft engine. Two of the piston engine manufacturers, Rolls-Royce and Pratt & Whitney, navigated the transition to jets successfully. Others, such as Ford, did not. General Electric was an entrant in the jet revolution, and became very successful. These are anomalies that the theory of disruption cannot explain. Although our bias is to assume that most managers most of the time are on top of their businesses and manage them in competent ways, it is also true that sometimes managers simply fall asleep at the switch.

12.  This partially explains, for example, why Dell Computer has been such a successful disruptor—because it has raced up-market in order to compete against higher-cost makers of workstations and servers such as Sun Microsystems. Gateway, in contrast, has not prospered to the same extent even though it had a similar initial business model, because it has not moved up-market as aggressively and is stuck with undifferentiable costs selling un-differentiable computers. We believe that this insight represents a useful addendum to Professor Michael Porter’s initial notion that there are two viable types of strategy—differentiation and low cost (Michael Porter, Competitive Strategy [New York: Free Press, 1980]). The research of disruption adds a dynamic dimension to Porter’s work. Essentially, a low-cost strategy yields attractive profitability only until the higher-cost competitors have been driven from a tier in the market. Then, the low-cost competitor needs to move up so that it can compete once again against higher-cost opponents. Without the ability to move up, a low-cost strategy becomes an equal-cost strategy.

13.  See Clayton M. Christensen, The Innovator’s Dilemma (Boston: Harvard Business School Press, 1997), 130.

14.  The concept of value networks was introduced in Clayton M. Christensen, “Value Networks and the Impetus to Innovate,” chapter 2 in The Innovator’s Dilemma. Professor Richard S. Rosenbloom of the Harvard Business School originally identified the existence of value networks when he advised Christensen’s early research. In many ways, the situation in a value network corresponds to a “Nash equilibrium,” developed by Nobel laureate John Nash (who became even more renowned through the movie A Beautiful Mind). In a Nash equilibrium, given Company A’s understanding of the optimal, self-interested (maximum-profit) strategy of each of the other companies in the system, Company A cannot see any better strategy for itself than the one it presently is pursuing. The same holds true for all other companies in the system. Hence, none of the companies is motivated to change course, and the entire system therefore is relatively inert to change. Insofar as the companies within a value network are in a Nash equilibrium, it creates a drag that constrains how fast customers can begin utilizing new innovations. This application of Nash equilibriums to the uptake of innovations was recently introduced in Bhaskar Chakravorti, The Slow Pace of Fast Change (Boston: Harvard Business School Press, 2003). Although Chakravorti did not make the linkage himself, his concept is a good way to visualize two things about the disruptive innovation model. It explains why the pace of technological progress outstrips the abilities of customers to utilize the progress. It also explains why competing against nonconsumption, creating a completely new value network, is often in the long run an easier way to attack an established market.

15.  Some people have concluded on occasion that when the incumbent leader doesn’t instantly get killed by a disruption, the forces of disruption somehow have ceased to operate, and that the attackers are being held at bay. (See, for example, Constantinos Charitou and Constantinos Markides, “Responses to Disruptive Strategic Innovation,” MIT Sloan Management Review, Winter 2003, 55.) These conclusions reflect a shallow understanding of the phenomenon, because disruption is a process and not an event. The forces are operating all of the time in every industry. In some industries it might take decades for the forces to work their way through an industry. In other instances it might take a few years. But the forces—which really are the pursuit of the profit that is associated with competitive advantage—are always at work. Similarly, other writers on occasion have noticed that the leader in an industry actually did not get killed by a disruption, but skillfully caught the wave. They then conclude that the theory of disruption is false. This is erroneous logic as well. When we see an airplane fly, it does not disprove the law of gravity. Gravity continues to exert force on the flying plane—it’s just that engineers figured out how to deal with the force. When we see a company succeed at disruption, it is because the management team figured out how to harness the forces to facilitate success.

16.  See Clayton M. Christensen and Richard S. Tedlow, “Patterns of Disruption in Retailing,” Harvard Business Review, January–February 2000, 42– 45.

17.  Ultimately, Wal-Mart was able to create processes that turned assets faster than Kmart. This allowed it to earn higher returns at comparable gross profit margins, giving Wal-Mart a higher sustainable growth rate.

18.  The reason it is so much easier for firms in the position of the full-service department stores to flee from the disruption rather than stand to fight it is that in the near term, inventory and asset turns are hard to change. The full-service department stores offered to customers a much broader product selection (more SKUs per category), which inevitably depressed inventory turns. Discounters not only offered a narrower range of products that focused only on the fastest-turning items, but also their physical infrastructure typically put all merchandise on the sales floor. Department stores, in contrast, often had to maintain stockrooms to provide back-up for the limited quantities of any given item that could be placed on their SKU-laden shelves. Hence, when disruptive discounters invaded a tier of their merchandise mix from below, the department stores could not readily drop margins and accelerate turns. Moving up-market where margins still were adequate was always the more feasible and attractive alternative.

19.  Low-end disruptions are a direct example of what economist Joseph Schum-peter termed “creative destruction.” Low-end disruptions create a step-change cost reduction within an industry—but it is achieved by entrant firms destroying the incumbents. New-market disruption, in contrast, entails a period of substantial creative creation—new consumption—before the destruction of the old occurs

20.  For a deeper exploration of the macroeconomic impact of disruption, see Clayton M. Christensen, Stuart L. Hart, and Thomas Craig, “The Great Disruption,” Foreign Affairs 80, no. 2 (March–April 2001): 80–95; and Stuart L. Hart and Clayton M. Christensen, “The Great Leap: Driving Innovation from the Base of the Pyramid,” MIT Sloan Management Review, Fall 2002, 51–56. The Foreign Affairs paper asserts that disruption was the fundamental engine of Japan’s economic miracle of the 1960s, 1970s, and 1980s. Like other companies, these disruptors—Sony, Toyota, Nippon Steel, Canon, Seiko, Honda, and others—have soared to the high end, now producing some of the world’s highest-quality products in their respective markets. Like the American and European companies that they disrupted, Japan’s giants are now stuck at the high end of their markets, where there is no growth. The reason America’s economy did not stagnate for an extended period after its leading companies got pinned to the high end was that people could leave those companies, pick up venture capital on the way down, and start new waves of disruptive growth. Japan’s economy, in contrast, lacks the labor market mobility and the venture capital infrastructure to enable this. Hence, Japan played the disruptive game once and profited handsomely. But it is stuck. There truly seem to be microeconomic roots to the country’s macroeconomic malaise. The Sloan paper builds upon the Foreign Affairs piece, asserting that today’s developing nations are an ideal initial market for many disruptive innovations, and that disruption is a viable economic development policy.

21.  Our choice of wording in this paragraph is important. When customers cannot differentiate products from each other on any dimension that they can value, then price is often the customer’s basis of choice. We would not say, however, that when a consumer buys the lowest-priced alternative, the axis of competition is cost based. The right question to ask is whether customers will be willing to pay higher prices for further improvements in functionality, reliability, or convenience. As long as customers reward improvements with commensurately higher prices, we take it as evidence that the pace of performance improvement has not yet overshot what customers can use. When the marginal utility that customers receive from additional improvements on any of these dimensions approaches zero, then cost is truly the basis of competition.

22.  We emphasize the term product strategy in this sentence because there certainly seems to be scope for two other low-end disruptive plays in this market. One would be a private-label strategy to disrupt the Hewlett-Packard brand. The other would be a low-cost distribution strategy through an online retailer such as Dell Computer.

23.  There actually is a fourth strategy to be evaluated here—making components for sale to Hewlett-Packard and its subsystem suppliers. We will discuss this strategy at greater length in chapters 4 and 5.

24.  Matsushita, in fact, attempted entry with a sustaining strategy of exactly this sort in the 1990s. Despite its strong Panasonic brand and its world-class capabilities in assembling electromechanical products, the company has been bloodied and has captured minimal market share.

CHAPTER THREE

WHAT PRODUCTS WILL

CUSTOMERS WANT TO BUY?

What products should we develop as we execute our disruptive strategy? Which market segments should we focus upon? How can we know for sure, in advance, what product features and functions the customers in those segments will and will not value? How should we communicate the benefits of our products to our customers, and what brand-building strategy can best create enduring value?

All companies face the continual challenge of defining and developing products that customers will scramble to buy. But despite the best efforts of remarkably talented people, most attempts to create successful new products fail. Over 60 percent of all new-product development efforts are scuttled before they ever reach the market. Of the 40 percent that do see the light of day, 40 percent fail to become profitable and are withdrawn from the market. By the time you add it all up, three-quarters of the money spent in product development investments results in products that do not succeed commercially.[1] These development efforts are all launched with the expectation of success, but they seem to flourish or flop in unexpected ways. Once again, we argue that the failures are really not random at all: They are predictable—and avoidable—if managers get the categorization stage of theory right. Of the many dimensions of business building, the challenge of creating products that large numbers of customers will buy at profitable prices screams out for accurately predictive theory.

The process that marketers call market segmentation is, in our parlance, the categorization stage of theory building. Only if managers define market segments that correspond to the circumstances in which customers find themselves when making purchasing decisions can they accurately theorize which products will connect with their customers. When managers segment markets in ways that are mis-aligned with those circumstances, market segmentation can actually cause them to fail—essentially because it leads managers to aim their new products at phantom targets.

We begin this chapter by describing a way to think about market segmentation that might differ from what you’ve seen before. We believe that this approach, based on the notion that customers “hire” products to do specific “jobs,” can help managers segment their markets to mirror the way their customers experience life. In so doing, this approach can also uncover opportunities for disruptive innovation.

We will then crawl beneath this concept of segmentation and explore the forces that cause even the best managers to segment their markets erroneously. A lot of marketers actually know how to do what we urge in this chapter. The problem is that predictable forces in operating companies cause companies to segment markets in counterproductive ways. Finally, we show how segmenting markets according to the jobs that customers are trying to get done addresses other important marketing challenges—such as brand management and product positioning—to help disruptive businesses grow. Taken together, this set of insights constitutes a theory of how to connect disruptive innovations with the right customers in order first to create a foothold in a market and then to grow profitably along the sustaining trajectory into market-dominating products and services.

Pomp and Circumstances in Segmenting Markets

Much of the art of marketing focuses on segmentation: identifying groups of customers that are similar enough that the same product or service will appeal to all of them.[2] Marketers often segment markets by product type, by price point, or by the demographics and psychographics of the individuals or companies who are their customers. With all the effort expended on segmentation, why do the innovation strategies based on these categorization or segmentation schemes fail so frequently? The reason, in our view, is that these delineations are defined by the attributes of products and customers. As we see over and over in this book, theories based on attribute-based categorizations can reveal correlations between attributes and outcomes. But it is only when marketing theory offers a plausible statement of causality and is built upon circumstance-based categorization (segmentation) schemes that managers can confidently assert what features, functions, and positioning will cause customers to buy a product.

Predictable marketing requires an understanding of the circumstances in which customers buy or use things. Specifically, customers—people and companies—have “jobs” that arise regularly and need to get done. When customers become aware of a job that they need to get done in their lives, they look around for a product or service that they can “hire” to get the job done. This is how customers experience life. Their thought processes originate with an awareness of needing to get something done, and then they set out to hire something or someone to do the job as effectively, conveniently, and inexpensively as possible. The functional, emotional, and social dimensions of the jobs that customers need to get done constitute the circumstances in which they buy. In other words, the jobs that customers are trying to get done or the outcomes that they are trying to achieve constitute a circumstance-based categorization of markets.[3] Companies that target their products at the circumstances in which customers find themselves, rather than at the customers themselves, are those that can launch predictably successful products. Put another way, the critical unit of analysis is the circumstance and not the customer.

To see why this is so, consider a quick-service restaurant chain’s effort to improve its milkshake sales and profits.[4] This chain’s marketers segmented its customers along a variety of psychobehavioral dimensions in order to define a profile of the customer most likely to buy milkshakes. In other words, it first structured its market by product— milkshakes—and then segmented it by the characteristics of existing milkshake customers. These are both attribute-based categorization schemes. It then assembled panels of people with these attributes, and explored whether making the shakes thicker, chocolatier, cheaper, or chunkier would satisfy them better. The chain got clear inputs on what the customers wanted, but none of the improvements to the product significantly altered sales or profits.

A new set of researchers then came in to understand what customers were trying to get done for themselves when they “hired” a milkshake, and this approach helped the chain’s managers see things that traditional market research had missed. To learn what customers sought when they hired a milkshake, the researchers spent an eighteen-hour day in a restaurant carefully chronicling who bought milkshakes. They recorded the time of each milkshake purchase, what other products the customer purchased, whether the customer was alone or with a group, whether he or she consumed it on the premises or drove off with it, and so on. The most surprising insight from this work was that nearly half of all milkshakes were bought in the early morning. Most often, the milkshake was the only item these customers purchased, and it was rarely consumed in the restaurant.

The researchers returned to interview customers who purchased a morning milkshake to understand what they were trying to get done when they bought it, and they asked what other products they hired instead of a milkshake on other days when they had to get the same job done. Most of these morning milkshake customers had hired it to achieve a similar set of outcomes. They faced a long, boring commute and needed something to make the commute more interesting! They were “multitasking”—they weren’t yet hungry, but knew that if they did not eat something now, they would be hungry by 10:00. They also faced constraints. They were in a hurry, were often wearing their work clothes, and at most had only one free hand.

When these customers looked around for something to hire to get this job done, sometimes they bought bagels. But bagels got crumbs all over their clothes and the car. If the bagels were topped with cream cheese or jam, their fingers and the steering wheel got sticky. Sometimes they hired a banana to do the job, but it got eaten too fast and did not solve the boring commute problem. The sorts of sausage, ham, or egg sandwiches that the restaurant also sold for breakfast made their hands and the steering wheel greasy, and if customers tried to drag out the time they took to eat the sandwich, it got cold. Doughnuts didn’t last through the 10:00 hunger attack. It turned out that the milkshake did the job better than almost any available alternative. If managed competently, it could take as long as twenty minutes to suck the viscous milkshake through the thin straw, addressing the boring commute problem. It could be eaten cleanly with one hand with little risk of spillage, and the customers felt less hungry after consuming the shake than after using most of the alternatives. Customers were not satisfied that the shake was healthy food, but it didn’t matter because becoming healthy wasn’t the job for which they were hiring the product.[5]

The researchers observed that at other times of the day, it was often parents who purchased milkshakes, in addition to a complete meal, for their children. What job were they trying to get done? They were emotionally exhausted from repeatedly having to say “No” to their kids all day, and they just needed to feel like they were reasonable parents. They hired milkshakes as an innocuous way to placate their children and to feel like they were loving parents. The researchers observed that the milkshakes didn’t do this job very well, though. They saw parents waiting impatiently after they had finished their own meal while their children struggled to suck the thick milkshake up the thin straw. Many were discarded half-full when the parents declared that time had run out.

Segmenting the market along demographic or psychographic lines indeed provides information on individual customers.[6] But the same busy father who needs a viscous, time-consuming milkshake in the morning needs something very different later in the day for his child. When researchers asked customers who have multiple jobs in their lives what attributes of the milkshake they should improve upon, and when the researchers then averaged each consumer’s response with those of others in the same demographic or psychographic segment, it led to a one-size-fits-none product that didn’t do well any of the jobs that customers were trying to get done.[7]

Who is the quick-service chain really competing against in the morning? Its statistics compare its sales with the milkshake sales of competing chains. But in the customers’ minds, the morning milkshake competes against boredom, bagels, bananas, doughnuts, instant breakfast drinks, and possibly coffee. In the evening, milkshakes compete against cookies, ice cream, and promised purchases in the future that parents hope their children won’t remember.

Knowing what job a product gets hired to do (and knowing what jobs are out there that aren’t getting done very well) can give innovators a much clearer road map for improving their products to beat the true competition from the customer’s perspective—in every dimension of the job. To tackle the boring commute job, for example, the chain’s managers could swirl in tiny chunks of real fruit. This would nail the boring commute job even better, because the drivers would at random suck crisp, flavorful chunks into their mouths, adding a dimension of unpredictability and anticipation to a monotonous morning routine. (Remember, fruit might make it healthier, but improving health is not the primary job that the shake gets hired to do.) The chain could make the shake even thicker, so it would last longer. And they could set up a self-service machine in each restaurant that customers could operate with a prepaid card, to get in and out fast.

Addressing the evening job-to-be-done would entail a very different product—one with lower viscosity for quicker consumption, and served in a small, entertainingly designed container. It would be an inexpensive add-on to the bundled children’s meal, so that when a child begged the parent for it, the parent could readily say “OK” with little forethought.

If the restaurant chain implemented innovations such as these that really helped get the jobs done and discarded improvements that were irrelevant to the jobs that the product is hired to do, it would succeed—but not by capturing milkshake sales from competing quick-service chains or by cannibalizing other products on its menu. Rather, the growth would come by taking share from products in other categories that customers sometimes employed, with limited satisfaction, to get their particular jobs done. And perhaps more important, the products would find new growth among “nonconsumers.” Competing against nonconsumption often offers the biggest source of growth in a world of one-size-fits-all products that do no jobs satisfactorily. We will return to this topic in chapter 4.

Using Circumstance-Based Segmentation

to Gain a Disruptive Foothold

The first time that builders of a new-growth business need to assess what the target customers really are trying to get done is when they are searching for the disruptive foothold—the initial product or service that is the point of entry for a new-market disruption. When managers position a disruptive product squarely on a job that has been poorly addressed in the past that a lot of people are trying to get done, they create a launch pad for subsequent growth through sustaining innovations that build on the initial platform.[8]

How can managers identify these foothold opportunities? It may never be possible to get every dimension of a product introduction in a new-market disruption right at the outset, which makes it very important to use the methods of strategy discovery we outline in chapter 8. We believe, however, that a jobs-to-be-done lens can help innovators come to market with an initial product that is much closer to what customers ultimately will discover that they value. The way to get as close as possible to this target is to develop hypotheses by carefully observing what people seem to be trying to achieve for themselves, and then to ask them about it.[9]

Sony’s founder, Akio Morita, was a master at watching what consumers were trying to get done and at marrying those insights with solutions that helped them do the job better. Between 1950 and 1982, Sony successfully built twelve different new-market disruptive growth businesses. These included the original battery-powered pocket transistor radio, launched in 1955, and the first portable solid-state black-and-white television, in 1959. They also included videocassette players; portable video recorders; the now-ubiquitous Walkman, introduced in 1979; and 3.5-inch floppy disk drives, launched in 1981. How did Sony find these foothold applications that yielded such tremendous up-side fruit?

Every new-product launch decision during this era was made personally by Morita and a trusted group of about five associates. They searched for disruptive footholds by observing and questioning what people really were trying to get done. They looked for ways that miniaturized, solid-state electronics technology might help a larger population of less-skilled and less-affluent people to accomplish, more conveniently and at less expense, the jobs they were already trying to get done through awkward, unsatisfactory means. Morita and his team had an extraordinary track record in finding these footholds for disruption.

Interestingly, 1981 signaled the end of Sony’s disruptive odyssey, and for the next eighteen years the company did not launch a single new disruptive growth business. The company continued to be innovative, but its innovations were sustaining in character—they were better products targeted at existing markets. Sony’s PlayStation, for example, is a great product, but it was a late entrant into a well-established market. Likewise, its Vaio notebook computers are great products, but they too were late entrants into a well-established market.

What caused this abrupt shift in Sony’s innovation strategy? In the early 1980s Morita began to withdraw from active management of the company in order to involve himself in Japanese politics.[10] To take his place, Sony began to employ marketers with MBA’s to help identify new-growth opportunities. The MBA’s brought with them sophisticated, quantitative, attribute-based techniques for segmenting markets and assessing market potential. Although these methods uncovered some underserved opportunities on trajectories of sustaining improvement in established markets, they were weak at synthesizing insights from intuitive observation. In searching for an initial product foothold in new-market disruption, observation and questioning to determine what customers are trying to do, coupled with strategies of rapid development and fast feedback, can greatly improve the probability that a company’s products will converge quickly upon a job that people are trying to get done.

Innovations That Will Sustain the Disruption

Gaining a foothold is just the first battle in the war. The exciting growth happens when an innovation improves in ways that allow it to displace incumbent offerings. These are sustaining improvements, relative to the initial innovation: improvements that stretch to meet the needs of more and more profitable customers.

With low-end disruptions, it can be easy to determine the right sequence of product improvements in the up-market march. After the steel minimills established their foothold in the rebar market, for example, the next logical step was fairly obvious: Tackle angle iron and thicker bars and rods—the grades of steel that were just above rebar. For Target Stores, the goal was to replicate the product line, brands, and ambiance that previously were only available in expensive, full-service department stores. The low-end disruptor’s marketing task is to extend the lower-cost business model up toward products that do the jobs that more profitable customers are trying to get done.

With new-market disruptions, in contrast, the challenge is to invent the upward path, because nobody has been up that trajectory before. Choosing the right improvements is critical to the disruptive march up-market. Here again, job-based segmentation logic can help.

Let’s examine one of the hottest markets of the last decade—hand-held wireless electronic devices. The BlackBerry, a handheld wireless e-mail device made by the Canadian company Research in Motion (RIM), is an important competitor in this field. RIM found the BlackBerry’s disruptive foothold at a new spot on the third axis in the disruption diagram, competing against nonconsumption by bringing the ability to receive and send e-mail to new contexts such as waiting lines, public transit, and conference rooms. So what’s next? How does RIM sustain the product improvement and growth trajectory for its BlackBerry? Surely, dozens of new ideas are pouring into RIM executives’ offices every month for improvements that might be introduced in the next-generation BlackBerry. Which of these ideas should RIM invest in, and which should it ignore? These are crucial decisions, with hundreds of millions of dollars in profits at stake in a rapidly growing market.

RIM’s executives could believe that their market is structured by product categories characterized by some moniker such as “We compete in handheld wireless devices.” If so, they will see the BlackBerry as competing against products such as the Palm Pilot, Handspring’s Treo, Sony’s Clié, mobile telephone handsets made by Nokia, Motorola, and Samsung, and Microsoft Pocket-PC-based devices such as Compaq’s I-Paq and Hewlett-Packard’s Jordana. In order to get ahead of these competitors, RIM would need to develop better products faster than the competition. Sony’s Clié, for example, has a digital camera. Nokia’s phones offer not just live conversation and voice messages, but short text messaging as well. The Palm Pilot’s consummately convenient calendaring, rolodexing, and note-keeping features have almost become industry standards. And does the fact that Compaq and Hewlett-Packard offer stripped-down versions of Word and Excel software mean that RIM will be left behind if it does not follow suit?

Defining the market by the characteristics of the product causes managers to think that in order to beat the competition, RIM would need to build some number of these features into its next-generation BlackBerry device. RIM’s competitors, of course, would be thinking the same thing—all trying to cram their competitors’ superior features into their products in a race to get ahead of the pack. As suggested in table 3-1, our worry is that defining market segments in a product-based way actually causes a headlong, arms race–like rush toward undifferentiable, one-size-fits-all products that perform poorly any specific jobs that customers might hire them to do.

Alternatively, RIM’s executives might segment their market in demographic terms—targeting the business traveler, for example—and then add to the BlackBerry those product improvements that would meet those customers’ needs. This framing would lead RIM to consider a very different set of innovations. Stripped-down customer relationship management (CRM) software might be considered essential, because it would allow salespeople to review account histories and order status quickly before contacting customers. Downloadable electronic books and magazines would obviate customers’ having to carry bulky reading material in their briefcases. Wireless Internet access, with the attendant capabilities to alter travel reservations, trade stocks, and find restaurants via global positioning satellites, could be very appealing. Expense-reporting software coupled with the ability to transmit reports to headquarters wirelessly might be a must.

Every executive who has participated in decisions to define and fund innovation projects will empathize with the tortured difficulty of answering questions such as these. No wonder that many have come to regard innovation as a random crap shoot—or worse, a game of Russian roulette.

TABLE 3 - 1

How You View the Market for Handheld Devices Will Determine What Product Features You Consider to Be Relevant

Product View

Demographic View

Job-to-Be-Done View

Market Definition

The handheld wireless device market

Market Definition

The traveling salesperson

Market Definition

Use small snippets of time productively

Competitors

Palm Pilot, Handspring Treo, Sony Clié, HP Jordana, Compaq I-Paq, wireless phones

Competitors

Notebook computers, wireline Internet access, wireless and wireline telephones

Competitors

Wireless telephones, Wall Street Journal , CNN Airport News, listening to boring presentations, doing nothing

Features to consider

Digital camera

Features to consider

Wireless Internet access; bandwidth for data

Features to consider

E-mail

Word

Voice mail

Downloadable CRM

Excel

data/functionality

Voice phone

Outlook

Wireless access to online

Headline news, frequent

travel agencies

updates

Voice phone

Online stock trading

Simple, single-player games

Organizer

E-books and e-technical

Entertaining “top ten” lists

Handwriting recognition

manuals

Always on

E-mail

Voice

But what if RIM structured the segments of this market according to the jobs that people are trying to get done? We’ve not conducted serious research on this, but just from watching people who pull out their BlackBerries, it seems to us that most of them are hiring it to help them be productive in small snippets of time that otherwise would be wasted. You see BlackBerry owners reading e-mails while waiting in line at airports. When an executive puts an always-on BlackBerry on the table in a meeting, what is she trying to do? Just in case the meeting gets a little slow or boring, she wants to be able to glance through a few messages unobtrusively, just to be a bit more productive. When the pace of the meeting picks up, she can slide the BlackBerry aside and pay attention again.

What is the BlackBerry competing against? What gets hired when people need to be productive in small snippets of time and they don’t pick up a BlackBerry? They often pick up a wireless phone. Sometimes they pick up the Wall Street Journal. Sometimes they make notes to themselves. Sometimes they stare mindlessly at the CNN Airport Network, or sit with glazed eyes in a boring meeting. From the customer’s point of view, these are the BlackBerry’s most direct competitors.

What improvements on the basic BlackBerry wireless e-mail platform does this framing of the market imply? Word, Excel, and CRM software are probably out—it’s just really hard to boot up, shift mental gears, be productive, and gear down these activities within a five-minute snippet of time. Snap-on digital cameras likewise aren’t likely to be hired to get this job done.

However, wireless telephony is a no-brainer for RIM, because leaving and returning voice messages is another way to be productive in small snippets of time. Financial news headlines and stock quotes would help the BlackBerry compete more effectively against the Wall Street Journal. And mindless, single-player games or automatically downloaded Letterman-like lists of ten might help the BlackBerry gain share against boredom. Viewing the market in terms of the jobs that its customers are trying to get done would define for RIM an innovation agenda that is grounded in the way its customers live their lives. The good news for RIM shareholders is that this appears to be the trajectory the BlackBerry is on.[11]

Doing this make-me-productive-in-small-snippets-of-time job perfectly is not trivial, of course. Adding voice telephony to the BlackBerry would increase power consumption. This, however, is the type of challenge classically associated with sustaining innovation. RIM’s biggest issue is probably not a lack of engineering talent; it is deciding which problems it should deploy that talent against.[12]

What should Palm do? In the context of the job that the BlackBerry is hired to do, a camera makes no sense. But might it make sense on a product like the Palm Pilot that is used to keep track of people? In addition to just displaying a name card, a camera would enable users to store the person’s image as well—helping Palm Pilot users be better organized by remembering not just people’s names but their faces, too.[13]

In the Japanese mobile phone market, the strategies of mobile telephony providers J-Phone and NTT DoCoMo to add a camera and photo viewer to the mobile phone and to provide the data services required to send and receive low-quality digital photos met with instant success in the early 2000s. Why? A few years earlier these firms had created a booming new-market disruption selling wireless Internet access through services like DoCoMo’s I-Mode. Their customers were primarily teenagers, who had hired mobile access to the Internet in order to have fun with their friends downloading wallpaper and ring tones. The popularity of limited-functionality cameras and photo viewers on these teenagers’ phones makes sense when viewed through the lens of jobs to be done: Mobile phones that send and receive photos offer these young people more and newer kinds of fun.

Should European and North American service and handset providers attempt to emulate this success by incorporating this functionality in their phones? At this writing, we expect camera-equipped phones to take off much more slowly in these markets, because many mobile phone users in these markets are adults who seem to have hired mobile phones to get work done or exchange important information in small snippets of time. Cameras and viewers rarely help get these jobs done better. If these companies were to market phones and these services to teenagers and children as a new way to have fun by taking and transmitting images, this product feature could create substantial growth. But if they follow their demonstrated propensity to deploy the functionality as a high-priced feature on phones that serious multitasking adults have hired to get down to business rather than play, our bet is that little growth will result.

If RIM evolved the BlackBerry to help people be ever more productive in small snippets of time, if Palm evolved its Pilot to help people be ever better organized, and if J-Phone’s handsets were optimized to help teenagers have fun, the products would become quite differentiated in consumers’ minds—and each could grow to own a large market share of its respective job. And because these different jobs arise at different points in time and space in consumers’ lives, we’d bet that for a very long time most consumers would opt to own each product individually rather than having a single, Swiss army knife–like device—that is, until a one-size-fits-all device can do all these jobs without compromising functionality, simplicity, and convenience.

Unfortunately, it appears that many manufacturers in this space are now on a collision course. Each seems bent on packing every other competitor’s functionality into a single, all-purpose device. Unchecked, this will lead to commoditized, undifferentiated products that don’t do really well any of the jobs that they once got hired to do. This need not be so. The suicidal trajectory results from framing the market in terms of the attributes of products and the attributes of customers, rather than in terms of jobs to be done.

Why Do Executives Segment Markets Counterproductively?

In many ways, what we have said to this point is not news—or at least it shouldn’t be. Good researchers have written persuasively, using their own vocabulary, that a jobs-to-be-done perspective is the only way to see accurately what products and services customers will value in the future, and why.[14] Indeed, all executives would say that they dream of dominating their market with a highly differentiated product. And most marketers will claim that the very purpose of their work is to understand what customers do with their products.

In the face of such desires and beliefs, why do so many managers instead seem to rush headlong in the other direction, basing product improvement trajectories on attribute-based segmentation schemes that lead to undifferentiated, one-size-fits-all products? There are at least four reasons or countervailing forces in established companies that cause managers to target innovations at attribute-based market segments that are not aligned with the way that customers live their lives. The first two reasons—the fear of focus and the demand for crisp quantification—reside in companies’ resource allocation processes. The third reason is that the structure of many retail channels is attribute focused, and the fourth is that advertising economics influence companies to target products at customers rather than circumstances.

Fear of Focus

One reason why it is difficult to create packages of products and services that do particular jobs well is that the more clearly a product is focused on getting a specific job done perfectly, the less appealing it might become when hired for other jobs. Clarifying what job a product should be hired to do, unfortunately, often clarifies what it should not be hired to do. Focus helps and it hurts—and it is easier to quantify the hurt than the help.

This is an especially vexing issue for companies such as RIM, Palm, Nokia, and HP as they chart course into a seemingly uncertain future. Each company is more or less positioned, for now, on a specific job: RIM’s BlackBerry and Nokia in killing time productively, Palm’s Pilot in keeping folks organized, and HP in stripped-down access to computer-based tasks.

If they define their market in terms of the product category, the most tangible growth opportunities are customers and applications that already have been captured by the other companies. So RIM looks to organizer software to help it steal Palm’s customers, even as Palm wrestles with ways to make its Pilot a mobile e-mail device.[15] If these companies frame the market as a product category, then not to pack all these features into the product indeed seems to sacrifice growth potential.

In contrast, a theory of growth that is grounded on circumstance-based categories—jobs to be done—would lead RIM not to copy most features in other handheld devices. This is because the real competition comes from newspapers, mobile phones, CNN Airport Network, and plain old boredom. There is exciting growth potential within this job, if RIM can improve its product so that it does the job better than the real competition. It would grow the size of the product category by stealing share from competitors that are outside the category. Furthermore, pursuing this trajectory of improvement would enhance, rather than destroy, RIM’s product differentiation and its consequent ability to sustain profit margins.

Focus is scary—until you realize that it only means turning your back on markets you could never have anyway. Sharp focus on jobs that customers are trying to get done holds the promise of greatly improving the odds of success in new-product development.

Senior Executives’ Demand for Quantification of Opportunities

The job that line executives often hire market research to do in the resource allocation process is to define the size of the opportunity, not to understand how customers and markets work.

The information technology (IT) systems in most companies collect, aggregate, and summarize data in various ways to help managers make better decisions. The reports are undoubtedly helpful, but they also lead companies to develop new products and services destined to fail in the marketplace. Almost all corporate IT reports are structured around one of three constructs: products, customers, and organizational units. The data show managers how much of each product is being sold, how profitable each is, which customers are buying which products, and what costs and revenues are associated with servicing each customer. IT systems also report revenues and costs by business units, so that managers can measure the success of the organizations for which they have responsibility.

The odds of developing successful new products begin to tumble when managers collectively begin to assume that the customer’s world is structured in the same way that the data are aggregated. When managers define market segments along the lines for which data are available rather than the jobs that customers need to get done, it becomes impossible to predict whether a product idea will connect with an important customer job. Using these data to define market segments causes managers to aim innovation at phantom targets. When they frame the customer’s world in terms of products, innovators start racing against competitors by proliferating features, functions, and flavors of products that mean little to customers.[16] Framing markets in terms of customer demographics, they average across several different jobs that arise in customers’ lives and develop one-size-fits-all products that rarely leave most customers fully satisfied. And framing markets in terms of an organization’s boundaries further restricts innovators’ abilities to develop products that will truly help their customers get the job done perfectly.

Like it or not, although market researchers often develop a solid understanding of the jobs that customers are trying to do, the primary language through which the nature of the opportunity must be described in the resource allocation process is the language of market size. Asking marketers to understand this concept is not the solution to the problem—because whether it is called “marketing myopia” or jobs-to-be-done, this concept has been taught before.[17] It is a process problem. Because senior managers typically hire market research to quantify the size of opportunities rather than to understand the customer, the resource allocation process systematically and predictably perverts companies’ concept of the structure of their market so that it ultimately conforms to the lines along which data are available.

As a result, corporate IT systems and the CIOs who administer them figure among the most important contributors to failure in innovation. Data purchased from external sources have the same impact, because they are structured by product attributes, not by job. The readily available data actually obfuscate the paths to growth.

The solution is not to use data that are collected for historical performance measurement purposes in the processes of new-product development. Keep such data quarantined: They are the wrong data for the job. The size and nature of job-based or circumstance-based market categories actually can be quantified, but this entails a different research process and statistical methodology than is typically employed in most market quantification efforts.[18]

The Structure of Channels

Many retail and distribution channels are organized by product categories rather than according to the jobs that customers need to get done.[19] This channel structure limits innovators’ flexibility in focusing their products on jobs that need to be done, because products need to be slotted into the product categories to which shelf space has been allocated.

As an illustration of this challenge, a manufacturer of power tools observed that when hanging a door, tradesmen used at least seven different tools, none of which were job specific, and wasted a lot of time picking up these tools and putting them down. The company developed a new tool concept positioned on the job that made it much easier to hang doors accurately. However, it could not be categorized as a plane, a chisel, a screwdriver, a drill, a level, or a hammer. When the company presented the product to the tool buyer of a major retail chain, the buyer responded, “Look. I have a job to do. Here’s the plan-o-gram for my shelf space. I buy drills, sanders, and saws. The vendor that offers the most horsepower at a price point gets the space. Your product doesn’t help me.”

This phenomenon leads many new-market disruptors to seek new channels to the customer—a topic we address in chapter 4. If the product is disruptive to the established retail or wholesale channels because it doesn’t help those institutions make more money in the way they are structured to make money, they won’t sell it. Consequently, successful disruptive innovators often find that their product must enable a new class of retailers, distributors, or value-added resellers to move up-market and disrupt established channels.[20]

Solving this problem by devising a new channel that is structured and motivated to sell the disruptive, job-positioned product seems ludicrous to executives who need innovations to grow very big, very fast. Doesn’t a big established channel promise a much faster ramp to volume? Ironically, it often does not. Finding or building new channels often means turning your back on profits that probably would not have materialized in existing channels anyway.

Advertising Economics and Brand Strategies

The fourth reason why marketing executives tend to segment markets by product or customer attributes is to facilitate communication with customers. It seems easier to devise a communications strategy and to choose the most cost-effective marketing media buys if consumer markets are sliced along dimensions such as age, sex, lifestyle, or product category. The same seems true if marketers slice commercial markets by geography, industry, or size of business. But when communication strategies drive segmentation schemes, the attributes of the targeted customers can confuse the product development process, causing companies to develop products that do several jobs poorly, and none perfectly.

Think back to our example of the quick-service food restaurant’s milkshakes, and consider a member of a demographic segment—a forty-year-old married man with two young sweet-toothed children, who also has a long, boring commute to work and gets hungry at lunchtime. What and how should the chain communicate to this customer? If it tells him that he can quickly buy a viscous, interestingly chunky milkshake from a self-serve machine when he needs something to keep his hands busy during his boring commute, how can the chain also tell him that he should come back to hire a small liquid shake when he needs to capitulate to his children? Or drop by to hire a hamburger when feed-me-fast-at-lunchtime is the job? Sending separate communications about each of these jobs to the same customer is prohibitively expensive, and yet communicating all of them to the customer at once would be confusing. So what’s the chain to do?

The answer is that just as it needs to develop products for the circumstance and not the customer, the chain needs to communicate to the circumstance, and not necessarily to the consumer. It can communicate to the circumstance with a brand, if it employs the right branding strategy. If it does this, then when customers find themselves in the circumstance, they will think instinctively of the brand and know what product to buy in order to get that job done.

Brands are, at the beginning, hollow words into which marketers stuff meaning. If a brand’s meaning is positioned on a job to be done, then when the job arises in a customer’s life, he or she will remember the brand and hire the product. Customers pay significant premiums for brands that do a job well.

Some executives worry that a low-end disruptive product might harm their established brand. They can escape this problem by appending a second word to their corporate brand. We call this word a purpose brand because it communicates to a circumstance—to a job that the disruptive product should be hired to do. If customers hire a disruptive product to do the wrong job, it will disappoint and thereby tarnish the corporation’s brand.[21] If the disruptive product is hired for the job that it was designed to do, it will delight the customer and thereby strengthen the corporate brand—even though the disruptive product’s functionality may not be as good as that of mainstream products. This is because customers define quality within the context of the job to be done.

Let’s examine Kodak’s experience when it launched single-use cameras, which were a classic new-market disruption. Because of their inexpensive plastic lenses, the quality of photographs taken with single-use cameras was not as good as the photos taken by good 35mm cameras. As a result, the proposition to launch a single-use camera business encountered vigorous opposition within Kodak’s film division. The corporation finally gave responsibility for the opportunity to a completely different organizational unit, which launched single-use cameras with a purpose brand—the Kodak Fun-saver. This was a product to be hired when customers needed to save memories of fun occasions but had forgotten to bring a camera. The Funsaver camera competed against nonconsumption. Customers whose basis of comparison was to have no photos at all were delighted with the quality of this solution to saving their fun. Creating a purpose brand for a disruptive job differentiated the product, clarified its intended use, delighted the customers, and thereby strengthened the Kodak brand.

Marriott Corporation has done the same thing by developing a brand architecture that is consistent with several different jobs its customers experience in life. This architecture has facilitated the creation of new disruptive businesses, while strengthening the Marriott brand at the same time. Under the endorsement of the Marriott brand, we have been taught to hire a Marriott Hotel when the job is to convene a major business meeting, and to choose a Courtyard by Marriott (“The hotel designed by business travelers for business travelers”) when the job is to get a clean, quiet place to work into the evening. We learned to hire Fairfield Inn by Marriott when the job is finding an inexpensive place to stay as a family, and Residence Inn by Marriott to find a home away from home. The Marriott brand remains unsullied by all of this, because the purpose brands make the job clear.

In contrast, if Marriott marketers had positioned Courtyard hotels in a segment defined by a lower price point—a cheaper, lower-quality solution to the same job that the top-tier Marriott-brand hotels are hired to do—then the disruption could indeed have damaged the Marriott brand. But if a crisply defined purpose brand guides customers to hire the various hotels to do very different jobs, and if the hotel chains each are designed to do their respective jobs perfectly, then they all will be viewed as high-quality hotels, thereby strengthening the endorsing power of the Marriott brand. Brand strategies that make it easy for customers to make the connection between a job that arises and the product they can hire to do the job perfectly can make disruption all the easier.

The Dangers of Asking Customers to Change Jobs

At a fundamental level, the things that people want to accomplish in their lives don’t change quickly. This is why in our disruptive innovation research, the trajectories of improvement that customers can utilize in any given application or tier of the market tend to be quite flat. Given this stability, an idea stands little chance of success if it requires customers to prioritize jobs they haven’t cared about in the past. Customers don’t just “change jobs” because a new product becomes available. Rather, the new product will succeed to the extent it helps customers accomplish more effectively and conveniently what they’re already trying to do.

Let’s test the viability of a new-product idea by exploring the potential for digital imaging to create growth by disrupting photographic film. How did most of us use photographic film prior to digital photography? We wanted good shots, so we often took multiple pictures of the same pose, in case somebody blinked at the wrong instant. When we dropped our film off at the developer’s, most of us ordered double prints. If one of the pictures turned out well, we wanted a spare easily available to send to a friend or relative. We brought the photos home, flipped through them, put them back into the envelope, and put them into a box or drawer. About 98 percent of all images were looked at only once. Only rare, conscientious people went back and mounted the best photos in an album. Most of us wanted to maintain good photo albums and intended to do so, but the fact was that we just had higher priorities.

Some digital imaging companies then came along with interesting propositions. “If you’ll just take the time to learn how to use this software, you can edit out the red-eye in all those flash pictures that you only look at once” was one. “You can now keep all your pictures neatly arranged and sortable in online photo albums” was another. It turns out that the vast majority of digital camera owners do neither of these things. Why? Because they weren’t prioritizing those things before. Innovations that make it easier for customers to do what they weren’t already trying to get done must compete against customers’ priorities. This is very hard to do.

Digital camera owners use their cameras for jobs they already had been trying to get done. For example, most of us use such a camera to verify on the spot that the image is good, and if it isn’t, we delete it and try again—the same job as taking multiple shots on film of the same pose. And we send digital images much less expensively and conveniently to far more people over the Internet than we ever had been able to do when we ordered double prints. (Interestingly, have you noticed what we do after we’ve looked at an image that has been e-mailed to us? We click “close,” putting it back in some “envelope” on our hard drive.) The things we prioritize in our lives are remarkably stable.

Another example: Hundreds of millions have been spent to apply new technologies—the Internet and e-book displays, specifically—to reshape the college textbook industry. Innovators have attempted to develop and sell tablets that can display downloaded e-books. And with many textbooks, you can click on a URL to obtain far more information about the topic than could possibly be included within the limits of a book. Would we expect these investments to generate significant growth? Our guess is that they will not. Although we would like to believe that all undergraduate students are rigorous seekers of knowledge, the job that many college students are really trying to get done, from our observation, is to pass their courses without having to read the textbook at all.

These companies have spent a lot of money helping students to do more easily something that they have been trying not to do. It would probably take far less money to create from the same technology a service called “Cram.com”—a utility that would make it easier and cheaper for students to cram more effectively for their exams. This would likely work because cramming is something that students already are trying to do, but with marginal efficacy. There are a lot of textbook-avoiders on campuses—a huge market of nonconsumption.

After logging on, Cram.com would ask subscribers what course they need to cram for—say, College Algebra. Then it would ask which of this list of textbooks the professor expected them to have read by now. It would ask them to click on the type of problem that they are having trouble with, and it would walk them through a tutorial.

The next year, Cram.com would need to offer a new and improved service, one that made it even easier and faster to cram better—inching up from the least-conscientious to the sporadically diligent tiers of the student population. After a few years, two students might be overheard in the college bookstore anguishing over the exorbitant price of a textbook: “You know, my brother took that course last year. He’s a good student, but he never even bought the book. He just used Cram.com from the beginning of the semester, and he did great.” Bingo. A new-market disruption that helped customers achieve what they already had been trying to do.

Identifying disruptive footholds means connecting with specific jobs that people—your future customers—are trying to get done in their lives. The problem is that in an attempt to build convincing business cases for new products, managers are compelled to quantify the opportunities they perceive, and the data available to do this are typically cast in terms of product attributes or the demographic and psychographic profiles of a given population of potential consumers. This mismatch between the true needs of consumers and the data that shape most product development efforts leads most companies to aim their innovations at nonexistent targets. The importance of identifying these jobs to be done goes beyond simply finding a foothold. Only by staying connected with a given job as improvements are made, and by creating a purpose brand so that customers know what to hire, can a disruptive product stay on its growth trajectory.

Notes

1.   See, for example, chapter 7 in Dorothy Leonard, Wellsprings of Knowledge (Boston: Harvard Business School Press, 1996).

2.   Some researchers (for example, Joe Pine, in his classic work Mass Customization [Boston: Harvard Business School Press, 1992]) argues that ultimately segmentation may be unimportant because individual customers’ needs might be addressed individually. Although this is conceivable, getting there will take some time. We will show in chapters 5 and 6 that in many circumstances it is not possible. Segmentation, in other words, will always be important.

3.   We are deeply indebted to two of our colleagues who originally introduced us to this way of thinking about the structure of markets. The first is Richard Pedi, CEO of Gage Foods in Bensenville, Illinois. Rick coined for us the language “jobs to be done.” Independently, Anthony Ulwick of Lansana, Florida–based Strategyn, Inc., has developed and used a very similar concept in his consulting work, using the phrase “outcomes that customers are seeking.” Tony has published a number of pieces on these concepts, including “Turn Customer Input into Innovation,” Harvard Business Review , January 2002, 91–98. Tony uses these concepts to help his firm’s clients develop products that connect with what their customers are trying to get done. We are also indebted to David Sundahl, who as Professor Christensen’s research associate helped formulate many of the initial ideas upon which this chapter was built.

4.   Many of the details in this account have been changed to protect the proprietary interests of the company while preserving the fundamental character of the study and its conclusions.

5.   The language in this paragraph reveals a nested system. Within the overarching job to be done are many unique outcomes that need to be achieved in order for the job to be done perfectly. Hence, when we use the term outcome in our work on segmentation, we refer to the individual things that need to be done right, such as lasting a long time, not creating a mess, and so on, in order for the job to get done right.

6.   One can see this problem even in the recent marketing trend toward so-called markets of one. Markets of one drive companies to provide customization options that meet all the needs of individual customers. But customization comes at a price. What is more, it often does not provide an understanding of the underlying outcomes-driven logic of customer purchasing decisions. Because market research tools as sophisticated as geocoding pay attention to the attributes of people, they cannot yield market segmentation schemes that make sense to customers—each of whom has many jobs that he or she is trying to get done. There actually is a lot of commonality in jobs to be done within a population of people and companies, suggesting that targeting markets of one may often not be a viable or desirable marketing objective.

7.   The observation that customers search across product categories to find ways to achieve needed outcomes is grounded in psychological research, which demonstrates that our perceptual systems are geared toward understanding what we can use objects to do and whether they are optimal for such purposes. For example, psychologist James J. Gibson, widely respected for his research on theories of perception, has written about “affordances,” a concept that mirrors what we term “jobs” or “outcomes.” According to Gibson, “The affordances of the environment are what it offers . . . , what it provides or furnishes, either for good or ill.” Gibson asserts that we see the world not in terms of primary qualities, like being yellow or being twenty-four ounces by volume, but in terms of outcomes: “What we perceive when we look at objects are their [outcomes], not their qualities. We can discriminate the dimensions of difference if required to do so in an experiment, but what the object affords us is what we normally pay attention to.” What matters about the ground, for example, is that it provides us a platform on which to stand, walk, build, and so forth. We don’t “hire” the ground for its color or moisture content per se. The affordances of products, in Gibson’s terms, are the outcomes that those products enable their users to achieve. See James J. Gibson, The Ecological Approach to Visual Perception (Boston: Houghton Mifflin, 1979), 127.

8.   Finding a “killer app” has been a holy grail of innovators ever since Larry Downes and Chunka Mui popularized the term in Unleashing the Killer App (Boston: Harvard Business School Press, 1998). Unfortunately, much of what has been written on this search has simply comprised accounts of historically successful killer apps. We think that a rigorous study of such applications would show that they were killers because the product or service was squarely positioned on a job that a lot of people already were trying to get done—the innovation in question simply helped them get it done better, and more conveniently.

9.   The firm headed by Mr. Ulwick that we mentioned in note 3 has proprietary methods for categorizing job-defined markets and measuring their size.

10.  This information was recounted to us in a July 2000 interview with Mickey Schulhoff, who worked for over twenty years as CEO of Sony America and served for much of this time as a member of Sony Corporation’s board of directors.

11.  We must emphasize here that we have absolutely no inside information about any of the companies or products mentioned in this section, nor have we conducted any formal market research on these products or jobs. Rather, we have written this material simply to illustrate how theories that are constructed on circumstance-based categories about what products will connect with customers can bring clarity and predictability to what historically has been a hit-and-miss task in innovation. It may very well be, for example, that given RIM’s strategy of emphasizing sales to enterprises rather than individual customers, it is the corporate CIO manager who has the job to do: being sure that the firm’s knowledge workers are able to communicate and be contacted on a real-time, no-excuses basis. The same exercise would be useful if applied to this job.

12.  As this book was being written, in fact, RIM and Nokia announced a partnership through which Nokia will license RIM’s software to enable wireless e-mail on Nokia’s phones—a deal that makes sense for both firms because in many ways their products are hired to do the same job. Whether one would prefer to produce the BlackBerry that ultimately will compete against wireless phones to do this job, or whether it would be better to provide the software inside others’ wireless phones, as the new Nokia-RIM arrangement provides, is a question that the theory in chapters 5 and 6 will address.

13.  We have gone out on the end of a very long limb in making these statements, because the future has not yet happened. We have presented this analysis provocatively in order to illustrate the fundamental principle. In all probability, the makers of wireless hand-held devices will engage in a headlong rush to incorporate every competitor’s latest features on their products, leading the industry very prematurely to a situation in which products are un-differentiated, commoditized, one-size-fits-all solutions. When this happens, we urge our readers not to conclude that “Christensen and Raynor were wrong.” We would assert that although some blurring and copying of features will inevitably occur, the longer each manufacturer focuses on incorporating those features and functions that do a unique job well and the longer they position their marketing message on that unique job, the faster the suppliers of these devices will grow because they will gain share not against each other, but against other products and services that get hired to do those jobs. We would also argue that these firms will preserve their differentiability and profitability longer if they focus their improvement trajectory on a unique job. The fact that they are unlikely to do this does not disprove the principle.

14.  See, for example, Leonard, Wellsprings of Knowledge ; Eric von Hippel, The Sources of Innovation (New York: Oxford University Press, 1988); and Stefan Thomke, Experimentation Matters: Unlocking the Potential of New Technologies for Innovation (Boston: Harvard Business School Press, 2003).

15.  In concept, of course, being able to carry one small device that does everything in a briefcase or purse is something that all customers would say they want. But it is rare that there are no technological trade-offs to adding diverse functionality to a product. Software makes it less expensive to tailor a single physical platform to do a range of focused jobs. Our proposition, however, is that even in this situation, a company would do better by using one single hardware platform to market different software-defined, optimized products that are positioned on different jobs. It is likely that for a long time electronic devices that combine such a wide range of functionality in the interests of doing many jobs simultaneously—organize me, connect me, help me have fun, and so forth—are likely to end up more like a Swiss army knife: a pretty good knife, terrible scissors, a marginal bottle opener, and a crummy screwdriver. As long as the jobs that customers need to get done arise at independent points in time and space, we would expect that most customers will continue to carry multiple devices until a one-size-fitsall omnibus device can do all jobs as well as its focused competitors.

16.  The experience that Intuit had in disrupting the small business accounting software market with its QuickBooks product typifies this situation. Until the early 1990s the only available small business software had been written by accountants for accountants. Because they defined their market in terms of the product, they framed their competitors as other makers of accounting software. The vision that this framing gave them about how to get ahead of their competitors, therefore, was to engage in an arms race of sorts: Be faster adding features and functionality in the form of new reports and analyses that could be run. The industry gradually converged upon undifferentiated, one-size-fits-all products, into which everybody had appended everybody else’s features.

Intuit’s marketers were wont to watch what jobs the customers of Intuit’s Quicken personal financial management software were trying to get done for themselves when using the product. In the course of doing this, they observed to their surprise that a large proportion of Quicken users were employing it to keep track of their small business’s finances. The job, they learned, was basically to keep track of cash. These small business owners had their fingers in every dimension of their business and did not need all of the financial reports and analyses that the prevailing software providers had cobbled into their products. Intuit launched QuickBooks at this job that small business owners needed to get done—“Just help me be sure I don’t run out of cash”—and succeeded spectacularly. Within two years the company had seized 85 percent of the market with a disruptive product that lacked most of the functionality of the competing products.

17.  Theodore Levitt has been a leading proponent of this view among those who research and write about issues in marketing. Christensen remembers that when he was an M.B.A. student he heard Ted Levitt declare, “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole.” In our words, they have a job to do, and they hire something to do the job. Levitt’s best-known explanation of these principles is found in Theodore Levitt, “Marketing Myopia,” Harvard Business Review, September 1975, reprint 75507.

18.  For suggestions on how the magnitude of job-defined market segments can be measured, see Anthony W. Ulwick, “Turn Customer Input into Innovation,” Harvard Business Review, January 2002, 91–98.

19.  We are grateful to Mike Collins, founder and CEO of the Big Idea Group, for his comments that led to many of the ideas in this section. Mike reviewed an early draft of this chapter, and his thoughts were extraordinarily helpful.

20.  One reason that some (but not all) “category killer” retail formats—companies such as Home Depot and Lowe’s—have been able to disrupt established retailers so successfully is that they are organized around jobs to be done.

21.  Because many marketers inadvertently and over time tend to segment their markets along attribute-based categorizations of products and people, it is unfortunate, but not surprising, that they often do to their brands the same thing that they have done to their products. Brands often have become omnibus words that don’t do well any of the jobs that customers need to get done when they hire the brand. Because most advertisers want a brand’s meaning to be flexible enough for a range of products to be housed under its umbrella, many brands have lost their association with a job. When this happens, customers remain confused about what product to buy to get the job done when they find themselves in a particular circumstance.

CHAPTER FOUR

WHO ARE THE BEST CUSTOMERS

FOR OUR PRODUCTS?

Which customers should we target? Which customer base will be the most valuable foundation for future growth? Is our growth potential greatest if we pursue the largest markets? How can we predict which competitors will target which sets of customers? What sales and distribution channels will most capably embrace our product and devote the resources required to grow the market as fast as possible?

The message of chapter 2 was that although sustaining innovations are critical to the growth of existing businesses, a disruptive strategy offers a much higher probability of success in building new-growth businesses. Chapter 3’s message was that managers often segment markets along the lines for which data are available, rather than in ways that reflect the things that customers are trying to get done. Using flawed segmentation schemes, they often introduce products that customers don’t want, because they aim at a target that is irrelevant to what customers are trying to get done. This chapter addresses two questions that are closely tied to the last: Which initial customers are most likely to become the solid foundation upon which we can build a successful growth business? And how should we reach them?

It’s relatively straightforward to find the ideal customers for a lowend disruption. They are current users of a mainstream product who seem disinterested in offers to sell them improved-performance products. They may be willing to accept improved products, but they are unwilling to pay premium prices to get them.[1] The key to success with low-end disruptions is to devise a business model that can earn attractive returns at the discount prices required to win business at the low end.

It is much trickier to find the new-market customers (or “nonconsumers”) on the third axis of the disruptive innovation model. How can you know whether current nonconsumers can be enticed to begin consuming? When only a fraction of a population is using a product, of course, some of the nonconsumption may simply reflect the fact that there just isn’t a job needing to be done in the lives of those non-consumers. That is why the “jobs question” is a critical early test for a viable new-market disruption. A product that purports to help non-consumers do something that they weren’t already prioritizing in their lives is unlikely to succeed.

For example, throughout the 1990s a number of companies thought they saw a growth opportunity in the significant proportion of American households that did not yet own a computer. Reasoning that the cause of nonconsumption was that computers cost too much, they decided that they could create growth by developing an “appliance” that could access the Internet and perform the basic functions of a computer at a price around $200. A number of capable companies, including Oracle, tried to open this market, but failed. We suspect that there just weren’t any jobs needing to get done in those nonconsuming households for which less-expensive computers were a solution. chapter 3 taught us that circumstances like this are not good growth opportunities.

Another kind of nonconsumption occurs, however, when people are trying to get a job done but are unable to accomplish it themselves because the available products are too expensive or too complicated. Hence, they put up with getting it done in an inconvenient, expensive, or unsatisfying way. This type of nonconsumption is a growth opportunity. A new-market disruption is an innovation that enables a larger population of people who previously lacked the money or skill now to begin buying and using a product and doing the job for themselves. From this point onward, we will use the terms nonconsumers and nonconsumption to refer to this type of situation, where the job needs to get done but a good solution historically has been beyond reach. We sometimes say that innovators who target these new markets are competing against nonconsumption.

We’ll begin with three short case studies of new-market disruption, and then synthesize across these histories a common pattern that typifies the customers, applications, and channels where new-market disruptions tend to find their foothold. We’ll explore why so few companies historically have sought nonconsumers as the foundation for growth, and then close by suggesting what to do about it.

New-Market Disruptions: Three Case Histories

New-market disruptions follow a remarkably consistent pattern, regardless of the type of industry or the era in history when the disruption occurred. In this section we’ll synthesize this pattern from three disruptions: one from the 1950s, one that began in the 1980s and continues in the present, and a third that is still in its nascent stage. In these and scores of other cases we’ve studied, it is stunning to see the sins of the past so regularly visited upon the later generations of disruptees. Today we can see dozens of companies making the same predictable mistakes, and the disruptors capitalizing on them.

The Disruption of Vacuum Tubes by Transistors

Scientists at AT&T’s Bell Laboratories invented the transistor in 1947. It was disruptive relative to the prior technology, vacuum tubes. The early transistors could not handle the power required for the electronic products of the 1950s—tabletop radios, floor-standing televisions, early digital computers, and products for military and commercial telecommunications. As depicted in the original value network of figure 4-1, the vacuum tube makers, such as RCA, licensed the transistor from Bell Laboratories and brought it into their own laboratories, framing it as a technology problem. As a group they aggressively invested hundreds of millions of dollars trying to make solid-state technology good enough that it could be used in the market.

FIGURE 4 - 1

Value Networks for Vacuum Tubes and Transistors

While the vacuum tube makers worked feverishly in their laboratories targeting the existing market, the first application emerged in a new value network on the third axis of the disruption diagram: a germanium transistor hearing aid, an application that valued the low power consumption that made transistors worthless in the mainstream market. Then in 1955 Sony introduced the world’s first battery-powered, pocket transistor radio—an application that again valued transistors for attributes that were irrelevant in mainstream markets, such as low power consumption, ruggedness, and compactness.

Compared with the tabletop radios made by RCA, the sound from the Sony pocket radio was tinny and static-laced. But Sony thrived because it chose to compete against nonconsumption in a new value network. Rather than marketing its radio to consumers who owned tabletop devices, Sony instead targeted the rebar of humanity—teenagers, few of whom could afford big vacuum tube radios. The portable transistor radio offered them a rare treat: the chance to listen to rock and roll music with their friends in new places out of the earshot of their parents. The teenagers were thrilled to buy a product that wasn’t very good, because their alternative was no radio at all.

The next application emerged in 1959, with the introduction of Sony’s twelve-inch black-and-white portable television. Again, Sony’s strategy was to compete against nonconsumption, as it made televisions available to people who previously couldn’t afford them, many of whom lived in small apartments that lacked the space for floor-standing televisions. These customers were delighted to own products that weren’t nearly as good as the large TVs in the established market, because the alternative was no television at all.

As these major new disruptive markets for transistor-based products emerged, the traditional makers of vacuum tube–based appliances felt no pain because Sony wasn’t competing for their customers. Furthermore, the vacuum tube makers’ aggressive efforts to develop solid-state electronics in their own laboratories gave them comfort that they were doing what they should about the future.

When solid-state electronics finally became good enough to handle the power required in large televisions and radios, Sony and its retailers simply vacuumed out the customers from the original plane, as depicted in figure 4-1. Within a few years the vacuum tube–based companies, including the venerable RCA, had vaporized.

Targeting customers who had been nonconsumers worked magic for Sony in two ways. First, because its customers’ reference point was having no television or radio at all, they were delighted with simple, crummy products. The performance hurdle that Sony had to clear therefore was relatively easy. This entailed a much lower R&D investment prior to commercialization than the vacuum tube makers had to make to commercialize the identical technology. The established market presented a much higher performance barrier to surmount, because customers there would only embrace solid-state electronics when they became superior to vacuum tubes in those applications.[2]

Second, Sony’s sales grew to significant levels before RCA and its competitors felt any threat. The painlessness of Sony’s attack persisted even after its products improved to become performance-competitive with low-end vacuum tube–based products. When Sony started to pull the least-attractive customers from the original value network into its new one, losing those who bought their lowest-margin products actually felt good to makers of vacuum tube–based appliances. They were immersed in an aggressive up-market foray of their own into color television. These were large, complicated machines that sold for very attractive margins in their original value network. As a result, the vacuum tube companies’ profit margins actually improved as they were being disrupted. There simply was no crisis to prompt them to counterattack Sony.

When the crisis became clear, the manufacturers of vacuum tube products couldn’t just switch to the new technology and pull customers back into their old business model, because the cost structure of that model and of their distribution and sales channels was not competitive. The only way they could have retained or recaptured their customers would have been to reposition their companies in the new value network. That would have entailed, among other restructurings, shifting to a completely different channel of distribution.

Vacuum tube–based appliances were sold through appliance stores that made most of their profits replacing burned-out vacuum tubes in the products they had sold. Appliance stores couldn’t make money selling solid-state televisions and radios because they didn’t have vacuum tubes that would burn out. Sony and the other vendors of transistor-based products therefore had to create a new channel in their new value network. These were chain stores such as F. W. Woolworth and discount retailers such as Korvette’s and Kmart, which themselves had been “nonvendors”—they hadn’t been able to sell radios and televisions because they had lacked the ability to service burned-out vacuum tubes. When RCA and its vacuum tube cohort finally started making solid-state products and turned to the discount channel for distribution, they found that the shelf space had already been claimed.

The punishing thing about this outcome, of course, is that RCA and its colleagues didn’t fail because they didn’t invest aggressively in the new technology. They failed because they tried to cram the disruption into the largest and most obvious market, which was filled with customers whose business could only be won by selling them a product that was better in performance or cost than they already were using.

Angioplasty: A Disruption of Heart-Stopping Proportions

Balloon angioplasty is an ongoing example of a new-market disruption. Prior to the early 1980s, the only people with heart disease who could receive interventional therapy were those who were at high and immediate risk of death. There was a lot of nonconsumption in this market: Most people who suffered from heart disease simply went untreated. Angioplasty enabled a new group of providers—cardiologists—to treat coronary artery disease by threading a catheter into a partially clogged artery of these previously untreated patients and puffing up a balloon. It was often ineffective: Half of the patients suffered restenosis, or a reclogging of the artery, within a year. But because the procedure was simple and inexpensive, more patients with partially occluded arteries could begin receiving treatment. The cardiologists benefited too, because even without being trained in surgery they could keep the fees for themselves, and had to refer fewer patients to the heart surgeons, who earned the most handsome fees. Angioplasty thereby created a huge new growth market in cardiac care.

If its inventors had attempted to market angioplasty as a sustaining technology—a better alternative than cardiac bypass surgery—it would not have worked. Angioplasty couldn’t solve difficult blockage problems at the outset. Any attempt to improve it enough so that heart surgeons would choose angioplasty over bypass surgery would have entailed extraordinary time and expense.

Could the inventors have commercialized angioplasty as a lowend disruption—a less-expensive way for heart surgeons to treat their least-sick patients? No. Patients and surgeons weren’t yet overserved by the efficacy of bypass surgery.

The successful disruptive innovators chose a third approach: enabling less-seriously ill patients to receive therapy that was better than the alternative (nothing), and enabling cardiologists profitably to pull into their own practices patients who previously had to wait until they were sick enough to be referred to more expensive experts. Under these circumstances a booming new market emerged.

Figure 4-2 shows the growth that resulted from this disruption. Interestingly, for a very long time cardiac bypass surgery continued to grow, even as angioplasty began thriving and improving in its new value network. The reason was that in their efforts to treat patients with partially occluded arteries, cardiologists discovered many more patients whose arteries were too clogged to be opened with angioplasty—patients whose disease previously was not diagnosed. So heart surgeons felt no threat—in fact, they felt healthy, for a long time—just like the large steel mills and the makers of vacuum tubes.[3]

As cardiologists and their device suppliers pursued the higher profits that came from better products and premium services, they discovered that they could insert stents to prop open even difficult-to-open arteries. (Stents caused the up-kink in angioplasty growth that began in 1995.) Customers who otherwise would have needed bypass surgery are now being pulled into the new value network, and the cardiologists have done this without having to be trained as heart surgeons. This disruption has been underway for two decades, but the surgeons only recently have sensed the threat as the number of open-heart cardiac surgeries has begun to decline. In the most complex tiers of the market, there will be demand for open-heart surgery for a long time. But that market will shrink—and now that the disruption is apparent, there is little that the heart surgeons can do.

FIGURE 4 - 2

Number of Angioplasty and Cardiac Bypass Surgery Procedures

Like pocket radios and portable TVs, the “channels”—the venues in which interventional cardiac care is delivered—are also being disrupted. Bypass surgery is a hospital-based procedure because of the risks it entails. But little by little, as technology has improved cardiologists’ ability to diagnose and prevent complications, more and more angioplasty procedures are being performed in cardiac care clinics, whose costs make them disruptive relative to full-service hospitals.

Solar Versus Conventional Electrical Energy

Consider solar energy as a third example. It defies profitable commercialization despite billions of dollars invested to make the technology viable. This is indeed daunting when the business plan is to compete against conventional sources of electricity in developed countries. About two-thirds of the world’s population has access to electric power transmitted from central generating stations. In advanced economies this power is available almost all the time, is a very cost-effective means of getting work done, and is available essentially twenty-four hours per day, cloudy and sunny weather alike. This is a tough standard for solar energy to compete against.

Yet if developers of this technology instead targeted nonconsumers—the two billion people in South Asia and Africa who have no access to conventionally generated electricity—the prospects for solar energy might look quite different. The standard of comparison for those potential customers is no electricity at all. Their homes aren’t filled with power-hungry appliances, either, so it would be a vast improvement over the present state of affairs for these customers if they could store enough energy during daylight to power an electric light at night. Solar energy would be much less expensive, and would probably entail fewer headaches from governmental approvals and corruption, than would building a conventional generation and distribution infrastructure in those areas.

Some might protest that photovoltaic cells are simply too expensive ever to be made and sold profitably to impoverished populations. Maybe. But many of the technical paradigms in present photovoltaic technology were developed in attempts at sustaining innovation—to push the bleeding edge of performance as far as possible in the quest to compete against consumption in North America and Europe. Targeting new unserved markets would lower the performance hurdle, allowing some to conclude, for example, that instead of building the cells on silicon wafers they can deposit the required materials onto a sheet of plastic in a continuous, roll-to-roll process.

If history is any guide, the commercially viable innovations in clean energy will not come from government-financed research projects designed to make solar energy a preferred source of power in developed markets. Rather, the successful innovations will emerge from companies who carve disruptive footholds by targeting nonconsumption and moving up-market with better products only after they have started simple and small.

Extracting Growth from Nonconsumption: A Synthesis

We distill from these histories four elements of a pattern of new-market disruption. Managers can use this pattern as a template to find ideal customers and market applications for disruptive innovations, or they can use it to shape nascent ideas into business plans that match this proven pattern for generating new-market growth. These elements are as follows:

1. The target customers are trying to get a job done, but because they lack the money or skill, a simple, inexpensive solution has been beyond reach.

2. These customers will compare the disruptive product to having nothing at all. As a result, they are delighted to buy it even though it may not be as good as other products available at high prices to current users with deeper expertise in the original value network. The performance hurdle required to delight such new-market customers is quite modest.

3. The technology that enables the disruption might be quite sophisticated, but disruptors deploy it to make the purchase and use of the product simple, convenient, and foolproof. It is the “foolproofedness” that creates new growth by enabling people with less money and training to begin consuming.

4. The disruptive innovation creates a whole new value network. The new consumers typically purchase the product through new channels and use the product in new venues.

The history of each new-market disruptor in figure 2-4 mirrors this pattern. From Black & Decker to Intel, from Microsoft to Bloomberg, from Oracle to Cisco, from Toyota to Southwest Airlines, and from Intuit’s QuickBooks to Salesforce.com, new-market disruptions fit this pattern. In so doing, they have been a dominant engine of growth not just for shareholder value but for the world economy.

Disruptions that fit this pattern succeed because while all of this is happening, the established competitors view the entrants in the emerging market as irrelevant to their well-being.[4] The growth in the new value network does not affect demand in the mainstream market for some time—in fact, incumbents sometimes prosper for a time because of the disruption. What is more, the incumbents are comfortable that they have sensed the threat and are responding. But it is the wrong response. They invest massive sums trying to advance the technology enough to please the customers in the existing value network. In so doing, they force the disruptive technology to compete on a sustaining basis—and nearly always, they fail.

It’s quite stunning, when you think about it. This pattern would strike most managers as a dream come true. What more could you want than a situation where customers are easily delighted, powerful competitors ignore you, and you’re locked arm-in-arm with channel partners in a win-win race toward exciting growth? We will explore next why this dream so often becomes a nightmare instead, and then suggest what to do about it.

What Makes Competing Against Nonconsumption So Hard?

The logic of competing against nonconsumption as the means for creating new-growth markets seems obvious. Despite this, established companies repeatedly do just the opposite. They choose to compete at the outset against consumption, trying to stretch the disruptive innovation to compete against—and ultimately supplant—established products, sold by well-entrenched competitors in large, obvious market applications. Doing this requires enormous amounts of money, and such attempts almost always fail. Established firms almost always do this, rather than shaping their ideas to fit the pattern of successful disruption noted earlier. Why?

In a very insightful stream of research, Harvard Business School Professor Clark Gilbert has helped us understand the fundamental mechanism that causes the established competitors in an industry to consistently cram the disruptive technology into the mainstream market. With that understanding, Gilbert also provides guidance to established company executives on how to avoid this trap, and capture the growth created by disruption instead.[5]

Threats Versus Opportunities

Gilbert has borrowed insights from the fields of cognitive and social psychology, as exemplified in the work of Nobel Prize winners Daniel Kahneman and Amos Tversky, to study disruption.[6] Kahneman and Tversky examined how individuals and groups perceive risk and noted that if you frame a phenomenon to an individual or a group as a threat, it elicits a far more intense and energetic response than if you frame the same phenomenon as an opportunity. Furthermore, other researchers have observed that when people encounter a significant threat, a response called “threat rigidity” sets in. The instinct of threat rigidity is to cease being flexible and to become “command and control” oriented—to focus everything on countering the threat in order to survive.[7]

You can see exactly this behavior among the established firms that experience new-market disruptions. Because the disruptions emerge at a time when the established firms’ core business is robust, framing the new-market disruption as an opportunity simply does not get people’s attention: It makes little sense to invest in new-growth businesses when the present ones are doing well.

When visionary executives and technologists do see the disruption coming, they frame it as a threat, seeing that their companies could be imperiled if these technologies succeed. This framing as a threat rather than an opportunity is what elicits a resource commitment from the established firms to address the technology. But because they instinctively define the disruption as a threat, they focus on being able to protect their customers and their current business. They want to be there with the new technology ready when they must switch to it in order to protect their current customers. This causes the organization to pursue a strategy that not only misses the growth opportunity but also leads to its eventual destruction—because the disruptors who take root in nonconsumption eventually kill them. This just means, however, that established firms must reposition themselves on the other side of the dilemma, at the appropriate time.

How to Get Commitment and Flexibility

Gilbert’s work, fortunately, not only defines an innovator’s dilemma but suggests a way out. The solution is twofold: First, get top-level commitment by framing an innovation as a threat during the resource allocation process. Later, shift responsibility for the project to an autonomous organization that can frame it as an opportunity.

In his study of how major metropolitan newspapers responded to the threat or opportunity of going online, Gilbert showed that in the initial period of threat framing, the project to address the disruption was always housed within the budgetary and strategic responsibility of the mainstream organization—because it had to be. In the case of newspapers, this entailed putting the newspaper online. The advertisers and readers of the online version were the same as those of the paper version. The newspapers did exactly what the vacuum tube and solar energy companies did: try to make the disruptive technology good enough that existing customers would use it instead of the existing physical newspaper.

At first blush, this market targeting seems senseless: Concerns about cannibalism become self-fulfilling prophecies. But threat framing makes sense of the paradox. Because current customers are the lifeblood of the company, they must be protected at all costs: “If the technology ever does in fact become good enough to begin to steal away our customers, we will be there with the new technology, ready to defend ourselves.”

In contrast to the dilemma facing the incumbents, threat framing isn’t a vexing issue for entrant firms. For them, the disruption is pure opportunity. This asymmetry of perceptions explains why incumbents so consistently try to cram the disruptive technology into mainstream markets, whereas the entrants pursue the new-market opportunity. Understanding this asymmetry, however, points to a solution. After senior managers have made a resolute commitment to address the disruption, responsibility to commercialize the disruption needs to be placed in an independent organizational unit for which the innovation represents pure opportunity.

This is what Gilbert noted in his newspaper study. After the initial period of threat framing that elicited resource commitment, Gilbert noted that a number of newspaper organizations spun off their online groups to become independently managed, stand-alone profit centers. When this happened, members of the newly independent groups switched their orientation, seeing themselves as involved in an opportunity with significant growth potential. When this happened, quite rapidly those organizations evolved significantly away from being just online replications of the newspaper. They implemented different services, found different suppliers, and earned their revenue from a different set of advertisers than the mainstream paper. Those newspapers that continued to house responsibility for their online effort within the mainstream news organization, in contrast, have continued on the self-destructive course of cannibalism, offering an online newspaper in defense of the core business.

Gilbert’s recommendations are summarized in figure 4-3. The disruption is best framed as a threat within the resource allocation process in order to garner adequate resources. But once the investment commitment has been made, those engaged in venture building must see only upside opportunity to create new growth. Otherwise, they will find themselves with a dangerous lack of flexibility or commitment.

An initial decision to fund a disruptive growth business is not the end of the resource allocation process or of the conflict between threat and opportunity framing. For several years in each annual budgeting cycle, the disruptive opportunity will seem insignificant. The way that many corporate entrepreneurs deal with these annual challenges to the value of new-growth ventures is by promising big numbers in the future in exchange for resources in the present. This is suicidal for two reasons. First, the biggest markets whose size can be substantiated are those that exist. The very effort to articulate a convincing case for resources actually forces the entrepreneurs to cram the innovation as a sustaining technology in the existing market. Second, if results fall short of projected numbers, senior managers often conclude that the potential market size is disappointingly small—and they cut resources as a result.

FIGURE 4 - 3

How to Garner Resource Commitments and Target Them at Disruptive Growth Opportunities

How do you deal with the rational need of the executives who manage resource allocation to focus investments where the risk/reward opportunity is most attractive? The answer is not to change the rules of evidence in the resource allocation process, because in successful companies, the well-honed operation of this process is critical to success on the sustaining trajectory. Decisions in that process can be rules based, because the environment is clear.

But companies that hope to create growth through new-market disruption need another, parallel process into which they can channel potentially disruptive opportunities. Ideas will enter this parallel process only partially formed. Those who manage this process then need to shape them into business plans that conform to the four elements of the pattern noted previously. Executives who allocate resources in this process should approve or kill project budgets based on fit with the pattern, not numerical rules. Fit constitutes a much more reliable predictor of success than do numbers in the uncertain environment of new-market disruption. If a project fits the pattern, executives can approve it with confidence that the initial conditions are conducive to successful growth.[8] Ultimate success, of course, depends on aligning all the related actions and decisions that we discuss in later chapters.

Reaching New-Market Customers Often

Requires Disruptive Channels

In the final pages of this chapter, we hope to amplify the fourth element of the pattern of successful new-market disruption: going to market through a disruptive channel. The term channel as it is commonly used in business refers to the wholesale and retail companies that distribute and sell products. We assign a broader meaning to this word, however: A company’s channel includes not just wholesale distributors and retail stores, but any entity that adds value to or creates value around the company’s product as it wends its way toward the hands of the end user. For example, we will consider computer makers such as IBM and Compaq as the channels that Intel’s microprocessors and Microsoft’s operating system use to reach the end-use customer. A physician’s practice is the channel through which many health care products provide the needed care to patients. A company’s salesforce is an important channel through which all products must pass.

We use this broader definition of channel because there needs to be symmetry of motivation across the entire chain of entities that add value to the product on its way to the end customer. If your product does not help all of these entities do their fundamental job better—which is to move up-market along their own sustaining trajectory toward higher-margin business—then you will struggle to succeed. If your product provides the fuel that entities in the channel need to move toward improved margins, however, then the energy of the channel will help your new venture succeed.

Disruption causes others to be disinterested in what you are doing. This is exactly what you want with competitors: You want them to ignore you. But offering something that is disruptively unattractive to your customers—which includes all of the downstream entities that compose your channel—spells disaster. Companies in your channel are customers with a job to get done, which is to grow profitably.

Retailers and Distributors Need to Grow Through Disruption, Too

Retailers and distributors face competitive economics similar to those of the minimills we described in chapter 2. They need to keep moving up. If they don’t, and just sell the same mix of merchandise against competitors whose costs and business models are similar, margins will erode to the minimum sustainable levels. This need to move up-market is a powerful, persistent disruptive energy in the channel. Harnessing it is crucial to success.

If a retailer or distributor can carry its business model up-market into higher-margin tiers, the incremental gross margin falls almost directly to the bottom line. Hence, innovating managers should find channels that will see the new product as a fuel to propel the channel up-market. When disruptive products enable the channel to disrupt its competitors, then the innovators harness the energies of the channel in building the disruption.

When Honda began its disruption of the North American motorcycle market with its small, cheap Super Cub motorized bicycle, the fact that it could not get Harley-Davidson motorcycle dealers to carry Honda products was good news, not bad—because the salespeople in the dealerships always would have been able to make higher commissions by choosing to sell Harleys instead of Hondas. Honda’s business took off when it began to distribute through power equipment and sporting goods retailers, because it gave those retailers a chance to migrate toward higher-margin product lines. In each of the most successful disruptions we have studied, the product and its channel to the customer formed this sort of mutually beneficial relationship.

This is an important reason why Sony became such a successful disruptor. Discount retailers such as Kmart, which had no after-sale capability to repair vacuum tube–based electronic products, were emerging at the same time as Sony’s disruptive products. Solid-state radios and televisions constituted the fuel that enabled the discounters to disrupt appliance stores. By selecting a channel that had up-market disruptive potential itself, Sony harnessed the energies of its channel to promote and position its products.

The fuel that a disruptive company provides to its channel will become spent, meaning that getting your products in the channels that stand to benefit the most is a perpetual challenge. This happened to Sony. After the discounters had driven the appliance stores out of the consumer electronics market and the products were being sold by equal-cost discount retailers, margins on those products eroded to subsistence levels. Consumer electronics no longer provided the fuel that the discounters needed to move up-market. Consequently, they de-emphasized electronics, gradually leaving them to be sold in even lower-cost retailers such as Circuit City and Best Buy. The discount department stores had to then look to clothing, which was the next fuel that would enable them to move up and compete against higher-margin retailers again.

Value-added distributors or resellers face the same motivations as retailers. As an example, Intel and SAP established a joint venture called Pandesic in 1997 to develop and sell a simpler, less-expensive version of SAP’s enterprise resource planning (ERP) software to small and medium-sized businesses—a new-market disruption.[9] SAP’s products historically had been targeted at huge enterprises, which would ante up several million dollars to purchase the software, and another $10 million to $200 million to implement it. The sale and implementation of SAP’s products was largely done by its channel partners—implementation consultants such as Accenture, which experienced tremendous growth riding the ERP wave.

Pandesic’s managers decided to take their lower-priced, easier-to-implement ERP package to market through the same channel partners. But when the IT implementation consultants had to choose whether to spend their time selling huge multimillion-dollar SAP implementation projects to global corporations or selling lower-ticket Pandesic software and straightforward implementation projects to small businesses, how would you expect them to expend their energy? Naturally, they pushed big-ticket SAP product implementations that helped them make the most money given their size and cost structure. There was no energy for Pandesic’s disruptive product in the channel that Pandesic chose, and the venture failed.

A company’s own salesforce will react the same way, especially if they work on commission. Every day salespeople need to decide which customers to call on, and which they will not call on. When they are with customers, they must decide which products they will promote and sell, and which they will not mention. The fact that they are your own employees doesn’t matter much: Salespeople can only prioritize those things that it makes sense for them to prioritize, given the way they make money. Rarely will people who sell a company’s mainstream products on the sustaining trajectory be successful in pushing the disruptive ones. It is foolish to give them a special financial incentive to push the disruptive products, because that would take their eye off their critical responsibility of selling the most profitable products on the sustaining trajectory. Disruptive products require disruptive channels.

Customers as Channels

For materials and components manufacturers, the end-use products constitute an important entity in their channel. In a similar way, service providers who use a product in order to deliver their service are the product’s channel to the end-use customer. For example, computer makers such as Compaq and Dell Computer constitute the “channel” by which Intel’s microprocessors reach an important market. The improvements in Intel’s microprocessor have been the fuel propelling makers of desktop machines up-market so that they can continue to compete against higher-cost computer makers such as Sun.

The same situation exists in service businesses. Just as lower-performing products can take root in simple applications and then get disruptively better, so too technological progress often enables less-skilled service providers to disrupt more highly trained and expensive providers above them. In a way that is analogous to Intel’s relationship with Dell, it is the potentially disruptive service providers that constitute the channel for the companies providing the enabling disruptive technology.

Let us illustrate the importance of fueling a disruptive channel by visiting health care again. In this industry today, many physicians are in a dogfight similar to that of the steel minimills. They are locked in a price-driven struggle against other physicians’ practices and the companies that reimburse for the cost of care, working ever harder to make attractive income. A major health care equipment company has begun launching a series of disruptive products that will help office-based caregivers to move disruptively upward—to pull into their own practices procedures that historically had to be referred to more expensive outpatient clinics.

One example is in diagnosing and resolving colon disorders. To date, if a patient appeared to have a possible lesion or tumor in the colon, the physician would perform a colonoscopy in a relatively expensive clinic or hospital. Threading the flexible scope through a serpentine colon requires the skill of a very capable specialist. If the colonoscopy revealed a problem, then the patient would be referred to an even higher-cost surgeon, who would operate to correct the problem in an even higher-cost hospital. This company is introducing a technology that is much easier to use and that will enable the less-specialized diagnosing physicians to perform these procedures safely and effectively right in their offices—and thereby to pull into the cost structure of their office value-added procedures that historically could only be done in more expensive channels.

This device could be marketed as a sustaining innovation to the specialists who already have mastered the difficult-to-use traditional scopes. You can imagine what the physician would ask the salesperson: “Why do I need this? Does it allow me to see better or do more than what I have right now? Is the scope cheaper? Won’t this thing here break?” This is a sustaining-technology conversation.

If the company marketed this as a disruptive technology enabling less-specialized physicians to do this procedure in their offices, however, the physician would likely ask, “What will it take to get trained on this thing?” This is a disruptive conversation.

What kinds of customers will provide the most solid foundation for future growth? You want customers who have long wanted your product but were not able to get one until you arrived on the scene. You want to be able to easily delight these customers, and you want them to need you. You want customers whom you can have all to yourself, protected from the advances of competitors. And you want your customers to be so attractive to those you work with that everyone in your value network is motivated to cooperate in pursuing the opportunity.

The search for customers like this is not a quixotic quest. These are the kinds of customers that you find when you shape innovative ideas to fit the four elements of the pattern of competing against nonconsumption.

Despite how appealing these kinds of customers appear to be on paper, the resource allocation process forces most companies, when faced with an opportunity like this, to pursue exactly the opposite kinds of customers: They target customers who already are using a product to which they have become accustomed. To escape this dilemma, managers need to frame the disruption as a threat in order to secure resource commitments, and then switch the framing for the team charged with building the business to be one of a search for growth opportunities. Carefully managing this process in order to focus on these ideal customers can give new-growth ventures a solid foundation for future growth.

Notes

1.   Economists have great language for this phenomenon. As the performance of a product overshoots what customers are able to utilize, the customers experience diminishing marginal utility with each increment in product performance. Over time the marginal price that customers are willing to pay for an improvement comes to equal the marginal utility that they receive from consuming the improvement. When the marginal increase in price that a company can sustain in the market for an improved product approaches zero, it suggests that the marginal utility that customers derive from using the product also is approaching zero.

2.   We stated earlier that few technologies are intrinsically sustaining or disruptive in character. These are extremes in a continuum, and the disruptiveness of an innovation can only be described relative to various companies’ business models, to customers, and to other technologies. What the transistor case illustrates is that attempting to commercialize some technologies as sustaining innovations in large and obvious markets is very costly.

3.   Figure 4-2 was constructed from data provided by the American Heart Association National Center. Because these data measure only those procedures performed in hospitals, angioplasty procedures that were performed in outpatient and other nonhospital settings are not included. This means that the angioplasty numbers in the chart are underestimated, and that the underestimation becomes more significant over time.

4.   There are many other examples of this, in addition to those cited in the text. For example, full-service stock brokers such as Merrill Lynch continue to move up-market in their original value network toward clients of even larger net worth, and their top and bottom lines improve as they do so. They do not yet feel the pain that they ultimately will experience as the online discount brokers find ways to provide ever-better service.

5.   See Clark Gilbert and Joseph L. Bower, “Disruptive Change: When Trying Harder Is Part of the Problem,” Harvard Business Review, May 2002, 94–101; and Clark Gilbert, “Can Competing Frames Co-exist? The Paradox of Threatened Response,” working paper 02-056, Boston, Harvard Business School, 2002.

6.   Daniel Kahneman and Amos Tversky, “Choice, Values, and Frames,” American Psychologist 39 (1984): 341–350. Kahneman and Tversky published prodigiously on these issues. This reference is simply an example of their work.

7.   The phenomenon of threat rigidity has been examined by a number of scholars, notably Jane Dutton and her colleagues. See, for example, Jane E. Dutton and Susan E. Jackson, “Categorizing Strategic Issues: Links to Organizational Action,” Academy of Management Review 12 (1987): 76–90; and Jane E. Dutton, “The Making of Organizational Opportunities—An Interpretive Pathway to Organizational Change,” Research in Organizational Behavior 15 (1992): 195–226.

8.   Arthur Stinchcombe has written eloquently on the proposition that getting the initial conditions right is key to causing subsequent events to happen as desired. See Arthur Stinchcombe, “Social Structure and Organizations,” in Handbook of Organizations, ed. James March (Chicago: McNally, 1965), 142–193.

9.   Clark Gilbert, “Pandesic—The Challenges of a New Business Venture,” case 9-399-129 (Boston: Harvard Business School, 2000).

CHAPTER FIVE

GETTING THE SCOPE OF THE BUSINESS RIGHT

Which activities should a new-growth venture do internally in order to be as successful as possible as fast as possible, and which should it outsource to a supplier or a partner? Will success be best built around a proprietary product architecture, or should the venture embrace modular, open industry standards? What causes the evolution from closed and proprietary product architectures to open ones? Might companies need to adopt proprietary solutions again, once open standards have emerged?

Decisions about what to in-source and what to procure from suppliers and partners have a powerful impact on a new-growth venture’s chances for success. A widely used theory to guide this decision is built on categories of core and competence. If something fits your core competence, you should do it inside. If it’s not your core competence and another firm can do it better, the theory goes, you should rely on them to provide it.[1]

Right? Well, sometimes. The problem with the core-competence/ not-your-core-competence categorization is that what might seem to be a noncore activity today might become an absolutely critical competence to have mastered in a proprietary way in the future, and vice versa.

Consider, for example, IBM’s decision to outsource the microprocessor for its PC business to Intel, and its operating system to Microsoft. IBM made these decisions in the early 1980s in order to focus on what it did best—designing, assembling, and marketing computer systems. Given its history, these choices made perfect sense. Component suppliers to IBM historically had lived a miserable, profit-free existence, and the business press widely praised IBM’s decision to out-source these components of its PC. It dramatically reduced the cost and time required for development and launch. And yet in the process of outsourcing what it did not perceive to be core to the new business, IBM put into business the two companies that subsequently captured most of the profit in the industry.

How could IBM have known in advance that such a sensible decision would prove so costly? More broadly, how can any executive who is launching a new-growth business, as IBM was doing with its PC division in the early 1980s, know which value-added activities are those in which future competence needs to be mastered and kept inside? [2]

Because evidence from the past can be such a misleading guide to the future, the only way to see accurately what the future will bring is to use theory. In this case, we need a circumstance-based theory to describe the mechanism by which activities become core or peripheral. Describing this mechanism and showing how managers can use the theory is the purpose of chapters 5 and 6.

Integrate or Outsource?

IBM and others have demonstrated—inadvertently, of course—that the core/noncore categorization can lead to serious and even fatal mistakes. Instead of asking what their company does best today, managers should ask, “What do we need to master today, and what will we need to master in the future, in order to excel on the trajectory of improvement that customers will define as important?”

The answer begins with the job-to-be-done approach: Customers will not buy your product unless it solves an important problem for them. But what constitutes a “solution” differs across the two circumstances in figure 5-1: whether products are not good enough or are more than good enough. The advantage, we have found, goes to integration when products are not good enough, and to outsourcing—or specialization and dis-integration—when products are more than good enough.

FIGURE 5 - 1

Product Architectures and Integration

To explain, we need to explore the engineering concepts of interdependence and modularity and their importance in shaping a product’s design. We will then return to figure 5-1 to see these concepts at work in the disruption diagram.

Product Architecture and Interfaces

A product’s architecture determines its constituent components and subsystems and defines how they must interact—fit and work together—in order to achieve the targeted functionality. The place where any two components fit together is called an interface. Interfaces exist within a product, as well as between stages in the value-added chain. For example, there is an interface between design and manufacturing, and another between manufacturing and distribution.

An architecture is interdependent at an interface if one part cannot be created independently of the other part—if the way one is designed and made depends on the way the other is being designed and made. When there is an interface across which there are unpredictable interdependencies, then the same organization must simultaneously develop both of the components if it hopes to develop either component.

Interdependent architectures optimize performance, in terms of functionality and reliability. By definition, these architectures are proprietary because each company will develop its own interdependent design to optimize performance in a different way. When we use the term interdependent architecture in this chapter, readers can substitute as synonyms optimized and proprietary architecture.

In contrast, a modular interface is a clean one, in which there are no unpredictable interdependencies across components or stages of the value chain. Modular components fit and work together in well-understood and highly defined ways. A modular architecture specifies the fit and function of all elements so completely that it doesn’t matter who makes the components or subsystems, as long as they meet the specifications. Modular components can be developed in independent work groups or by different companies working at arm’s length.

Modular architectures optimize flexibility, but because they require tight specification, they give engineers fewer degrees of freedom in design. As a result, modular flexibility comes at the sacrifice of performance.[3]

Pure modularity and interdependence are the ends of a spectrum: Most products fall somewhere between these extremes. As we shall see, companies are more likely to succeed when they match product architecture to their competitive circumstances.

Competing with Interdependent Architecture

in a Not-Good-Enough World

The left side of figure 5-1 indicates that when there is a performance gap—when product functionality and reliability are not yet good enough to address the needs of customers in a given tier of the market—companies must compete by making the best possible products. In the race to do this, firms that build their products around proprietary, interdependent architectures enjoy an important competitive advantage against competitors whose product architectures are modular, because the standardization inherent in modularity takes too many degrees of design freedom away from engineers, and they cannot optimize performance.

To close the performance gap with each new product generation, competitive forces compel engineers to fit the pieces of their systems together in ever-more-efficient ways in order to wring the most performance possible out of the technology that is available. When firms must compete by making the best possible products, they cannot simply assemble standardized components, because from an engineering point of view, standardization of interfaces (meaning fewer degrees of design freedom) would force them to back away from the frontier of what is technologically possible. When the product is not good enough, backing off from the best that can be done means that you’ll fall behind.

Companies that compete with proprietary, interdependent architectures must be integrated: They must control the design and manufacture of every critical component of the system in order to make any piece of the system. As an illustration, during the early days of the mainframe computer industry, when functionality and reliability were not yet good enough to satisfy the needs of mainstream customers, you could not have existed as an independent contract manufacturer of mainframe computers because the way the machines were designed depended on the art that would be used in manufacturing, and vice versa. There was no clean interface between design and manufacturing. Similarly, you could not have existed as an independent supplier of operating systems, core memory, or logic circuitry to the mainframe industry because these key subsystems had to be interdependently and iteratively designed, too.[4]

New, immature technologies are often drafted into use as sustaining improvements when functionality is not good enough. One reason why entrant companies rarely succeed in commercializing a radically new technology is that breakthrough sustaining technologies are rarely plug-compatible with existing systems of use.[5] There are almost always many unforseen interdependencies that mandate change in other elements of the system before a viable product that incorporates a radically new technology can be sold. This makes the new product development cycle tortuously long when breakthrough technology is expected to be the foundation for improved performance. The use of advanced ceramics materials in engines, the deployment of high-bandwidth DSL lines at the “last mile” of the telecommunications infrastructure, the building of superconducting electric motors for ship propulsion, and the transition from analog to digital to all-optical telecommunications networks could all only be accomplished by extensively integrated companies whose scope could encompass all of the interdependencies that needed to be managed. This is treacherous terrain for entrants.

For these reasons it wasn’t just IBM that dominated the early computer industry by virtue of its integration. Ford and General Motors, as the most integrated companies, were the dominant competitors during the not-good-enough era of the automobile industry’s history. For the same reasons, RCA, Xerox, AT&T, Standard Oil, and US Steel dominated their industries at similar stages. These firms enjoyed near-monopoly power. Their market dominance was the result of the not-good-enough circumstance, which mandated interdependent product or value chain architectures and vertical integration.[6] But their hegemony proved only temporary, because ultimately, companies that have excelled in the race to make the best possible products find themselves making products that are too good. When that happens, the intricate fabric of success of integrated companies like these begins to unravel.

Overshooting and Modularization

One symptom that these changes are afoot—that the functionality and reliability of a product have become too good—is that salespeople will return to the office cursing a customer: “Why can’t they see that our product is better than the competition? They’re treating it like a commodity!” This is evidence of overshooting. Such companies find themselves on the right side of figure 5-1, where there is a performance surplus. Customers are happy to accept improved products, but they’re unwilling to pay a premium price to get them.[7]

Overshooting does not mean that customers will no longer pay for improvements. It just means that the type of improvement for which they will pay a premium price will change. Once their requirements for functionality and reliability have been met, customers begin to redefine what is not good enough. What becomes not good enough is that customers can’t get exactly what they want exactly when they need it, as conveniently as possible. Customers become willing to pay premium prices for improved performance along this new trajectory of innovation in speed, convenience, and customization. When this happens, we say that the basis of competition in a tier of the market has changed.

The pressure of competing along this new trajectory of improvement forces a gradual evolution in product architecture, as depicted in figure 5-1—away from the interdependent, proprietary architectures that had the advantage in the not-good-enough era toward modular designs in the era of performance surplus. Modular architectures help companies to compete on the dimensions that matter in the lower-right portions of the disruption diagram. Companies can introduce new products faster because they can upgrade individual subsystems without having to redesign everything. Although standard interfaces invariably force compromise in system performance, firms have the slack to trade away some performance with these customers because functionality is more than good enough.

Modularity has a profound impact on industry structure because it enables independent, nonintegrated organizations to sell, buy, and assemble components and subsystems.[8] Whereas in the interdependent world you had to make all of the key elements of the system in order to make any of them, in a modular world you can prosper by outsourcing or by supplying just one element. Ultimately, the specifications for modular interfaces will coalesce as industry standards. When that happens, companies can mix and match components from best-of-breed suppliers in order to respond conveniently to the specific needs of individual customers.

As depicted in figure 5-1, these nonintegrated competitors disrupt the integrated leader. Although we have drawn this diagram in two dimensions for simplicity, technically speaking they are hybrid disruptors because they compete with a modified metric of performance on the vertical axis of the disruption diagram, in that they strive to deliver rapidly exactly what each customer needs. Yet, because their nonintegrated structure gives them lower overhead costs, they can profitably pick off low-end customers with discount prices.

From Interdependent to Modular Design—and Back

The progression from integration to modularization plays itself out over and over as products improve enough to overshoot customers’ requirements.[9] When wave after wave of sequential disruptions sweep through an industry, this progression repeats itself within each wave. In the original mainframe value network of the computer industry, for example, IBM enjoyed unquestioned dominance in the first decade with its interdependent architectures and vertical integration. In 1964, however, it responded to cost, complexity, and time-to-market pressure by creating a more modular design starting with its System 360. Modularization forced IBM to back away from the frontier of functionality, shifting from the left to the right trajectory of performance improvement in figure 5-1. This created space at the high end for competitors such as Control Data and Cray Research, whose interdependent architectures continued to push the bleeding edge of what was possible.

Opening its architecture was not a mistake for IBM: The economics of competition forced it to take these steps. Indeed, modularity reduced development and production costs and enabled IBM to custom-configure systems for each customer. This created a major new wave of growth in the industry. Another effect of modularization, however, was that nonintegrated companies could begin to compete effectively. A population of nonintegrated suppliers of plug-compatible components and subsystems such as disk drives, printers, and data input devices enjoyed lower overhead costs and began disrupting IBM en masse.[10]

This cycle repeated itself when minicomputers began their new-market disruption of mainframes. Digital Equipment Corporation initially dominated that industry with its proprietary architecture when minicomputers really weren’t very good, because its hardware and operating system software were interdependently designed to maximize performance. As functionality subsequently approached adequacy, however, other competitors such as Data General, Wang Laboratories, and Prime Computer that were far less integrated but much faster to market began taking significant share.[11] As happened in mainframes, the minicomputer market boomed because of the better and less-expensive products that this intensified competition created.

The same sequence occurred in the personal computer wave of disruption. During the early years, Apple Computer—the most integrated company with a proprietary architecture—made by far the best desktop computers. They were easier to use and crashed much less often than computers of modular construction. Ultimately, when the functionality of desktop machines became good enough, IBM’s modular, open-standard architecture became dominant. Apple’s proprietary architecture, which in the not-good-enough circumstance was a competitive strength, became a competitive liability in the more-than-good-enough circumstance. Apple as a consequence was relegated to niche-player status as the growth explosion in personal computers was captured by the nonintegrated providers of modular machines.

The same transition will have occurred before long in the next two waves of disruptive computer products—notebook computers and hand-held wireless devices. The companies that are most successful in the beginning are those with optimized, interdependent architectures. Companies whose strategy is prematurely modular will struggle to be performance-competitive during the early years when performance is the basis of competition. Later, architectures and industry structures will evolve toward openness and dis-integration.

Figure 5-2 summarizes these transitions in the personal computer industry in a simplified way, showing how the proprietary systems and vertically integrated company that was strongest during the industry’s initial not-good-enough years gave way to a nonintegrated, horizontally stratified population of companies in its later years. It almost looks like the industry got pushed through a bologna slicer. The chart would look similar for each of the value networks in the industry. In each instance, the driver of modularization and dis-integration was not the passage of time or the “maturation” of the industry per se.[12] What drives this process is this predictable causal sequence:

1. The pace of technological improvement outstrips the ability of customers to utilize it, so that a product’s functionality and reliability that were not good enough at one point overshoot what customers can utilize at a later point.

2. This forces companies to compete differently: The basis of competition changes. As customers become less and less willing to reward further improvements in functionality and reliability with premium prices, those suppliers that get better and better at conveniently giving customers exactly what they want when they need it are able to earn attractive margins.

3. As competitive pressures force companies to be as fast and responsive as possible, they solve this problem by evolving the architecture of their products from being proprietary and interdependent toward being modular.

4. Modularity enables the dis-integration of the industry. A population of nonintegrated firms can now outcompete the integrated firms that had dominated the industry. Whereas integration at one point was a competitive necessity, it later becomes a competitive disadvantage.[13]

FIGURE 5 - 2

The Transition from Vertical Integration to Horizontal Stratification in the Microprocessor-Based Computer Industry

Figure 5-2 is simplified, in that the integrated business model did not disappear overnight—rather, it became less dominant as the trajectory of performance improvement passed through each tier of each market and the modular model gradually became more dominant.

We emphasize that the circumstances of performance gaps and performance surpluses drive the viability of these strategies of architecture and integration. This means, of course, that if the circumstances change again, the strategic approach must also change. Indeed, after 1990 there has been some reintegration in the computer industry. We describe one factor that drives reintegration in the next section, and return to it in chapter 6.

The Drivers of Reintegration

Because the trajectory of technological improvement typically outstrips the ability of customers in any given tier of the market to utilize it, the general current flows from interdependent architectures and integrated companies toward modular architectures and nonintegrated companies. But remember, customers’ needs change too. Usually this happens at a relatively slower pace, as suggested by the dotted lines on the disruption diagram. On occasion there can be a discontinuous shift in the functionality that customers demand, essentially shifting the dotted line in figure 5-1 upward. This flips the industry back toward the left side of the diagram and resets the clock into an era in which integration once again is the source of competitive advantage.

For example, in the early 1980s Apple Computer’s products employed a proprietary architecture involving extensive interdependence within the software and across the hardware–software interface. By the mid-1980s, however, a population of specialized firms such as WordPerfect and Lotus, whose products plugged into Microsoft’s DOS operating system through a well-defined interface, had arisen to dethrone Apple’s dominance in software. Then in the early 1990s, the dotted lines of functionality that customers needed in PC software seemed to shift up as customers began demanding to transfer graphics and spreadsheet files into word processing documents, and so on. This created a performance gap, flipping the industry to the not-good-enough side of the world where fitting interdependent pieces of the system together became competitively critical again.

In response, Microsoft interdependently knitted its Office suite of products (and later its Web browser) into its Windows operating system. This helped it stretch so much closer to what customers needed than could the population of focused firms that the nonintegrated software companies, including WordPerfect and Lotus’s 123 spreadsheet, vaporized very quickly. Microsoft’s dominance did not arise from monopolistic malfeasance. Rather, its integrated value chain under not-good-enough conditions enabled it to make products whose performance came closer to what customers needed than could nonintegrated competitors under those conditions.[14]

Today, however, things may be poised to flip again. As computing becomes more Internet-centric, operating systems with modular architectures (such as Linux), and modular programming languages (such as Java) constitute hybrid disruptions relative to Microsoft. This modularity is enabling a population of specialized firms to begin making incursions into this industry.

In a similar way, fifteen years ago in optical telecommunications the bandwidth available over a fiber was more than good enough for voice communication; as a consequence, the industry structure was horizontally stratified, not vertically integrated. Corning made the optical fiber, Siemens cabled it, and other companies made the multiplexers, the amplifiers, and so on. As the screams for more bandwidth intensified in the late 1990s, the dotted line in figure 5-1 shifted up, and the industry flipped into a not-good-enough situation. Corning found that it could not even design its next generation of fiber if it did not interdependently design the amplifier, for example. It had to integrate across this interface in order to compete, and it did so. Within a few years, there was more than enough bandwidth over a fiber, and the rationale for being vertically integrated disappeared again.

The general rule is that companies will prosper when they are integrated across interfaces in the value chain where performance, however it is defined at that point, is not good enough relative to what customers require at the next stage of value addition. There are often several of these points in the complete value-added chain of an industry. This means that an industry will rarely be completely nonintegrated or integrated. Rather, the points at which integration and nonintegration are competitively important will predictably shift over time.[15] We return to this notion in greater detail in chapter 6.

Aligning Your Architecture Strategy to Your Circumstances

In a modular world, supplying a component or assembling outsourced components are both appropriate “solutions.” In the interdependent world of inadequate functionality, attempting to provide one piece of the system doesn’t solve anybody’s problem. Knowing this, we can predict the failure or success of a growth business based on managers’ choices to compete with modular architectures when the circumstances mandate interdependence, and vice versa.

Attempting to Grow a Nonintegrated Business When

Functionality Isn’t Good Enough

It’s tempting to think you can launch a new-growth business by providing one piece of a modular product’s value. Managers often see specialization as a less daunting path to entry than providing an entire system solution. It costs less and allows the entrant to focus on what it does best, leaving the rest of the solution to other partners in the ecosystem. This works in the circumstances in the lower-right portions of the disruption diagram. But when functionality and reliability are inadequate, the seemingly lower hurdle that partnering or outsourcing seems to present usually proves illusory, and causes many growth ventures to fail. Modularity often is not technologically or competitively possible during the early stages of many disruptions.

To succeed with a nonintegrated, specialist strategy, you need to be certain you’re competing in a modular world. Three conditions must be met in order for a firm to procure something from a supplier or partner, or to sell it to a customer. First, both suppliers and customers need to know what to specify—which attributes of the component are crucial to the operation of the product system, and which are not. Second, they must be able to measure those attributes so that they can verify that the specifications have been met. Third, there cannot be any poorly understood or unpredictable interdependencies across the customer–supplier interface. The customer needs to understand how the subsystem will interact with the performance of other pieces of the system so that it can be used with predictable effect. These three conditions—specifiability, verifiability, and predictability—constitute an effective modular interface.

When product performance is not good enough—when competition forces companies to use new technologies in nonstandard product architectures to stretch performance as far as possible—these three conditions often are not met. When there are complex, reciprocal, unpredictable interdependencies in the system, a single organization’s boundaries must span those interfaces. People cannot efficiently resolve interdependent problems while working at arm’s length across an organizational boundary.[16]

Modular Failures in Interdependent Circumstances

In 1996 the United States government passed legislation to stimulate competition in local telecommunication services. The law mandated that independent companies be allowed to sell services to residential and business customers and then to plug into the switching infrastructure of the incumbent telephone companies. In response, many nonintegrated competitive local exchange carriers (CLECs) such as Northpoint Communications attempted to offer high-speed DSL access to the Internet. Corporations and venture capitalists funneled billions of dollars into these companies.

The vast majority of CLECs failed. This is because DSL service was in the interdependent realm of figure 5-1. There were too many subtle and unpredictable interdependencies between what the CLECs did when they installed service on a customer’s premises and what the telephone company had to do in response. It wasn’t necessarily the technical interface that was the problem. The architecture of the telephone companies’ billing system software, for example, was interdependent—making it very difficult to account and bill for the cost of a “plugged-in” CLEC customer. The fact that the telephone companies were integrated across these interdependent interfaces gave them a powerful advantage. They understood their own network and IT system architectures and could consequently deploy their offerings more quickly with fewer concerns about the unintended consequences of reconfiguring their own central office facilities.[17]

Similarly, in the eagerly anticipated wireless-access-to-data-over-the-Internet industry, most European and North American competitors tried to enter as nonintegrated specialists, providing one element of the system. They relied prematurely on industry standards such as Wireless Applications Protocol (WAP) to define the interfaces between the handset device, the network, and the new content being developed. Companies within each link in the value chain were left to their own devices to determine how best to exploit the wireless Internet. Almost no revenues and billions in losses have resulted. The “partnering” theology that had become de rigueur among telecommunications investors and entrepreneurs who had watched Cisco succeed by partnering turned out to be misapplied in a different circumstance in which it couldn’t work—with tragic consequences.

Appropriate Integration

In contrast, Japan’s NTT DoCoMo and J-Phone have approached the new-market disruptive opportunity of the wireless Internet with far greater integration across stages of the value chain. These growth ventures already claim tens of millions of customers and billions in revenue.[18] Although they do not own every upstream or downstream connection in the value chain, DoCoMo and J-Phone carefully manage the interfaces with their content providers and handset manufacturers. Their interdependent approach allows them to surmount the technological limitations of wireless data and to create user interfaces, a revenue model, and a billing infrastructure that make the customer experience as seamless as possible.[19]

The DoCoMo and J-Phone networks comprise competing, proprietary systems. Isn’t this inefficient? Executives and investors indeed are often eager to hammer out the standards before they invest their money, to preempt wasteful duplication of competing standards and the possibility that a competitor’s approach might emerge as the industry’s standard. This works when functionality and reliability and the consequent competitive conditions permit it. But when they do not, then having competing proprietary systems is not wasteful.[20] Far more is wasted when huge sums are spent on an architectural approach that does not fit the basis of competition. True, one system ultimately may define the standard, and those whose standards do not prevail may fall by the wayside after their initial success, or they may become niche players. Competition of this sort inspired Adam Smith and Charles Darwin to write their books.

Parenthetically, we note that in some of its ventures abroad, such as in its partnership with AT&T Wireless in the United States, DoCoMo has followed its partners’ strategy of adopting industry standards with less vertical integration and has stumbled badly, just like its American and European counterparts. It’s not DoCoMo that makes the difference. It’s employing the right strategy in the right circumstances that makes the difference.

Being in the Right Place at the Right Time

We noted earlier that the pure forms of interdependence and modularity are the extremes on a continuum, and companies may choose strategies anywhere along the spectrum at any point in time. A company may not necessarily fail if it starts with a prematurely modular architecture when the basis of competition is functionality and reliability. It will simply suffer from an important competitive disadvantage until the basis of competition shifts and modularity becomes the predominant architectural form. This was the experience of IBM and its clones in the personal computer industry. The superior performance of Apple’s computers did not preclude IBM from succeeding. IBM just had to fight its performance disadvantage because it opted prematurely for a modular architecture.

What happens to the initial leaders when they overshoot, after having jumped ahead of the pack with performance and reliability advantages that were grounded in proprietary architecture? The answer is that they need to modularize and open up their architectures and begin aggressively to sell their subsystems as modules to other companies whose low-cost assembly capability can help grow the market. Had good theory been available to provide guidance, for example, there is no reason why the executives of Apple Computer could not have modularized their design and have begun selling their operating system with its interdependent applications to other computer assemblers, preempting Microsoft’s development of Windows. Nokia appears today to be facing the same decision. We sense that adding even more features and functions to standard wireless handsets is overshooting what its less-demanding customers can utilize; and a dis-integrated handset industry that utilizes Symbian’s operating system is rapidly gaining traction. The next chapter will show that a company can begin with a proprietary architecture when disruptive circumstances mandate it, and then, when the basis of competition changes, open its architecture to become a supplier of key subsystems to low-cost assemblers. If it does this, it can avoid the traps of becoming a niche player on the one hand and the supplier of an undifferentiated commodity on the other. The company can become capitalism’s equivalent of Wayne Gretzky, the hockey great. Gretzky had an instinct not to skate to where the puck presently was on the ice, but instead to skate to where the puck was going to be. chapter 6 can help managers steer their companies not to the profitable businesses of the past, but to where the money will be.

There are few decisions in building and sustaining a new-growth business that scream more loudly for sound, circumstance-based theory than those addressed in this chapter. When the functionality and reliability of a product are not good enough to meet customers’ needs, then the companies that will enjoy significant competitive advantage are those whose product architectures are proprietary and that are integrated across the performance-limiting interfaces in the value chain. When functionality and reliability become more than adequate, so that speed and responsiveness are the dimensions of competition that are not now good enough, then the opposite is true. A population of nonintegrated, specialized companies whose rules of interaction are defined by modular architectures and industry standards holds the upper hand.

At the beginning of a wave of new-market disruption, the companies that initially will be the most successful will be integrated firms whose architectures are proprietary because the product isn’t yet good enough. After a few years of success in performance improvement, those disruptive pioneers themselves become susceptible to hybrid disruption by a faster and more flexible population of nonintegrated companies whose focus gives them lower overhead costs.

For a company that serves customers in multiple tiers of the market, managing the transition is tricky, because the strategy and business model that are required to successfully reach unsatisfied customers in higher tiers are very different from those that are necessary to compete with speed, flexibility, and low cost in lower tiers of the market. Pursuing both ends at once and in the right way often requires multiple business units—a topic that we address in the next two chapters.

Notes

1.   We are indebted to a host of thoughtful researchers who have framed the existence and the role of core and competence in making these decisions. These include C. K. Prahalad and Gary Hamel, “The Core Competence of the Corporation,” Harvard Business Review, May–June 1990, 79–91; and Geoffrey Moore, Living on the Fault Line (New York: HarperBusiness, 2002). It is worth noting that “core competence,” as the term was originally coined by C. K. Prahalad and Gary Hamel in their seminal article, was actually an apology for the diversified firm. They were developing a view of diversification based on the exploitation of established capabilities, broadly defined. We interpret their work as consistent with a well-respected stream of research and theoretical development that goes all the way back to Edith Penrose’s 1959 book The Theory of the Growth of the Firm (New York: Wiley). This line of thinking is very powerful and useful. As it is used now, however, the term “core competence” has become synonymous with “focus”; that is, firms that seek to exploit their core competence do not diversify—if anything, they focus their business on those activities that they do particularly well. It is this “meaning in use” that we feel is misguided.

2.   IBM arguably had much deeper technological capability in integrated circuit and operating system design and manufacturing than did Intel or Microsoft at the time IBM put these companies into business. It probably is more correct, therefore, to say that this decision was based more on what was core than what was competence. The sense that IBM needed to outsource was based on the correct perception of the new venture’s managers that they needed a far lower overhead cost structure to become acceptably profitable to the corporation and needed to be much faster in new-product development than the company’s established internal development processes, which had been honed in a world of complicated interdependent products with longer development cycles, could handle.

3.   In the past decade there has been a flowering of important studies on these concepts. We have found the following ones to be particularly helpful: Rebecca Henderson and Kim B. Clark, “Architectural Innovation: The Reconfiguration of Existing Product Technologies and the Failure of Established Firms,” Administrative Science Quarterly 35 (1990): 9–30; K. Monteverde, “Technical Dialog as an Incentive for Vertical Integration in the Semiconductor Industry,” Management Science 41 (1995): 1624–1638; Karl Ulrich, “The Role of Product Architecture in the Manufacturing Firm,” Research Policy 24 (1995): 419–440; Ron Sanchez and J. T. Mahoney, “Modularity, Flexibility and Knowledge Management in Product and Organization Design,” Strategic Management Journal 17 (1996): 63–76; and Carliss Baldwin and Kim B. Clark, Design Rules: The Power of Modularity (Cambridge, MA: MIT Press, 2000).

4.   The language we have used here characterizes the extremes of interdependence, and we have chosen the extreme end of the spectrum simply to make the concept as clear as possible. In complex product systems, there are varying degrees of interdependence, which differ over time, component by component. The challenges of interdependence can also be dealt with to some degree through the nature of supplier relationships. See, for example, Jeffrey Dyer, Collaborative Advantage: Winning Through Extended Enterprise Supplier Networks (New York: Oxford University Press, 2000).

5.   Many readers have equated in their minds the terms disruptive and breakthrough. It is extremely important, for purposes of prediction and understanding, not to confuse the terms. Almost invariably, what prior writers have termed “breakthrough” technologies have, in our parlance, a sustaining impact on the trajectory of technological progress. Some sustaining innovations are simple, incremental year-to-year improvements. Other sustaining innovations are dramatic, breakthrough leapfrogs ahead of the competition, up the sustaining trajectory. For predictive purposes, however, the distinction between incremental and breakthrough technologies rarely matters. Because both types have a sustaining impact, the established firms typically triumph. Disruptive innovations usually do not entail technological breakthroughs. Rather, they package available technologies in a disruptive business model. New breakthrough technologies that emerge from research labs are almost always sustaining in character, and almost always entail unpredictable interdependencies with other subsystems in the product. Hence, there are two powerful reasons why the established firms have a strong advantage in commercializing these technologies.

6.   Professor Alfred Chandler’s The Visible Hand (Cambridge, MA: Belknap Press, 1977) is a classic study of how and why vertical integration is critical to the growth of many industries during their early period.

7.   Economists’ concept of utility, or the satisfaction that customers receive when they buy and use a product, is a good way to describe how competition in an industry changes when this happens. The marginal utility that customers receive is the incremental addition to satisfaction that they get from buying a better-performing product. The increased price that they are willing to pay for a better product will be proportional to the increased utility they receive from using it—in other words, the marginal price improvement will equal the improvement in marginal utility. When customers can no longer utilize further improvements in a product, marginal utility falls toward zero, and as a result customers become unwilling to pay higher prices for better-performing products.

8.   Sanchez and Mahoney, in “Modularity, Flexibility and Knowledge Management in Product and Organization Design,” were among the first to describe this phenomenon.

9.   The landmark work of Professors Carliss Baldwin and Kim B. Clark, cited in note 3, describes the process of modularization in a cogent, useful way. We recommend it to those who are interested in studying the process in greater detail.

10.  Many students of IBM’s history will disagree with our statement that competition forced the opening of IBM’s architecture, contending instead that the U.S. government’s antitrust litigation forced IBM open. The antitrust action clearly influenced IBM, but we would argue that government action or not, competitive and disruptive forces would have brought an end to IBM’s position of near-monopoly power.

11.  Tracy Kidder’s Pulitzer Prize–winning account of product development at Data General, The Soul of a New Machine (New York: Avon Books, 1981), describes what life was like as the basis of competition began to change in the minicomputer industry.

12.  MIT Professor Charles Fine has written an important book on this topic as well: Clockspeed (Reading, MA: Perseus Books, 1998). Fine observed that industries go through cycles of integration and nonintegration in a sort of “double helix” cycle. We hope that the model outlined here and in chapter 6 both confirms and adds causal richness to Fine’s findings.

13.  The evolving structure of the lending industry offers a clear example of these forces at work. Integrated banks such as J.P. Morgan Chase have powerful competitive advantages in the most complex tiers of the lending market. Integration is key to their ability to knit together huge, complex financing packages for sophisticated and demanding global customers. Decisions about whether and how much to lend cannot be made according to fixed formulas and measures; they can only be made through the intuition of experienced lending officers.

Credit scoring technology and asset securitization, however, are disrupting and dis-integrating the simpler tiers of the lending market. In these tiers, lenders know and can measure precisely those attributes that determine whether borrowers will repay a loan. Verifiable information about borrowers—such as how long they have lived where they live, how long they have worked where they work, what their income is, and whether they’ve paid other bills on time—is combined to make algorithm-based lending decisions. Credit scoring took root in the 1960s in the simplest tier of the lending market, in department stores’ decisions to issue their own credit cards. Then, unfortunately for the big banks, the disruptive horde moved inexorably up-market in pursuit of profit—first to general consumer credit card loans, then to automobile loans and mortgage loans, and now to small business loans. The lending industry in these simpler tiers of the market has largely dis-integrated. Specialist nonbank companies have emerged to provide each slice of added value in these tiers of the lending industry. Whereas integration is a big advantage in the most complex tiers of the market, in overserved tiers it is a disadvantage.

14.  Our conclusions support those of Stan J. Liebowitz and Stephen E. Margolis in Winners, Losers & Microsoft: Competition and Antitrust in High Technology (Oakland, CA: Independent Institute, 1999).

15.  Another good illustration of this is the push being made by Apple Computer, at the time of this writing, to be the gateway to the consumer for multimedia entertainment. Apple’s interdependent integration of the operating system and applications creates convenience, which customers value at this point because convenience is not yet good enough.

16.  Specifiability, measurability, and predictability constitute what an economist would term “sufficient information” for an efficient market to emerge at an interface, allowing organizations to deal with each other at arm’s length. A fundamental tenet of capitalism is that the invisible hand of market competition is superior to that of managerial oversight as a coordinating mechanism between actors in a market. This is why, when a modular interface becomes defined, an industry will dis-integrate at that interface. However, when specifiability, measurability, and predictability do not exist, efficient markets cannot function. It is under these circumstances that managerial oversight and coordination perform better than market competition as a coordinating mechanism.

This is an important underpinning of the award-winning findings of Professor Tarun Khanna and his colleagues, which show that in developing economies, diversified business conglomerates outperform focused, independent companies, whereas the reverse is true in developed economies. See, for example, Tarun Khanna and Krishna G. Palepu, “Why Focused Strategies May Be Wrong for Emerging Markets,” Harvard Business Review, July–August 1997, 41–51; and Tarun Khanna and Jan Rivkin, “Estimating the Performance Effects of Business Groups in Emerging Markets,” Strategic Management Journal 22 (2001): 45–74.

A bedrock set of concepts in understanding why organizational integration is critical when the conditions of modularity are not met is developed in the transaction cost economics (TCE) school of thought, which traces its origins to the work of Ronald Coase (R. H. Coase, “The Nature of the Firm,” Econometrica 4 [1937]: 386–405). Coase argued that firms were created when it got “too expensive” to negotiate and enforce contracts between otherwise “independent” parties. More recently, the work of Oliver Williamson has proven seminal in the exploration of transaction costs as a determinant of firm boundaries. See, for example, O. E. Williamson, Markets and Hierarchies (New York: Free Press, 1975); “Transaction Cost Economics,” in The Economic Institutions of Capitalism, ed., O. E. Williamson (New York: Free Press, 1985), 15–42; and “Transaction-Cost Economics: The Governance of Contractual Relations,” in Organiational Economics, ed., J. B. Barney and W. G. Ouichi (San Francisco: Jossey-Bass, 1986). In particular, TCE has been used to explain the various ways in which firms might expand their operating scope: either through unrelated diversification (C. W. L. Hill, et al., “Cooperative Versus Competitive Structures in Related and Unrelated Diversified Firms,” Organization Science 3, no. 4 [1992]: 501–521); related diversification (D. J. Teece, “Economics of Scope and the Scope of the Enterprise,” Journal of Economic Behavior and Organization 1 [1980]: 223–247); and D. J. Teece, “Toward an Economic Theory of the Multiproduct Firm,” Journal of Economic Behavior and Organization 3 [1982], 39–63); or vertical integration (K. Arrow, The Limits of Organization [New York: W. W. Norton, 1974]; B. R. G. Klein, et al., “Vertical Integration, Appropriable Rents and Competitive Contracting Process,” Journal of Law and Economics 21 [1978] 297–326; and K. R. Harrigan, “Vertical Integration and Corporate Strategy,” Academy of Management Journal 28, no. 2 [1985]: 397–425). More generally, this line of research is known as the “market failures” paradigm for explaining changes in firm scope (K. N. M. Dundas, and P. R. Richardson, “Corporate Strategy and the Concept of Market Failure,” Strategic Management Journal 1, no. 2 [1980]: 177–188). Our hope is that we have advanced this line of thinking by elaborating more precisely the considerations that give rise to the contracting difficulties that lie at the heart of the TCE school.

17.  Even if the incumbent local exchange carriers (ILECs) didn’t understand all the complexities and unintended consequences better than CLEC engineers, organizationally they were much better positioned to resolve any difficulties, since they could appeal to organizational mechanisms rather than have to rely on cumbersome and likely incomplete ex ante contracts.

18.  See Jeffrey Lee Funk, The Mobile Internet: How Japan Dialed Up and the West Disconnected (Hong Kong: ISI Publications, 2001). This really is an extraordinarily insightful study from which a host of insights can be gleaned. In his own language, Funk shows that another important reason why DoCoMo and J-Phone were so successful in Japan is that they followed the pattern that we describe in chapters 3 and 4 of this book. They initially targeted customers who were largely non-Internet users (teenaged girls) and helped them get done better a job that they had already been trying to do: have fun with their friends. Western entrants into this market, in contrast, envisioned sophisticated offerings to be sold to current customers of mobile phones (who primarily used them for business) and current users of the wire-line Internet. An internal perspective on this development can be found in Mari Matsunaga, The Birth of I-Mode: An Analogue Account of the Mobile Internet (Singapore: Chuang Yi Publishing, 2001). Matsunaga was one of the key players in the development of i-mode at DoCoMo.

19.  See “Integrate to Innovate,” a Deloitte Research study by Michael E. Raynor and Clayton M. Christensen. Available at < http://www.dc.com/vcd>, or upon request from delresearch@dc.com.

20.  Some readers who are familiar with the different experiences of the European and American mobile telephony industries may take issue with this paragraph. Very early on, the Europeans coalesced around a prenegotiated standard called GSM, which enabled mobile phone users to use their phones in any country. Mobile phone usage took off more rapidly and achieved higher penetration rates than in America, where several competing standards were battling it out. Many analysts have drawn the general conclusion from the Europeans’ strategy of quickly coalescing around a standard that it is always advisable to avoid the wasteful duplication of competing mutually incompatible architectures. We believe that the benefits of a single standard have been largely exaggerated, and that other important differences between the United States and Europe which contributed significantly to the differential adoption rates have not been given their due.

First, the benefits of a single standard appear to have manifested themselves largely in terms of supply-side rather than demand-side benefits. That is, by stipulating a single standard, European manufacturers of network equipment and handsets were able to achieve greater scale economies than companies manufacturing for the North American markets. This might well have manifested itself in the form of lower prices to consumers; however, the relevant comparison is not the cost of mobile telephony in Europe versus North America—these services were not competing with each other. The relevant comparison is with wireline telephony in each respsective market. And here it is worth noting that wireline local and long distance telephony services are much more expensive in Europe than in North America, and as a result, wireless telephony was a much more attractive substitute for wireline in Europe than in North America. The putative demand-side benefit of transnational usage has not, to our knowledge, been demonstrated in the usage patterns of European consumers. Consequently, we would be willing to suggest that a far more powerful cause of the relative success of mobile telephony in Europe was not that schoolgirls from Sweden could use their handset when on holiday in Spain, but rather the relative improvement in ease of use and cost provided by mobile telephony versus the wireline alternative.

Second, and perhaps even more important, European regulation mandated that “calling party pays” with respect to mobile phone usage, whereas North American regulators mandated that “mobile party pays.” In other words, in Europe, if you call someone’s mobile phone number, you pay the cost of the call; to the recipient, it’s free. In North America, if someone calls you on your mobile phone, it’s on your dime. As a result, Europeans were far freer in giving out their mobile phone numbers, hence increasing the likelihood of usage. For more on this topic, see Strategis Group, “Calling Party Pays Case Study Analysis; ITU-BDT Telecommunication Regulatory Database”; and ITU Web site: <http://www.itu.int/ITU-D/ict/statistics>.

Teasing out the effects of each of these contributors (the GSM standard, lower relative price versus wireline, and calling party pays regulation), as well as others that might be adduced is not a trivial task. But we would suggest that the impact of the single standard is far less than typically implied, and certainly is not the principal factor in explaining higher mobile phone penetration rates in Europe versus North America.

CHAPTER SIX

HOW TO AVOID COMMODITIZATION

What causes commoditization? Is it the inevitable end-state of all companies in competitive markets? Can companies take action at any point in their development that can arrest its onset? Once the tide of commoditization has swept through an industry, can the flow reverse back toward proprietary, differentiated, profitable products? How can I respond to this?

Many executives have resigned themselves to the belief that, no matter how miraculous their innovations, their inevitable fate is to be “commoditized.” These fears are grounded in painful experience. Here’s a frightening example: The first one-gigabyte 3.5-inch disk drives were introduced to the world in 1992 at prices that enabled their manufacturers to earn 60 percent gross margins. These days, disk drive companies are struggling to eke out 15 percent margins on drives that are sixty times better. This isn’t fair, because these things are mechanical and microelectronic marvels. How many of us could mechanically position the head so that it stored and retrieved data in circular tracks that are only 0.00008 inch apart on the surface of disks, without ever reading data off the wrong track? And yet disk drives of this genre are regarded today as undifferentiable commodities. If products this precise and complicated can be commoditized, is there any hope for the rest of us?

It turns out that there is hope. One of the most exciting insights from our research about commoditization is that whenever it is at work somewhere in a value chain, a reciprocal process of de-commoditization is at work somewhere else in the value chain.[1] And whereas commoditization destroys a company’s ability to capture profits by undermining differentiability, de-commoditization affords opportunities to create and capture potentially enormous wealth. The reciprocality of these processes means that the locus of the ability to differentiate shifts continuously in a value chain as new waves of disruption wash over an industry. As this happens, companies that position themselves at a spot in the value chain where performance is not yet good enough will capture the profit.

Our purpose in this chapter is to help managers understand how these processes of commoditization and de-commoditization work, so that they can detect when and where they are beginning to happen. We hope that this understanding can help those who are building growth businesses to do so in a place in the value chain where the forces of de-commoditization are at work. We also hope it helps those who are running established businesses to reposition their firms in the value chain to catch these waves of de-commoditization as well. To return to Wayne Gretzky’s insight about great hockey playing, we want to help managers develop the intuition for skating not to where the money presently is in the value chain, but to where the money will be.[2]

The Processes of Commoditization and De-commoditization

The process that transforms a profitable, differentiated, proprietary product into a commodity is the process of overshooting and modularization we described in chapter 5. At the leftmost side of the disruption diagram, the companies that are most successful are integrated companies that design and assemble the not-good-enough enduse products. They make attractive profits for two reasons. First, the interdependent, proprietary architecture of their products makes differentiation straightforward. Second, the high ratio of fixed to variable costs that often is inherent in the design and manufacture of architecturally interdependent products creates steep economies of scale that give larger competitors strong cost advantages and create formidable entry barriers against new competitors.

This is why, for example, IBM, as the most integrated competitor in the mainframe computer industry, held a 70 percent market share but made 95 percent of the industry’s profits: It had proprietary products, strong cost advantages, and high entry barriers. For the same reasons, from the 1950s through the 1970s, General Motors, with about 55 percent of the U.S. automobile market, garnered 80 percent of the industry’s profits. Most of the firms that were suppliers to IBM and General Motors, in contrast, had to make do with subsistence profits year after year. These firms’ experiences are typical. Making highly differentiable products with strong cost advantages is a license to print money, and lots of it.[3]

We must emphasize that the reason many companies don’t reach this nirvana or remain there for long is that it is the not-good-enough circumstance that enables managers to offer products with proprietary architectures that can be made with strong cost advantages versus competitors. When that circumstance changes—when the dominant, profitable companies overshoot what their mainstream customers can use—then this game can no longer be played, and the tables begin to turn. Customers will not pay still-higher prices for products they already deem too good. Before long, modularity rules, and commoditization sets in. When the relevant dimensions of your product’s performance are determined not by you but by the subsystems that you procure from your suppliers, it becomes difficult to earn anything more than subsistence returns in a product category that used to make a lot of money. When your world becomes modular, you’ll need to look elsewhere in the value chain to make any serious money.

The natural and inescapable process of commoditization occurs in six steps:

1. As a new market coalesces, a company develops a proprietary product that, while not good enough, comes closer to satisfying customers’ needs than any of its competitors. It does this through a proprietary architecture, and earns attractive profit margins.

2. As the company strives to keep ahead of its direct competitors, it eventually overshoots the functionality and reliability that customers in lower tiers of the market can utilize.

3. This precipitates a change in the basis of competition in those tiers, which . . .

4. . . . precipitates an evolution toward modular architectures, which . . .

5. . . . facilitates the dis-integration of the industry, which in turn . . .

6. . . . makes it very difficult to differentiate the performance or costs of the product versus those of competitors, who have access to the same components and assemble according to the same standards. This condition begins at the bottom of the market, where functional overshoot occurs first, and then moves up inexorably to affect the higher tiers.

Note that it is overshooting—the more-than-good-enough circumstance—that connects disruption and the phenomenon of commoditization. Disruption and commoditization can be seen as two sides of the same coin. A company that finds itself in a more-than-good-enough circumstance simply can’t win: Either disruption will steal its markets, or commoditization will steal its profits. Most incumbents eventually end up the victim of both, because, although the pace of commoditization varies by industry, it is inevitable, and nimble new entrants rarely miss an opportunity to exploit a disruptive foothold.

There can still be prosperity around the corner, however. The attractive profits of the future are often to be earned elsewhere in the value chain, in different stages or layers of added value. That’s because the process of commoditization initiates a reciprocal process of de-commoditization. Ironically, this de-commoditization—with the attendant ability to earn lots of money—occurs in places in the value chain where attractive profits were hard to attain in the past: in the formerly modular and undifferentiable processes, components, or subsystems.[4]

To visualize the reciprocal process, remember the steel minimills from chapter 2. As long as the minimills were competing against integrated mills in the rebar market, they made a lot of money because they had a 20 percent cost advantage relative to the integrated mills. But as soon as they drove the last high-cost competitor out of the rebar market, the low-cost minimills found themselves slugging it out against equally low-cost minimills in a commodity market, and competition among them caused pricing to collapse. The assemblers of modular products generally receive the same reward for victory as the minimills did whenever they succeed in driving the higher-cost competitors and their proprietary architectures out of a tier in their market: The victorious disruptors are left to slug it out against equally low-cost disruptors who are assembling modular components procured from a common supplier base. Lacking any basis for competitive differentiation, only subsistence levels of profit remain. A low-cost strategy works only as long as there are higher-cost competitors left in the market.[5]

The only way that modular disruptors can keep profits healthy is to carry their low-cost business models up-market as fast as possible so that they can keep competing at the margin against higher-cost makers of proprietary products. Assemblers of modular products do this by finding the best performance-defining components and subsystems and incorporating them in their products faster than anyone else.[6] The assemblers need the very best performance-defining components in order to race up-market where they can make money again. Their demand for improvements in performance-defining components, as a result, throws the suppliers of those components back to the not-good-enough side of the disruption diagram.

Competitive forces consequently compel suppliers of these performance-defining components to create architectures that, within the subsystems, are increasingly interdependent and proprietary. Hence, the performance-defining subsystems become de-commoditized as the result of the end-use products becoming modular and commoditized.

Let us summarize the steps in this reciprocal process of decommoditization:

1. The low-cost strategy of modular product assemblers is only viable as long as they are competing against higher-cost opponents. This means that as soon as they drive the high-cost suppliers of proprietary products out of a tier of the market, they must move up-market to take them on again in order to continue to earn attractive profits.

2. Because the mechanisms that constrain or determine how rapidly they can move up-market are the performance-defining subsystems, these elements become not good enough and are flipped to the left side of the disruption diagram.

3. Competition among subsystem suppliers causes their engineers to devise designs that are increasingly proprietary and interdependent. They must do this as they strive to enable their customers to deliver better performance in their end-use products than the customers could if they used competitors’ subsystems.

4. The leading providers of these subsystems therefore find themselves selling differentiated, proprietary products with attractive profitability.

5. This creation of a profitable, proprietary product is the beginning, of course, of the next cycle of commoditization and decommoditization.

Figure 6-1 illustrates more generally how this worked in the product value chain of the personal computer industry in the 1990s. Starting at the top of the diagram, money flowed from the customer to the companies that designed and assembled computers; as the decade progressed, however, less and less of the total potential profit stayed with the computer makers—most of it flowed right through these companies to their suppliers.[7]

As a result, quite a bit of the money that the assemblers got from their customers flowed over to Microsoft and lodged there. Another chunk flowed to Intel and stopped there. Money also flowed to the makers of dynamic random access memory (DRAM), such as Samsung and Micron, but not much of it stopped at those stages in the value chain in the form of profit. It flowed through and accumulated instead at firms like Applied Materials, which supplied the manufacturing equipment that the DRAM makers used. Similarly, money flowed right through the assemblers of modular disk drives, such as Maxtor and Quantum, and tended to lodge at the stage of value added where heads and disks were made.

FIGURE 6 - 1

Where the Money Was Made in the PC Industry’s Product Value Chain

What is different about the baskets in the diagram that held money, versus those through which the money seemed to leak? The tight baskets in which profit accumulated for most of this period were products that were not yet good enough for what their immediate customers in the value chain needed. The architectures of those products therefore tended to be interdependent and proprietary. Firms in the leaky-basket situation could only hang onto subsistence profits because the functionality of their products tended to be more than good enough. Their architectures therefore were modular.

If a company supplies a performance-defining but not-yet-good-enough input for its customers’ products or processes, it has the power to capture attractive profit. Consider the DRAM industry as an example. While the architecture of their own chips was modular, DRAM makers could not be satisfied even with the very best manufacturing equipment available. In order to succeed, DRAM makers needed to make their products at ever-higher yields and ever-lower costs. This rendered the functionality of equipment made by firms such as Applied Materials not good enough. The architecture of this equipment became interdependent and proprietary as a consequence, as the equipment makers strove to inch closer to the functionality that their customers needed.

It is important never to conclude that an industry such as disk drives or DRAMs is inherently unprofitable, whereas others such as microprocessors or semiconductor manufacturing equipment are inherently profitable. “Industry” is usually a faulty categorization scheme.[8] What makes an industry appear to be attractively profitable is the circumstance in which its companies happen to be at a particular point in time, at each point in the value-added chain, because the law of conservation of attractive profits is almost always at work (see the appendix to this chapter). Let’s take a deeper look at the disk drive industry to see why this is so.

For most of the 1990s, in the market tiers where disk drives were sold to makers of desktop personal computers, the capacity and access times of the drives were more than adequate. The drives’ architectures consequently became modular, and the gross margins that the nonintegrated assemblers of 3.5-inch drives could eke out in the desktop PC segment declined to around 12 percent. Nonintegrated disk drive assemblers such as Maxtor and Quantum dominated this market (their collective market share exceeded 90 percent) because integrated manufacturers such as IBM could not survive on such razor-thin margins.

The drives had adequate capacity, but the assemblers could not be satisfied even with the very best heads and disks available, because if they maximized the amount of data they could store per square inch of disk space, they could use fewer disks and heads in the drives—which was a powerful driver of cost. The heads and disks, consequently, became not good enough and evolved toward complex, interdependent subassemblies. Head and disk manufacturing became so profitable, in fact, that many major drive makers integrated backward into making their own heads and disks.[9]

But it wasn’t the disk drive industry that was marginally profitable—it was the modular circumstance in which the 3.5-inch drive makers found themselves. The evidence: The much smaller 2.5-inch disk drives used in notebook computers tended not to have enough capacity during this same era. True to form, their architectures were interdependent, and the products had to be made by integrated companies. As the most integrated manufacturer and the one with the most advanced head and disk technology in the 1990s, IBM made 40 percent gross margins in 2.5-inch drives and controlled 80 percent of that market. In contrast, IBM had less than 3 percent of the unit volume in drives sold to the desktop PC market, where its integration rendered it uncompetitive.[10]

At the time we first published our analysis of this situation in 1999, it appeared that the capacity of 2.5-inch disk drives was becoming more than good enough in the notebook computer application as well—presaging, for what had been a beautiful business for IBM, the onset of commoditization.[11] We asserted that IBM, as the most integrated drive maker, actually was in a very attractive position if it played its cards right. It could skate to where the money would be by using the advent of modularity to decouple its head and disk operations from its disk drive design and assembly business. If IBM would begin to sell its most advanced heads and disks to competing 2.5-inch disk drive makers—aggressively putting them into the business of assembling modular 2.5-inch drives—it could eventually de-emphasize the assembly of drives and focus on the more profitable head and disk components. In so doing, IBM could continue to enjoy the most attractive levels of profit in the industry. In other words, on the not-good-enough side of the disruptive diagram, IBM could fight in the war and win. On the more-than-good-enough side, a better strategy is to sell bullets to the combatants.[12]

IBM made similar moves several years earlier in its computer business, through its decisions to decouple its vertical chain and to sell its technology, components, and subsystems aggressively in the open market. Simultaneously it created a consulting and systems integration business in the high end and moved to de-emphasize the design and assembly of computers. As IBM skated to those points in the value-added chain where complex, nonstandard integration needed to occur, it led to a remarkable—and remarkably profitable—transformation of a huge company in the 1990s.

The bedrock principle bears repeating: The companies that are positioned at a spot in a value chain where performance is not yet good enough will capture the profit. That is the circumstance where differentiable products, scale-based cost advantages, and high entry barriers can be created.

To the extent that an integrated company such as IBM can flexibly couple and decouple its operations, rather than irrevocably sell off operations, it has greater potential to thrive profitably for an extended period than does a nonintegrated firm such as Compaq. This is because the processes of commoditization and de-commoditization are continuously at work, causing the place where the money will be to shift across the value chain over time.

Core Competence and the ROA-Maximizing Death Spiral

Firms that are being commoditized often ignore the reciprocal process of de-commoditization that occurs simultaneously with commoditization, either a layer down in subsystems or next door in adjacent processes. They miss the opportunity to move where the money will be in the future, and get squeezed—or even killed—as different firms catch the growth made possible by de-commoditization. In fact, powerful but perverse investor pressure to increase returns on assets (ROA) creates strong incentives for assemblers to skate away from where the money will be. And having failed to recognize their modular, commoditized circumstance, the firms turn to attribute-based core competence theory to make decisions they may later regret.

How can firms that assemble modular products meet investors’ demands that they improve their return on assets or capital employed? They cannot improve the numerator of the ROA ratio because differentiating their product or producing it at lower costs than competitors is nearly impossible. Their only option is to shrink the denominator of the ROA ratio by getting rid of assets. This would be difficult in an interdependent world that demanded integration, but the modular architecture of the product actually facilitates dis-integration. We will illustrate how this happens using a disguised example of the interactions between a component supplier and an assembler of modular personal computers. We’ll call the two firms Components Corporation and Texas Computer Corporation (TCC), respectively.

Components Corporation begins by supplying simple circuit boards to TCC. As TCC wrestles with investor pressure to get its ROA up, Components Corp. comes up with an interesting proposition: “We’ve done a good job making these little boards for you. Let us supply the whole motherboard for your computers. We can easily beat your internal costs.”

“Gosh, that would be a great idea,” TCC’s management responds. “Circuit board fabrication isn’t our core competence anyway, and it is very asset intensive. This would reduce our costs and get all those assets off our balance sheet.” So Components Corp. takes on the additional value-added activity. Its revenues increase smartly, and its profitability improves because it is utilizing its manufacturing assets better. Its stock price improves accordingly. As TCC sheds those assets, its revenue line is unaffected. But its bottom line and its return on assets improve—and its stock price improves accordingly.

A short time later Components Corp. approaches TCC’s management again. “You know, the motherboard really is the guts of the computer. Let us assemble the whole computer for you. Assembling those products really isn’t your core competency, anyway, and we can easily beat your internal costs.”

“Gosh, that would be a great idea,” TCC’s management responds. “Assembly isn’t our core competence anyway, and if you did our product assembly, we could get all those manufacturing assets off our balance sheet.” Again, as Components Corp. takes on the additional value-added activity, its revenues increase smartly and its profitability improves because it is utilizing its manufacturing assets better. Its stock price improves accordingly. And as TCC sheds its manufacturing assets, its revenue line is unaffected. But its bottom line and its return on assets improve—and its stock price improves accordingly.

A short time later Components Corp. approaches TCC’s management again. “You know, as long as we’re assembling your computers, why do you need to deal with all the hassles of managing the inbound logistics of components and the outbound logistics of customer shipments? Let us deal with your suppliers and deliver the finished products to your customers. Supply chain management really isn’t your core competence, anyway, and we can easily beat your internal costs.”

“Gosh, that would be a great idea,” TCC’s management responds. “This would help us get those current assets off our balance sheet.” As Components Corp. takes on the additional value-added activity, its revenues increase smartly and its profitability improves because it is pulling higher value-added activities into its business model. Its stock price improves accordingly. And as TCC sheds its current assets, its revenue line is unaffected. But its profitability improves—and its stock price gets another bounce.

A short time later Components Corp. approaches TCC’s management again. “You know, as long as we’re dealing with your suppliers, how about you just let us design those computers for you? The design of modular products is little more than vendor selection anyway, and since we have closer relationships with vendors than you do, we could get better pricing and delivery if we can work with them from the beginning of the design cycle.”

“Gosh, that would be a great idea,” TCC’s management responds. “This would help us cut fixed and variable costs. Besides, our strength really is in our brand and our customer relationships, not in product design.” As Components Corp. takes on the additional value-added activity, its revenues increase further and its profitability improves because it is pulling higher value-added activities into its business model. Its stock price improves accordingly. And as TCC sheds cost, its revenue line is unaffected. But its profitability improves—and its stock price gets another nice little pop—until the analysts realize that the game is over.

Ironically, in this Greek tragedy Components Corp. ends up with a value chain that is actually more highly integrated than TCC’s was when this spiral began, but often with the pieces reconfigured to allow Components Corp. to deliver against the new basis of competition, which is speed to market and the ability to responsively configure what is delivered to customers in ever-smaller segments of the market. Each time TCC off-loaded assets and processes to Components Corp., it justified its decision in terms of its own “core competence.” It did not occur to TCC’s management that the activities in question weren’t Components Corporation’s core competencies, either. Whether or not something is a core competence is not the determining factor of who can skate to where the money will be.

This story illustrates another instance of asymmetric motivations—the component supplier is motivated to integrate forward into the very pieces of value-added activity that the modular assembler is motivated to get out of. It is not a story of incompetence. It is a story of perfectly rational, profit-maximizing decisions—and because of this, the ROA-maximizing death spiral traps many companies that find themselves assembling modular products in a too-good world. At the same time, it offers another avenue for creating new-growth businesses, in addition to the disruptive opportunities described in chapter 2. The assembler rids itself of assets, but it retains its revenues and often temporarily improves its bottom-line profit margins when it decides to outsource its back-end operations to contract suppliers. It feels good. When the supplier takes on the same pieces of business that the assembler was motivated to get out of, it also feels good, because it increases the back-end supplier’s revenues, profits, and stock price. For many suppliers, eating their way up the value chain creates opportunities to design subsystems with increasingly optimized internal architectures that become key performance drivers of the modular products that its customers assemble.

This is how Intel became a vendor of chipsets and motherboards, which constitute a much more critical proportion of a computer’s added value and performance than did the bare microprocessor. Nypro, Inc., a custom injection molder of precision plastic components whose history we will examine later in this book, has followed a similar growth strategy and has become a major manufacturer of ink-jet printer cartridges, computers, handheld wireless devices, and medical products. Nypro’s ability to precision-mold complex structures is interdependent with its abilities to simplify assembly.

Bloomberg L.P. has done the same thing, eating its way up Wall Street’s value chain. It started by providing simple data on securities prices and subsequently integrated forward, automating much of the analytics. Bloomberg has disruptively enabled an army of people to access insights that formerly only highly experienced securities analysts could derive. Bloomberg has continued to integrate forward from the back end, so that portfolio managers can now execute most trades from their Bloomberg terminals over a Bloomberg-owned electronic communications network (ECN) without needing a broker or a stock exchange. Issuers of certain government securities can now even auction their securities to institutional investors within Bloomberg’s proprietary system. Back-end suppliers such as First Data and State Street enjoy a similar position vis-à-vis commercial banks. Venerable Wall Street institutions are being disrupted and hollowed out—and they don’t even realize it because outsourcing the asset-intensive back end is a compelling mandate that feels good once the front end has become modular and commoditized.

Core competence, as it is used by many managers, is a dangerously inward-looking notion. Competitiveness is far more about doing what customers value than doing what you think you’re good at. And staying competitive as the basis of competition shifts necessarily requires a willingness and ability to learn new things rather than clinging hopefully to the sources of past glory. The challenge for incumbent companies is to rebuild their ships while at sea, rather than dismantling themselves plank by plank while someone else builds a new, faster boat with what they cast overboard as detritus.

What can growth-hungry managers do in situations like this? In many ways, the process is inevitable. Assemblers of modular products must, over time, shed assets in order to reduce costs and improve returns—financial market pressure leaves managers with few alternatives. However, knowing that this is likely to happen gives those same managers the opportunity to own or acquire, and manage as separate growth-oriented businesses, the component or subsystem suppliers that are positioned to eat their way up the value chain. This is the essence of skating to where the money will be.[13]

Good Enough, Not Good Enough, and the Value of Brands

Executives who seek to avoid commoditization often rely on the strength of their brands to sustain their profitability—but brands become commoditized and de-commoditized, too. Brands are most valuable when they are created at the stages of the value-added chain where things aren’t yet good enough. When customers aren’t yet certain whether a product’s performance will be satisfactory, a well-crafted brand can step in and close some of the gap between what customers need and what they fear they might get if they buy the product from a supplier of unknown reputation. The role of a good brand in closing this gap is apparent in the price premium that branded products are able to command in some situations. For similar logic, however, the ability of brands to command premium prices tends to atrophy when the performance of a class of products from multiple suppliers is manifestly more than adequate.

When overshooting occurs, the ability to command attractive profitability through a valuable brand often migrates to those points in the value-added chain where things have flipped into a not-yet-good-enough situation. These often will be the performance-defining subsystems within the product, or at the retail interface when it is the speed, simplicity, and convenience of getting exactly what you want that is not good enough. These shifts define the opportunities in branding.

For example, in the early decades of the computer industry, investment in complex and unreliable mainframe computer systems was an unnerving task for most managers. Because IBM’s servicing capability was unsurpassed, the brand of IBM had the power to command price premiums of 30 to 40 percent, compared with comparable equipment. No corporate IT director got fired for buying IBM. Hewlett-Packard’s brand commanded similar premiums.

How did the brands of Intel and Microsoft Windows subsequently steal the valuable branding power from IBM and Hewlett-Packard in the 1990s? It happened when computers came to pack good-enough functionality and reliability for mainstream business use, and modular, industry-standard architectures became predominant in those tiers of the market. At that point, the microprocessor inside and the operating system became not good enough, and the locus of the powerful brands migrated to those new locations.

The migration of branding power in a market that is composed of multiple tiers is a process, not an event. Accordingly, the brands of companies with proprietary products typically create value mapping upward from their position on the improvement trajectory—toward those customers who still are not satisfied with the functionality and reliability of the best that is available. But mapping downward from that same point—toward the world of modular products where speed, convenience, and responsiveness drive competitive success—the power to create profitable brands migrates away from the end-use product, toward the subsystems and the channel.[14]

This has happened in heavy trucks. There was a time when the valuable brand, Mack, was on the truck itself. Truckers paid a significant premium for Mack the bulldog on the hood. Mack achieved its preeminent reliability through its interdependent architecture and extensive vertical integration. As the architectures of large trucks have become modular, however, purchasers have come to care far more whether there is a Cummins or Caterpillar engine inside than whether the truck is assembled by Paccar, Navistar, or Freightliner.

Apparel is another industry in which the power to brand has begun to migrate to a different stage of the value-added chain. As elsewhere, it has happened because a changed basis of competition has redefined what is not good enough. A generation ago most of the valuable brands were on the products. Levi’s brand jeans and Gant brand shirts, for example, enjoyed strong and profitable market shares because many of the competing products were not nearly as sturdily made. These branded products were sold in department stores, which trumpeted their exclusive ability to sell the best brands in clothing.

Over the past fifteen years, however, the quality of clothing from a wide range of manufacturers has become assured, as producers in low-labor-cost countries have improved their capabilities to produce high-quality fabrics and clothing. The basis of competition in the apparel industry has changed as a consequence. Specialized retailers have stolen a significant share of market from the broad-line department stores because their focused merchandise mix allows the customers they target to find what they want more quickly and conveniently. What is not good enough in certain tiers of the apparel industry has shifted from the quality of the product to the simplicity and convenience of the purchasing experience. Much of the ability to create and maintain valuable brands, as a consequence, has migrated away from the product and to the channel because, for the present, it is the channel that addresses the piece of added value that is not yet good enough.[15] We don’t even question who makes the dresses in Talbot’s, the sweaters for Abercrombie & Fitch, or the jeans at Gap and Old Navy. Much of the apparel sold in those channels carries the brand of the channel, not the manufacturer.[16]

A View of the Automobile Industry’s Future Through the Lenses of This Model

Most of our examples of commoditization and de-commoditization have been drawn from the past. To show how this theory can be used to look into the future, this section discusses how this transformation is under way in the automobile industry, initiating a massive transfer of the ability to make attractive profits in the future away from automobile manufacturers and toward certain of their suppliers. Even the power to cultivate valuable brands is likely to migrate to the subsystems. This transformation will probably take a decade or two to fully accomplish, but once you know what to look for, it is easy to see that the processes already are irreversibly under way.

The functionality of many automobiles has overshot what customers in the mainstream markets can utilize. Lexus, BMW, Mercedes, and Cadillac owners will probably be willing to pay premium prices for more of everything for years to come. But in market tiers populated by middle- and lower-price-point models, car makers find themselves having to add more and better features just to hang onto their market share, and they struggle to convince customers to pay higher prices for these improvements. The reliability of models such as Toyota’s Camry and Honda’s Accord is so extraordinary that the cars often go out of style long before they wear out. As a result, the basis of competition—what is not good enough—is changing in many tiers of the auto market. Speed to market is important. Whereas it used to take five years to design a new-model car, today it takes two. Competing by customizing features and functions to the preferences of customers in smaller market niches is another fact of life. In the 1960s, it was not unusual for a single model’s sales to exceed a million units per year. Today the market is far more fragmented: Annual volumes of 200,000 units are attractive. Some makers now promise that you can walk into a dealership, custom-order a car, and have it delivered in five days—roughly the response time that Dell Computer offers.

In order to compete on speed and flexibility, automakers are evolving toward modular architectures for their mainstream models. Rather than uniquely designing and knitting together individual components procured from hundreds of suppliers, most auto companies now procure subsystems from a much narrower base of “tier one” suppliers of braking, steering, suspension, and interior cockpit subsystems. Much of this consolidation in the supplier base has been driven by the cost-saving opportunities that it affords—opportunities that often were identified and quantified by analytically astute consulting firms.

The integrated American automakers have been forced to dis-integrate in order to compete with the speed, flexibility, and reduced overhead cost structure that this new world demands. General Motors, for example, spun off its component operations into a separate publicly traded company, Delphi Automotive, and Ford spun off its component operations as Visteon Corporation. Hence, the same thing is happening to the auto industry that happened to computers: Overshooting has precipitated a change in the basis of competition, which precipitated a change in architecture, which forced the dominant, integrated firms to dis-integrate.

At the same time, the architecture is becoming progressively more interdependent within most of the subsystems. The models at lower price points in the market need improved performance from their subsystems in order to compete against higher-cost models and brands in the tiers of the market above them. If Kia and Hyundai used their low-cost Korean manufacturing base to conquer the subcompact tier of the market and then simply stayed there, competition would vaporize profits. They must move up, and once their architectures have become modular the only way to do this is to be fueled by ever-better subsystems.

The newly interdependent architectures of many subsystems are forcing the tier-one suppliers to be less flexible at their external interface. The automobile designers are increasingly needing to conform their designs to the specifications of the subsystems, just as desktop computer makers need to conform the designs of their computers to the external interfaces of Intel’s microprocessor and Microsoft’s operating system. As a consequence, we would expect that the ability to earn attractive profits is likely to migrate away from the auto assemblers, toward the subsystem vendors.[17]

In chapter 5 we recounted how IBM’s PC business outsourced its microprocessor to Intel and its operating system to Microsoft, in order to be fast and flexible. In the process, IBM hung on to where the money had been—design and assembly of the computer system—and put into business the two companies that were positioned where the money would be. General Motors and Ford, with the encouragement of their consultants and investment bankers, have just done the same thing. They had to decouple the vertical stages in their value chains in order to stay abreast of the changing basis of competition. But they have spun off the pieces of value-added activity where the money will be, in order to stay where the money has been.[18]

These findings have pervasive implications for managers seeking to build successful new-growth businesses and for those seeking to keep current businesses robust. The power to capture attractive profits will shift to those activities in the value chain where the immediate customer is not yet satisfied with the performance of available products. It is in these stages that complex, interdependent integration occurs—activities that create steeper scale economics and enable greater differentiability. Attractive returns shift away from activities where the immediate customer is more than satisfied, because it is there that standard, modular integration occurs. We hope that in describing this process in these terms, we might help managers to predict more accurately where new opportunities for profitable growth through proprietary products will emerge. These transitions begin on the trajectories of improvement where disruptors are at work, and proceed up-market tier by tier. This process creates opportunities for new companies that are integrated across these not-good-enough interfaces to thrive, and to grow by “eating their way up” from the back end of an end-use system. Managers of industry-leading businesses need to watch vigilantly in the right places to spot these trends as they begin, because the processes of commoditization and de-commoditization both begin at the periphery, not the core.

Appendix: The Law of Conservation of Attractive Profits

Having described these cycles of commoditization and de-commoditization in terms of products, we can now make a more general statement concerning the existence of a general phenomenon that we call the law of conservation of attractive profits. Our friend Chris Rowen, CEO of Tensilica, pointed out to us the existence of this law, whose appellation was inspired by the laws of conservation of energy and matter that we so fondly remember studying in physics class. Formally, the law of conservation of attractive profits states that in the value chain there is a requisite juxtaposition of modular and interdependent architectures, and of reciprocal processes of commoditization and decommoditization, that exists in order to optimize the performance of what is not good enough. The law states that when modularity and commoditization cause attractive profits to disappear at one stage in the value chain, the opportunity to earn attractive profits with proprietary products will usually emerge at an adjacent stage.[19]

We’ll first illustrate how this law operates by examining handheld devices such as the RIM BlackBerry and the Palm Pilot, which constitute the latest wave of disruption in the computing industry. The functionality of these products is not yet adequate, and as a consequence their architectures are interdependent. This is especially true for the BlackBerry, because its “always on” capability mandates extraordinarily efficient use of power. Because of this, the BlackBerry engineers cannot incorporate a one-size-fits-all Intel microprocessor into their device. It has far more capability than is needed. Rather, they need a modular microprocessor design—a system-on-a-chip that is custom-configured for the BlackBerry—so that they do not have to waste space, power, or cost on functionality that is not needed.

The microprocessor must be modular and conformable in order to permit engineers to optimize the performance of what is not good enough, which is the device itself. Note that this is the opposite situation from that of a desktop computer, where it is the microprocessor that is not good enough. The architecture of the computer must therefore be modular and conformable in order to allow engineers to optimize the performance of the microprocessor. Thus, one side or the other must be modular and conformable to allow for optimization of what is not good enough through an interdependent architecture.

In similar ways, application software programs that are written to run on Microsoft’s Windows operating systems need to be conformed to Windows’ external interface; the Linux operating system, on the other hand, is modular and conformable to optimize the performance of software that runs on it.

We have found this “law” to be a useful way to visualize where the money will migrate in the value chain in a number of industries. It is explored in greater depth in a forthcoming book by Clayton Christensen, Scott Anthony, and Erik Roth, Seeing What’s Next (Boston: Harvard Business School Press, 2004).

This law also has helped us understand the juxtaposition of modular products with interdependent services, because services provided with the products can go through similar cycles of commoditization and de-commoditization, with consequent implications for where attractive profitability will migrate.

We noted previously that when the functionality and reliability of a product become more than good enough, the basis of competition changes. What becomes not good enough are speed to market and the rapid and responsive ability to configure products to the specific needs of customers in ever-more-targeted market segments. The customer interface is the place in the value chain where the ability to excel on this new dimension of competition is determined. Hence, companies that are integrated in a proprietary way across the interface to the customer can compete on these not-good-enough dimensions more effectively (and be rewarded with better margins) than can those firms that interface with their customers only in an arm’s-length, “modular” manner. Companies that integrate across the retail interface to the customer, in this circumstance, can also earn above-average profits.

We would therefore not say that Dell Computer is a nonintegrated company, for example. Rather, Dell is integrated across the not-good-enough interface with the customer. The company is not integrated across the more-than-good-enough modular interfaces among the components within its computers. Figure 6-2 summarizes in a simplified way how the profitable points of proprietary integration have migrated in the personal computer industry.

On the left side of the diagram, which represents the earliest years of the desktop computer industry when product functionality was extremely limited, Apple Computer, with its proprietary architecture and integrated business model, was the most successful firm and was attractively profitable. The firms that supplied the bare components and materials to Apple, and the independent, arm’s-length retailers that sold the computers, were not in nearly as attractive a position. In the late 1990s, the processes of commoditization and de-commoditization had transferred the points at which proprietary integration could build proprietary competitive advantage to

FIGURE 6 - 2

The Shifting Locus of Advantage in the PC Industry’s Process Value Chain

We believe that this is an important factor that explains why Dell Computer was more successful than Compaq during the 1990s. Dell was integrated across an important not-good-enough interface, whereas Compaq was not. We also would expect that a proper cost accounting would show that Dell’s profits from retailing operations are far greater than the profits from its assembly operations.

Notes

1.   There are two ways to think of a product or service’s value chain. It can be conceptualized in terms of its processes, that is, the value-added steps required to create or deliver it. For example, the processes of design, component manufacture, assembly, marketing, sales, and distribution are generic processes in a value chain. A value chain can also be thought of in terms of components, or the “bill of materials” that go into a product. For example, the engine block, chassis, braking systems, and electronic subassemblies that go into a car are components of a car’s value chain. It is helpful to keep both ways of thinking about a value chain in mind, since value chains are also “fractal”—that is, they are equally complex at every level of analysis. Specifically, for a given product that goes through the processes that define its value chain, various components must be used. Yet every component that is used has its own sequence of processes through which it must pass. The complexity of analyzing a product’s value chain is essentially irreducible. The question is which level of complexity one wishes to focus on.

2.   This discussion builds heavily on Professor Michael Porter’s five forces framework and his characterization of the value chain. See Michael Porter, Competitive Strategy (New York: Free Press, 1980) and Competitive Advantage (New York: The Free Press, 1985). Analysts often use Porter’s five forces framework to determine which firms in a value-added system can wield the greatest power to appropriate profit from others. In many ways, our model in chapters 5 and 6 provides a dynamic overlay on his five forces model, suggesting that the strength of these forces is not invariant over time. It shows how the power to capture an above-average portion of the industry’s profit is likely to migrate to different stages of the value chain in a predictable way in response to the phenomena we describe here.

3.   As a general observation, when you examine what seems to be the hey-day of most major companies, it was (or is) a period when the functionality and reliability of their products did not yet satisfy large numbers of customers. As a result, they had products with proprietary architectures, and made them with strong competitive cost advantages. Furthermore, when they introduced new and improved products, the new products could sustain a premium price because functionality was not yet good enough and the new products came closer to meeting what was needed. This can be said for the Bell telephone system; Mack trucks; Caterpillar earthmoving equipment; Xerox photocopiers; Nokia and Motorola mobile telephone handsets; Intel microprocessors; Microsoft operating systems; Cisco routers; the IT consulting businesses of EDS or IBM; the Harvard Business School; and many other companies.

4.   In the following text we will use the term subsystem to mean, generally, an assembly of components and materials that provides a piece of the functionality required for an end-use system to be operational.

5.   Once again, we see linkages to Professor Michael Porter’s notion that there are two viable “generic” strategies: differentiation and low cost (see chapter 2, note 12). Our model describes the mechanism that causes neither of these strategies to be sustainable. Differentiability is destroyed by the mechanism that leads to modularization and dis-integration. Low-cost strategies are viable only as long as the population of low-cost competitors does not have sufficient capacity to supply what customers in a given tier of the market demand. Price is set at the intersection of the supply and demand curves—at the cash cost of the marginal producer. When the marginal producer is a higher-cost disruptee, then the low-cost disruptors can make attractive profits. But when the high-cost competitors are gone and the entire market demand can be supplied by equally low-cost suppliers of modular products, then what was a low-cost strategy becomes an equal-cost strategy.

6.   Not all the components or subsystems in a product contribute to the specific performance attributes of value to customers. Those that drive the performance that matters are the “performance-defining” components or subsystems. In the case of a personal computer, for example, the microprocessor, the operating system, and the applications have long been the performance-defining subsystems.

7.   Analysts’ estimates of how much of the industry’s money stayed with computer assemblers and how much “leaked” through to back-end or subsystem suppliers are summarized in “Deconstructing the Computer Industry,” BusinessWeek, 23 November 1992, 90–96. As we note in the appendix to this chapter, we would expect that much of Dell’s profit comes from its direct-to-customer retailing operations, not from product assembly.

8.   With just a few seconds’ reflection, it is easy to see that the investment management industry suffers from the problem of categorization along industry-defined lines that are irrelevant to profitability and growth. Hence, they create investment funds for “technology companies” and other funds for “health care companies.” Within those portfolios are disruptors and disruptees, companies on the verge of commoditization and those on the verge of decommoditization, and so on. Michael Mauboussin, chief investment strategist at Credit Suisse First Boston, recently wrote an article on this topic. It builds on the model of theory building that we have summarized in the introduction of this book, and its application to the world of investing is very insightful. See Michael Mauboussin, “No Context: The Importance of Circumstance-Based Categorization,” The Consiliant Observer, New York: Credit Suisse First Boston, 14 January 2003.

9.   Those of our readers who are familiar with the disk drive industry might see a contradiction between our statement that much of the money in the industry was earned in head and disk manufacturing and the fact that the leading head and disk makers, such as Read-Rite and Komag, have not prospered. They have not prospered because most of the leading disk drive makers—particularly Seagate—integrated into their own head and disk making so that they could capture the profit instead of the independent suppliers.

10.  IBM did have profitable volume in 3.5-inch drives, but it was at the highest-capacity tiers of that market, where capacity was not good enough and the product designs therefore had to be interdependent.

11.  A more complete account of these developments has been published in Clayton M. Christensen, Matt Verlinden, and George Westerman, “Disruption, Disintegration and the Dissipation of Differentiability,” Industrial and Corporate Change 11, no. 5 (2002): 955–993. The first Harvard Business School working papers that summarized this analysis were written and broadly circulated in 1998 and 1999.

12.  We have deliberately used present- and future-tense verbs in this paragraph. The reason is that at the time this account was first written and submitted to publishers, these statements were predictions. Subsequently, the gross margins in IBM’s 2.5-inch disk drive business deteriorated significantly, as this model predicted they would. However, IBM chose to sell off its entire disk drive business to Hitachi, giving to some other company the opportunity to sell the profitable, performance-enabling components for this class of disk drives.

13.  We have written elsewhere that the Harvard Business School has an extraordinary opportunity to execute exactly this strategy in management education, if it will only seize it. Harvard writes and publishes the vast majority of the case studies and many of the articles that business school professors have used as components in courses whose architecture is of interdependent design. As on-the-job management training and corporate universities (which are nonintegrated assemblers of modular courses) disrupt traditional MBA programs, Harvard has a great opportunity to flip its business model through its publishing arm and sell not just case studies and articles as bare-bones components but also value-added subsystems as modules. These should be designed to make it simple for management trainers in the corporate setting to custom-assemble great material, deliver it exactly when it is needed, and teach it in a compelling way. (See Clayton M. Christensen, Michael E. Raynor, and Matthew Verlinden, “Skate to Where the Money Will Be,” Harvard Business Review, November 2001.)

14.  This would suggest, for example, that Hewlett-Packard’s branding power would be strong mapping upward to not-yet-satisfied customers from the trajectory of improvement on which its products are positioned. And it suggests that the HP brand would be much weaker, compared with the brands of Intel and Microsoft, mapping downward from that same point to more-than-satisfied customers.

15.  We are indebted to one of Professor Christensen’s Harvard MBA students, Alana Stevens, for many of these insights, which she developed in a research paper entitled “A House of Brands or a Branded House?” Stevens noted that branding power is gradually migrating away from the products to the channels in a variety of retailing categories. Manufacturers of branded food and personal care products such as Unilever and Procter & Gamble, for example, fight this battle of the brands with their channels every day, because many of their products are more than good enough. In Great Britain, disruptive channel brands such as Tesco and Sainsbury’s have decisively won this battle after first starting at the lower price points in each category and then moving up. In the United States, branded products have clung more tenaciously to shelf space, but often at the cost of exorbitant slotting fees. The migration of brands in good-enough categories is well under way in channels such as Home Depot and Staples. Where the products’ functionality and reliability have become more than good enough and it is the simplicity and convenience of purchase and use that is not good enough, then the power to brand has begun migrating to the channel whose business model is delivering on this as-yet-unsatisfied dimension.

Procter & Gamble appears to be following a sensible strategy by launching a series of new-market disruptions that simultaneously provide needed fuel for its channels’ efforts to move up-market, and preserve P&G’s power to keep the premium brand on the product. Its Dryel brand do-it-yourself home dry cleaning system, for example, is a new-market disruption because it enables individuals to do for themselves something that, historically, only a more expensive professional could do. Do-it-yourself dry cleaning is not yet good enough, so the power to build a profitable brand is likely to reside in the product for some time. What is more, just as Sony’s solid-state electronics products enabled discount merchandisers to compete against appliance stores, so P&G’s Dryel gives Wal-Mart a vehicle to move up-market and begin competing against dry cleaning establishments. P&G is doing the same thing with its introduction of its Crest brand do-it-yourself teeth whitening system, a new-market disruption of a service that historically could only be provided by professionals. We thank one of Professor Christensen’s former students, David Dintenfass, a global brand manager at Procter & Gamble, for pointing this out to us.

16.  As we have shared these hypotheses with students, some of the more stylishly dressed among them have asked whether this applies also to the highest-fashion brands, such as Gucci, and in product categories such as cosmetics. Those who know us probably have observed that dressing ourselves in fashionable, branded merchandise just isn’t a job that we have been trying to get done in our lives. We confess, therefore, to having no intuition about the world of high fashion. It will probably persist profitably forever. Who are we to know?

17.  Remaining competitive at the level of the process-defined value chain that the current auto assemblers dominate is likely to require that they move toward new distribution structures—an integration of supply chains and customer interfaces in a way that effectively exploits the modularity of the product itself. How this can be done and its performance implications are explored at length in the Deloitte Research study “Digital Loyalty Networks,” available for download at < http://www.dc.com/research>, or upon request from delresearch@dc.com.

18.  Those of our readers who believe in the efficiency of capital markets and the abilities of investors to diversify their portfolios will see no tragedy in these decisions. After these divestitures the shareholders of the two auto giants found themselves owning stock in companies that design and assemble cars, and in companies that supply performance-enabling subsystems. It is because we are writing this book for the benefit of managers in firms like General Motors and Ford that we characterize these decisions as unfortunate.

19.  We say “usually” here because there are exceptions (most, but not all, of which prove the rule). We note in the text of this chapter, for example, that two modular stages of added value can be juxtaposed—as DRAM memory chips fit in modular personal computers. And there are instances where two interdependent architectures need to be integrated, such as when enterprise resource planning software from companies such as SAP needs to be interleaved into companies’ interdependent business processes. The fact that neither side is modular and configurable is what makes SAP implementations so technically and organizationally demanding.

CHAPTER SEVEN

IS YOUR ORGANIZATION CAPABLE

OF DISRUPTIVE GROWTH?

Who should we chose to run new-growth businesses? Which organizational unit in the company will do the best job of building a successful growth business around this particular idea, and which units will likely botch it? What is the best way to structure the team that develops and launches this product? When is creating an autonomous organization important for success, and when is it folly? How can we predict precisely what an organizational unit is capable and incapable of accomplishing? How can we create new capabilities?

A surprising number of innovations fail not because of some fatal technological flaw or because the market isn’t ready. They fail because responsibility to build these businesses is given to managers or organizations whose capabilities aren’t up to the task. Corporate executives make this mistake because most often the very skills that propel an organization to succeed in sustaining circumstances systematically bungle the best ideas for disruptive growth. An organization’s capabilities become its disabilities when disruption is afoot.[1] This chapter offers a theory to guide executives as they choose a management team and build an organizational structure that together will be capable of building a successful new-growth business. It also outlines how the choices of managers and structure ought to vary by circumstance.

Resources, Processes, and Values

What does this awfully elastic term capability really mean? We’ve found it helpful to unpack the concept of capabilities into three classes or sets of factors that define what an organization can and cannot accomplish: its resources, its processes, and its values—a triptych we refer to as the RPV framework. Although each of these terms requires careful definition and analysis, taken together we’ve found that they provide a powerful way to assess an organization’s capabilities and disabilities in ways that can make disruptive innovation much more likely to succeed.[2]

Resources

Resources are the most tangible of the three factors in the RPV framework. Resources include people, equipment, technology, product designs, brands, information, cash, and relationships with suppliers, distributors, and customers. Resources are usually people or things—they can be hired and fired, bought and sold, depreciated or built. Most resources are visible and often are measurable, so managers can readily assess their value. They tend to be quite flexible as well: It is relatively easy to transport them across the boundaries of organizations. An engineer who is a valuable contributor in a large company can quickly become a valuable contributor in a start-up. Technology that was developed for telecommunications can be valuable in health care. Cash is a very flexible resource.

Of all the resource choices required to successfully build new-growth businesses, the one that most often trips a venture up is the choice of its managers. We have examined innumerable failed efforts to create new-growth business and would estimate that in as many as half of these cases, those close to the situation judge that, in retrospect, the wrong people had been chosen to lead the venture.[3] Why is the selection process for key managerial resources so vexingly unpredictable?

Why Those with the Right Stuff Are Often the Wrong People

We suspect that the mistakes happen when firms choose managers at any level—from CEO to business unit head to project manager— based on what we call “right stuff” thinking, borrowing the term from Tom Wolfe’s famous book and the 1983 movie of the same name.[4] Many search committees and hiring executives classify candidates by right-stuff attributes. They assume that successful managers can be identified using phrases such as “good communicator,” “results oriented,” “decisive,” and “good people skills.” They often look for an uninterrupted string of past successes to predict that more successes are in store. The theory in use is that if you find someone with a track record and with the right-stuff attributes, then he or she can successfully manage the new business venture. But in the parlance of this book, right-stuff thinking gets the categories wrong.[5]

An alternative, circumstance-based theory articulated by Professor Morgan McCall can, in our view, serve as a much more reliable guide for executives who are attempting to get the right people in the right positions at the right time.[6] McCall asserts that the management skills and intuition that enable people to succeed in new assignments were shaped through their experiences in previous assignments in their careers. A business unit therefore can be thought of as a school, and the problems that managers have confronted within it constitute the “curriculum” that was offered in that school. The skills that managers can be expected to have and lack, therefore, depend heavily upon which “courses” they did and did not take as they attended various schools of experience.

Managers who have successfully worked their way up the ladder of a stable business unit—for example, a division that manufactures standard high-volume electric motors for the appliance industry—are likely to have acquired the skills that were necessary to succeed in that context. The “graduates” of this school would have finely honed operational skills in managing quality programs, process improvement teams, and cost-control efforts. Even the most senior manufacturing executives from such a school would likely be weak, however, in starting up a new plant, because one encounters very different problems in starting up a new plant than in running a well-tuned one.

When a slowly growing firm’s leaders decide they need to launch a new-growth business to restore their company’s vitality, who should they tap to head the venture? A talented manager from the core business who has demonstrated a record of success? An outsider who has started and grown a successful company? The school-of-experience view suggests that both of these managers might be risky hires. The internal candidate would have learned how to meet budgeted numbers, negotiate major supply contracts, and improve operational efficiency and quality, but might not have attended any “courses” on starting a new business in his or her prior career assignments. An outside entrepreneur might have learned a lot about building new fast-moving organizations, but would have little experience competing for resources and bucking inappropriate processes within a stable, efficiency-oriented operating culture.

In order to be confident that managers have developed the skills required to succeed at a new assignment, one should examine the sorts of problems they have wrestled with in the past. It is not as important that managers have succeeded with the problem as it is for them to have wrestled with it and developed the skills and intuition for how to meet the challenge successfully the next time around. One problem with predicting future success from past success is that managers can succeed for reasons not of their own making—and we often learn far more from our failures than our successes. Failure and bouncing back from failure can be critical courses in the school of experience. As long as they are willing and able to learn, doing things wrong and recovering from mistakes can give managers an instinct for better navigating through the minefield the next time around.

To illustrate how powerfully managers’ prior experiences can shape the skills that they bring to a new assignment, let us continue chapter 4’s discussion of Pandesic, the high-profile joint venture between Intel and SAP that was launched in 1997 to create a new-market disruption selling enterprise resource planning (ERP) software to small businesses. Intel and SAP hand-picked some of their most successful, tried-and-true executives to lead the venture.

Pandesic ramped to 100 employees in eight months, and quickly established offices in Europe and Asia. Within a year it had announced forty strategic partnerships with companies such as Compaq, Hewlett-Packard, and Citibank. Pandesic executives boldly announced their first product in advance of launch to warn would-be competitors to stay away from the small business marketspace. The company inked distribution and implementation agreements with the same IT consulting firms that had served as such capable channel partners for SAP’s large-company systems. The product, initially intended to be simple ERP software delivered to small businesses via the Internet, evolved into a completely automated end-to-end solution. Pandesic was a spectacular failure. It sold very few systems and shut its doors in February 2001 after having spent more than $100 million.

It is tempting to use 20/20 hindsight to explain this failure. Pandesic’s channel partners weren’t motivated to sell the product because it was disruptive to their economic model. The company quickly ramped up expenses to establish a global presence, hoping to build a steeper ramp to volume. But this increased dramatically the volume required to break even. The product evolved into a complex solution instead of the simple small business software that originally was envisioned. Its features got specified and locked in before a single paying customer had used the product.

The Pandesic team did a lot of things wrong, certainly. But the truly interesting question isn’t what they did wrong. It is how such capable, experienced, and respected managers—among the best that Intel and SAP had to offer—could have made these mistakes.

To see how managers with great track records could steer a venture so wrong, let’s look at their qualifications for the task from the schools-of-experience point of view. This can be done in three steps. First, imagine yourself at Pandesic on day one, when the executives were agreeing to start this disruptive venture. With only foresight and no hindsight allowed, what challenges or problems could you predict with perfect certainty that this venture would encounter? Here are a few of the problems that we could know we would face:

- We know for sure that we aren’t sure if our strategy is right—and yet we have to figure out the right strategy, develop consensus, and build a business around it.

- We don’t know how this market ought to be segmented. “Small business” probably isn’t right, and “industry vertical” probably isn’t right. We have to figure out what jobs the customers are trying to get done, and then design products and services that do the job.

- We need to find or create a distribution channel that will be energized by the opportunity to sell this product.

- Our corporate parents will bequeath gifts upon us such as overhead, planning requirements, and budgeting cycles. We will need to accept some and fend off others.

- We need to become profitable, and we must manage perceptions and expectations so that our corporate parents will willingly continue to make the investments required to fuel our profitable growth.

Now, as the second step, let’s apply McCall’s theory. List the courses that we would want members of Pandesic’s management team to have taken in earlier career assignments in the school of experience—experiences through which they would have developed the intuition and skill to understand and manage this set of foreseeable problems. This listing of experiences should constitute a “hiring specification” for the senior management team. Rather than specifying a set of right-stuff attributes, the first step specifies the circumstances in which the new team will be asked to manage. The second step matches those circumstances against the challenges with which the managers of the new venture need already to have wrestled.

We would, in Pandesic’s instance, want a CEO who in the past had launched a venture thinking he or she had the right strategy, realized it wasn’t working, and then iterated toward a strategy that did work. We’d want a marketing executive who had insightfully figured out how a just-emerging market was structured, had helped to shape a new product and service package that did an important job well for customers who had been nonconsumers, and so on.

With that list complete, our third step would be to compare that set of needed experiences and perspectives with the experiences on the resumés of the managers who led Pandesic. Despite their extraordinary track records in managing the global operations of very successful companies, none of the executives who were tapped to run this venture had faced any of these kinds of problems before. The schools of experience that they had attended taught them how to manage huge, complex, global organizations that served established markets with well-defined product lines. None of them had ever wrestled with establishing an initial market foothold with a disruptive product.[7]

One of the most vexing dilemmas that stable corporations face when they seek to rekindle growth by launching new businesses is that their internal schools of experience have offered precious few courses in which managers could have learned how to launch new disruptive businesses. In many ways, the managers that corporate executives have come to trust the most because they have consistently delivered the needed results in the core businesses cannot be trusted to shepherd the creation of new growth. Human resources executives in this situation need to shoulder a major burden. They need to monitor where in the corporation’s schools of experience the needed courses might be created, and ensure that promising managers have the opportunity to be appropriately schooled before they are asked to take the helm of a new-growth business. When managers with the requisite education cannot be found internally, they need to ensure that the management team, as a balanced composite, has within it the requisite perspectives from the right schools of experience. We will return to this challenge later in this chapter.

Finding managers who have been appropriately schooled is a critical first step in assembling the capabilities required to succeed. But it is only the first step, because the capabilities of organizations are a function of resources other than people, and of elements beyond just resources, namely, processes and values. To these we now turn.

Processes

Organizations create value as employees transform inputs of resources—the work of people, equipment, technology, product designs, brands, information, energy, and cash—into products and services of greater worth. The patterns of interaction, coordination, communication, and decision making through which they accomplish these transformations are processes.[8] Processes include the ways that products are developed and made and the methods by which procurement, market research, budgeting, employee development and compensation, and resource allocation are accomplished.

Processes differ not only in their purpose, but also in their visibility. Some processes are “formal,” in the sense that they are explicitly defined, visibly documented, and consciously followed. Other processes are “informal,” in that they are habitual routines or ways of working that have evolved over time, which people adopt simply because they work or because “. . . that’s the way we do things around here.” Still other methods of working and interacting have proven so effective for so long that people unconsciously follow them—they constitute the culture of the organization. Whether they are formal, informal, or cultural, however, processes define how an organization transforms inputs into things of greater value.[9]

Processes are defined or evolve de facto to address specific tasks. When managers use a process to execute the tasks for which it was designed, it is likely to perform efficiently. But when the same, seemingly efficient process is employed to tackle a very different task, it often seems bureaucratic and inefficient. In other words, a process that defines a capability in executing a certain task concurrently defines disabilities in executing other tasks.[10] In contrast to the flexibility of many resources, processes by their very nature are meant not to change. They are established to help employees perform recurrent tasks in a consistent way, time after time. One reason that focused organizations perform so well is that their processes are always aligned to the tasks.[11]

Innovating managers often try to start new-growth businesses using processes that were designed to make the mainstream business run effectively. They succumb to this temptation because the new game begins before the old game ends. Disruptive innovations typically take root at the low end of markets or in new planes of competition at a time when the core business still is performing at its peak—when it would be crazy to revolutionize everything. It seems simpler to have one-size-fits-all processes for doing things, but very often the cause of a new venture’s failure is that the wrong processes were used to build it.

The most crucial processes to examine usually aren’t the obvious value-adding processes involved in logistics, development, manufacturing, and customer service. Rather, they are the enabling or back-ground processes that support investment decisions. These include how market research is habitually done, how such analysis is translated into financial projections, how plans and budgets are negotiated and how those numbers are delivered, and so on. These processes are where many organizations’ most serious disabilities in creating disruptive growth businesses reside.

Some of these processes are hard to observe, and it can therefore be quite difficult to judge whether the mainstream organization’s processes will facilitate or impede a new-growth business. You can make a good guess, however, by asking whether the organization has faced similar situations or tasks in the past. We would not expect an organization to have developed a process for accomplishing a particular task if it has not repeatedly addressed a task like that before. For example, if an organization has repeatedly formulated strategic plans for established businesses in existing markets, then a process that planners follow in formulating such plans likely will have coalesced, and managers will instinctively follow that process. But if that organization has not repeatedly formulated plans for competing in markets that do not yet exist, it is safe to assume that no processes for making such plans exist.[12]

Values

The third class of factors that affect what an organization can or cannot accomplish is its values. Some corporate values are ethical in tone, such as those that guide decisions to ensure patient well-being at Johnson & Johnson or that guide plant safety at Alcoa. But in the RPV framework, values have a broader meaning. An organization’s values are the standards by which employees make prioritization decisions—those by which they judge whether an order is attractive or unattractive, whether a particular customer is more important or less important than another, whether an idea for a new product is attractive or marginal, and so on.[13]

Employees at every level make prioritization decisions. At the executive tiers, these decisions often take the form of whether or not to invest in new products, services, and processes.[14] Among salespeople, they consist of on-the-spot, day-to-day decisions about which customers they will call on, which products to push with those customers, and which products not to emphasize. When an engineer makes a design choice or a production scheduler puts one order ahead of another, it is a prioritization decision.

The larger and more complex a company becomes, the more important it is for senior managers to train employees at every level, acting autonomously, to make prioritization decisions that are consistent with the strategic direction and the business model of the company. That is why successful senior executives spend so much time articulating clear, consistent values that are broadly understood throughout the organization. Over time, a company’s values must evolve to conform to its cost structure or its income statement, because if the company is to survive, employees must prioritize those things that help the company to make money in the way that it is structured to make money.

Whereas resources and processes are often enablers that define what an organization can do, values often represent constraints—they define what the organization cannot do. If, for example, the structure of a company’s overhead costs requires it to achieve gross profit margins of 40 percent, a powerful value or decision rule will have evolved that encourages employees not to propose, and senior managers to kill, ideas that promise gross margins below 40 percent. Such an organization would be incapable of succeeding in low-margin businesses—because you can’t succeed with an endeavor that cannot be prioritized. At the same time, a different organization’s values, shaped around a very different cost structure, might enable it to accord high priority to the very same project. These differences create the asymmetries of motivation that exist between disruptors and disruptees.

Over time, the values of successful firms tend to evolve in a predictable fashion in at least two dimensions. The first relates to acceptable gross margins. As companies upgrade their products and services to capture more attractive customers in premium tiers of their markets, they often add overhead cost. As a result, gross margins that at one point were quite attractive will seem unattractive at a later point. Companies’ values change as they migrate up-market.[15]

The second dimension along which values can change relates to how big a business has to be in order to be interesting. Because a company’s stock price represents the discounted present value of its projected earnings stream, most managers typically feel compelled not just to maintain growth but to maintain a constant rate of growth. For a $40 million company to grow 25 percent, it needs to find $10 million in new business the next year. For a $40 billion company to grow 25 percent, it needs to find $10 billion in new business the next year. An opportunity that excites a small organization simply isn’t large enough to be interesting to a very large one. One of the bittersweet rewards of success is, in fact, that as companies become large, they literally lose the capability to enter small emerging markets. Their size and success put extraordinary resources at their disposal. Yet they cannot deploy those resources against the small disruptive markets of today that will be the large markets of tomorrow, because their values will not permit it.

Executives and Wall Street financiers who engineer mega-mergers among already huge companies in order to achieve cost savings need to account for the impact of these actions on the resultant companies’ values. Although the merged corporations might have more resources to throw at new-product development, their commercial organizations tend to lose their appetites for all but the biggest blockbuster opportunities. Huge size constitutes a very real disability in creating new-growth businesses. But as we will show later in this chapter, when large corporations keep the flexibility to have small business units within them, they can continue to have decision makers who can become excited about emerging opportunities.

The Migration of Capabilities

In the start-up stages of a business, much of what gets done is attributable to its resources—particularly its people. The addition or departure of a few key people can have a profound influence on its success. Over time, however, the organization’s capabilities shift toward its processes and values. As people work together successfully to address recurrent tasks, processes become defined. And as the business model takes shape and it becomes clear which types of business need to be accorded highest priority, values coalesce. In fact, one reason that many soaring young hot-product companies flame out after they go public is that the key initial resource—the founding team—fails to institute the processes or the values that can help the company follow up with a sequence of hot new products.

Success is easier to sustain when the locus of the capability to innovate successfully migrates from resources to processes and values. It actually begins to matter less which people get assigned to which project teams. In large, successful management consulting firms, for example, hundreds of new MBA’s join the firm every year, and almost as many leave. But they are able to crank out high-quality work year after year because their capabilities are rooted in their processes and values rather than in their resources.

As a new company’s processes and values are coalescing, the actions and attitudes of the company’s founder typically have a profound impact. The founder often has strong opinions about the way employees ought to work together to reach decisions and get things done. Founders similarly impose their views of what the organization’s priorities need to be. If the founder’s methods are flawed, of course, the company will likely fail. But if those methods are useful, employees will collectively experience for themselves the validity of the founder’s problem-solving methodologies and criteria for decision making. As they successfully use those methods of working together to address recurrent tasks, processes become defined. Likewise, if the company becomes financially successful by prioritizing various uses of its resources according to criteria that reflect the founder’s priorities, the company’s values begin to coalesce.

As successful companies mature, employees gradually come to assume that the priorities they have learned to accept, and the ways of doing things and methods of making decisions that they have employed so successfully, are the right way to work. Once members of the organization begin to adopt ways of working and criteria for making decisions by assumption, rather than by conscious decision, then those processes and values come to constitute the organization’s culture.[16] As companies grow from a few employees to hundreds and thousands, the challenge of getting all employees to agree on what needs to be done and how it should be done so that the right jobs are done repeatedly and consistently can be daunting for even the best managers. Culture is a powerful management tool in these situations. Culture enables employees to act autonomously and causes them to act consistently.

Hence, the location of the most powerful factors that define the capabilities and disabilities of an organization migrates over time—from resources toward visible, conscious processes and values, and then toward culture. When the organization’s capabilities reside primarily in its people, changing to address new problems is relatively simple. But when the capabilities have come to reside in processes and values and especially when they have become embedded in culture, change can become extraordinarily difficult.

Every organizational change entails a change in resources, processes, or values, or some combination of these. The tools required to manage each of these types of change are different. Moreover, established organizations typically face the opportunity to create new growth businesses—and the consequent requirement to utilize different resources, processes, and values—at a time when the mainstream business is still very healthy—when executives must not change the resources, processes, and values that enable core businesses to sustain their success. This requires a much more tailored approach to managing change than many managers have felt to be necessary, as we will discuss next.[17]

Selecting the Right Organizational Home

for a New Disruptive Business

We noted in chapter 2 that the incumbent leaders in an industry almost always emerge victorious in sustaining-technology battles, whereas historically they have almost always lost the battles of disruption. The RPV framework of organizational capabilities helps us see why the leading firms’ track records differ so markedly across these two tasks. The industry leaders develop and introduce sustaining technologies over and over again: In the study of the computer disk drive industry that was the foundation of The Innovator’s Dilemma, 111 of the 116 new technologies were sustaining ones. Year after year, as established companies introduce new and improved products in order to gain an edge over the competition, they refine processes for evaluating the technological potential and assessing their customers’ needs for alternative sustaining technologies. In other words, the organizations develop a capability for sustaining innovation that resides in their processes. Sustaining-technology investments also fit the values of the leading companies, because they promise improved profit margins from better or cost-reduced products.[18]

On the other hand, disruptive innovations occur so intermittently that no company has a practiced process for handling them. Furthermore, because disruptive products typically promise lower gross profit dollars per unit sold and cannot be used by the best customers, disruptions are inconsistent with the leading companies’ values. Established companies have the resources—the engineers, money, and technology—required to succeed at both sustaining and disruptive technologies. But their processes and values constitute disabilities in their efforts to succeed at disruptive innovation.

In contrast, smaller, disruptive companies are actually more capable of pursuing emerging growth markets. They lack resources, but that doesn’t constrain them. Their values can embrace small markets, and their cost structures can accommodate lower margins per unit sold. Their less formal market research and resource allocation processes allow managers to proceed intuitively rather than having to be backed up by careful research and analysis. All of these advantages add up to enormous opportunity or looming disaster, depending on your perspective. Executives who are building new-growth businesses therefore need to do more than assign managers who have been to the right schools of experience to the problem. They must ensure that responsibility for making the venture successful is given to an organization whose processes will facilitate what needs to be done and whose values can prioritize those activities. The theory is that the requirements of an innovation need to fit with the host organization’s processes and values, or the innovation will not succeed.

In many ways, the RPV framework is a way of thinking through the management of change of any sort. A change involves the creation of new resources, new processes, or new values. It is rare that wholesale change on any of these dimensions is warranted in a successful company, because usually the existing resources, processes, and values are capably supporting established, healthy businesses, even as new resources, processes, and values are needed to support new ones. If executives can stop using one-process- and one-organization-fits-all policies for all types of innovations, they can greatly improve the probabilities that their growth ventures will succeed.

Figure 7-1 offers a framework to help managers decide when they can exploit current organizational capabilities and when they should create or acquire new capabilities to launch a new-growth business. The left vertical axis in figure 7-1 measures the extent to which the existing processes—the patterns of interaction, communication, coordination, and decision making currently used in the organization—are the ones that will get the new job done effectively. If the fit is good (toward the lower end of the scale), the project manager can exploit the organization’s existing processes and coordinate work that is done within the existing functional units. If not, new processes and new types of team interactions will be required.

FIGURE 7 - 1

A Framework for Finding the Right Organizational Structure and Home

The lower horizontal axis asks managers to assess whether the organization’s values will allocate to the new initiative the resources it will need in order to become successful. If there is a poor fit, then the mainstream organization’s values will accord low priority to the project; that is, the project is potentially disruptive relative to its business model. The upper horizontal axis in figure 7-1 captures on a continuum the level of autonomy needed by an organizational unit attempting to exploit an innovation. For disruptive innovations, setting up an autonomous organization to develop and commercialize the venture will be absolutely essential to its success. At the other extreme, however, if there is a strong sustaining fit, then the manager can expect that the energy and resources of the mainstream organization will coalesce behind it because the project is sustaining. There is no reason for skunkworks or spin-offs in such cases.

The right vertical axis maps three types of organizational structures that can be used to either exploit or overcome existing processes. The development team charged with shepherding an innovation to market can be either heavyweight, lightweight, or functional (all defined later in this chapter). The four regions in figure 7-1 integrate the challenges of dealing with different types of fit with the mainstream organization’s processes and values. Region A depicts a situation in which a manager is faced with a breakthrough but sustaining technological change. It fits the organization’s values, but it presents the organization with different types of problems to solve and therefore requires new types of interaction and coordination among groups and individuals. This circumstance mandates a heavyweight project team (described later). In region B, where the project fits the company’s processes as well as its values, the new venture can easily be developed by coordinating across functional boundaries within the existing organization. Region C denotes a disruptive technological change that fits neither the organization’s existing processes nor its values. To ensure success in such instances, the managers should create an autonomous organization. Region D typifies projects in which products or services similar to those in the mainstream need to be sold within a fundamentally lower-overhead business model. These ventures can leverage the main organization’s logistics management processes, but they need very different budgeting, management, and profit and loss profiles.[19]

In using figure 7-1, it is important to remember that disruption is a relative term. What is disruptive to one company might have a sustaining impact on another. For example, Dell Computer began by selling computers over the telephone. For Dell, the initiative to begin selling over the Internet was a sustaining innovation. It helped Dell make more money in the way it was already structured to make money. Not surprisingly Dell adopted Internet retailing very successfully. For Compaq, Hewlett-Packard, and IBM, however, marketing directly to customers was decidedly disruptive because of its impact on their retail channel partners. They couldn’t make room for Internet distribution within their existing organizations, and so their attempts to incorporate this new channel were far less successful. The only way they could have succeeded at becoming leaders in marketing computers directly to customers was to have done it within an autonomous business unit, and possibly with a new brand.

Similarly, the Internet is a sustaining technology relative to catalog retailers such as Lands’ End, and so we would expect them to incorporate it into their existing processes. But it is disruptive relative to bricks-and-mortar retailers such as Macy’s, which would require autonomous units in order to exploit on-line retailing in a way that could create truly disruptive growth.[20] Similarly, the Internet is a sustaining technology to discount stockbrokers such as Ameritrade, and a disruptive technology to full-service brokers such as Merrill Lynch.

Organizations cannot disrupt themselves. So when Merrill Lynch implemented Internet-based equities trading within its mainstream brokerage organization, the effect was essentially to bring better information to Merrill’s full-service brokers, to help them do an even better job servicing the needs of their high-net-worth clients. The Internet system was shaped as a sustaining technology relative to Merrill Lynch—and no other outcome would be possible. Furthermore, this was a wise thing for Merrill Lynch to do. Its brokerage business for wealthy clients is a beautiful, profitable business, and Merrill would be crazy not to make it even better and even more profitable.[21] But Merrill’s executives should not conclude that they have addressed the threat and opportunity of discount online brokerage that is posed by Charles Schwab. They could only do that if they acquired or created an autonomous unit whose values or cost structure helps them earn attractive profits at discount prices.

This is an important reason for our observation in chapter 4 that established companies are prone to cram disruptive ideas into the mainstream market, forcing them to compete against consumption on a sustaining-technology basis. As long as the strategies for developing and commercializing these disruptive innovations are developed within the mainstream organization, this is the only outcome that we can expect. An organization’s processes and values ensure that it can only implement sustaining innovations.

Creating New Capabilities

The RPV model can be a useful guide for executives who determine that they need to create new capabilities because those that their organization presently has aren’t well suited for building new-growth businesses. This can be framed as a make-or-buy decision. We typically frame make-or-buy decisions as relating to resources, such as training managers internally or hiring them from outside. But processes and values can also be made or bought, as the following discussion describes.

Creating Management Bench Strength

In many ways, building the management bench strength required to launch a sequence of new-growth businesses is a chicken-or-the-egg problem. Maximizing the probabilities of success means identifying managers who are able, here and now, to grapple successfully with the challenges of building new businesses. But to develop managers for the future, organizations need to put up-and-coming managers into situations and responsibilities for which they are not yet qualified. It is the only way they can learn the skills required to succeed. You need to be creating successful businesses in order to have the right curriculum within your internal schools of experience in which next-generation managers can learn. And yet having capable managers in place is a prerequisite to building these growth businesses. Successfully wrestling with these dimensions of the innovator’s dilemma is a critical responsibility of a director of human resources.

By the time a company reaches substantial size, most executives have established processes to identify a set of early-career, high-potential managers who should be prepared, ready and waiting, with the skills to succeed in the situations that will confront the company in the future. In many companies, employees are chosen for this high-potential management track based on early evidence of right-stuff attributes. In these firms, recruiting and promoting up-and-coming leaders entails sifting through lots of people in order to find those few who possess the desired end-state attributes in some nascent form.

The school-of-experience theory, however, says that potential should not be measured by attributes, but rather by the ability to acquire the attributes and skills needed for future situations. The talent to be sought, in other words, is the ability to learn what needs to be learned from the experiences in which the high-potential employee will be schooled in the future. By focusing on ability to learn, it is possible to avoid the trap of assuming that the finite list of competencies important for today are those that will be required in the future. A performance appraisal form targeted at identifying high-potential people would certainly cover basic technical and cognitive requirements, but would not ask for a ranking on right-stuff attributes. It would focus on learning-oriented measures such as “seeks opportunities to learn,” “seeks and uses feedback,” “asks the right questions,” “looks at things from new perspectives,” and “learns from mistakes.” Some attributes of a good learner will show up as achievements, of course, but the quest is to determine whether an employee is willing to learn new skills.

Putting people in positions where they will learn, however, creates its own dilemma. Those who are “ready now,” who are deemed to be fully qualified to handle a given job, by definition have the least to learn by doing it. And those who have the most to learn bring the least experience to the task. McCall notes that, as a result, many managers who are intensely focused on delivering ever-improving results often are the worst at developing next-generation management bench strength. It takes extraordinary discipline and vision on the part of senior executives to balance the tension between deploying fully qualified employees to deliver results now versus giving learning opportunities to high-potential employees who need further development. But strike this balance they must.

Some firms deal with this tension by turning repeatedly to the labor markets, raiding other companies for people with the requisite skills already in full flower. Harkening back to chapters 5 and 6, we believe that one reason why internal management training is becoming more pervasive is because managers don’t yet perform well enough. In-house management development processes in many ways can create an optimized, interdependent interface between the skills of the manager and the processes and values of the company. In situations where management performance is not yet good enough, outsourcing “modular” managers and attempting to plug them into a company’s complex, interdependent system of resources, processes, and values often does not work well.[22]

A company that works to develop a sequence of new-growth businesses can build a virtuous cycle in management development. Launching growth business after growth business creates a set of rigorous, demanding schools in which next-generation executives can learn how to lead disruption. Companies that only sporadically attempt to create new-growth businesses, in contrast, offer to their next-generation executives precious few of the courses they need to successfully sustain growth.

Making New Processes

The right vertical axis in figure 7-1 shows the kind of development team that is required to create appropriate processes for a new-growth business. When different processes need to be created, it requires what Harvard Business School Professors Kim Clark and Steven Wheelwright call a heavyweight team.[23] The term refers to a group of people who are pulled out of their functional organizations and placed in a team structure that allows them to interact over different issues at a different pace and with different organizational groups than they habitually could across the boundaries of functional organizations. Heavyweight teams are tools to create new processes, or new ways of working together. In contrast, lightweight or functional teams are tools to exploit existing processes.

We can use the concepts of interdependence and modularity from chapter 5 to visualize a heavyweight team and understand when it is important to create one. When there is a well-defined interface between the activities of two different people or organizational groups—meaning that you can clearly specify what each is supposed to deliver, you can measure and verify what they deliver, and there are no unanticipated interdependencies between what one does and what the other must do in response—then those people and groups can interface at arm’s length and need not be on the same team. When these conditions are not met, then all unpredictable interdependencies should be incorporated within the boundaries of a heavyweight team. The team’s external boundary can be drawn where there are modular interfaces. New methods of working together can coalesce within this team as it addresses its task. These can then become codified as processes if the team is kept intact and addresses a similar task repeatedly.[24]

To be successful, heavyweight teams should be co-located. Team members bring their functional expertise to the group, but they do not represent their functional group’s “interests” on the team. Their responsibilities are simply to do what needs to be done in order for the project to be successful—even if that course of action is not optimal for their functional group. Many companies have used heavyweight teams successfully as a method for creating new processes. Chrysler, for example, historically structured its product development groups around specific components, such as electrical systems. When the changing basis of competition in its industry forced Chrysler to accelerate the development of new automobiles in the early 1990s, Chrysler organized its development teams around platforms like the minivan, instead of the technical subsystems. The heavyweight teams that Chrysler created were consequently not as good at focusing on component design, but the teams forged new processes that were much faster and more efficient in creating entirely new car designs. This was a critical achievement as the basis of competition changed. Companies as diverse as Medtronic in cardiac pacemakers, IBM in disk dives, and Eli Lilly with its schizophrenia drug Zyprexa have used heavyweight teams as vehicles for creating different, faster processes.[25]

Drawing flow diagrams does not create radically different processes. Rather, executives build processes by giving a group of people in a heavyweight team a new problem that the organization has not confronted before. After the team has successfully addressed the challenge, the team needs to confront a similar problem again, and then again. Ultimately, this new way of working will become ensconced within the team and then can diffuse throughout the organization.

Creating New Values

Companies can create new prioritization criteria, or values, only by setting up new business units with new cost structures. Charles Schwab, for example, set up its disruptive online brokerage venture as a completely autonomous organization. It priced online trades at $29.95, compared with the average price of nearly $70 that Schwab had been charging for trades executed through its telephone and office-based brokers. The separate unit was indeed disruptive to the mainstream. It grew so fast that within eighteen months the company decided to fold what had been the mainstream business into the new disruptive organization. The corporation’s values, which in our model are synonymous with its cost structure, were thereby transformed by launching a successful disruptive enterprise. Schwab’s corporate values changed when the disruptive business displaced the old organization, whose values were incapable of prioritizing the disruptive growth business.

The reason an organization cannot disrupt itself is that successful organizations can only naturally prioritize innovations that promise improved profit margins relative to their current cost structure. For Schwab, therefore, it was far more straightforward to create a new business model that could view $29.95 as a profitable proposition than it would have been to hack enough cost out of the original organization so that it could make money at the disruptive price point. This is the best way to change values because the new, disruptive game almost always must begin while the established business still has substantial, profitable sustaining potential.

What does autonomous mean? Our research suggests that geographical separation from the core business is not a critical dimension of autonomy. Nor is ownership structure. There is no reason why a disruptive venture cannot be wholly owned by its parent. The key dimensions of autonomy relate to processes and values. The disruptive business needs to have the freedom to create new processes and to build a unique cost structure in order to be profitable as it makes and sells even its earliest products. Making the judgment calls about which of the mainstream businesses’ processes and overhead costs the new venture should and should not accept is a key role of the CEO in building new-growth businesses. We will return to this in chapter 10.

Buying Resources, Processes, and Values

Managers often think that acquiring rather than developing a set of capabilities makes competitive and financial sense. Unfortunately, companies’ track records in developing new capabilities through acquisition are frighteningly spotty. The RPV framework can be a useful way to frame the challenge of integrating acquired organizations. Every time one company acquires another, it buys its resources, its processes, and its values. Acquiring managers therefore need to begin by asking, “What is it that really made this company that I just bought so expensive? Did I justify the price because of its resources—its people, products, technology, or market position? Or was a substantial portion of its worth created by its processes and values—its unique ways of working and decision making that have enabled the company to understand and satisfy customers; develop, make, and deliver new products in a timely way; and to do so within a cost structure that gave it disruptive potential?”

If the acquired company’s processes and values are the real drivers of its success, then the last thing the acquiring manager wants to do is to integrate the company into the new parent organization. Integration will vaporize many of the processes and values of the acquired firm as its managers are required to adopt the buyer’s way of doing business and have their new-growth proposals evaluated according to the decision criteria of the acquiring company. If its processes and values were the reason for its historical success, a better strategy is to let the acquired business stand alone, and for the parent to infuse its resources into the acquired firm’s processes and values. This strategy, in essence, truly constitutes the acquisition of new capabilities.

If, on the other hand, the company’s resources were the primary rationale for the acquisition, then integrating the firm into the parent makes a lot of sense—essentially plugging the acquired people, products, technology, and customers into the parent’s processes as a way of leveraging the parent’s existing capabilities.

The RPV model can illuminate Daimler-Benz’s acquisition of Chrysler and its subsequent efforts to integrate the two organizations. Chrysler had few resources that could be considered unique in comparison to its competitors. Much of its success in the market of the 1990s was rooted in its processes—particularly in its heavyweight-team product design process, which could create classy new designs in twenty-four months. Chrysler’s values were also worth a lot, because it could design and produce a car with one-fifth as many overhead employees as Daimler. What would have been the best way for Daimler to leverage the capabilities it acquired in Chrysler? By keeping it independent and infusing Daimler’s resources into Chrysler’s processes and its cost structure. Instead, as Wall Street began its demanding drumbeat for cost savings, analysts with little sense for processes and even less for values pressured Daimler management into consolidating the two organizations in order to cut costs. We suspect that integrating the two companies will compromise many of the key processes and the values that made Chrysler such an attractive acquisition.

In contrast, many of Cisco Systems’ acquisitions worked well—because, we would argue, it has kept resources, processes, and values in the right perspective. Most of the companies that Cisco has acquired were small firms less than two years old: early-stage organizations whose market value was built primarily upon their resources, particularly their engineers and products. Cisco has a well-defined, deliberate process by which it essentially plugs these resources into the parent’s processes and systems, and it has a carefully cultivated method of keeping the engineers of the acquired company happily on the Cisco payroll. In the process of integration, Cisco throws away whatever nascent processes and values came with the acquisition, because those weren’t what Cisco paid for. On a couple of occasions when the company acquired a larger, more mature organization— notably its 1996 acquisition of StrataCom—Cisco did not integrate. Rather, it let StrataCom stand alone, and infused its substantial resources into the organization to help it grow at a more rapid rate.[26]

The Costs of Getting It Wrong

Great opportunities can be missed and millions of dollars wasted when managers have high-potential ideas but place them in an organizational context that is not suited to the task. Two high-profile examples of this are Bank One’s effort to create WingspanBank.com in the late 1990s, and F. W. Woolworth’s effort to build Woolco into a leading discount retailer in the 1960s. Let’s look at them through the lens of this theory.

Bank One’s Wingspan

Bank One’s credit card division, First USA, worked with a leading management consulting firm to launch an online bank called Wingspan in the late 1990s. They set Wingspan up as a wholly owned but autonomous organization that would have separate customers and a separate brand; it therefore was free to pillage Bank One’s business. The authors of the strategy apparently felt that the newness and disruptive nature of online banking meant that Wingspan had the best chance of success as a separate company.

The litmus tests in chapter 2, however, suggest that online banking is a sustaining innovation relative to the business models of the leading retail banks. Online banks cannot compete against nonconsumption, because almost all computer owners and users in the United States already have bank accounts. Hence, a new-market disruption just isn’t possible: Online banking can only compete against consumption. The other disruptive alternative, crafting a low-end attack, would require first finding a set of customers who are overserved by the functionality and reliability of current banking products and services and, second, entail creating a business model that can earn attractive profits at the discount prices required to win the business of customers in the least-demanding tiers of the market. Given the high advertising costs of attracting customers and with no cost advantage in the cost of money, this also is not feasible.[27]

Because disruption is impossible, Internet banking can only be deployed as a sustaining technology relative to the business model of retail banks. A significant portion of their best customers in fact want the convenience, and in most instances the cost per transaction is lower when it is done over the Internet than when done in a branch or via an ATM. Hence, there was no reason why Bank One needed to set this effort up separately. Indeed, in a sustaining battle the established firms almost always win.

F.W. Woolworth and Discount Retailing

In 1962 F.W. Woolworth, one of the world’s leading retailers, established its discount department store arm, Woolco, as a wholly owned but autonomously managed, free-standing division—and well it should have. Discount retailing was disruptive from a values standpoint, and it required fundamentally different operating processes. Woolworth’s variety stores averaged 35 percent gross margins and turned inventories over about 3.4 times per year. Discount retailing entailed average gross margins of only 23 percent, and to earn acceptable returns these retailers needed to turn inventories about 5 times per year.[28]

In 1971, Woolworth’s corporate executives decided to integrate the management, buying, and logistics functions of Woolco back into the mainstream of Woolworth in order to leverage these fixed costs across the volumes of both businesses. The result? Within a year, the values of the mainstream business had forced Woolco’s margins up to 34 percent, and Woolco’s inventory turns declined to four times—both mirroring the profit model of the F. W. Woolworth stores. Woolco ultimately had to be closed. Very quickly, just as we saw with Merrill Lynch’s implementation of Internet brokerage, the business model of the potentially disruptive business simply had to conform itself to the processes and values of the organization in which it was housed. As a general law of organizational nature, there is no other possible outcome. Organizations cannot disrupt themselves. Managers can only do what makes sense to them, given the context in which they work. As a disruptive opportunity, Woolco needed to remain separate. As a sustaining opportunity, Internet banking needed to be integrated within Bank One’s mainstream.

Managers whose organizations are confronting opportunities to grow must first determine that they have the people and other resources required to succeed. They then need to ask two further questions: Are the processes by which work habitually gets done in the organization appropriate for this new project? And will the values of the organization give this initiative the priority it needs? Established companies can improve their odds for success in disruptive innovation if they use functionally oriented and heavyweight teams where each is appropriate, and if they commercialize sustaining innovations in mainstream organizations but put disruptive ones in autonomous organizations.

A primary reason successful innovation seems difficult and unpredictable is that firms often employ talented people whose management skills were honed to address stable companies’ problems. And often, managers are set to work within processes and values that weren’t designed for the new task. Instead of accepting onesize-fits-all policies, if executives will spend time ensuring that capable people work in organizations with processes and values that match the task, they will create a major point of leverage in successfully creating new growth.

Notes

1.   One of the most important studies on this topic is summarized in Dorothy Leonard-Barton, “Core Capabilities and Core Rigidities: A Paradox in Managing New Product Development,” Strategic Management Journal 13 (1992): 111–125.

2.   The concepts in this chapter attempt to build on a respected tradition of scholarship about the capabilities of organizations that is known in academic circles as the “resource-based view” (RBV) of the firm. This tradition sees resources as the defining asset of a firm, and seeks to explain interfirm differences in performance and growth in terms of differences in resource complements. See, for example, K. R. Conner, “A Historical Comparison of Resource-Based Theory and Five Schools of Thought Within IO Economics: Do We Have a New Theory of the Firm?” Journal of Management 17, no. 1 (1991): 121–154. The seminal works in this stream are E. T. Penrose, The Theory of the Growth of the Firm (London: Basil Blackwell, 1959); and B. Wernerfelt, “A Resource-Based View of the Firm,” Strategic Management Journal 5 (1984): 171–180. More recent work includes M. Peteraf, “The Cornerstones of Competitive Advantage: A Resource-Based View,” Strategic Management Journal 14, no. 3 (1993): 179–192; and J. Barney, “The Resource-Based Theory of the Firm,” Organization Science 7, no. 5 (1996): 469.

We have defined “resources” far more narrowly than many RBV researchers, using additional concepts—namely, processes and values—to capture other important constituent elements of firms’ capabilities that some have chosen to include in the category of resources. See, for example, D. Teece and G. Pisano, “The Dynamic Capabilities of Firms: An Introduction,” Industrial and Corporate Change 3, no. 3 (1994): 537–556; R. M. Grant, “The Resource-Based Theory of Competitive Advantage,” California Management Review 33, no. 3 (1991): 114–135; and J. Barney, “Organizational Culture: Can It Be a Source of Sustained Competitive Advantage?” Academy of Management Review 11, no. 3 (1986): 656–665. Our belief is that what has become in many cases a debate over definitions of the phenomenon is actually a failure of categorization. The framework and theory presented in this chapter were summarized in preliminary form in a chapter added to the second edition of The Innovator’s Dilemma. This model was initially published in Clayton Christensen and Michael Overdorf, “Meeting the Challenge of Disruptive Change,” Harvard Business Review, March– April 2000.

3.   Findings reported by managerial psychologists RHR International corroborate this estimate. RHR recently reported that up to 40 percent of newly hired senior executives either quit, significantly underperform, or are fired within two years of assuming their new positions (Globe & Mail, 1 April 2003, B1).

4.   Tom Wolfe, The Right Stuff (New York: Farrar, Straus, and Giroux, 1979).

5.   Consistent with our statements in chapter 1 about how robust theory can bring predictability to an endeavor, much early research about how to hire the right people into the right jobs has categorized potential managers by their attributes. Remember that the early researchers in aviation observed a high correlation between the possession of attributes such as wings and feathers and the ability to fly. But they were only able to make statements about correlation or association, not causality. It is only when researchers identify the fundamental causal mechanism, and then understand the different circumstances in which practitioners might find themselves, that things can become highly predictable. In this case, possession of many right-stuff attributes might be quite highly correlated with success in an assignment, but it is not the fundamental causal mechanism of success.

6.   Morgan McCall, High Flyers: Developing the Next Generation of Leaders (Boston: Harvard Business School Press, 1998). This book offers a refreshing, intellectually rigorous way of thinking about how managers learn, and of assessing whether a manager is capable of successfully addressing challenges that lie ahead. We highly recommend that practitioners who are interested in learning more about how to get the right people into the right place at the right time read the book in its entirety.

7.   At a later point in the venture’s development, of course, it will need executives who have taken these courses in the school of experience that relate to scaling a business—and later still, to efficiently operating an organization. One reason many new ventures flame out after an initial, single-product success is that the founders lack the intuition and experience in creating processes that can repeatedly create better products and produce and deliver them reliably.

8.   The most logical, comprehensive characterization of processes that we have seen is in David Garvin, “The Processes of Organization and Management,” Sloan Management Review, Summer 1998. When we use the term processes, we mean for it to include all of the types of processes that Garvin has defined.

9.   Under various labels, many scholars have explored at length the notion of “processes” as the fundamental building block of organizational capability and competitive advantage. Perhaps among the most influential of such works is R. R. Nelson and S. G. Winter, An Evolutionary Theory of Economic Change (Cambridge, MA: Belknap Press, 1982). Nelson and Winter refer to “routines” rather than processes, but the fundamental concept is the same. They establish that firms build competitive advantage by developing better routines than other firms, and that superior routines are developed only through the faithful replication of effective behaviors. Once established, good routines are difficult to change. See, for example, M. T. Hannan and J. Freeman, “The Population Ecology of Organizations,” American Journal of Sociology 82, no. 5 (1977): 929–964.

Subsequent work has explored and demonstrated the power of the concept of processes (called, variously, organizational capabilities, dynamic capabilities, and core competencies) as a source of competitive advantage. Examples of this work include D. J. Collis, “A Resource-Based Analysis of Global Competition: The Case of the Bearings Industry,” Strategic Management Journal 12 (1991): 49–68; D. Teece and G. Pisano, “The Dynamic Capabilities of Firms: An Introduction,” Industrial and Corporate Change 3, no. 3 (1994): 537–556; and C. K. Prahalad and G. Hamel, “The Core Competence of the Corporation,” Harvard Business Review, May–June 1990, 79–91.

Our view is that although this stream of research has been extremely insightful, like the work on the resource-based view to which we referred in note 3, it suffers from the limitation either of expanding the definition of “process” to include all possible determinants of competitive advantage or, in the interests of intellectual integrity, of excluding important elements of firms’ capabilities from its scope of analysis. For more on this, see A. Nanda, “Resources, Capabilities, and Competencies,” in Organizational Learning and Competitive Advantage, eds. B. Moingeon and A. Edmondson (New York: The Free Press, 1996), 93–120.

10.  See Leonard-Barton, “Core Capabilities and Core Rigidities.”

11.  See C. Wickham Skinner, “The Focused Factory,” Harvard Business Review, May–June 1974.

12.  Chet Huber, who was the founding president of General Motors’ OnStar telematics service, reflected for us on how critical the distinction is between resources (people) and processes: “One of my biggest lessons has been realizing that the company needed to be entrepreneurial and not the individuals within the company. [The individuals] needed to act more like synchronized swimmers to keep the organization very well aligned.” Clayton M. Christensen and Erik Roth, “OnStar: Not Your Father’s General Motors (A),” Case 9-602-081 (Boston: Harvard Business School), 12.

13.  The concept of values, as we define the term here, is similar to the constructs of “structural context” and “strategic context” that have emerged in scholarly work about the resource allocation process. Important works in this tradition include J. L. Bower, Managing the Resource Allocation Process (Homewood, IL: Richard D. Irwin, 1972), and R. Burgelman, “Corporate Entrepreneurship and Strategic Management: Insights from a Process Study,” Management Science 29, no. 12 (1983): 1349–1364.

14.  chapter 8 examines in much greater depth the effect that values have on resource allocation and strategy making.

15.  For example, Toyota entered the North American market with its Corona model, a product targeting the lowest-priced tiers of the market. As the entry-level tier of the market became crowded with look-alike models from Nissan, Honda, and Mazda, competition among equally low-cost competitors drove down profit margins. Toyota developed more sophisticated cars targeted at higher tiers of the market in order to improve its margins. Its Corolla, Camry, 4-Runner, Avalon, and Lexus families of cars have been introduced in response to the same competitive pressures—Toyota kept its margins healthy by migrating up-market. In the process, Toyota has had to add costs to its operation to design, build, and support cars of this caliber. It subsequently decided to exit the entry-level tiers of the market, having found the margins it could earn there to be unacceptable given its changed cost structure.

Toyota recently introduced its Echo model in an attempt to reenter the entry-level tier with a $14,000 car—reminiscent of American automakers’ periodic attempts to reestablish positions at the low end of the market. To be successful, Toyota management will have to swim against a very strong current. It is one thing for Toyota senior management to decide to launch this new model. But to implement this strategy successfully, many people in the Toyota system—including its dealers—will have to agree that selling more cars at lower margins is a better way for the company to boost profits and equity values than selling more Camrys, Avalons, and Lexuses. Only time will tell for certain whether Toyota will be successful at bucking the company’s evolved values.

16.  See Edgar Schein, Organizational Culture and Leadership (San Francisco: Jossey-Bass, 1988). Our description of the development of an organization’s culture draws heavily from Schein’s research.

17.  Professors Michael Tushman of Harvard and Charles O’Reilly of Stanford have studied deeply the need to manage organizations in this way to create what they call “ambidextrous organizations.” As we understand their work, they assert that it is not enough simply to spin off an autonomous organization to pursue important but disruptive innovations that don’t match the mainstream organization’s values. The reason is that too often, executives spin it off to get the disruption off their agenda so that they can focus on managing the core business. To create a truly ambidextrous organization, Tushman and O’Reilly assert that the two different organizations need to be located within a business unit. Responsibility for managing the disruptive and sustaining organizations needs to be at a level in the organization where the two are not treated as businesses in a portfolio. Rather, they should be within a group or business unit whose management has the bandwidth to pay careful attention to what should be integrated and shared across the groups, and what should be implemented autonomously. See Michael L. Tushman and Charles A. O’Reilly, Winning Through Innovation: A Practical Guide to Leading Organizational Change and Renewal (Boston: Harvard Business School Press, 2002).

18.   Historically, some venture capital–backed start-ups, particularly in telecommunications and health care, have followed a strategy of developing a breakthrough sustaining innovation—leapfrogging ahead of the leader on the sustaining curve—and then quickly selling out to the larger established company that is moving up the trajectory behind them. This strategy works—not because the established companies’ values constrain them from targeting the same innovation, but because their processes aren’t as fast as those of the start-ups. This is a proven way to turn a profit, but it is not a route by which a new-growth business can be created. Either by acquiring the product or by outmuscling the entrant, the established company will in the end be offering the improved product as part of its product line, and the venture that developed it first will not exist. The start-ups essentially comprise heavyweight project teams, which develop products autonomously and then get disbanded when the products are ready for commercialization. It is a mechanism by which established companies with attractively priced equity can pay for research and development with equity, rather than expense.

19.  Dow Corning Corporation’s establishment of its Xiameter subsidiary is an example of exactly this situation. Xiameter is a high-dependability, low-overhead sales and distribution business model that allows the company to make attractive profits on commodity-level pricing of standard silicone products. Customers who need higher-cost services to guide their purchasing decisions can purchase their silicones through Dow Corning’s mainstream sales and distribution structure.

20.  We make this statement for illustrative purposes only. At the time of this writing, catalog and online retailing are so well established as a disruptive wave in retailing that if a department store were to attempt to create a major new online growth business, it would be following a sustaining strategy as an entrant, relative to the firms that created online retailing. Even a giant like Macy’s would likely lose to the firms that are already on a sustaining march up the disruptive trajectory. Acquiring a firm that has a strong position on that disruptive trajectory—as Sears did when it bought Lands’ End—is about the only way that department stores could now catch that wave.

21.  Like Merrill Lynch, Goldman Sachs has also implemented Internet-based trading systems for their existing customers within their mainstream, full-service brokerage businesses. The technology was, as a consequence, implemented in a manner that sustained the values, or cost structure, of those business units. In fact, the implementation of Internet-based trading capabilities probably added cost to the companies’ structures, because it was an additional option and did not displace the traditional broker-based trading channel. See Dennis Campbell and Frances Frei, “The Cost Structure and Customer Profitability Implications of Electronic Distribution Channels: Evidence from Online Banking,” working paper, Harvard Business School, Boston, 2002.

22.  An interesting stream of research is coming to this same conclusion. See, for example, Rakesh Khurana, Searching for a Corporate Savior: The Irrational Quest for Charismatic CEOs (Princeton, NJ: Princeton University Press, 2003). Khurana has found that bringing into a company high-profile “superstar” managers—those who in our parlance have many of the most coveted right-stuff attributes in abundance—meets with failure far more frequently than many have supposed.

23.  See Kim B. Clark and Steven C. Wheelwright, “Organizing and Leading Heavyweight Development Teams,” California Management Review 34 (Spring 1992): 9–28. The concepts described in this article are extremely important. We highly recommend that managers interested in these problems study it thoughtfully. Clark and Wheelwright define a heavyweight team as one in which team members typically are dedicated and co-located. The charge of each team member is not to represent his or her functional group on the team, but to act as a general manager—to assume responsibility for the success of the entire project, and to be actively involved in the decisions and work of members who come from each functional area. As they work together to complete their project, they will work out new ways of interacting, coordinating, and decision making that will come to compose the new processes, or new capabilities, that will be needed to succeed in the new enterprise on an ongoing basis. These ways of getting work done then get institutionalized as the new business or product line grows.

24.  The fundamental conceptual breakthrough that leads to the conclusions in this paragraph comes from the seminal study by Rebecca M. Henderson and Kim B. Clark, “Architectural Innovation: The Reconfiguration of Existing Systems and the Failure of Established Firms,” Administrative Science Quarterly 35 (1990): 9–30. This is the research that, in our view, elevated the state of theory building in process research from attribute-based categories to circumstance-based categories. Their essential idea is that over a period of time, the patterns of interaction, communication, and coordination among those responsible for designing a new product (the product development process that a company follows) will come to mirror the pattern in which the components of the product interact within the architecture of the product. In the circumstance in which the architecture is unchanged from one generation to the next, this habitual process will facilitate the kinds of interactions that are necessary for success. But in the circumstance in which the development organization needs to change the architecture significantly, so that different people need to interact with different people about different topics and with different timing, the same habitual process will impede success.

In many ways, the diagnosis and recommendations about process change that are on the vertical axes of figure 7-1 derive from Henderson and Clark’s work. The diagnoses and recommendations on the horizontal axes that relate to the values of the organization derive from The Innovator’s Dilemma, which in turn built on the work of Professors Bower and Burgelman that we have cited elsewhere. This body of research also seems to have lifted the state of theory from attribute-based categorizations to circumstance-based theory.

25.  We have observed a frustrating tendency among managers to seek one-size-fits-all solutions to the challenges they face, rather than to develop a way of applying solutions that are appropriate to the problem. On this particular issue, some managers seem to have concluded in the 1990s that heavyweight teams were the “answer,” and flipped their entire development organizations into using heavyweight development teams for all projects. After a few years, most of them decided that heavyweight teams, while they offered benefits in terms of speed and integration, were too expensive—and they then flipped their entire organizations back into the lightweight mode. Some of the companies cited in the text have suffered these problems, and have not learned how to employ the appropriate types of team in the appropriate circumstance.

26.  See Charles A. Holloway, Steven C. Wheelwright, and Nicole Tempest, “Cisco Systems, Inc.: Acquisition Integration for Manufacturing,” Case OIT26 (Palo Alto and Boston: Stanford University Graduate School of Business and Harvard Business School, 1998).

27.  We recognize that this is a dangerous statement to make; probably a more accurate statement is that at the time of this writing, nobody seems to have been able to devise a viable disruptive strategy for online banking. It is possible, for example, that E*Trade Bank is successfully building a low-end disruptive bank. We cited in note 21 one of an ongoing series of papers that Professor Frances Frei of the Harvard Business School has been writing with various coauthors about the impact of providing new service channels to customers. When established banks have added ATM, telephone, and online services to customers, they have not been able to discontinue the old channels of service, such as live tellers and loan officers. As a consequence, Frei has have shown that the provision of lower-cost channels of service actually adds cost, because they are additive and not substitutive. It is possible that E*Trade Bank, without the legacy infrastructure and costs of in-person service, can actually create a business model whose costs are low enough that it can earn attractive returns at the discount prices required to win the business of overserved customers.

28.  A retailer’s inventory turns are not simple to ratchet up (see chapter 2, note 18). When heading up, retailers carry a relatively rigid structure of inventory turns into higher margin products, resulting in an immediate improvement in ROI. Heading down-market entails carrying the same rigid turnover structure into lower-margin products, resulting in an immediate hit to ROI. This is a very asymmetric part of the world.

CHAPTER EIGHT

MANAGING THE STRATEGY DEVELOPMENT PROCESS

Don’t just tell me that the right strategy is crucial for success. How do I come up with a strategy that works? What process for formulating strategy is most likely to generate a strategy that will lead to success? Is it better to be the pioneer in an emerging market, or to be a follower once the market’s topography is clearer? When should we let innovations bubble up from within the company? When and why should we drive things from the top? Which aspects of strategy formulation do senior executives need to manage most closely?

Most questions about strategy that arise in building a new business concern the substance of the strategy. Managers are anxious that their strategy be the right one. There is an even more important strategy question, however, that most managers forget to ask—and it is the reason many ventures end up with flawed strategies. This crucial question relates to the process of strategy formulation that the venture’s management team will use to develop and implement a winning plan. Although executives are understandably obsessed with finding the right strategy, they can actually wield greater leverage by managing the process used to develop the strategy—by making sure that the right process is used in the right circumstances.

Innovative ideas always emerge in a half-baked, partially formed condition, as we have noted. They subsequently go through a shaping process that transforms them into the fully fleshed-out business plan, complete with strategy, that is required to win funding. This chapter describes two simultaneous but fundamentally different processes of strategy development, and presents a circumstance-based theory that indicates which of these processes management should rely on as the most reliable source of strategic insight at different stages of business development. It then describes the workings of the resource allocation process, which is the filter through which all strategic actions must flow in order to affect the company’s course. The chapter ends by describing some tools and concepts that executives can use to manage the ongoing processes of strategy formulation more effectively.

Two Processes of Strategy Formulation

In every company there are two simultaneous processes through which strategy comes to be defined. Figure 8-1 suggests that both of these strategy-making processes—deliberate and emergent—are always operating in every company.[1] The deliberate strategy-making process is conscious and analytical. It is often based on rigorous analysis of data on market growth, segment size, customer needs, competitors’ strengths and weaknesses, and technology trajectories. Strategy in this process typically is formulated in a project with a discrete beginning and end, and then implemented “top down.” We hope that the theories discussed in this book can help executives and their advisers devise even better deliberate strategies for creating and sustaining growth than have been possible through traditional methods of data analysis.

Deliberate strategies are the appropriate tool for organizing action if three conditions are met. First, the strategy must encompass and address correctly all of the important details required to succeed, and those responsible for implementation must understand each important detail in management’s deliberate strategy. Second, if the organization is to take collective action, the strategy needs to make as much sense to all employees as they view the world from their own context as it does to top management, so that they will all act appropriately and consistently. Finally, the collective intentions must be realized with little unanticipated influence from outside political, technological, or market forces. Because it is difficult to find a situation in which all three of these conditions apply, the emergent strategy-making process almost always alters the strategy that the company actually implements.[2]

FIGURE 8 - 1

The Process by Which Strategy Is Defined and Implemented

Emergent strategy, which as depicted in figure 8-1 bubbles up from within the organization, is the cumulative effect of day-to-day prioritization and investment decisions made by middle managers, engineers, salespeople, and financial staff. These tend to be tactical, day-to-day operating decisions that are made by people who are not in a visionary, futuristic, or strategic state of mind. For example, Sam Walton’s decision to build his second store in another small town near his first one in Arkansas for purposes of logistical and managerial efficiency, rather than building it in a large city, led to what became Wal-Mart’s brilliant strategy of building in small towns discount stores that were large enough to preempt competitors’ ability to enter. Emergent strategies result from managers’ responses to problems or opportunities that were unforeseen in the analysis and planning stages of the deliberate strategy-making process. When the efficacy of a strategy that was developed through an emergent process is recognized, it is possible to formalize it, improve it, and exploit it, thus transforming an emergent strategy into a deliberate one.

Emergent processes should dominate in circumstances in which the future is hard to read and in which it is not clear what the right strategy should be. This is almost always the case during the early phases of a company’s life. However, the need for emergent strategy arises whenever a change in circumstances portends that the formula that worked in the past may not be as effective in the future. On the other hand, the deliberate strategy process should be dominant once a winning strategy has become clear, because in those circumstances effective execution often spells the difference between success and failure.[3]

The Crucial Role of Resource Allocation

in the Strategy Development Process

Figure 8-1 charts the confluence of these deliberate and emergent decision-making processes in defining actual strategy. Ideas and initiatives, whether of deliberate or emergent origin, are filtered through the resource allocation process, as represented by the center-left box in the figure. The resource allocation process determines which of the deliberate and emergent initiatives get funded and implemented, and which are denied resources. Actual strategy is manifest only through the stream of new products, processes, services, and acquisitions to which resources are allocated.

The resource allocation process is typically complex and diffused, operating at every level and all the time. If the values that guide prioritization decisions in resource allocation are not carefully tied to the company’s deliberate strategy (and often they are not), then significant disparities can develop between a company’s deliberate strategy and its actual strategy. Actively monitoring, understanding, and controlling the criteria by which day-to-day resource allocation decisions are made at all levels of the organization are among the highest-impact challenges a manager can tackle in the strategy development process.

Initiatives that receive funding and other resources from the resource allocation process can be called strategic actions, as opposed to strategic intentions. Intel chairman Andrew Grove has counseled, “To understand companies’ actual strategies, pay attention to what they do, rather than what they say.” [4] In our parlance, this means that a company’s strategy is what comes out of the resource allocation process, not what goes into it.

As the company does these things, managers then confront and respond to unexpected crises and opportunities, and their experiences cycle back into the emergent process. As managers learn what works and what doesn’t in the competitive marketplace, their improved understanding flows back into the deliberate strategy process. Each resource allocation decision, no matter how slight, shapes what the company actually does. This creates a new set of opportunities and problems and generates new deliberate and emergent inputs into the process.

How does this critical resource allocation process work? It is powerfully driven by the values of the organization, which, as noted in chapter 7, are the criteria by which managers and employees make prioritization decisions. Most of the ideas for developing new products, services, and businesses bubble up from employees within the organization. Middle managers cannot carry all of these ideas up to senior management for approval and funding, however. The values or criteria that middle managers use to decide which ideas they will promote and which they will allow to languish play a crucial role in determining what comes out of the resource allocation process. We noted in chapter 1 that once middle managers decide an idea has merit, they engage with the innovators in a process of shaping the idea into a fully fleshed-out business plan that can win funding. The values that senior management employ in these funding decisions therefore exert an equally powerful influence on the types of ideas that can and cannot emerge from the resource allocation process.[5]

Two factors exert a particularly important influence on the values that guide resource allocation decisions. The first is the company’s cost structure, which determines the gross profit margins that it must earn to cover overhead costs and make a profit. Good managers have a very difficult time according priority in the resource allocation process to innovative proposals that will not maintain or improve the organization’s profit margins.[6] The second factor is the size threshold that new opportunities must meet in order to get through the resource allocation filter. This threshold grows higher as a company becomes larger. Opportunities that were seen as energizing in a company’s resource allocation process when the company was small get filtered out as “not big enough to be interesting” in the larger company.

In addition to these powerful, direct determinants of the values that guide senior executives’ priorities in resource allocation, other criteria that are subtly embedded in diffused processes throughout the company influence what lower-level employees are able to prioritize. These combine to exert additional influence on which initiatives can pass through the resource allocation filter. An example of these factors is the short tenure in assignment that is typical in the career path of high-potential employees. Management development systems in most organizations move high-potential employees into new positions of responsibility every two to three years in order to help them master management skills in various parts of the business. This practice is critical in management development, but its effect is to influence midlevel managers to accord priority to projects that will pay off within the typical tenure that they expect in their jobs. They want to produce improved results that will merit attractive promotions.

Other factors are embedded within the sales force’s incentive compensation system. Salespeople’s decisions about which customers to focus on and which products to emphasize are critical elements of the diffused resource allocation process and are heavily influenced by how they are compensated. Customers also exert a powerful influence on the sorts of initiatives that survive the resource allocation process. You can’t build a business around a product that your customers don’t want, because the customers pay the bills. Although managers think that they control the resource allocation process, customers often exert even more powerful de facto control over how money can and cannot be spent. Competitors’ actions likewise exert powerful influence. When a competitor’s action threatens to steal customers or growth opportunities away, managers have almost no choice but to push a response through the resource allocation filter.

The resource allocation process, in other words, is a diffused, unruly, and often invisible process. Executives who hope to manage the strategy process effectively need to cultivate a subtle understanding of its workings, because strategy is determined by what comes out of the resource allocation process, not by the intentions and proposals that go into it.

An Illustration of Resource Allocation in

Strategy Making: The Case of Intel

Intel began as a manufacturer of semiconductor memories, and its founding engineers developed the world’s first commercially viable dynamic random access memory (DRAM) chips.[7] In 1971 an Intel engineer serendipitously invented the microprocessor during a funded development project for a Japanese calculator company, Busicom. Although DRAMs continued to account for the lion’s share of company sales through the 1970s, Intel’s sales of microprocessors grew gradually in a host of small, emerging applications.

Every month Intel’s production schedulers met to allocate the available production capacity across their products, which ranged from DRAMs to EPROMs and microprocessors.[8] The sales department would bring to this meeting its forecast shipments by product, and accounting would bring a rank ordering of those products by gross margins per wafer start. The highest-margin product would then be allocated the production capacity needed to meet its forecast shipments. The next-highest-margin product would then get the capacity it needed in order to meet its forecast shipments, and so on, until the product line with the lowest gross margins was allocated whatever residual capacity remained. Gross margins per wafer start, in other words, constituted the values of the organization that were used in this critical resource allocation decision.

Japanese DRAM makers attacked the U.S. market in the early 1980s, causing pricing levels to drop precipitously and relegating DRAMs to the lowest ranking by gross margin of Intel’s products. Because there was less intense competition, microprocessors consistently earned among the most attractive gross margins in Intel’s product portfolio. The resource allocation process therefore systematically diverted manufacturing capacity away from DRAMs and into microprocessors. This occurred without any explicit management decision to change strategy. Senior management, in fact, continued to invest two-thirds of R&D dollars into the DRAM business even as the resource allocation process was executing a systematic exit from DRAMs.[9]

Finally, by 1984, when the company had plunged into financial crisis and DRAMs had contracted to just a fraction of Intel’s volume, senior management recognized that Intel had become a microprocessor company. They stopped DRAM R&D spending, and Gordon Moore and Andy Grove made their storied exit through the company’s revolving lobby door as managers of the old company, and reentered as managers of the new company.[10] But it was the resource allocation process that transformed Intel from a DRAM company into a microprocessor company. Intel’s remarkable strategy shift was not the result of an intended strategy articulated within the executive ranks; rather, it emerged through the daily decisions made by middle managers as they allocated resources.[11]

Once this new business opportunity had become clear, then it was time to manage strategy in an assertive, deliberate mode—which Intel management did masterfully. By keeping a strong and sometimes ruthless hand on the resource allocation filter, management screened out bubbling-up initiatives that did not directly support the microprocessor business. Both strategy processes were crucial. A viable strategic direction had to coalesce from the emergent side of the process, because nobody could foresee clearly enough the future of microprocessor-based desktop computers. But once the winning strategy became apparent, it was just as critical to Intel’s ultimate success that the senior management then seized control of the resource allocation process and deliberately drove the strategy from the top.

Match the Strategy-Making Process to

the Stage of Business Development

Intel’s history illustrates that strategies rarely follow a simple sequence from formulation to implementation. Furthermore, strategy is never static. Most companies must at the outset chart their course in a deliberate direction because they need to start going somewhere. We hope that the theories in this book will help those who create new businesses to deliberately target a viable strategy with much more accuracy than was possible in the past. But even with this guidance, there will be much to be discovered.

Research suggests that in over 90 percent of all successful new businesses, historically, the strategy that the founders had deliberately decided to pursue was not the strategy that ultimately led to the business’s success.[12] Entrepreneurs rarely get their strategies exactly right the first time. The successful ones make it because they have money left over to try again after they learn that their initial strategy was flawed, whereas the failed ones typically have spent their resources implementing a deliberate strategy before its viability could be known. One of the most important roles of senior management during a venture’s early years is to learn from emergent sources what is working and what is not, and then to cycle that learning back into the process through the deliberate channel. As Mintzberg and Waters advise, “Openness to emergent strategy enables management to act before everything is fully understood—to respond to an evolving reality rather than having to focus on a stable fantasy. . . . Emergent strategy itself implies learning what works—taking one action at a time in a search for that viable pattern or consistency.” [13]

Effective managers eventually recognize the viable pattern that constitutes a successful strategy. At this point, with a firm hand on the criteria used as filters in the resource allocation process, managers need to make strategy formulation much more deliberate. Rather than continuing to feel their way into the marketplace, they need to boldly execute the strategy that they have learned will work. Intel, Wal-Mart, and a host of other companies each saw a viable strategy emerge that was substantially different than their founders had envisioned. But once the model was clear, they executed that strategy aggressively.

Managing Two Fundamentally Different

Strategy Processes: A Rare and Tricky Skill

In most waves of disruptive growth, a host of competitors are drawn to the opportunity. Firms that do not emerge from the pack as leaders fail in one of two places. First, many of the initial entrants fail because they spend their money aggressively implementing a deliberate strategy in the nascent stages when the right strategy cannot be known. The second point of failure occurs after the market and its applications become clear to the firms that have managed the emergent strategy process most effectively. The firms that then get left in the dust are those whose executives do not seize deliberate control of resource allocation and focus all investments in executing the race up-market.

The switch from an emergent to a deliberate strategy mode is crucial to success in a corporation’s initial disruptive business. But the CEO’s job in managing this process does not end there, because the deliberate strategy process often becomes a subsequent impediment to a company’s efforts to launch new waves of successful disruptive growth. This happens in two ways. First, the filters in the resource allocation process of successful companies become so well attuned to the successful strategy that they filter out all but the initiatives that sustain the existing business—causing them to ignore the disruptive innovations that create the next waves of growth. Just as important, once deliberate strategy processes have become embedded within organizations, they find it difficult to employ emergent processes again when launching new businesses.

A company’s efforts to catch new waves of disruptive growth need to be guided through emergent processes. Simultaneously, however, because the corporation’s established businesses typically have many years of profitability remaining even while the disruptive new-growth business is getting underway, the mainstream business needs to be driven by deliberate strategy processes to guide the sustaining innovations that will keep it competitive and profitable.

In our studies we have found a good number of companies whose executives have perceived the need to allocate resources to create new disruptive growth businesses before it is too late. But very, very rarely have we seen executives who have consistently demonstrated the ability to manage the strategy development process appropriately across a range of businesses in various stages of maturity. After they have entered a deliberate strategy mode they find it very difficult to let new businesses be guided through an emergent process.

For example, Prodigy Communications, a joint venture between Sears and IBM, was a pioneer in online services in the early 1990s. The managers of Sears and IBM were extraordinarily bold in resource allocation: They invested over a billion dollars in what was a very uncertain, potentially disruptive innovation. But they weren’t as successful in managing the strategy process—in helping Prodigy define a viable strategy through emergent processes even while the parent companies were managing their mainstream businesses deliberately.

Prodigy’s original business plan envisioned that consumers would use online services primarily to access information and make online purchases. In 1992, management realized that Prodigy’s two million subscribers were spending more time sending e-mail than downloading information or making purchases online. The architecture of Prodigy’s computer and communications infrastructure had been designed to optimize transactions processing and information delivery, and Prodigy consequently began charging extra fees to subscribers who sent more than thirty e-mail messages per month. Rather than seeing e-mail as an emergent strategy signal, the company tried to filter it out, because in a deliberate mode, management’s job was to implement the original strategy.

America Online (AOL) luckily entered the market later, after customers had discovered that e-mail was a primary reason for subscribing to an online service. With a technology infrastructure tailored to messaging and its “You’ve got mail” signature, AOL became much more successful.

In light of our model, Prodigy’s mistake was not that it entered the market early. Nor was it a mistake that management targeted online information retrieval and shopping as the primary attraction of an online service. Nobody could know at the outset precisely how online services would be used.[14] The executives’ mistake was to employ a deliberate strategy process before the strategy’s viability could be known. Had Prodigy kept strategic and technological flexibility to respond to emergent strategic evidence, the company could have had a huge lead over AOL and CompuServe (the third major online service provider). A similar challenge confronted the set of companies that responded in the early 1990s to the widely held view that a large market for handheld personal digital assistants was about to emerge. Many of the leading computer makers—including NCR, Apple, Motorola, IBM, and Hewlett-Packard—targeted this market, along with a few start-up firms such as Palm. All sensed that the market wanted a handheld computing device. Apple was one of the most aggressive of the innovators in this space. Its Newton cost $350 million to develop because of the technologies, such as handwriting recognition, that were required to build as much functionality into the product as possible. Hewlett-Packard also invested aggressively to design and build its tiny Kittyhawk disk drive for this market.

In the end, the products just weren’t good enough to be a substitute for notebook computers, and each of the companies scrapped its effort—except Palm. Palm’s original strategy was to provide an operating system for these personal digital assistants.[15] When its customers’ strategies failed, Palm searched around for another application and came up with the concept of an electronic personal organizer.

What were the strategic mistakes here? The computer companies employed deliberate strategy processes from the beginning to the end. They invested massively to implement their strategies, and then wrote the projects off when the strategies proved wrong. Palm was the only firm that shifted to an emergent strategy process when its original deliberate strategy failed. When a viable strategy emerged, Palm shifted back toward a deliberate process as it migrated up-market.

Clearly, this is not simple stuff.

Points of Executive Leverage in the Strategy-Making Process

The resource allocation process is the filter through which all strategic actions must flow. Because it is so complex and diffused throughout a company, it is rare that senior executives can simply devise a new strategy and “implement” it. Rather, defining and implementing strategy entails managing the conditions under which the strategy and resource allocation processes operate so that the strategy process can work efficiently, given the circumstances that each of the company’s organizations is in. Effective, appropriate processes will generate the needed strategic insights. The remainder of this chapter focuses on three points of executive leverage on the strategy process. Managers must:

1. Carefully control the initial cost structure of a new-growth business, because this quickly will determine the values that will drive the critical resource allocation decisions in that business.

2. Actively accelerate the process by which a viable strategy emerges by ensuring that business plans are designed to test and confirm critical assumptions using tools such as discovery-driven planning.

3. Personally and repeatedly intervene, business by business, exercising judgment about whether the circumstance is such that the business needs to follow an emergent or deliberate strategy-making process. CEOs must not leave the choice about strategy process to policy, habit, or culture.

Create a Cost Structure that Finds the Right Customers Attractive

Note that we didn’t identify “memos from the executive office” as a way of influencing the organization’s values. That is because the power of a venture’s cost structure overwhelms “being strategically important” as a criterion that drives resource allocation decisions.[16] Executives must pay very careful initial attention to creating a cost structure and business model within which orders from the kinds of ideal customers we described in chapter 4 will appear to be profitable. Otherwise, it will be impossible to build a business with those customers as a foundation.[17]

Let us illustrate by bringing things close to home, recounting Clayton Christensen’s own experience in running a venture capital–backed company that he founded with several MIT professors in the early 1980s, before he retreated to academia. The company was formed to exploit exciting technology to make products with a class of remarkable materials called advanced ceramics, and the history is recounted in a set of cases under the disguised name Materials Technology Corporation (MTC).[18]

MTC’s strategy was to become a major manufacturer of products made from these advanced ceramic materials. Because the materials business is capital intensive, Christensen and his colleagues knew from the beginning that MTC would need lots of capital to carry the company to break-even—they estimated about $60 million. In the early 1980s this was a lot of money to raise. What drove the amount needed was not just the cost of the physical facilities, but also the length of the product development cycle. Because of MTC’s position at the beginning of the value chain, it needed to win contracts to develop new components for its customers, who would then use those advanced components to make next-generation products of their own. Developing and testing the components easily took one to two years. When MTC succeeded, then and only then could the customers initiate their own cycle to design and test the new products that MTC’s advanced materials had enabled. The customers’ development processes typically took two to four additional years. In other words, MTC’s strategy entailed enduring a lot of expense before the revenue could begin rolling in.[19]

Christensen decided to cover the cost of MTC’s research and development staff by negotiating multimillion dollar joint development contracts from major corporate partners, in much the same way that many biotechnology companies have funded their protracted development processes. When MTC sold a major development contract to create the technology required to manufacture the products that its strategy envisioned, it then had to hire the scientists and engineers to do the work.

The strategy worked well for a couple of years. Then MTC’s first major development contract was completed, and the funding that had covered the salaries of three Ph.D. scientists and five engineers came to an end. Given the slow ramp to volume production inherent in MTC’s product development cycle, how could the company cover their salaries? These were some of the best materials scientists in the world, and they just couldn’t be sent packing. So the company had to sell another development contract to whomever would pay MTC enough money to cover their salaries and overhead. When the next funded project reached its end, the firm had to sell another funded program to cover the company’s high fixed costs, and so on. The company started with a strategy to be a volume product manufacturer. But very quickly and without intention, management began implementing a strategy to become a contract research house. There just wasn’t any way that the gross margins generated by initial volumes of manufactured products could cover the overheads that had to be put in place to deliver what MTC sold to its first customers.

MTC’s long development cycle and huge funding need represent an extreme example, but every new corporate venture experiences its own version of this challenge. It is the habit of large, established companies to ramp up expenses ahead of revenues, because in a world of deliberate strategy and sustaining innovation, these are safe bets. But these outlays define a cost structure very quickly, and before you know it you’ve got yourself a business model that defines the kind of business that does or does not look attractive. Ultimately MTC did become a manufacturing company, but only through wrenching layoffs and by restructuring the nature of its costs. It was only by creating a new cost structure that a new type of customer order could appear to be attractive and could thereby be accorded priority in resource allocation.

This example illustrates why executives need to pay careful attention to getting the initial conditions right. The only way that a new venture’s managers can compete against nonconsumption with a simple product is to put in place a cost structure that makes such customers and products financially attractive. Minimizing major cost commitments enables a venture to enthusiastically pursue the small orders that are the initial lifeblood of disruptive businesses in their emergent years.

Accelerating the Emergent Strategy Process

Executives whose ventures are in a discovery mode need not passively watch what evolves in the emergent strategy process. They can employ a rigorous method called discovery-driven planning to help a viable strategy emerge much more quickly and purposefully than is likely to happen through less-structured trial and error.[20]

Most deliberate strategic planning processes go through four steps, as suggested in table 8-1. First, innovators make assumptions about the future and about the success that a new business idea will enjoy. These assumptions might be grounded in good predictive theory, but often they are grounded in the way things worked in the past. In the second step, the innovators make financial projections based on those assumptions, and third, senior executives approve the proposal based on the financial projections. Fourth, the team responsible for the new venture goes off to implement the strategy. There frequently is a loop from the second step back to the first in this deliberate process. Because the innovators and middle managers typically know how good the numbers have to look in order for the proposal to get funded, they often will cycle back and revise the assumptions that they are making in order to make the numbers work.

This process does not work badly in a world of sustaining improvements and deliberate strategy. But when it is used for decision making in the emergent world of disruption, this process causes bad decisions to be made because the assumptions upon which the projections and decisions are built often prove wrong.

Discovery-driven planning is a way to actively manage the emergent strategy process. As depicted in table 8-1, it involves reordering the four steps. The first step is to make the financial projections—the targeted or required financial performance of the venture. The logic behind this is quite compelling. If everybody knows how good the numbers must look in order to win funding, why go through the cyclical charade of making and revising assumptions in order to make the numbers look good enough? The required income statement and return on investment should just be the standard first slide in every presentation. The second step, where the real work begins, is to compile an assumptions checklist. It answers the question, “We all know how good the numbers need to be. So what assumptions need to prove true in order for us to realistically expect that these numbers will materialize?” The assumptions on this list should be rank-ordered from most to least crucial. The list must include assumptions related to each of the theories in this book: that low-end or new-market disruptions are possible, that the targeted customers will use the new product for the jobs they are trying to get done, that the new venture will lead the company to the point in the value chain where the money will be in the future, and so on.

TABLE 8 - 1

A Discovery-Driven Method for Managing the Emergent Strategy Process

Sustaining Innovations:

Deliberate Planning

Disruptive Innovations:

Discovery-Driven Planning

(Note: decisions to initiate these projects can be grounded on numbers and rules.)

(Note: decisions to initiate these projects should be based on pattern recognition.)

1. Make assumptions about the future.

1. Make the targeted financial projections.

2. Define a strategy based on those

assumptions, and build financial

projections based on that strategy.

2. What assumptions must prove true in order for these projections to materialize?

3. Make decisions to invest based on those financial projections.

3. Implement a plan to learn—to test whether the critical assumptions are reasonable.

4. Implement the strategy in order to achieve the projected financial results.

4. Invest to implement the strategy.

The third and fourth steps in discovery-driven planning also reverse the order of the deliberate strategy process. The third step is to implement a plan. This is not a deliberate strategic plan, but rather a plan to test the validity of the most important assumptions. This plan needs to generate quickly, and with as little expense as possible, validating or invalidating information about the most critical assumptions. This enables innovators to revise the strategy prior to the fourth step—the decision to implement through significant investment. This can be done after the viability of various assumptions becomes more evident.

Innovators who are using the discovery-driven process frequently learn quite early that there just isn’t a reasonable set of assumptions to support a plan that will achieve the numbers the organization requires. This might imply that the idea simply can’t be shaped into a viable strategy at all. Or it might mean that the idea needs to be placed within a smaller business unit, whose values might not demand that it get prohibitively big prohibitively fast.

Managing the Mix of Emergent and Deliberate Strategies

Many processes in an organization can become so refined and effective that they simply keep chugging along with little top-management attention, freeing managers to worry about more nonstandard dimensions of the business. It is dangerous, however, to allow the strategy development process to operate on autopilot. At any given point in time, some businesses under a manager’s care may need to be managed through aggressive, deliberate strategy processes, while others need emergent processes.

Executives cannot twist an on/off valve to start and stop the flow of opportunities and problems from deliberate and emergent directions. These are always flowing in, and the CEO’s job is to manage constantly which direction should predominantly influence strategic thinking. The valve, which is the resource allocation process, can get really sticky—which is why CEOs need to keep their hands on the control constantly and consciously. When a viable strategy has emerged and it is time for execution, the CEO needs aggressively to switch to a deliberate strategy mode and stop funding emergent opportunities that might divert the company from its focus on the winning plan.

Once this has been done, however, executives often suffer amnesia and selectively remember only their success in deliberately implementing the successful strategy. They lose memory of the emergent process through which the successful strategy was discovered, and therefore forget to reset the strategy process to an emergent mode in those new organizations that are attempting to build the next growth businesses. Nearly all companies, as a result, employ one-size-fits-all deliberate strategy systems. This is a very common reason why new ventures launched by corporations and by many venture capital firms fail.[21] Managing the strategy process in ways that are appropriate to the circumstance can greatly improve the odds that a venture can succeed.

Simply seeking to have the right strategy doesn’t go deep enough. The key is to manage the process by which strategy is developed. Strategic initiatives enter the resource allocation process from two sources—deliberate and emergent. In circumstances of sustaining innovation and certain low-end disruptions, the competitive landscape is clear enough that strategy can be deliberately conceived and implemented. In the nascent stages of a new-market disruption, however, it is almost impossible to get the details of strategy right. Rather than executing a strategy, managers in this circumstance need to implement a process through which a viable strategy can emerge.

There are three points of executive leverage in strategy making. The first is to manage the cost structure, or values of the organization, so that orders of disruptive products from ideal customers can be prioritized. The second is discovery-driven planning—a disciplined process that accelerates learning what will and won’t work. The third is to vigilantly ensure that deliberate and emergent strategy processes are being followed in the appropriate circumstances for each business in the corporation. This is a challenge that few executives have mastered, and is one of the most important contributors to innovative failure in established companies.

Notes

1.   The notion that these two different processes coexist was articulated by Henry Mintzberg and James Waters in their classic paper “Of Strategies, Deliberate and Emergent,” Strategic Management Journal 6 (1985): 257. Stanford Professor Robert Burgelman is probably the preeminent scholar in this field, and many of his papers are cited in this chapter. Two important papers of his are “Intraorganizational Ecology of Strategy Making and Organizational Adaptation: Theory and Field Research,” Organization Science 2, no. 3 (August 1991): 239–262; and “Strategy as Vector and the Inertia of Coevolutionary Lock-in,” Administrative Science Quarterly 47 (2002): 325–357. Burgelman’s recent book, Strategy Is Destiny (New York: Free Press, 2002), summarizes many of his findings. Professors Rita McGrath and Ian MacMillan of the Columbia and Wharton Business Schools, respectively, have also studied these issues. We have found their article “Discovery-Driven Planning” (Harvard Business Review, July–August 1995) to be particularly helpful in understanding what processes of strategy development are appropriate in what circumstances. Finally, we have also drawn heavily on the work of Professor Amar Bhide, The Origin and Evolution of New Business (Oxford and New York: Oxford University Press, 2000).

2.   Mintzberg and Waters, “Of Strategies,” 258.

3.   This, too, is a departure from the traditional approach to thinking about the “right” way to set strategy. Typically, business scholars have adopted an “either-or” approach to the process of strategy formulation, as (in)famously demonstrated in the highly visible arm wrestle between Henry Mintzberg (“bottom-up”) and Igor Ansoff (“top-down”) in the pages of the Strategic Management Journal (vol. 11, 1990, and vol. 12, 1991).

4.   Andrew Grove, Only the Paranoid Survive (New York: Doubleday, 1996), 146.

5.   Professors Joseph L. Bower of the Harvard Business School and Robert Burgelman of Stanford are the leading scholars who have described how resources get allocated across competing alternative investments at all levels of the organization. See Joseph L. Bower, Managing the Resource Allocation Process (Boston: Harvard Business School Press, 1970); and Robert A. Burgelman and Leonard Sayles, Inside Corporate Innovation (New York: Free Press, 1986).

6.   The effect that such a filtering mechanism can have on a company’s strategy possibilities can be profound. 3M Corporation, for example, is one of the most innovative companies in modern history, in terms of its abilities to apply its core technological platforms to an array of market applications. Its insistence that all new products meet relatively high gross margin targets, however, has focused the company on a vast array of small, premium product niches and has prevented all but a few of its new products from becoming large mass-market businesses.

7.   This history has been chronicled in Robert A. Burgelman, “Fading Memories: A Process Study of Strategic Business Exit in Dynamic Environments,” Administrative Science Quarterly 29 (1994): 24–56; and in Grove, Only the Paranoid Survive.

8.   EPROMs are erasable, programmable, read-only memory circuits. Like its microprocessors, Intel’s EPROM product line also resulted from the emergent, rather than deliberate, process. See Burgelman, “Fading Memories.”

9.   There were strong reasons why senior management continued to invest in DRAMs. For example, management believed that DRAMs were the “technology driver” and that remaining competitive in DRAMs was essential in order to be competitive in other product lines.

10.  Grove, Only the Paranoid Survive.

11.  Microprocessors were a new-market disruptive technology in that they brought logic to applications where it previously had not been feasible, given the size and cost of the large printed wiring board logic circuitry that was used in the mainframe computers and minicomputers of the day. Relative to Intel’s business model, however, microprocessors were a sustaining innovation. The product helped Intel make more money in the way that it was structured to make money, and therefore resources were readily allocated to it. This illustrates a very important principle—that disruptiveness can only be expressed relative to the business model of a company and its competitors.

12.  Strong evidence for this is discussed in Amar Bhide, The Origin and Evolution of New Businesses (New York: Oxford University Press, 2000).

13.  Mintzberg and Waters, “Of Strategies,” 271.

14.  In a number of speeches and articles, Dr. John Seeley Brown has made this point—that it is very hard to predict in advance how people will end up using the disruptive technologies that change the way we live and work. We recommend all of Dr. Brown’s writings to our readers. He has influenced our own thinking in profound ways. See, for example, J. S. Brown, ed., Seeing Differently: Insights on Innovation (Boston: Harvard Business School Publishing, 1997); J. S. Brown, “Changing the Game of Corporate Research: Learning to Thrive in the Fog of Reality,” in Technological Innovation: Oversights and Foresights, eds. Raghu Garud, Praveen Rattan Nayyar, and Zur Baruch Shapira (New York: Cambridge University Press, 1997), 95–110; and J. S. Brown and Paul Duguid, The Social Life of Information (Boston: Harvard Business School Press, 2000).

15.  In the parlance of chapter 4, most of these firms were trying to cram the disruptive innovation—handheld devices—into the large, obvious mainstream market, notebook computers. True to form, this strategy proved to be very expensive, and they all failed.

16.  An important theoretical perspective called “resource dependence” asserts that it is the entities external to the organization that control what the organization can and cannot do. These entities—customers and investors—provide to the organization the resources that it needs to thrive. Managers cannot do things that are not in the interests of these external providers of resources, or they will withhold their resources and the company will die. See Jeffrey Pfeffer and Gerald R. Salancik, The External Control of Organizations: A Resource Dependence Perspective (New York: Harper & Row, 1978). The Innovator’s Dilemma devoted significant space to this issue, noting that the mechanism for managing change in the face of resource dependence is to create independent organizations that can be dependent on other providers of resources, who value the disruptive products.

17.  The distinguished sociologist Arthur Stinchcombe has written extensively on the importance of initial conditions in determining the subsequent chain of decisions and events.

18.  Clayton Christensen, “Materials Technology Corp.,” Case 9-694-075 (Boston: Harvard Business School, 1994); and Clayton Christensen, “Linking Strategy and Innovation: Materials Technology Corp.,” Case 9-696-082 (Boston: Harvard Business School, 1996).

19.  For Christensen, studying these problems as an academic has made it clear that MTC’s technology was a breakthrough sustaining innovation: The company was trying to bring better products into established markets, and the breakthrough technology entailed extensive interdependencies in development and design. MTC made many of the choices described in this book incorrectly—and as a result, although the company has survived and is profitable, the path was absolutely tortuous.

20.  See Rita Gunther McGrath and Ian C. MacMillan, “Discovery-Driven Planning,” Harvard Business Review, July–August 1995, 44–56. Professors McGrath and MacMillan have written a number of very useful things about managing the creation of new businesses, of which this article is representative. We encourage you to badger them in their offices at Columbia and Wharton, respectively, for more good ideas. In their article, they use the term “platform-based planning.” We have instead called this process “deliberate strategic planning” to be consistent with the language used elsewhere in this chapter.

21.  We are concerned that as venture capital firms have gradually become populated by less-experienced analysts who learned only about deliberate strategy in their MBA courses, they are subtly demanding more and more rigor, and data and evidence that the strategy of a business is right. They then pressure the management teams of their portfolio companies to “execute.” They only revert to an emergent mode when the initial investment has been squandered and the founding managers sacked, and there is no alternative but to seek a viable strategy through emergent processes.

CHAPTER NINE

THERE IS GOOD MONEY AND

THERE IS BAD MONEY

Does it matter whose money funds the business I want to grow? How might the expectations of the suppliers of my capital constrain the decisions I’ll be able to make? Is there something about venture capital that does a better job nurturing disruptive businesses than corporate capital? What can corporate executives do to ensure that the expectations that accompany their funding will cause managers to correctly make the decisions that will lead to success?

Getting funded is an obsession for most innovators with a great idea; as a result, most research about raising capital has focused on how to get it. For corporate entrepreneurs, writers often describe the capital budgeting process as a cumbersome bureaucracy and recommend that innovators find a well-placed “champion” in the hierarchy who can work the system of numbers and politics in order to get funding. For start-ups seeking venture capital, much advice is focused on structuring deals that do not give away too much control, while still allowing them to benefit from the networks and acumen that venture capital firms offer.[1]

Although this advice is useful, it skirts an issue that we think is potentially more important: The type of money that corporate executives provide to new-growth businesses and the type of capital that managers of those businesses accept represent fundamental early choices when launching a new-growth business. These are critical fork-in-the-road decisions, because the type and amount of money that managers accept define the investor expectations that they’ll have to meet. Those expectations then heavily influence the types of markets and channels that the venture can and cannot target. Because the process of securing funding forces many potentially disruptive ideas to get shaped instead as sustaining innovations that target large and obvious markets, the very process of getting the money to start a venture actually sends many of them on a march toward failure.

We have concluded that the best money during the nascent years of a business is patient for growth but impatient for profit. Our purpose in this chapter is to help corporate executives understand why this type of money tends to facilitate success, and to see how the other category of capital—which is impatient for growth but patient for profit—is likely to condemn innovators to a death march if it is invested at early stages. We also hope this chapter will help those who bankroll new businesses understand the forces that make their money good or bad for nurturing growth.

The most commonly used theories about good and bad money for new-growth ventures have been based on attributes rather than circumstances. Probably the most common attribute-based categorization is venture capital versus corporate capital. Other categories include public versus private capital, and friends and family versus professionally managed money. None of these categorization schemes supports a theory that can reliably predict whose money will best help new ventures to succeed. Sometimes money from each of these categories proves to be a boon, and sometimes it becomes the kiss of death.

We’ve already demonstrated why the money that funds a new-growth business needs to be patient for growth. Competing against nonconsumption and moving disruptively up-market are critical elements of a successful new-growth strategy—and yet by definition, these disruptive markets are going to be small for a time. The only way that a venture can instantly become big is for existing users of a high-volume product to be enticed to switch en masse to the new enterprise’s product. This is the province of sustaining innovation, and start-ups rarely can win a sustaining-innovation battle. Money should be impatient for growth in later-stage, deliberate-strategy circumstances, after a winning strategy for the new business has emerged.

Money needs to be impatient for profit to accelerate a disruptive venture’s initial emergent strategy process. When new ventures are expected to generate profit relatively quickly, management is forced to test as quickly as possible the assumption that customers will be happy to pay a profitable price for the product—that is, to see whether real products create enough real value for which customers will pay real money. If a venture’s management can keep returning to the corporate treasury to fund continuing losses, managers can postpone this critical test and pursue the wrong strategy for a long time. Expectations of early profit also help a venture’s managers to keep fixed costs low. A business model that can make money at low costs per unit is a crucial strategic asset in both new-market and low-end disruptive strategies, because the cost structure determines the type of customers that are and are not attractive. The lower it can start, the greater its upside. And finally, early profitability protects a growth venture from cutbacks when the corporate bottom line turns sour.[2]

In the following sections we describe in more detail how good money becomes bad. We recount this process from the point of view of corporate investors, with the hope that this telling of the story will help managers who are seeking funding to know good and bad money when they see it, and to understand the consequences of accepting each type. We hope also that venture capital investors and the entrepreneurs whom they fund will be able to see in these accounts parallel implications for their own operations. Bad money can come from venture and corporate investors—as can good money.

The Death Spiral from Inadequate Growth

Good money turns bad in a self-reinforcing downward spiral that makes it very difficult for even the best executives to do anything except preside over the company’s demise. There are five steps in this spiral. Once a company has fallen into it, it becomes almost impossible not to take the subsequent steps.

Step 1: Companies Succeed

After using an emergent strategy process to find a successful formula, a young company hits its stride with a product that helps customers get an important job done better than any competitor. With the winning strategy now clear, the executive team wrestles control of the strategy-making process away from emergent influences and deliberately focuses all investments to exploit this opportunity.[3] Anything that would divert resources from the crucial, deliberate focus on growing the core business is stomped out. Such focus is an essential requirement for success at this stage.[4] However, it means that no new-growth businesses are launched while the core business is still thriving.

This focus propels the company up its sustaining trajectory ahead of competitors who are less aggressive and less focused. Because margins at the high end are attractive, the company barely notices when it begins losing low-end, price-sensitive business in what comes to be viewed as a “commodity segment.” Exiting the lowest-margin products and replacing those revenues with higher-margin products at the top of the sustaining trajectory typically feels good, because overall gross profit margins improve.

Step 2: Companies Face a Growth Gap

Despite the company’s success, its executives soon realize that they are facing a growth gap. This is caused by the pesky tendency of Wall Street investors to incorporate expected growth into the present value of a stock—so that meeting growth expectations results only in a market-average rate of stock price appreciation. The only way that managers can cause their companies’ share prices to increase at a faster rate than the market average is to exceed the growth rate that investors have already built into the current price level. Hence, managers who seek to create shareholder value always face a growth gap—the difference between how fast they are expected to grow and how much faster they need to grow to achieve above-average returns for shareholders.[5]

As a rule, executives meet investor expectations through sustaining innovations. Investors understand the businesses in which companies presently compete and the growth potential that lies along the sustaining trajectory in those businesses—which they discount into the present value of the stock price. Sustaining innovation is therefore critical to maintaining a company’s share price.[6]

It is the creation of new disruptive businesses that allows companies to exceed investor expectations, and therefore to create unusual shareholder value. For precisely the reasons why established companies are prone to underestimate the growth potential in disruptive businesses, investors likewise have consistently underestimated (and therefore have been pleasantly surprised by) the growth potential of disruptions. Creating new disruptive businesses is the only way in the long term to continue creating shareholder value.

When a company’s revenues are denominated in millions of dollars, the amount of new business that managers need in order to close the growth gap—new revenues and profits from unknown and yet-tobe-discounted sources—also is denominated in the millions of dollars. But as a company’s revenues grow into the billions, the size threshold of new business that is required to sustain its growth rate, let alone exceed investors’ expectations, gets bigger and bigger and bigger. At some point the company will report slower growth than investors had discounted, and its stock price will take a hit as investors realize that they had overestimated the company’s growth prospects.

To get the stock price moving again, senior management announces a targeted growth rate that is significantly higher than the realistic underlying growth rate of the core businesses. This creates a growth gap even larger than the company has ever faced before—a gap that must be filled by new-growth products and businesses that the company has yet to conceive. Announcing an unrealistic growth rate is the only viable course of action. Executives who refuse to play this game will be replaced by managers who are willing to try. And companies that do not attempt to grow will see their market capitalization decline until they get acquired by companies that are eager to play.

Step 3: Good Money Becomes Impatient for Growth

When confronted with a large growth gap, the corporation’s values, or the criteria that are used to approve projects in the resource allocation process, will change. Anything that cannot promise to close the growth gap by becoming very big very fast cannot get through the resource allocation gate in the strategy process. This is where the process of creating new-growth businesses comes off the rails. When the corporation’s investment capital becomes impatient for growth, good money becomes bad money because it triggers a subsequent cascade of inevitable incorrect decisions.

Innovators who seek funding for the disruptive innovations that could ultimately fuel the company’s growth with a high probability of success now find that their trial balloons get shot down because they can’t get big enough fast enough. Managers of most disruptive businesses can’t credibly project that the business will become very big very fast, because new-market disruptions need to compete against nonconsumption and must follow an emergent strategy process. Compelling them to project big numbers forces them to declare a strategy that confidently crams the innovation into a large, existing, and obvious market whose size can be statistically substantiated. This means competing against consumption.

After senior executives have approved funding for this inflated growth project, the company’s managers cannot then back down and follow an emergent strategy that seeks to compete against nonconsumption. They are on the hook to deliver the growth that they projected. They therefore must ramp expenses according to plan.

Step 4: Executives Temporarily Tolerate Losses

It becomes clear that competing against consumption in a large and obvious market will be an expensive challenge, because if customers are to buy the product, it must perform better than the products that customers already are using. The team warns senior executives that stomaching huge losses is a prerequisite to winning the pot of gold. Determined to be visionary with the long-term interests of the company in mind, executives therefore accept the reality that the business will lose significant money for some time. There is no retreat. Executives convince themselves that investing for growth will result in growth, as if there were a linear relationship between the two—as if the more aggressively you invest to build the new business, the faster it will take off.[7]

In order to meet the budgeted timetable for rollout and ramp-up, the project managers put the cost structure in place before there are revenues—and because they must support a steep revenue ramp, these costs are substantial. But overfunding is hazardous to a new venture’s health, because heavy expense levels in turn define the sorts of customers and market segments that will and will not provide adequate revenues to cover those costs. If this happens, then customers who come from nonconsumption in emerging applications and are therefore delighted with simple products—in short, the ideal customers for a disruptive venture—inevitably become unattractive to the business. The ideal channels—those that need something to fuel their own disruptive march up-market against their competition—also become unattractive. Only the largest channels that reach the largest populations appear to be capable of bringing in enough revenue fast enough.

This completes the character transformation of the corporation’s money. It has become bad money for new-market disruption: Impatient for growth but patient for profit.

Step 5: Mounting Losses Precipitate Retrenchment

As the venture’s managers try to succeed by competing against consumption, they find all sorts of reasons why customers prefer to continue buying the products they have always used from the vendors they have always trusted. Often these reasons entail the kinds of interdependencies we discussed in chapter 5. Breakthrough sustaining innovations can rarely be hot-swapped into existing systems of use. Typically, many other unanticipated things need to change in order for customers to be able to benefit from using the new product. While revenues fall far short, expenses are on budget. Losses mount. The stock price then gets hammered again, as investors realize anew that their expectations for growth cannot be met.

A new management team gets brought in to rescue the stock price. To stanch the bleeding, the new team stops all spending except what is required to keep the core business strong. Refocusing on the core is welcome news. It is a tried-and-true formula for performance improvement, because the company’s resources, processes, and values have been honed exactly for this task. The stock price bounces in response, but as soon as the new price has fully discounted whatever growth potential exists in the core business, the new executives realize that they must invest to grow. But now the company faces an even greater growth gap, and the situation loops back to step 3, where the company needs new-growth businesses that can get really big really fast. That pressure then causes management to repeat the tragic sequence of wrong decisions again and again, until so much value has been destroyed that the company is acquired by another corporation, which itself had been unable to generate its own growth through disruption but saw in the acquisition a synergistic opportunity to wring cost out of the combination.

How to Manage the Dilemma of Investing for Growth

The dilemma of investing for growth is that the character of a firm’s money is good for growth only when the firm is growing healthily. Core businesses that are still growing provide cover for new-growth businesses. Senior executives who are bolstered by a sense that the pipeline of new sustaining innovations in established businesses will meet or exceed investors’ expectations can allow new businesses the time to follow emergent strategy processes while they compete against nonconsumption. It is when growth slows—when senior executives see that the sustaining-innovation pipeline is inadequate to meet investor expectations—that investing to grow becomes hard. The character of the firm’s money changes when new things must get very big very fast, and it won’t allow innovators to do what is needed to grow. When you’re a corporate entrepreneur and you sense this shift in the corporate context occurring, you had better watch out.

This dilemma traps nearly every company and is the causal mechanism behind the findings in Stall Points, the Corporate Strategy Board’s study that we cited in chapter 1.[8] This study showed that of the 172 companies that had spent time on Fortune’s list of the 50 largest companies between 1955 and 1995, 95 percent saw their growth stall to rates at or below the rate of GNP growth. Of the companies whose growth stalled, only 4 percent were able to successfully reignite their growth even to a rate of 1 percent above GNP growth. Once growth had stalled, the corporations’ money turned impatient for growth, which rendered it impossible to do the things required to launch successful growth businesses.

In recent years, the dilemma has become even more complex. If companies whose growth has stalled somehow find a way to launch a successful new-growth business, Wall Street analysts often complain that they cannot value the new opportunity appropriately because it is buried within a larger, slower-growing corporation. In the name of shareholder value, they demand that the corporation spin off the new-growth business to shareholders so that the full value of its exciting growth potential can be reflected in its own share price. If executives respond and spin it off, they may indeed “unlock” shareholder value. But after it has been unlocked they are left locked again in a low-growth business, facing the mandate to increase shareholder value.

In the face of this sobering evidence, chief executives—whose task it is to create shareholder value—must preserve the ability of their capital to nourish growth businesses in the ways that they need to be nourished. When executives allow the growth of core businesses to sag to lackluster levels, new-growth ventures must shoulder the whole burden of changing the growth rate of the entire corporation’s top and bottom lines. This forces the corporation to demand that the new businesses become very big very fast. Their capital as a consequence becomes poison for growth ventures. The only way to keep investment capital from spoiling is to use it when it is still good—to invest it from a context that is still healthy enough that the money can be patient for growth.

In many ways, companies whose shares are publicly held are in a self-reinforcing vise. Their dominant shareholders are pension funds. Corporations pressure the managers of their pension fund investments to deliver strong and consistent returns—because strong investment performance reduces the amount of profits that must be diverted to fund pension obligations. Investment managers therefore turn around and pressure the corporations whose shares they own to deliver consistent earnings growth that is unexpectedly accelerating. Privately held companies are not subject to many of these pressures. The expectations that accompany their capital therefore can often be more appropriate for the building of new-growth businesses.

Use Pattern Recognition, Not Financial Results,

to Signal Potential Stall Points

Because outsiders typically measure a company’s success by its financial results, executives are tempted to rely on changes in financial results as signals that they should take comfort or take action. This is folly, however, because the financial outcomes of the most recent period actually reflect the results of investments that were made years earlier to improve processes and to create new products and businesses. Financial results measure how healthy the business was, not how healthy the business is.[9] Financial results are a particularly bad tool to manage disruption, because moving up-market feels good financially, as we have noted previously.

Executives should gingerly use data of any sort when looking into the future, because reliable data are typically available only about the past and will be an accurate guide only if the future resembles the past.[10] To illustrate the limitations of data in disruptive decision making, let us recount an experience that Clayton Christensen had in a recent MBA class. He had written a paper that worried that the leading business schools’ traditional two-year MBA programs are being threatened by two disruptions. The most proximate wave, a low-end disruption, is executive evening-and-weekend MBA programs that enable working managers to earn MBA degrees in as little as a year. The most significant wave is a new-market disruption: on-the-job management training that ranges from corporate educational institutions such as Motorola University and GE’s Crotonville to training seminars in Holiday Inns.

Christensen asked for a student vote at the beginning of class: “After reading the paper, how many of you think that the leading MBA programs are being disrupted?” Three of the 102 students raised their hands. The other 99 took the position that these developments weren’t relevant to the venerable institutions’ fortunes.

Christensen then asked one of the three who was worried to explain why. “There’s a real pattern here,” he responded, and he listed six elements of the pattern. These included MBA salaries overshooting what operating companies can afford; the disruptors competing against nonconsumption; people hiring on-the-job education to get a very different job done; a shift in the basis of competition to speed, convenience, and customization; and interdependent versus modular curricula. He concluded that the pattern fit: All of the things that had happened to other companies as they were disrupted were indeed under way in management education. “That’s why I’d take this seriously,” he concluded.

Christensen then turned to those who weren’t concerned, and asked why. They tended to point to the data—the numbers of students still battling to be admitted into the leading schools, the attractive starting salaries of the graduates, the brand reputations of the programs, loyal alumni and great on-campus networking opportunities, and so on. None of the disruptive programs could come even close to competing on these dimensions.

Christensen then asked one of the most vocal defenders of the invincibility of the leading business schools, “What if you were dean of one of these schools. What data would convince you that this was something that you needed to address?”

“I’d look at the school’s market share among the CEOs of the Global 1000 corporations,” he responded. “If our market share started to drop, then I’d worry.” Christensen then asked whether that data would be a signal that he should begin addressing the problem or that the game was over. “Oh, I guess the game would be over by then,” he admitted.

“Anybody else?” Christensen pressed. “Imagine that you were dean. What data would convince you that you should take action?” Several proposed evidence that they would find convincing, but in every case, the class concluded that by the time convincing data became available, the game would be over for the high-quality two-year MBA programs.

When Christensen asked, “Should these schools view this as a threat or an opportunity?” there was another interesting reaction. There was little energy in the class regarding the growth opportunity that on-the-job management education presented for the leading business schools. We suspect that the reason for the students’ indifference is related to the threat-versus-opportunity paradox highlighted in chapter 3. At the time of this writing, the leading business schools are at the top of their game, by any measure of financial, academic, and competitive performance. They don’t need growth to feel healthy. There is nothing yet in the measures of strength and organizational vitality to suggest that the world these programs have enjoyed is likely to change.[11]

Create Policies to Invest Good Money Before It Goes Bad

When you’re driving a car, you can wait until the fuel gauge drops toward empty before you refill the tank, and once the tank is full again you can rev the car back up to full speed. It just isn’t possible to manage growth in the same way—to wait until the growth gauge begins falling toward zero before you seek a fill-up from new-growth businesses. The growth engine is a much more delicate machine that must be kept running continuously by process and policy, rather than by reacting when the growth gauge reads empty. We suggest three particular policies for keeping the growth engine running. Taken together, the policies force the organization to start early, start small, and demand early success.

- Launch new-growth businesses regularly when the core is still healthy—when it can still be patient for growth—not when financial results signal the need.

- Keep dividing business units so that as the corporation becomes increasingly large, decisions to launch growth ventures continue to be made within organizational units that can be patient for growth because they are small enough to benefit from investing in small opportunities.

- Minimize the use of profit from established businesses to subsidize losses in new-growth businesses. Be impatient for profit: There is nothing like profitability to ensure that a high-potential business can continue to garner the funding it needs, even when the corporation’s core businesses turn sour.

Start Early: Launch New-Growth Businesses Regularly While the Core Is Still Healthy

Establishing a policy that mandates the launch of new disruptive growth businesses in a predetermined rhythm is the only way that executives actually can avoid reacting after the growth engine has stalled. They must regularly launch or acquire new-growth businesses while their core businesses are still growing healthily, because when growth slows, the dramatic change in the company’s values that ensues makes growth impossible. If executives do this, and continue to shape the strategies of those businesses to be disruptive, soon a new business or two will punch into the realm of major revenue every year, ready to sustain the total corporation’s growth. If executives use their corporations’ investment capital when they can be patient for growth, the money will not spoil. It remains fresh, able to fund new-growth businesses.

Acquire New-Growth Businesses in a Predetermined Rhythm

Some executives of large, successful companies fear that even if they develop high-potential ideas and business plans for disruptive growth businesses, they just won’t be able to create the processes and values required to nurture them. They therefore are inclined to buy disruptive growth businesses, rather than to make them internally. Acquisition can be a very successful strategy if it is guided by good theory.

Many corporate acquisitions are triggered by the arrival of an investment banker with a business to sell. Decisions to acquire or not are often driven by discounted cash flow projections and an assessment of whether the business is undervalued or fixable or can yield cost savings through synergies with an existing business. Some of the theories that are used to justify these acquisitions prove to be accurate, and the acquisitions create great value. But most of them don’t.[12]

Corporate business development teams can just as readily acquire disruptive businesses. If they wait until the growth trajectories of these companies are obvious to everyone, of course, the disruptive companies may be too expensive to acquire. But if a business development team identifies candidates through the lenses of the theories in chapters 2 through 6 rather than waiting for conclusive historical evidence, then acquiring early-stage disruptive growth businesses in a regular rhythm can be a great strategy for creating and sustaining a corporation’s growth. In contrast to the acquisition of mature businesses that put a company on a higher but still flat revenue trajectory, acquiring early-stage disruptive companies can change the slope of the revenue trajectory.

One company whose fortunes have been heavily shaped by acquiring disruptive businesses has been Johnson & Johnson. For most of the 1990s, J&J was organized in three major operating groups—ethical pharmaceuticals, medical devices and diagnostics (MDD), and consumer products. Figure 9-1 shows that in 1993 the consumer and MDD groups were comparably sized, each generating just under $5 billion in sales. They subsequently grew at very different rates. The consumer business’s intrinsic growth trajectory was essentially flat, and it grew by acquiring big new revenue platforms, such as Neutrogena and Aveeno, whose growth trajectories were similarly flat. Although these acquisitions put the revenue line of the consumer group on a higher platform, they did not change the slope of the platform—and remember that it is changes in the slope of the platform, not the level of the platform, that create shareholder value at an above-average rate. Even with the acquisitions, the consumer group’s total revenues only grew at about a 4 percent annual rate over the decade.

In contrast, the MDD group of businesses grew at over 11 percent annually over the same period. This was driven by four disruptive businesses, each of which the company had acquired. J&J’s Ethicon Endo-Surgery company makes instruments for endoscopic surgery, a disruption relative to conventional invasive surgery. Its Cordis division makes instruments for angioplasty, which is disruptive relative to open-heart cardiac bypass surgery. The company’s Lifescan division makes portable blood glucose meters that enable patients with diabetes to test their own blood sugar levels instead of needing to go to hospital laboratories. And J&J’s Vistakon disposable contact lenses were disruptive relative to traditional lenses made by companies such as Bausch & Lomb. The strategies of each of these businesses fit precisely the litmus tests for new-market disruption described in chapter 2. Together, they have grown at a 43 percent annual rate since 1993, and now account for about $10 billion in revenue. The group’s overall growth rate was 11 percent because the other MDD group companies—those not on disruptive trajectories—grew in aggregate at a 3 percent annual rate. Both the consumer and MDD groups grew through acquisition. The growth rates of the two groups differed because MDD acquired businesses with disruptive potential, whereas the consumer group acquired premium businesses that were not disruptive.[13]

FIGURE 9 - 1

Johnson & Johnson Consumer Products (CP) Versus Medical Devices & Diagnostics (MDD) Revenue and Operating Profit, 1992–2001

Hewlett-Packard also sustained its growth for nearly two decades after its core lines of business matured, using a hybrid strategy for finding disruptions. Its acquisition of Apollo Computer, a leading workstation maker, was the platform upon which HP built its microprocessor-based computer businesses, which disrupted minicomputer makers such as Digital Equipment. HP’s ink-jet printer business, which today provides a significant portion of the corporation’s total profit, was a disruption that was conceived and launched internally, but within an organizationally autonomous business unit.

GE Capital, which was the primary engine of value creation for GE shareholders in the 1990s, has been a massive disruptor in the financial services industry. It has grown through a hybrid strategy of incubating disruptive businesses in some segments of the industry and acquiring others.

Start Small: Divide Business Units to Maintain Patience for Growth

The second policy imperative is to keep operating units relatively small. A decentralized company can maintain the values required to see and enthusiastically pursue disruptive innovations far longer than can a monolithic, centralized one, because the size that a new disruptive venture must reach to make a difference to a small business unit is more consistent with the revenue ramp of a new disruptive business.

Compare the perspective in a monolithic $20 billion company that needs to grow 15 percent annually with the perspective in a $20 billion corporation that is composed of twenty business units. The managers of the monolithic company will have to look at every proposed innovation from the perspective of needing to find $3 billion in new revenues beyond what was done in the prior year. The average perspective of the twenty business unit managers in the decentralized company, in contrast, is that they need to bring in $150 million of new business in the next year. In the multiple-business-unit firm there are more managers seeking disruptive growth opportunities, and more opportunities will look attractive to them.

In fact, most of the companies that appear to have transformed themselves over the past thirty years or so—companies such as Hewlett-Packard, Johnson & Johnson, and General Electric, for example—have been composed of a large number of smaller, relatively autonomous business units. These corporations have not transformed themselves by transforming the business models of their existing business units into disruptive growth businesses. The transformation was achieved by creating new disruptive business units and by shutting down or selling off mature ones that had reached the feasible end of their sustaining-technology trajectories.[14]

One reason the mortality rate of independent disk drive companies measured in The Innovator’s Dilemma was so high was that they all were single-business companies. As monolithic organizations—even relatively small ones—they had never learned how to manage nascent disruptive growth businesses alongside larger, maturing businesses. There were no processes for doing this.

In following the policy we are recommending, managers again need to be guided by theory, not by the numbers. Accountants will argue that redundant overhead expenses can be eliminated when business units are consolidated into much larger entities. Such analysts rarely assess the impact that consolidation has on the consequent demands in those mega-units that any new businesses that are launched must get very big very fast.[15]

Demand Early Success: Minimize Subsidization of New-Growth Ventures

The third policy, which is to expect new-growth businesses to generate profit relatively quickly, does two important things. First, it helps accelerate the emergent strategy process by forcing the venture to test as quickly as possible the assumption that there are customers who will pay attractive prices for the firm’s products. The fledgling business can then press on or change course based on this feedback. Second, forcing a venture to become profitable as soon as feasible helps protect it from being shut down when the core business turns sour.[16]

Honda: An Example of Forced Floundering

Not having much money proved to be a great blessing for Honda, for example, as it attacked the U.S. motorcycle market.[17] Founded in postwar Japan by motorcycle racing enthusiast Suchiro Honda, by the mid-1950s the company had become best known for its 50cc Super Cub, designed as a more powerful but easy-to-handle moped that could wind its way through crowded Japanese streets for use as a delivery vehicle.

When Honda targeted the U.S. motorcycle market in 1958, its management set a seat-of-the-pants sales target of 6,000 units a year, representing 1 percent of the U.S. market. Securing support for the U.S. venture was not merely a matter of convincing Mr. Honda. The Japanese Ministry of Finance also had to approve the release of the foreign currency needed to set up operations in America. Hard on the heels of Toyota’s failed introduction of the Toyopet car, the Ministry was loathe to give up scarce foreign exchange. Only $250,000 was released, of which only $110,000 was cash; the rest had to be in inventory.

Honda launched its U.S. operations with inventory in each of its 50cc, 125cc, 250cc, and 305cc models. The biggest bets were placed on the largest motorcycles, however, because the U.S. market was composed exclusively of large bikes. In our parlance, Honda set out to achieve a low-end disruption, hoping to pick off the most price-sensitive customers in the existing market with a low-price, full-sized motorcycle.

In 1960 Honda sold a few models of its larger machines, which promptly began to leak oil and blow their clutches. It turned out that Honda’s best engineers, whose skills had been honed through developing products that performed well in short stop-and-go bursts in congested streets, didn’t know what they didn’t know about the demands of the constant, high-speed, over-the-road travel that was common among motorcyclists in the United States. Honda had little choice but to invest its precious currency in sending the defective bikes via air freight back to Japan. The problem almost broke Honda.

With almost all of its resources devoted to supporting and promoting the problematic larger machines against well-financed and successful incumbents, the Honda personnel in the United States turned to using the 50cc Super Cubs as their own transportation. They were reliable, cheap to run, and Honda figured they couldn’t sell them anyway: There simply was no market for motorbikes that small. Right?

The exposure the Super Cub got from the daily use of the Honda management team in Los Angeles generated surprising interest from individuals and retailers—not motorcycle distributors, but sporting goods shops. Running low on cash thanks to the difficulties encountered in selling the big bikes, Honda decided to sell the Super Cubs just to stay afloat.

Little by little, continued success in selling the Super Cub and continued disappointment with the larger machines eventually redirected Honda’s efforts toward the creation of an entirely new market segment—off-road motorbikes. Priced at one-fourth the cost of a big Harley, these were sold to people without leather jackets who never would have purchased deep-throated cycles from the established U.S. or European makers. They were used for fun, not over-the-road transportation. Apparently a low-end disruption wasn’t a viable strategy because there just weren’t enough over-the-road bikers who were over-served by the brands and muscle of Harleys, Triumphs, and BMWs. What emerged was a new-market disruption, which Honda subsequently did a masterful job of deliberately exploiting.

What pushed Honda to discover this market was its lack of financial resources. This prevented its managers from tolerating significant losses and instead created an environment in which the venture’s managers had to respond to unanticipated successes. This is the essence of managing the emergent strategy process.[18]

It is important to remember that this policy—to limit expenses and seek early profit in order to accelerate the emergent strategy process—is not a one-size-fits-all mandate. In circumstances in which a viable strategy needs to emerge—such as new-market disruptions—this is a helpful policy. In low-end disruptions, the right strategy often is much clearer much earlier. As soon as the market applications become clear, and a business model that can viably and profitably address that market has emerged, aggressive investment—impatience for growth—is appropriate.

Insurance for When the Corporation Refocuses on the Core

Another reason why turning an early profit is important to a new business’s success is that funding for new ventures very often gets cut off not because the ventures are off-plan, but because the core business is sick and needs all of the corporation’s resources to recover. When the downturn occurs, new-growth ventures that cannot play a significant and immediate role in the corporation’s return to financial health simply get sacrificed, even though everybody involved knows that they are cutting off the road to the future in order to salvage the present. The need to survive trumps the need to grow.[19]

Dr. Nick Fiore, who periodically speaks to our students at the Harvard Business School, is a battle-scarred corporate innovator whose experiences illustrate these principles in action. Fiore was hired at different points in his career by the CEOs of two publicly traded companies to start new-growth businesses that would set their corporations on robust growth trajectories.[20] In both instances, the CEOs—powerful, reputable executives who were secure in their positions—had truthfully assured Fiore that the initiative to create new-growth businesses had the full and patient backing of the companies’ respective boards of directors.

Fiore cautions our students that if they ever receive such assurances, even from the most powerful and deep-pocketed executives in their companies, they had better watch out.

When you start a new growth business, there is a ticking clock behind you. The problem is that this clock ticks at a variable rate that is determined by the health of the corporate bottom line, not by whether your little venture is on plan. When the bottom line is healthy, this clock ticks patiently on. But if the bottom line gets troubled, the clock starts to tick real fast. When it suddenly strikes twelve, your new business had better be profitable enough that the corporate bottom line would look worse without you. You need to be part of the solution to the corporation’s immediate profit problems, or the guillotine blade will fall. This will happen because the board and the chairman have no option but to refocus on the core—despite what they may have told you with the best and most honest of intentions.[21]

This is why being impatient for profit is a virtuous characteristic of corporate capital. It forces new-growth ventures to ferret out the most promising disruptive opportunities quickly, and creates some (always imperfect) insurance against the venture’s getting zeroed out when the health of the larger organization becomes imperiled.

Figure 9-2 summarizes the virtues of policy-driven growth. It shows that appropriate policies, if well understood and appropriately implemented, can generate an upward spiral to replace the death spiral from inadequate growth that we described at the beginning of this chapter. When this happens, companies place themselves in a circumstance of continual growth. They invest their good money and avoid letting it go bad. This is the only way to avoid letting the growth engine stall and to sidestep the death spiral from inadequate growth.

FIGURE 9 - 2

Self-Reinforcing Spirals from Adequate and Inadequate Growth

Good Venture Capital Can Turn Bad, Too

Those working to build disruptive growth businesses within established corporations sometimes look longingly at the green grass on the other side of the corporate fence, where innovators who build independent start-ups not only can avoid the encumbrances of corporate bureaucracy but also have the freedom to fund their ideas with venture capital. The belief that venture capitalists can fund start-ups much more effectively than corporate capitalists is so pervasive, in fact, that the venture capital investment arms of many corporations refuse to participate in a deal unless an independent venture capital firm will co-invest.

We would argue, however, that the corporate-versus-venture distinction isn’t nearly as important as the willingness or inability to be patient for growth. Just like Honda, most successful venture capital firms had precious little capital to invest at the outset. The lack of money conferred on their ventures a superior capability in the emergent strategy process. When venture capitalists become burdened with lots of money, however, many of them seem to behave as corporate capitalists do in stages 3, 4, and 5 of the growth-gap spiral.

In the late 1990s venture investors plowed huge sums of capital into very early-stage companies, conferring extraordinary valuations upon them. Why would people with so much experience have done something so foolish as to invest all of that money in companies before they had products and customers? The answer is that they had to make investments of this size. Their small, early-stage investments had been so successful in the past that investors had shoveled massive amounts of capital into their new funds, expecting that they would be able to earn comparable rates of return on much larger amounts of money. The venture firms had not increased their number of partners in proportion to the increase in the assets that they were committed to invest. As a consequence, the partners simply could not be bothered with making little $2 million to $5 million early-stage investments of the very sort that had led to their initial success. Their values had changed. They had to demand that the ventures they invested in must become very big, very fast, just like their corporate counterparts.[22]

And just like their corporate counterparts, these funds then went through steps 3, 4, and 5 that were described at the beginning of this chapter. These venture funds weren’t victims of the bubble—the collapse in valuations that occurred between 2000 and 2002. In many ways they were the cause of it. They had moved up-market into the magnitudes of investment that normally are meted out in later deliberate strategy stages, but the early-stage companies in which they continued to invest were in a circumstance that needed a different type of capital and a different process of strategy.[23] The paucity of early-stage capital that continues to prevent many entrepreneurs with great disruptive growth ideas from getting funding as of the writing of this book is in many ways the result of so many venture capital funds being in their equivalent of step 5 of the death spiral—retrenching and focusing all of their money and attention to fix prior businesses.

We often have been asked whether it is a good idea or bad idea for corporations to set up corporate venture capital groups to fund the creation of new growth businesses. We answer that this is the wrong question: They have their categories wrong. Few corporate venture funds have been successful or long-lived; but the reason is not that they are “corporate” or that they are “venture.” When these funds fail to foster successful growth businesses, it is most often because they invested in sustaining rather than disruptive innovations or in modular solutions when interdependence was required. And very often, the investments fail because the corporate context from which the capital came was impatient for growth and perversely patient for profitability.

The experience and wisdom of the men and women who invest in and then oversee the building of a growth business are always important, in every situation. Beyond that, however, the context from which the capital is invested has a powerful influence on whether the start-up capital that they provide is good or bad for growth. Whether they are corporate capitalists or venture capitalists, when their investing context shifts to one that demands that their ventures become very big very fast, the probability that the venture can succeed falls markedly. And when capitalists of either sort follow sound theory—whether consciously or by intuition or happenstance—they are much more likely to succeed.

The central message of this chapter for those who invest and receive investment can be summed up in a single aphorism: Be patient for growth, not for profit. Because of the perverse dynamics of the death spiral from inadequate growth, achieving growth requires an almost Zen-like ability to pursue growth when it is not necessary. The key to finding disruptive footholds is to connect with a job in what initially will be small, nonobvious market segments—ideally, market segments characterized by nonconsumption.

Pressure for early profit keeps investors willing to invest the cash needed to fuel the growth in a venture’s asset base. Demanding early profitability is not only good discipline, it is critical to continued success. It ensures that you have truly connected with a job in markets that potential competitors are happy to ignore. As you seek out the early sustaining innovations that realize your growth potential, staying profitable requires that you stay connected with that job. This profitability ensures that you will maintain the support and enthusiasm of the board and shareholders. Internally, continued profitability earns you the continued support and enthusiasm of senior management who have staked their reputation, and the employees who have staked their careers, on your success. There is no substitute. Ventures that are allowed to defer profitability typically never get there.

Notes

1.   Many books have been written on the challenges of matching the right money with the right opportunity. Three that we have found to be useful are the following: Mark Van Osnabrugge and Robert J. Robinson, Angel Investing: Matching Startup Funds with Startup Companies: The Guide for Entrepreneurs, Individual Investors, and Venture Capitalists (San Francisco: Jossey-Bass, 2000); David Amis and Howard Stevenson, Winning Angels: The Seven Fundamentals of Early-Stage Investing (London: Financial Times Prentice Hall, 2001); and Henry Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology (Boston: Harvard Business School Press, 2003).

2.   A stream of academic research explores the nature of “first-mover advantage” (for example, M. B. Lieberman and D. B. Montgomery, “First-Mover Advantages,” Strategic Management Journal 9 [1988]: 41–58). This can manifest itself in “racing behavior” (T. R. Eisenmann, “A Note on Racing to Acquire Customers,” Harvard Business School paper, Boston, 2002) in the context of “get big fast” (GBF) strategies (T. R. Eisenmann, Internet Business Models: Text and Cases. New York: McGraw-Hill, 2001). The thinking in this field is that in some circumstances it is preferable to pursue a particular strategy very aggressively, even at the risk of pursuing a suboptimal strategy, because of the benefits of establishing a significant market position quickly. The drivers of the benefits of a GBF strategy are strong network effects in customer usage (N. Economides, “The Economics of Networks,” International Journal of Industrial Organization 14 [1996]: 673–699) or other forms of high customer switching costs. The arguments of this school of thought are well articulated and convincing, and suggest strongly that there are conditions when being patient for growth could undermine the long-run potential of a business.

Harvard Business School Professor William Sahlman, who also has studied this issue extensively, has noted in conversations with us that on occasion venture capital investors en masse conclude that a “category” is going to be “big”—even while there is no consensus which firms within that category are going to succeed. This results in a massive inflow of capital into the nascent industry, which funds more start-ups than can possibly survive, at illogical valuations. He notes that when investors and entrepreneurs are caught up in such a whirlwind, they almost have no alternative but to race to out-invest the competition. When the bubble pops, most of these investors and entrepreneurs will lose—and in fact in the aggregate, the venture capital industry loses money in these whirlwinds. The only way not to lose everything is to out-invest and out-execute the others.

The challenge is determining whether or not one is in such conditions. Compelling work by two scholars in particular suggests that network effects and switching costs that are sufficiently strong to overwhelm more prosaic determinants of success arise far less frequently than is generally asserted. See Stan J. Liebowitz and Stephen E. Margolis, The Economics of QWERTY: History, Theory, Policy, ed. Peter Lewin (New York: New York University Press, 2002.) As an example, Ohashi (“The Role of Network Externalities in the U.S. VCR Market 1976–86,” University of British Columbia working paper, available from SSRN) argues that Sony under-invested in customer acquisition in the VCR market, suggesting that it could have been successful had it “raced” harder. Economic modeling suggests that indeed, controlling for product quality, it makes sense to invest more aggressively in customer acquisition when network effects are present than when they are not.

This ceteris paribus assumption with respect to product quality, however, is somewhat heroic, for it assumes away the very reason to be patient and avoid racing. As Liebowitz and colleagues (The Economics of QWERTY) have shown, in the case of the Betamax/VHS battle, a critical element driving customer choice was recording time: Although first to market and offering better video quality, Betamax did not permit two-hour recording times—the minimum typically required to record a movie being broadcast over network television. This turned out to be a critical driver of consumer adoption. JVC’s VHS standard did enable this kind of recording, and met at least minimum acceptable standards for video fidelity. As a result, it was far better aligned with the job to be done, and this superior alignment overcame Betamax’s first-mover advantage. It is doubtful that the incremental market share that a more aggressive marketing spend by Sony might have yielded for the Betamax standard would have beaten back the superior VHS product.

With these caveats in place, it is nevertheless important to recognize the possibility of powerful payoffs to optimal racing behavior, which, in our language, would capture a particular aspect of the job to be done by a given product or service. In the case of network effects, this is captured by the notion that in order for a product to do a job well for me, it must also be doing this same job for many other people. To the extent that such competitive requirements undermine profitability where racing behavior is called for, the need to be patient for profits can be mitigated.

Because the focus of this book is to help corporate managers launch new-growth businesses consistently, we anticipate that they will be caught in GBF racing situations less often than, for example, certain venture capital investors whose strategies might be to participate in big categories.

3.   In the language of author and venture capitalist Geoffrey Moore, this is when the “tornado” happens. See Geoffrey A. Moore, Inside the Tornado (New York: HarperBusiness, 1995) and Living on the Fault Line (New York: HarperBusiness, 2000).

4.   We refer the reader again to Stanford Professor Robert Burgelman’s outstanding, book-length case study on the processes of strategy development and implementation at Intel, Strategy Is Destiny (New York: Free Press, 2002). In that account, Burgelman emphasizes how important it was that once the winning microprocessor strategy had emerged, Andy Grove and Gordon Moore very aggressively focused all of the corporation’s investments into that strategy.

5.   See Alfred Rappaport and Michael Mauboussin, Expectations Investing: Reading Stock Prices for Better Returns (Boston: Harvard Business School Press, 2001). We mentioned this point in chapter 1, but it merits repeating here. Because markets discount projected growth into the present stock price, companies that deliver what investors have foreseen and discounted will only earn market-average rates of return to shareholders. It is true that over the sweep of their histories, companies that grow at faster rates give higher returns to their shareholders than those that grow more slowly. But the particular shareholders in that history who realize above-average returns are those who find themselves holding the stock when the market realizes that its forecast of the company’s growth was too low.

6.   Cost reductions that enable a company to generate stronger cash flows than investors have expected also create shareholder value, of course. We classify these as sustaining innovations because they enable the leading companies to make more money in the way they are structured to make money. Because investors typically can expect ongoing efficiency improvements from any company, our statements here simply reflect the reality that generating shareholder value by exceeding investors’ expectations for operational efficiency typically can only raise share prices to a higher but flat plateau. Tilting the slope of the share price graph upward requires disruptive innovation.

7.   This is often true in sustaining situations—it is important to invest aggressively ahead of product launch to ensure that channels are filled and capacity exists to meet expected demand. But this is not the case in disruptive situations.

8.   See Corporate Strategy Board, Stall Points (Washington, DC: The Corporate Strategy Board, 1998).

9.   This is the theme of an important stream of work by Professor Robert Kaplan and his colleagues that has led them to advocate the use of a tool called the Balanced Scorecard, rather than financial statements, as a measure of an organization’s long-term strategic health. See, for example, Robert S. Kaplan and David P. Norton, The Strategy-Focused Organization (Boston: Harvard Business School Press, 2001).

10.  In asserting that managers ought to let theory guide their actions and not wait until convincing data have become available, we certainly hope that readers do not construe that we are advising managers to fly by the seat of their pants without numbers. Measuring in detail the operating performance of established lines of business, and making decisions based on such data, is crucial to profitable movement up the sustaining trajectory. When engaging in discovery-driven planning for a new disruptive business, the pro forma financial modeling of possible outcomes helps planners understand which assumptions are most important. Our case for theory-driven decisions is grounded in a belief that sound theory can help executives assign strategic meaning to numbers that otherwise might appear to be inconclusive, and to sort the signal from the noise as the data come in.

11.  As explored in chapter 6, we would expect that on-the-job management education, as a new-market disruption, will be a modular, nonintegrated industry where the ability to make attractive profits is unlikely to reside in the design and assembly of courses. And yet most of the business schools are attempting to compete in this market by designing and delivering custom executive education courses for large corporations. In our view, the business schools need a major dose of theory. Instead of simply selling cases and articles, a better strategy for them would be to create value-added curriculum modules that would enable tens of thousands of corporate training people to quickly slap together compelling content that helps employees learn exactly what they need to learn, when and where they need to learn it. It would also be critical to enable these trainers to teach these materials in such compelling and interesting ways that none of these on-the-job students has any desire ever to sit through a business school professor’s class again. If history were any guide, if the publishing divisions of the business schools did this, they would ultimately have a far broader impact, and be far more profitable, than their existing on-campus teaching organizations.

12.  The literature assessing the performance implications of merger and acquisition activity is enormous, and surprisingly unambiguous. Many studies have revealed that many, and perhaps even most, mergers destroy value in the acquiring firm; see, for example, Michael Porter “From Competitive Advantage to Competitive Strategy,” Harvard Business Review 65, no. 3 (1987), 43–59, and J. B. Young, “A Conclusive Investigation into the Causative Elements of Failure in Acquisitions and Mergers,” in Handbook of Mergers, Acquisitions, and Buyouts, ed. S. J. Lee and R. D. Colman (Englewood Cliffs, NJ: Prentice-Hall, 1981), 605–628. At best, the only winners appear to be the sellers; see, for example, G. A. Jarrell, J. A. Brickley, and J. M. Netter, “The Market for Corporate Control: The Empirical Evidence Since 1980,” Journal of Economic Perspectives 2 (1988): 21–48, and M. C. Jensen and R. S. Ruback, “The Market for Corporate Control: The Scientific Evidence,” Journal of Financial Economics 11 (1983): 5–50. Even if acquisition targets are “well-selected” from a conventional strategic point of view, there is significant evidence to suggest that implementation difficulties can derail the realization of any putative benefits; see, for example, Anthony B. Buono and James L. Bowditch, The Human Side of Mergers and Acquisitions: Managing Collisions Between People, Cultures, and Organizations (San Francisco: Jossey-Bass, 1988), and D. J. Ravenscraft and F. M. Scherer, “The Profitabiliy of Mergers,” International Journal of Industrial Organization 7 (1989): 101–116.

13.  We wish to emphasize that our message is not that acquisitions can solve a company’s growth problems. As we note in the text, even the successful acquisition of mature businesses does not change the growth trajectory of a corporation—it just places corporate revenues on a higher but flat plateau. In the late 1990s Cisco followed a very different acquisition strategy from the one we have described at J&J’s MDD business. Cisco’s packet-switching routers had created a powerful wave of disruption versus Lucent and Nortel, which made circuit-switching equipment for voice telephony. Most of Cisco’s acquisitions were sustaining relative to its business model and market position, in that they helped the company move up-market better and faster. They did not constitute platforms for new disruptive growth businesses.

14.  This is one of the conclusions of Professor Donald N. Sull’s recent book, Revival of the Fittest (Boston: Harvard Business School Press, 2003).

15.  We worry, in fact, that exactly this sort of reasoning has caused Hewlett-Packard’s senior executives to combine the company’s business units into a few massive organizations. The reorganization facilitated cost cutting, no doubt. But in our view, it can only exacerbate the company’s battle with its values at a time when reigniting growth is very important. At the same time—and this is why good theory is so important—“smallness” versus “bigness” is not the right categorization scheme when thinking about the benefits of these kinds of mergers or the advantages of smallness achieved by organizational separation or spin-outs. Consolidation can yield important cost savings, but as we point out in this chapter, it can corrupt the values needed to pursue potential disruptive opportunities. Smaller organizations—or big organizations that are blown apart into a series of smaller organizations—might have an easier time dealing with the challenges of embracing disruption-friendly values, but as we point out in chapters 5 and 6, organizations must also cope with the demands of architectural interdependencies, which can often require larger, more integrated organizations. In our view, it’s not so much about making trade-offs; that is, accepting inevitable compromises, as it is about recognizing the circumstances one is in and adopting the appropriate solution to the most pressing problem.

16.  We have often been asked how much money a venture should be allowed to lose, and how much time it should take until profits should be expected. There can, of course, be no rigid rules, because the fixed-cost intensity of each business will vary. Mobile telephony was a disruptive growth business that entailed large fixed-cost investments, and hence more significant losses than would many others. In making these recommendations, we simply hope to offer to executives the guiding principle that losing less is more.

17.  Honda’s experience is summarized on pages 153 to 156 of The Innovator’s Dilemma. That account has been condensed from a case study by Evelyn Tatum Christensen and Richard Tanner Pascale, “Honda (B),” Case 9-384-050 (Boston: Harvard Business School, 1983).

18.  Searching for unanticipated successes, rather than seeking to correct deviations from a plan, is one of the most important principles that Peter F. Drucker taught in his classic book Innovation and Entrepreneurship (New York: Harper & Row, 1985).

19.  This tendency to refocus immediately on the core when things get bad, even at the expense of the long-term solutions to the problem that caused the core to get sick, is known among behavioral psychologists as “threat rigidity.” See chapter 4 for more on this.

20.  Fiore’s experiences are detailed in Clayton M. Christensen and Tara Donovan, “Nick Fiore: Healer or Hitman? (A)” Case 9-601-062 (Boston: Harvard Business School, 2000).

21.  Presentation by Dr. Nick Fiore to Harvard Business School students, 26 February 2003.

22.  Professor William Sahlman of the Harvard Business School has studied the phenomenon of venture capital “bubble” investing for two decades. He observes that when many venture investors conclude that they need to have strong investment positions in a “category,” investors develop “capital market myopia”—a view that does not consider the impact that other firms’ investments will have on the probability that their individual investment will succeed. When massive amounts of available venture capital are focused on an industry where investors perceive steep scale economies and strong network effects, the funds and the companies in which they invest are compelled to engage in “racing” behavior. Firms seek to dramatically outspend the competition, because it is a company’s relative spending rate and its relative execution capability that drive success. Sahlman notes that once a race like this has started, venture funds have no option but to engage in that behavior if they want to participate in that investment category. Sahlman has observed that between the mid-1980s and the early 1990s—the period following the first of these investment bubbles—the returns to venture capital were zero. We have seen a similar decline in venture returns in the years following the dot-com and telecommunications investment bubble in the late 1990s.

23.  Big-ticket investing of money that is impatient for profit and growth is very appropriate in later stages of step 1 of the spiral, when the company needs to focus deliberately on a winning strategy that has become clear. Interestingly, Bain Capital, which has been one of the most successful investment firms over the past decade, made this transition very effectively. Bain started out making rather small venture investments. It provided the start-up funding for Staples, the office superstore, for example. It was so successful with its first fund that investors simply poured as much money into subsequent funds as Bain would let them. This meant that the firm’s values changed, and it could no longer prioritize small investments. In contrast to the behavior of the venture funds in the bubble, however, Bain stopped making early-stage investments as it got bigger. It became a later-stage private equity investor, and continued to perform magnificently. In the parlance of the model of theory building we presented in the introduction, as these investment funds grow, they find themselves in different circumstances. The strategies that led to success in one circumstance can lead to disaster in another. Bain Capital changed strategy as its circumstances changed. Many of the venture capital funds did not.

CHAPTER TEN

THE ROLE OF SENIOR EXECUTIVES

IN LEADING NEW GROWTH

How should senior executives allocate their time and energy across all of the businesses and initiatives that demand their attention? How should their oversight of sustaining innovations differ from their mode of management in disruptive situations? Is the creation of new growth businesses inherently an idiosyncratic, ad hoc undertaking, or might it be possible to create a repeatable process that successfully generates wave after wave of disruptive growth?

The senior executives of a company that seeks repeatedly to create new waves of disruptive growth have three jobs. The first is a near-term assignment: personally to stand astride the interface between disruptive growth businesses and the mainstream businesses to determine through judgment which of the corporation’s resources and processes should be imposed on the new business, and which should not. The second is a longer-term responsibility: to shepherd the creation of a process that we call a “disruptive growth engine,” which capably and repeatedly launches successful growth businesses. The third responsibility is perpetual: to sense when the circumstances are changing, and to keep teaching others to recognize these signals. Because the effectiveness of any strategy is contingent on the circumstance, senior executives need to look to the horizon (which often is at the low end of the market or in nonconsumption) for evidence that the basis of competition is changing, and then initiate projects and acquisitions to ensure that the corporation responds to the changing circumstance as an opportunity for growth and not as a threat to be defended against.[1]

Standing Astride the Sustaining–Disruptive Interface

Because processes begin to coalesce within a group that is confronted repeatedly with doing the same task, the engine that propels accomplishment in well-run companies gradually becomes less dependent on the capabilities of individual people, and becomes instead embedded in processes, as we described in chapter 7. After successful companies find their initial disruptive foothold, the task that recurs repeatedly is sustaining innovation, not disruption. Well-oiled, capable processes for successfully addressing sustaining opportunities have therefore coalesced in most successful companies. We know of no companies, however, that as yet have built processes for dealing with disruption—because launching disruptive businesses has not yet been a recurrent task.[2]

At present, therefore, the ability to create growth businesses through disruption resides in companies’ resources, and for reasons we’ll explore in this chapter, the most critical of these resources is the CEO or another very senior executive with comparable influence. We say “at present” because it does not always need to be so. If a company tackles the task of creating disruptive growth again and again, the ability to create successful disruptive growth businesses can become ensconced in a process as well—a process that this chapter calls a disruptive growth engine. Although we know of no company that has yet developed such an engine, we believe it is possible and propose four critical steps that senior executives can take to do so. A company that succeeds in creating a disruptive growth engine will place itself on a predictable path to profitable growth, consistently skating to the money-making opportunities of the future.

A Theory of Senior Executive Involvement

Until processes that can competently manage disruptive innovation have coalesced, the personal oversight of a senior executive is one of the most crucial resources that disruptive businesses need to reach success. One of the most discouraging dimensions of senior executives’ lives is the refrain by writers of many management books that they must be involved in order to fix whatever problem the book is about. Corporate ethics, shareholder value, business and product development, acquisitions, corporate citizenship, corporate culture, management development, and process improvement programs are all squeaky wheels that demand executive grease. Senior managers must pay close attention to managing the top line, the bottom line, and all the lines in between. Confronting such cacophony, executives need a good circumstance-based theory of executive involvement—a way to discern the circumstances in which their direct involvement actually is critical to success, and the circumstances in which they should delegate.

One of the most common theories of when senior executives should get involved in a decision and when they should not is based on an attribute of the decision, namely, the magnitude of money at stake. The theory asserts that lower-level managers can make small decisions or ones that involve minor changes, but that only senior executives have sufficient wisdom to make the big calls correctly. Almost every company enacts this theory through policies that give decision-making approval for smaller investments to lower-level executives and elevate big-ticket items for the scrutiny of the senior-most team.

Sometimes this theory accurately predicts the quality of decisions, but sometimes it doesn’t.[3] One problem with systems that reflect the send-the-big-decisions-to-the-big-people theory is that the data are in the divisions: There is an asymmetry of information along the vertical dimension of every organization. Reporting systems can indeed elevate the information that senior managers ask for, but the problem is that sometimes senior management doesn’t know what questions need to be asked.[4] Senior people in large organizations therefore typically can’t know much beyond what the managers below them choose to divulge. Worse, when midlevel managers have been through a few senior management decision cycles, they learn what the numbers must look like in order for senior management to approve proposals, and they learn what information ought not be presented to senior management because it might “confuse” them. Hence, a good portion of middle managers’ effort is spent winnowing the full amount of information into the particular subset that is required to win senior approval for projects that middle managers already have decided are important. Initiatives that don’t make sense to the middle managers rarely get packaged for the senior people’s consideration. Senior executives envision themselves as making the big decisions, but in fact they most often do not.

Because the senior-most executives in reality cannot participate when and where these decisions actually get made, decision-making processes that work well without senior attention are critical to success in circumstances of sustaining innovation. In the sustaining circumstance when capable processes exist—even in many big-ticket decisions—senior executives typically cannot improve the quality of the decision because of the asymmetry of information that exists.[5] This is when the gospel of “driving decisions down to the lowest level” and of “making the lowest level competent” is in fact good news.

Another version of the “size theory” states that large businesses require more active senior management involvement, whereas lower-level managers can cope with the demands of smaller organizational units. Fewer people and fewer assets, the belief goes, mean that less managerial skill is required. Sometimes this is the case, but sometimes it isn’t. Potentially disruptive businesses are small. But with their ill-defined strategies and demanding profitability targets, make-or-break decisions arise with alarming frequency, and such businesses have no processes for making these decisions correctly. In contrast, larger businesses in successful organizations typically have established customers with clearly articulated needs, and have finely honed resource allocation and production processes to serve those needs. The decision-making requirements of these organizations typically transcend the involvement of any given individual, and are typically—and appropriately—met by the orderly functioning of established processes.

Both of these theories get the categories wrong. A better, circumstance-based theory can help managers decide which decisions ought to be made at which levels. For those decisions that the mainstream processes and values were designed to make effectively (sustaining innovations, primarily), less senior executive involvement is needed. It is when senior executives sense that the processes and values of the mainstream organization were not designed to handle important decisions in an organization (which is typically the case in disruptive circumstances) that a senior executive needs to participate. Because the plans for disruptive businesses by definition need to be shaped by different criteria, and because the values of the mainstream business have evolved to weed out the very sorts of ideas that have disruptive potential, disruptive innovation is the category of circumstance in which powerful senior managers must personally be involved. Sustaining innovation is the circumstance in which delegation works effectively. A senior-most executive is the only one who can endorse the use of corporate processes when they are appropriate, and break the grip of those processes and decision rules when they are not.

Another reason why senior executives need to stand astride the interface between sustaining innovations and disruption is that managers of the mainstream business units need to be fully informed of the technological and business model innovations that are developed in the new disruptive business, because disruption often is where the most important improvements for the future of the entire corporation are incubated. If senior managers have properly schooled themselves in sound theories of strategy and management, they can coach the managers of important growth businesses on both the sustaining and disruptive sides of the interface to take the actions that are appropriate to each particular circumstance. Ensuring that deliberate and emergent strategy processes are employed in the right circumstances and that managers are hired whose experience is a match for the problems at hand are ongoing challenges on both sides of the divide.

The Importance of Meddling

One of our favorite teaching case studies about Nypro, Inc., illustrates when and why a senior-most executive needs personally to shepherd the creation of disruptive growth businesses.[6] Nypro is an extraordinarily successful custom injection molder of precision plastic parts. Much of the company’s innovative culture and financial success can be attributed to its owner and recently retired CEO, Gordon Lankton.

Nypro’s customers are global manufacturers of health care and microelectronic products. They require worldwide sourcing of plastic components whose complexity and dimensional tolerances demand the most sophisticated molding process capabilities. Nypro seeks to offer a uniform capability from any of its twenty-eight plants—whether in North America, Puerto Rico, Ireland, Mexico, Singapore, or China—under the mantra “Nypro is your local source . . . worldwide.” If Nypro sought to achieve this uniform capability by barring any plant from deviating from standard, company-wide procedures, it would kill innovation at the very level where it best occurs—the plants. Most of the important process innovations that help Nypro to make ever-better products are developed by engineering teams working to solve customer problems in far-flung individual plants, out of the eyesight and earshot of senior management. This situation is a stereotype of the dilemma that confronts most companies in one way or another: Companies need uniform capability but flexibility to change, and senior managers typically can’t even see what innovations are being considered and developed, let alone decide which ones merit investment.

In response to this challenge, Lankton created a system to surface the most important and successful innovations so that he could evaluate which improvements should be adopted by all plants, thereby enabling Nypro to offer a uniform but ever-improving global manufacturing capability. A key element of this system was a monthly financial reporting system that rank-ordered the plants’ performance along a number of important dimensions that Lankton judged to be the drivers of the company’s near-term financial performance and its long-term strategic success. These reports showed, for all to see, which plants were doing better and which needed to improve. Plant managers were evaluated on the measures of plant performance in these reports, and their reputation vis-à-vis each other was affected by the relative ranking of their plants. The system, in other words, provided ample motivation for managers to search for any innovation that would improve their performance and relative ranking.

Lankton created interlocking boards of directors for each plant, so that each board was composed of managers and engineers from several other plants. This kept information flowing among plants. The company augmented this with several global meetings each year for plant managers and engineers, in which they exchanged news about what process and product innovations each had implemented, and what the results had been. In time, there emerged a culture in which managers were intensely competitive to get ahead of each other, and yet were cooperative in sharing the process innovations each had developed.

Lankton watched carefully whenever one plant’s successful innovation began to be adopted by managers at other plants. This was a signal to him that the idea had merit. After several respected managers had copied another plant’s process innovation, Lankton had enough evidence to decide that the innovation should be implemented, and would then mandate that it become a standard practice worldwide. This method tested and validated sustaining innovations first, and then accelerated the implementation of those that had proved to be important.

By the mid-1990s it had become clear to Lankton that Nypro’s world was changing. His engineers could mold millions of complicated plastic parts per month to extremely tight tolerances. Even though there were a few applications that needed even greater precision, Nypro’s capabilities were more than good enough for the majority of the market, and other competitors had improved to compete favorably against Nypro’s cost and quality. Lankton sensed, in other words, that the basis of competition in his markets was beginning to change. He noted that the type of business that had led to Nypro’s success—very high-volume, high-precision molding—wasn’t growing nearly as rapidly as the demand for a wider variety of parts with smaller volumes. Some of these parts demanded high precision as well, but it was the ability to respond quickly with that precision that loomed as the key to success.

Sensing a change of circumstance and crafting a response is a role that only the CEO can fill. Lankton sensed this shift masterfully—but when he left it to the organization to implement the required change, it couldn’t. Here’s what happened.

To prepare Nypro for this shift in the basis of competition, Lankton commissioned a project at the company’s headquarters to develop a machine called “Novaplast” that could be set up in less than a minute.[7] The technology’s unique mold design enabled economical, low-pressure molding of a variety of precision parts in short run lengths.

To be consistent with the company’s practice, Lankton chose not to compel all plants to begin using the new machine. He made sure that all managers understood how the technology worked and what its strategic purpose was. He then made the machine available for plant managers to lease, hoping that this approach would minimize barriers to experimentation and adoption—and, as usual, to see whether those whose judgment he had learned to respect cast their votes for the technology. Six of Nypro’s plants leased the machine, but within four months four of those had returned their machines to headquarters. The reason: They had concluded that there just wasn’t any business that could be run economically on the machines. The two plants that kept the Novaplast machine had a long-standing order from a major manufacturer of AA-sized batteries to provide a thin-walled plastic liner that fit inside the metal casing of these batteries. The plants molded millions of these liners every month, and for unique reasons it turned out that the Novaplast machine could crank these parts out with higher yields and lower costs than could Nypro’s conventional high-volume, high-pressure machines.

The end of the teaching case pictures Lankton puzzling about this outcome. Why was it that he had seen so clearly the growing demand for rapid delivery of a widening variety of short-run precision parts, and yet his plants hadn’t been able to land any of that business for their Novaplast machines? Was it a victory or a failure that Novaplast’s ultimate success came from a very high-volume, standard, high-precision part?

The answer is that this is exactly the result we would expect from the processes and values that supported the existing business model. Nypro’s finely honed innovation engine shaped Novaplast as a sustaining technology, because this is exactly what the system was designed to do—to shape every investment to help the company make money in the way it was structured to make money. An organization cannot disrupt itself. It can only implement technologies in ways that sustain its profit or business model. The consequence for Nypro of allowing the standard process to remain in control is that (so far) the company has missed the chance to create a major new disruptive growth business.

To succeed at this disruption, Lankton would have needed to create a sales organization whose compensation structure energized salespeople to pursue this high-variety, low-volume-per-part business. He would have needed to build an operating organization whose processes were tuned to this work and to create measures of performance that were different from those that drove success in the core business. None of the processes of the core business could make these judgment calls correctly. This is why the CEO needs to stand astride the interface between mainstream business units and new disruptive growth businesses.[8]

Can Any Executive Lead Disruptive Growth?

Because the processes and values of the mainstream business by their very nature are geared to manage sustaining innovation, there is no alternative at the outset to the CEO or someone with comparable power assuming oversight responsibility for disruptive growth. Can only certain of these executives exercise this oversight effectively, or is it possible for any senior person to succeed? We noted in chapter 2 that most of the companies whose stock we wish we had owned in the past fifty years took root with a disruptive strategy. A few—but not many—of these companies subsequently caught or created other waves of disruption that kept the parent corporation growing at a robust pace for a time.

One of our most sobering realizations is that within the population of companies that successfully caught a subsequent wave of disruption and stayed atop their industries, the vast majority were still being run by the company’s founder at the time they tackled the disruption. Only a few companies that were run by professional (non-founder) managers have succeeded in creating new disruptive growth businesses. Table 10-1, although not exhaustive, illustrates what we have sensed.[9]

Table 10-1

Founder-Led Companies That Launched New Disruptive

Businesses

Company

Disruptive Growth Business

CEO/Founder

Bank One

Monoline credit cards (purchase of First USA)

John McCoy [a]

Charles Schwab

Online brokerage

Charles Schwab [b]

Dayton Hudson

Discount retailing (Target Stores)

The Dayton family

Hewlett-Packard

Microprocessor-based computers

David Packard

IBM

Minicomputers

Thomas Watson Jr. [c]

Intel

Low-end microprocessors (Celeron chip)

Andrew Grove

Intuit

QuickBooks small business accounting software; TurboTax personal tax assistance software; putting Quicken money management software online

Scott Cook

Microsoft

Internet-based computing; SQL and Access database software; Great Plains business solutions software

Bill Gates

Oracle

Centrally served software (applications service provider)

Larry Ellison

Quantum

3.5-inch disk drives

Dave Brown/ Steve Berkley

Sony

Transistor-based consumer electronics

Akio Morita

Teradyne

Integrated circuit testers based on CMOS processors

Alex d’Arbeloff

The Gap

Old Navy low-price-point casual clothing

Mickey Wexler

Wal-Mart

Sam’s Club

Sam Walton

a McCoy was not the founder, but was the primary architect of the acquisition strategy that drove Bank One to its prominence.

b The company’s co-CEO, David Pottruck, strongly assisted Charles Schwab in this effort.

c Again, Watson was the son of the founder, but was the primary driver of IBM’s success in mainframe digital computing.

It’s worth noting that these founder-led organizations were also essentially single-industry firms (that is, relatively undiversified when they faced the disruption), which, as chapter 9 noted, can make creating a new disruptive business even harder. We suspect that founders have an advantage in tackling disruption because they not only wield the requisite political clout but also have the self-confidence to override established processes in the interests of pursuing disruptive opportunities. Professional managers, on the other hand, often seem to find it difficult to push in disruptive directions that seem counterintuitive to most other people in the organization.

Table 10-2 shows, however, that there are some exceptions to the principle that only founders seem able to drive disruption. We know of five major companies that were run by professional managers at the time they launched successful disruptions. Of these, Johnson & Johnson, Procter & Gamble, and General Electric are all icons of diversification. IBM and Hewlett-Packard were relatively undiversified when their founders launched those companies’ first successful disruptive businesses; hence, they are listed in table 10-1. Later, when professional managers were running the show, these two firms launched or acquired additional disruptive businesses, but did so when the firms had become much more broadly diversified.

We suspect that because the professional managers of the companies listed in table 10-2 undertook their new disruptions in the context of a diversified, multibusiness corporation, it was easier for them to succeed. Although their capabilities as managerial resources were undoubtedly important in these actions, there were precedents and processes for creating or acquiring new businesses and managing them appropriately that assisted the professional CEOs in creating disruptive growth.[10]

Table 10-2

Professionally Managed Companies That Launched New

Disruptive Businesses

Company

Disruptive Growth Business

General Electric

GE Capital

Hewlett-Packard

Ink-jet printers

IBM

Personal computers

Johnson & Johnson

Glucose monitors, disposable contact lenses, equipment for endoscopic surgery and angioplasty

Procter & Gamble

Dryel home dry cleaning, inexpensive power toothbrushes, Crest brand tooth-whitening strips

Creating a Growth Engine: Embedding the

Ability to Disrupt in a Process

Launching a single successful disruptive business can create years of profitable growth for a company, as GE Capital did for its parent during the years when Jack Welch was at its helm. Disruption blessed Johnson & Johnson’s medical devices and diagnostics group, as we noted in chapter 9. Hewlett-Packard’s disruptive ink-jet printer is now the profit driver of the entire corporation. If it feels so good to disrupt once, why not do it again and again?

If a company launches a sequence of growth businesses, if its leaders repeatedly use the litmus tests for shaping ideas or acquiring nascent disruptions, and if they repeatedly use sound theories to make the other key business-building decisions well, we believe that a predictable, repeatable process for identifying, shaping, and launching successful growth can coalesce. A company that embeds the ability to do this in a process would own a valuable growth engine.

Such an engine would have four critical components, as depicted in figure 10-1. First, it needs to operate rhythmically and by policy, rather than in response to financial developments. This would ensure that new businesses get launched while the corporation is still growing robustly, and that new businesses would not be pressured to grow too big too fast. Second, the CEO or another senior executive who has the confidence and the authority to lead from the top when necessary must lead the effort. This is particularly important in the early years, when success still depends more on resources than on processes. Third, it would establish a small corporate-level group—movers and shapers—whose members develop a practiced, repeatable system for shaping ideas into disruptive business plans that are funded and launched. Fourth, it would include a system for training and retraining people throughout the organization to identify disruptive opportunities and to take them to the movers and shapers.[11]

Step 1: Start Before You Need To

The best time to invest for growth is, as we noted in chapter 9, when the company is growing. To build what will be a respectable growth business in five years, you have to start now. And you need to add new units to the portfolio of growth businesses in a rhythm that is dictated by the growth needs of the corporation five years hence. Companies that build while they are growing can shield their nascent high-potential businesses from Wall Street pressure, giving each one the time it needs to iterate toward a viable strategy and take off. Keep Wal-Mart in mind. In 2002 it generated nearly $220 billion in revenues. But from the time it opened its first discount store, it took a dozen years in today’s dollars until it passed the billion-dollar revenue threshold. Disruptions need a longer runway before they take off to huge volumes, so you have to start them before your annual report suggests that you’re leveling off.

FIGURE 10 - 1

The Disruptive Growth Engine

The best way to do this is to budget for it—not just an amount of capital set aside to invest in disruptive growth, but a budgeted number of new businesses that need to be launched each year.[12] Remember that we are not advocating establishment of a corporate venture capital fund whose structure is predicated on the belief that one cannot predict which investments will and will not pan out. We believe that the process of creating successful growth is capable of much greater predictability if managers use sound theories to shape ideas properly. The needed number of new businesses can therefore be launched each year with not just the hope but the expectation that they will succeed.

Step 2: Appoint a Senior Executive to Shepherd Ideas into the

Appropriate Shaping and Resource Allocation Processes

Creating a successful disruptive growth engine requires the careful coaching of the CEO or another senior manager who has the confidence and the power to exempt a venture from an established corporate process, to declare when different processes need to be created, and to ensure that the criteria being used in resource allocation are appropriate to the circumstance of each venture and the needs of the corporation. This executive must be well versed in disruptive innovation theory and should be able to separate ideas with disruptive potential from those that are best deployed on an established sustaining trajectory. The primary job of this manager is to make sure that ideas that are best used to create disruptive footholds are fed into a process that maximizes their chances of success.

As noted earlier, this executive role will change over time. At the outset it will entail monitoring and coaching individual decisions in individual growth businesses. Ultimately it will consist of monitoring the processes for collecting, shaping, and funding ideas; continued coaching and training; and monitoring the winds of changing circumstances in the company’s environment.

Step 3: Create a Team and a Process for Shaping Ideas

We asserted in chapter 1 that lack of interesting growth ideas is rarely a problem in companies that are in danger of losing their growth. The problem is that ideas often lose their disruptive growth potential in the shaping process that they go through in order to get funded. The challenge for this third component of the growth engine is therefore to create a separately operating process through which ideas can be shaped into high-potential disruptions.

Processes like this can be diagrammed at a high level on paper, but they become tangible only as a stable group of people successfully solves similar problems again and again. Senior management should therefore create a core team at the corporate level that is responsible for collecting disruptive innovation ideas and molding them into propositions that fit the litmus tests outlined in chapters 2 through 6 of this book. The members of this team have to understand these theories at a deep level, stick together, and apply them frequently. This experience will help them sense which ideas can and cannot be shaped into exciting disruptions, and to distinguish these from ideas whose potential is sustaining and should be funneled through the shaping and resource allocation process of an established business.

Despite the guidance that we hope this book provides, many dimensions of the strategy that ultimately will prove successful for growth ventures cannot be known at the outset. This means that this core shaping group cannot use the company’s standard strategic planning and budgeting processes when launching disruptive businesses. chapter 8 detailed an equally rigorous discovery-driven planning process for use in disruptive circumstances.[13] Members of the core group could coach each new venture’s management on these techniques for strategic planning and budgeting. We are confident that as they do this, their intuition and understanding of the ideas will improve far beyond what we now know and can convey in a limited book such as this.

Step 4: Train the Troops to Identify Disruptive Ideas

The fourth component of a well-functioning disruptive growth engine is the training of the troops, particularly sales, marketing, and engineering employees, because they are best positioned to encounter interesting growth ideas and to scout for small acquisitions with disruptive potential. They should be trained in the language of sustaining and disruptive innovation and absorb a deep understanding of the litmus tests, because it’s crucial that they come to know what kinds of ideas they should channel into the sustaining processes of established business units, what kinds should be directed into disruptive channels, and what ideas have the potential for neither. This is truly a situation in which “making the lowest level competent” will pay off in spades. Capturing ideas for new-growth businesses from people in direct contact with markets and technologies can be far more productive than relying on analyst-laden corporate strategy or business development departments—as long as the troops have the intuition to do the first-level screening and shaping themselves.

Senior executives need to play four roles in managing innovation. First, they must actively coordinate action and decisions when no processes exist to do the coordination. Second, they must break the grip of established processes when a team is confronted with new tasks that require new patterns of communication, coordination and decision making. Third, when recurrent activities and decisions emerge in an organization, executives must create processes to reliably guide and coordinate the work of employees involved. And fourth, because recurrent cultivation of new disruptive growth businesses entails the building and maintenance of multiple simultaneous processes and business models within the corporation, senior executives need to stand astride the interfaces of those organizations—to ensure that useful learning from the new growth businesses flows back into the mainstream, and to ensure that the right resources, processes, and values are always being applied in the right situation.

When an established company first undertakes the creation of a new disruptive growth business, senior executives need to play the first and second roles. Disruption is a new task, and appropriate processes will not exist to handle much of the required coordination and decision making related to the initial projects. Certain of the mainstream organization’s processes need to be pre-empted or broken because they will not facilitate the work that the disruptive team needs to do. To create a growth engine that sustains the corporation’s growth for an extended period, senior executives need to play the third role masterfully, because launching new disruptive businesses needs to become a rhythmic, recurrent task. This entails repeated training for the employees involved, so that they can instinctively identify potentially disruptive ideas and shape them into business plans that will lead to success. The fourth task, which is to stand astride the boundary between disruptive and mainstream businesses, actively monitoring the appropriate flow of resources, processes, and values from the mainstream business into the new one and back again, is the ongoing essence of managing a perpetually growing corporation.

Notes

1.   In this chapter we’ll use the term senior executives to refer to men and women in positions such as chairman, vice chairman, CEO, and president. Senior executives who can perform well the leadership roles we describe in this chapter need to have the power and the confidence to declare that certain corporate rules will and will not be followed, given the circumstances that a growth venture is in.

2.   As mentioned in chapter 8, Sony is the only example we know of that was a serial disruptor, having created a string of a dozen disruptive new-growth businesses between 1950 and 1982. Hewlett-Packard did it at least twice, when it launched microprocessor-based computers and ink-jet printers. More recently, our sense is that Intuit has been actively seeking to create new-growth businesses through disruptive means. But for the vast majority of companies, disruption has been at most a one-time event.

3.   We again refer readers to Robert Burgelman’s Strategy is Destiny, an extraordinarily insightful chronicle of how the ex ante and ex post quality of high-impact strategic decisions was distributed across the layers of management at Intel Corporation.

4.   Practices such as “management by walking around,” which was popularized by Thomas Peters and Robert Waterman in their management classic, In Search of Excellence (New York: Warner Books, 1982) are targeted at this challenge. The hope is that by walking around, senior managers might get a sense for what the important questions are, so that they can ask for the right information needed to make good decisions.

5.   Some would assert that senior-most executives still need to be involved in decisions about major expenditures because of their fiduciary responsibility not to spend more than the company has to spend. Even decisions like these, however, can be made through capable processes.

6.   This account summarizes a teaching case by Clayton Christensen and Rebecca Voorheis, “Managing Innovation at Nypro, Inc. (A),” Case 9-696-061 (Boston: Harvard Business School, 1995) and “Managing Innovation at Nypro, Inc. (B),” Case 9-697-057 (Boston: Harvard Business School, 1996).

7.   In our account of this history, we are using the language of our models. Lankton did not know of our research and therefore was guided by his own intuition, not our advice. His intuition was stunningly consistent with how we would have viewed the situation, however.

8.   Interestingly, despite the fact that the company has missed (so far) the opportunity to catch this wave of disruptive growth in high-variety, low-volume-per-model manufacturing, the company has done very well. It has followed the pattern outlined in chapter 6 of eating its way forward from the back end, integrating forward from component manufacturing into technologically interdependent subassemblies and even final product assembly. It (very profitably) tripled its revenues to nearly $1 billion between 1997 and 2002—a period in which several major competitors failed.

9.   The nature of these companies’ disruptions is analyzed in figure 2-4 and the appendix to chapter 2.

10.  Something else worth noting is that we have not studied the relative success rates of founder-led versus agent-led disruptive initiatives. All we can say on the basis of the analysis we have done so far is that the relative incidence of successful founder-led disruption is higher than for agent-led disruption. Just who has a better batting average we can’t yet say. For unfortunate but understandable reasons, data on failed business creation efforts are hard to come by.

11.  Clayton M. Christensen, Mark Johnson, and Darrell K. Rigby, “Foundations for Growth: How to Identify and Build Disruptive New Businesses,” MIT Sloan Management Review, Spring 2002, 22–31. We are grateful to Darrell Rigby for pointing out the possibility that an engine of growth might be created.

12.  A good tool to use in this budgeting process is called aggregate project planning. Steven C. Wheelwright and Kim B. Clark described this method in their book Revolutionizing Product Development (New York: Free Press, 1992). Their concept has been extended to the corporate resource allocation process in a course note by Clayton Christensen, “Using Aggregate Project Planning to Link Strategy, Innovation, and the Resource Allocation Process,” Note 9-301-041 (Boston: Harvard Business School, 2000).

13.  See Rita G. McGrath and Ian MacMillan, “Discovery-Driven Planning,” Harvard Business Review, July–August 1995, 44–54.

EPILOGUE

PASSING THE BATON

Managers rarely can exercise unbridled free agency. Powerful and predictable forces act upon them. These forces include the need to move up-market to maintain profit margins; the need to satisfy existing customers; the forces of commoditization and decommoditization; the mandate to grow from an ever-larger revenue base; and the fact that the processes and values that define the capabilities of one business model simultaneously define disabilities for other business models. These forces do not Calvinistically predestine managers to take a particular sequence of actions, but they strongly influence the types of choices that managers do and do not confront, and they shape the attractiveness of the different choices relative to the managers’ situations. In this book we have tried to show that when companies face the wrong side of these forces, they lead to predictable growth pathologies. But when companies harness these same forces, they can put wind in their sails. The predictability of these forces makes it possible to capture them and turn them to your advantage in seeking, exploiting, and sustaining new growth opportunities.

If this were a book for mariners, it would be filled with discussions of sailing with or against tides and currents, and how to set sail in order to take advantage of the prevailing winds. Such a book would make it easy to see that where and when you start, relative to the direction that those forces want to carry you, can make a huge difference in how easy it is to get where you want to go.

Similarly, we hope that this book makes it easy to see that where you start, relative to the direction of the competitive, technological, and profit-seeking forces acting upon you, can make a huge difference in the probability that you will succeed. This view simplifies the challenge of creating new-growth businesses. It means that when you start a new business you do not need to envision accurately the details of your strategy or predict foresightedly how technology will evolve. Rather, you need to focus primarily on getting the initial conditions right. If you start from a good place, then the choices that lead to success will look like the right choices. In order to exploit these choices, you need to create a business model whose resources, processes, and values can harness these forces so that they propel you toward success rather than blow you away.

Accurately researched and written histories would reveal that many founders of successful companies—including many of the disruptive companies arrayed in figure 2-4—had the wrong strategy in mind when they started. But due to some combination of intuition and luck, they put themselves in a situation in which they were confronted with attractive choices. Doing what made sense led to a next set of attractive choices, and so on. The initial conditions under which they started and the business structures that they created allowed them to catch the trends and forces that subsequently propelled them toward successful growth.

The structures and initial conditions that are required for successful growth are enumerated in the chapters of this book. They include starting with a cost structure in which attractive profits can be earned at low price points and which can then be carried up-market; being in a disruptive position relative to competitors so that they are motivated to flee rather than fight; starting with a set of customers who had been nonconsumers so that they are pleased with modest products; targeting a job that customers are trying to get done; skating to where the money will be, not to where it was; assigning managers who have taken the right courses in the school of experience and putting them to work within processes and organizational values that are attuned to what needs to be done; having the flexibility to respond as a viable strategy emerges; and starting with capital that can be patient for growth. If you start in conditions such as these, you do not need to see deeply into the future. Attractive choices that lead to success will present themselves. It is when you start in conditions that are opposite to these that attractive options may not appear, and the right choices will be difficult to make.

We also believe that the overwhelming odds that corporations will stop growing and be unable to restart growth can be deferred much longer than has so far seemed possible. Executives who understand how these forces create growth pathologies can counteract them better when the tide of these forces begins to shift from opportunity toward threat.

A principal refrain in this book is that blindly copying the best practices of successful companies without the guidance of circumstance-contingent theory is akin to fabricating feathered wings and flapping hard. Replicating their success is not about duplicating their attributes; it’s about understanding how to generate lift. Good theories are circumstance-based. They describe how managers need to employ different strategies as circumstances change in order to achieve the needed results. The use of one-size-fits-all processes and values historically has made the creation of growth torturous. One of the most valuable contributions you can make in the growth-creation process, therefore, is to keep watching for changes in circumstances. If you do this, you can understand when and why changes need to be made long before the evidence is clear to those whose vision is not clarified by theory.

Who? Me? Use Theory?

While The Innovator’s Dilemma sought to build a theory, our purpose in writing The Innovator’s Solution has been to teach you as a manager how to use theory. If your reaction has been that theory is too complicated—that you’re an action-driven manager and are not a theory-driven person—think again. Reread the passage in Molière’s The Bourgeois Gentleman in which Monsieur Jourdain finds the writing of poetry intimidating. Remember how delighted he is to learn that he can use the other option, which is to compose his love letter in prose, because he has unwittingly been speaking prose all his life? While you may not have known it, you have been using theory for the whole of your managerial life. Whenever you have taken an action or made a plan, it was predicated upon a theory in your mind that your actions would lead to the envisioned outcome. So using theory to create successful growth businesses needn’t feel strange. You are—though perhaps unwittingly—a practiced theoretician.

We conclude with a summary of our advice to executives who seek solutions to the innovator’s dilemma.

1. Never say yes to a strategy that targets customers and markets that look attractive to an established competitor. Keep sending the team back to the drawing board until they’ve identified a disruptive foothold that established competitors will be happy to ignore or be relieved to walk away from. If you create asymmetries of motivation, your competitors will help you win. Though you may not have done this before, it should feel good if you are accustomed to bloody fights of sustaining innovation against motivated competitors.

2. If your team targets customers who already are using pretty good products, send them back to see if they can find a way to compete against nonconsumption. When your customers are delighted to have a simple, inexpensive product because their alternative is to have nothing, all the techniques for pleasing customers that you learned in Marketing 101 will be easy and inexpensive. This also should spell welcome relief compared with the alternative, which is the massive investment typically required to make disruptive technologies preferable to the established products that customers already are comfortable using.

3. If there are no nonconsumers available, ask your team to explore whether a low-end disruption is feasible. They must devise a business model that can make attractive profits at the discount prices required to capture customers at the low end of the market, who can’t use all the functionality for which they currently must pay. If this isn’t possible either, then don’t invest—or at least, don’t invest with the expectation that this will create a significant growth business.

4. If the project leader ever uses the phrase, “If we can just get the customer to . . . ,” terminate the conversation. Send the team back to find a way to help customers get done more conveniently and inexpensively what they already are trying to get done. Competing wishfully against customers’ manifest priorities has shortened the tenure-in-job of some pretty good people.

5. If the team’s product or marketing plan focuses on market segments whose boundaries mirror your organization’s boundaries, or if the targeted market is segmented along the lines for which data are readily available (by product type, price point, or demographic category), send the team back. Ask them to segment the market in ways that mirror the jobs that customers are trying to get done. Remind the team that you still have no alternative but to hire a one-size-fits-all milkshake for at least two different jobs that arise regularly in your life. The milkshake business is stalled because quick-service restaurants keep improving the shake’s attributes rather than doing each job better and better—which would grow the category by helping shakes to steal share from the real competition.

6. If your team’s product improvement road map assumes that the basis of competition won’t change—that the types of improvements that merited good margins in the past will continue to merit those margins in the future—look at the low end. Often you can see there the opportunity to change the basis of competition.

7. If your disruptive product or service is not yet good enough and your team seems enthralled with industry standards and the attendant outsourcing and partnering deals, raise a big red flag. If you prematurely pursue modularity and open standards, or if you keep a proprietary architecture closed while the basis of competition changes, you’ll struggle to succeed. Remember what made Wayne Gretzky so good. It is better to develop competencies where the money will be made in the future than to cling tenaciously to those skills that made you successful in the past.

8. If your team assures you that you’ll succeed because a new venture fits your company’s core competence, tell them that you can’t deal in fuzzy concepts. Ask for answers to three specific questions:
• Do we have the resources to succeed?

• Will our processes—the ways we have learned to work together to succeed in our established businesses—facilitate what needs to be done to succeed in the new business?

• Will our values, or the criteria that folks here use to prioritize one thing over another, enable the critical people to give the needed priority to this initiative when compared with the other initiatives that compete for their time, money, and talent?

Use the answers to these questions to choose the right organizational structure and the right organizational home for this project.

9. Ask these three questions about each of the entities that constitute the venture’s channels as well. It’s not just you. The channel companies’ processes and values—their methods and motivations—can cause your venture to come off the rails or even stall before leaving the station.

10. Unfortunately, you may need to distrust the managers whom you have learned to trust. The managers in your organization who have most consistently delivered results in the past may be the least skilled at delivering success in new-growth businesses. In choosing the management team for your new venture, don’t look at the attributes that describe the people you might tap to lead a new-growth venture, or at the magnitude of their past responsibilities. Search their résumés for the problems they have grappled with, and compare them to the problems that you know this venture must confront.

11. Be sure that in the beginning years after a venture is launched, the development team remains convinced that they aren’t sure what the best strategy is, in terms of products, customers, and applications. Insist that the team give you a plan to accelerate the emergence of a viable strategy. Call a halt to decisive plans to implement any strategy before there is evidence that it works.

12. Be impatient for profit. When someone tells you as a senior executive that you must endure years of substantial losses before a new business will become huge and profitable, this flags a plan to cram a disruptive technology into a sustaining role in an established market. Some investments in sustaining technologies with extensive interdependencies across the value chain can indeed require years of massive investment. Let established competitors tackle those. In disruptive circumstances, patiently enduring years of losses generally allows a team to pursue the wrong strategy for a long time.

13. Keep your company growing so that you can be patient for growth. Disruption—and competing against nonconsumption in particular—requires a longer runway before a steep ascent is possible. If corporate growth slows and you then force the new businesses to attempt too fast a takeoff, you will force the management to make other fatal mistakes. The other side to this mandate is important as well. If you’re slated to lead a new venture and corporate management says you need to become very big very fast, what you really are hearing is that management is going to make you cram your disruptive technology into an established market. When you sense this, don’t take the job. You are very likely to fail.

Note that there is no mandate on this list that executives be brilliant strategists in order to supervise the building of new disruptive growth businesses. That’s the whole point of this book. The disruptive companies listed in chapter 2 didn’t succeed because their founders foresaw the entire strategy. If it depended on the brilliance of the founders and the correctness of their strategies, then success would be unpredictable indeed.

Many successful companies have disrupted once. A few, including IBM, Intel, Microsoft, Hewlett-Packard, Johnson & Johnson, Kodak, Cisco, and Intuit, have disrupted several times. Sony did it repeatedly between 1955 and 1982, before its engine of disruption got shut down. To our knowledge, no company has been able to build an engine of disruptive growth and keep it running and running. That reality has made this a risky book for us to write: Few business books say “Do this; no one’s ever done it before.” But there is little choice. Creating and sustaining successful growth has, historically speaking, vexed some great managers.

Given the existence of principles but no precedent, we have simply done our best to suggest how successful growth can be created and sustained. We have offered an integrated body of theory derived from the successes and the failures of hundreds of different companies, each of which has illuminated a different aspect of the innovator’s dilemma. And so we now pass the baton to you, in the hope that you will find our efforts to be a valuable foundation upon which to build your own innovator’s solution.

ABOUT THE AUTHORS

Clayton M. Christensen is the Robert and Jane Cizik Professor of Business Administration at Harvard Business School. He holds a joint appointment in the Technology and Operations Management and General Management faculty groups. His research and teaching interests center on the management of technological innovation and finding new markets for new technologies. Prior to joining the HBS faculty, Christensen served as Chairman and President of CPS Corporation, a materials science firm that he cofounded with several MIT professors. He was also a White House Fellow in the administration of President Ronald Reagan and was a member of the staff of the Boston Consulting Group.

Christensen’s publications have received numerous academic awards, including the 1997 Global Business Book Award for his book The Innovator’s Dilemma. He serves as a consultant to the management teams of many of the world’s leading corporations and serves as a member of The Church of Jesus Christ of Latter-day Saints in as many ways as he can.

Christensen holds a B.A. in economics from Brigham Young University, an M.Phil. in economics from Oxford University, where he studied as a Rhodes Scholar, and an MBA and DBA from Harvard Business School. He and his wife, Christine, are the parents of five children.

Michael E. Raynor is a Director in Deloitte Research, the thought leadership arm of Deloitte, the global professional services firm. He has worked with some of the firm’s most significant clients across many industries, including telecommunications, media, computer hardware and software, financial services, energy, and health care. He is also a professor at the Richard Ivey School of Business in London, Canada, where he teaches in the MBA and Executive Education programs. He focuses on innovation and corporate strategy in his research, writing, and client work, exploring the challenges of sustaining success through innovation and ways to cope with and exploit the constantly shifting demands of uncertain competitive environments.

Raynor is the author or coauthor of many book chapters and articles in a wide range of publications, including the Harvard Business Review, Long-Range Planning, the Journal of Applied Corporate Finance, the Journal of Business Strategy, and Engineering Economist.

Raynor holds an undergraduate degree in philosophy from Harvard University, where he was a John Harvard Scholar. He received his MBA from Ivey, where he received the Nelson M. Davis Memorial Scholarship for excellence, and his DBA from Harvard Business School, where he received the George S. Dively Memorial Award for research excellence. He is Annabel’s husband, and they are Charlotte’s parents.

The Innovator's DNA:

Mastering the Five Skills of Disruptive Innovators

Jeff Dyer

Hal Gregersen

Clayton M. Christensen

Harvard Business Review Press

Boston, Massachusetts

Copyright

Copyright 2011 Jeff Dyer, Hal Gregersen, and Clayton M. Christensen

All rights reserved

No part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording, or otherwise), without the prior permission of the publisher. Requests for permission should be directed to permissions@hbsp.harvard.edu, or mailed to Permissions, Harvard Business School Publishing, 60 Harvard Way, Boston, Massachusetts 02163.

First eBook Edition: July 2011

ISBN: 978-1-4221-3481-8

Contents

Copyright

Introduction

Part One

Disruptive Innovation Starts with You

1

The DNA of Disruptive Innovators

2

Discovery Skill #1

Associating

3

Discovery Skill #2

Questioning

4

Discovery Skill #3

Observing

5

Discovery Skill #4

Networking

6

Discovery Skill #5

Experimenting

Part Two

The DNA of Disruptive Organizations and Teams

7

The DNA of the World’s Most Innovative Companies

8

Putting the Innovator’s DNA into Practice

People

9

Putting the Innovator’s DNA into Practice

Processes

10

Putting the Innovator’s DNA into Practice

Philosophies

Conclusion: Act Different, Think Different, Make a Difference

Appendix A: Sample of Innovators Interviewed

Appendix B: The Innovator’s DNA Research Methods

Appendix C: Developing Discovery Skills

Notes

Acknowledgments

About the Authors

Introduction

INNOVATION. It’s the lifeblood of our global economy and a strategic priority for virtually every CEO around the world. In fact, a recent IBM poll of fifteen hundred CEOs identified creativity as the number-one “leadership competency” of the future.[1] The power of innovative ideas to revolutionize industries and generate wealth is evident from history: Apple iPod outplays Sony Walkman, Starbucks’s beans and atmosphere drown traditional coffee shops, Skype uses a strategy of “free” to beat AT&T and British Telecom, eBay crushes classified ads, and Southwest Airlines flies under the radar of American and Delta. In every case, the creative ideas of innovative entrepreneurs produced powerful competitive advantages and tremendous wealth for the pioneering company. Of course, the retrospective $1 million question is, how did they do it? And perhaps the prospective $10 million question is, how could I do it?

The Innovator’s DNA tackles these fundamental questions—and more. The genesis of this book centered on the question that we posed years ago to “disruptive technologies” guru and coauthor Clayton Christensen: where do disruptive business models come from? Christensen’s best-selling books, The Innovator’s Dilemma and The Innovator’s Solution, conveyed important insight into the characteristics of disruptive technologies, business models, and companies. The Innovator’s DNA emerged from an eight-year collaborative study in which we sought a richer understanding of disruptive innovators—who they are and the innovative companies they create. Our project’s primary purpose was to uncover the origins of innovative—and often disruptive—business ideas. So we interviewed nearly a hundred inventors of revolutionary products and services, as well as founders and CEOs of game-changing companies built on innovative business ideas. These were people such as eBay’s Pierre Omidyar, Amazon’s Jeff Bezos, Research In Motion’s Mike Lazaridis, and Salesforce.com’s Marc Benioff. For a full list of innovators we interviewed whom we quote in this book, see appendix A; virtually all of the innovators we quote, with the exception of Steve Jobs (Apple), Richard Branson (Virgin), and Howard Schultz (Starbucks)—who have written autobiographies or have given numerous interviews about innovation—are from our interviews.

We also studied CEOs who ignited innovation in existing companies, such as Procter & Gamble’s A. G. Lafley, eBay’s Meg Whitman, and Bain & Company’s Orit Gadiesh. Some entrepreneurs’ companies that we studied were successful and well known; some were not (for example, Movie Mouth, Cow-Pie Clocks, Terra Nova BioSystems). But all offered a surprising and unique value proposition relative to incumbents. For example, each offered new or different features, pricing, convenience, or customizability compared to their competition. Our goal was less to investigate the companies’ strategies than it was to dig into the thinking of the innovators themselves. We wanted to understand as much about these people as possible, including the moment (when and how) they came up with the creative ideas that launched new products or businesses. We asked them to tell us about the most valuable and novel business idea that they had generated during their business careers, and to tell us where those ideas came from. Their stories were provocative and insightful, and surprisingly similar.

As we reflected on the interviews, consistent patterns of action emerged. Innovative entrepreneurs and executives behaved similarly when discovering breakthrough ideas. Five primary discovery skills—skills that compose what we call the innovator’s DNA—surfaced from our conversations. We found that innovators “Think Different,” to use a well-known Apple slogan. Their minds excel at linking together ideas that aren’t obviously related to produce original ideas (we call this cognitive skill “associational thinking” or “associating”). But to think different, innovators had to “act different.” All were questioners, frequently asking questions that punctured the status quo. Some observed the world with intensity beyond the ordinary. Others networked with the most diverse people on the face of the earth. Still others placed experimentation at the center of their innovative activity. When engaged in consistently, these actions—questioning, observing, networking, and experimenting—triggered associational thinking to deliver new businesses, products, services, and/or processes. Most of us think creativity is an entirely cognitive skill; it all happens in the brain. A critical insight from our research is that one’s ability to generate innovative ideas is not merely a function of the mind, but also a function of behaviors. This is good news for us all because it means that if we change our behaviors, we can improve our creative impact.

After surfacing these patterns of action for famous innovative entrepreneurs and executives, we turned our research lens to the less famous but equally capable innovators around the world. We built a survey based on our interviews that taps into the discovery skills of innovative leaders: associating, questioning, observing, networking, and experimenting. To date, we have collected self-reported and 360-degree data on these discovery skills from over five hundred innovators and over five thousand executives in more than seventy-five countries (for information about our assessments for individuals and companies, go to our Web site: http://www.InnovatorsDNA.com). We found the same pattern for famous as well as less famous leaders. Innovators were simply much more likely to question, observe, network, and experiment compared to typical executives. We published the results of our research in Strategic Entrepreneurship Journal, the top academic journal focused on entrepreneurs (details of our study are reported in appendix B).[2] We also published our findings in an article titled “The Innovator’s DNA,” which was the runner-up for the 2009 Harvard Business Review McKinsey Award.

Who Is Classified as an Innovator?

Perhaps one of the most surprising findings from the past thirty years of entrepreneurship research is that entrepreneurs do not differ significantly (on personality traits or psychometric measures) from typical business executives.[a] We usually meet this finding with skepticism, since most of us intuitively believe that entrepreneurs are somehow different from other executives. Note that our research focused on innovators and, in particular, innovative entrepreneurs rather than entrepreneurs. Here’s why. Innovative entrepreneurs start companies that offer unique value to the market. When someone opens a dry cleaner or a mortgage business, or even a set of Volkswagen dealerships or McDonald’s franchises, researchers put them all in the same category of entrepreneur as the founders of eBay (Pierre Omidyar) and Amazon (Jeff Bezos). This creates a categorization problem when trying to find out whether innovative entrepreneurs differ from typical executives. The fact is that most entrepreneurs launch ventures based on strategies that are not unique and certainly not disruptive. Among entrepreneurs as a whole, only 10 percent to 15 percent qualify as “innovative entrepreneurs” of the kind we’re discussing.

Our study includes four types of innovators: (1) start-up entrepreneurs (as we described earlier), (2) corporate entrepreneurs (those who launch an innovative venture from within the corporation), (3) product innovators (those who invent a new product), and (4) process innovators (those who launch a breakthrough process). Our process inventor category includes folks like A. G. Lafley, who initiated a set of innovative processes at Procter & Gamble that sparked numerous new product innovations. In all cases, the original idea for the new business, product, or process must be the innovator’s idea. While these different types of innovators have numerous similarities, they also have some differences, as we will show in the chapters that follow.

a. This is evident in the conclusions of numerous studies on entrepreneurs, including the following:

“After a great deal of research, it is now often concluded that most of the psychological differences between entrepreneurs and managers in large organizations are small or non-existent” (L. W. Busenitz and J. B. Barney, “Differences Between Entrepreneurs and Managers in Large Organizations,” Journal of Business Venturing 12, 1997).

“There appears to be no discoverable pattern of personality characteristics that distinguish between successful entrepreneurs and non-entrepreneurs” (W. Guth, “Director’s Corner: Research in Entrepreneurship,” The Entrepreneurship Forum, winter 1991).

“Most of the attempts to distinguish between entrepreneurs and small business owners or managers have discovered no differentiating features” (R. H. Brockhaus and P. S. Horwitz, “The Psychology of the Entrepreneur” in The Art and Science of Entrepreneurship, 1986).

We then turned to see what we could learn about the DNA of innovative organizations and teams. We started by looking at BusinessWeek’s annual ranking of innovative companies. This ranking, based on votes from executives, identified companies with a reputation for being innovative. A quick look at the BusinessWeek lists from 2005 to 2009 shows Apple as number one and Google, number two. OK, intuitively that sounds right. But we felt that the BusinessWeek methodology (executives voting on which companies are innovative) produces a list that is largely a popularity contest based on past performance. Indeed, do General Electric, Sony, Toyota, and BMW deserve to be on the list of most innovative companies today? Or are they simply there because they have been successful in the past?

To answer these questions, we developed our own list of innovative companies based on current innovation prowess (and expectations of future innovations). How did we do this? We thought the best way was to see whether investors—voting with their wallets—could give us insight into which companies they thought most likely to produce future innovations: new products, services, or markets. We teamed up with HOLT (a division of Credit Suisse Boston that had done a similar analysis for The Innovator’s Solution) to develop a methodology for determining what percentage of a firm’s market value could be attributed to its existing businesses (products, services, markets). If the firm’s market value was higher than the cash flows that could be attributed to its existing businesses, then the company would have a growth and innovation premium (for our purposes, we’ll just call it an innovation premium). An innovation premium is the proportion of a company’s market value that cannot be accounted for from cash flows of its current products or businesses in its current markets. It is the premium the market gives these companies because investors expect them to come up with new products or markets—and they expect the companies to be able to generate high profits from them (see chapter 7 for details on how the premium is calculated). It is a premium that every executive, and every company, would like to have.

We unveil our list of the most innovative companies—ranked by innovation premium—in chapter 7. Not surprisingly, we found that our top twenty-five companies include some on the BusinessWeek list—such as Apple, Google, Amazon, and Procter & Gamble. These companies averaged at least a 35 percent innovation premium over the past five years. But we also learned that companies such as Salesforce.com (software), Intuitive Surgical (health care equipment), Hindustan Lever (household products), Alstom (electrical equipment), and Monsanto (chemicals) have similar premiums. And as we studied these firms in greater detail, we learned that they are also very innovative. As we examined both our list and the BusinessWeek list of innovative companies, we saw several patterns.

First, we noticed that compared to typical companies they were far more likely to be led by an innovative founder or a leader who scored extremely high on the five discovery skills that compose the innovator’s DNA (their average discovery quotient was in the eighty-eighth percentile, which meant they scored higher than 88 percent of people taking our discovery skills assessment). Innovative companies are almost always led by innovative leaders. Let us say this again: Innovative companies are almost always led by innovative leaders. The bottom line: if you want innovation, you need creativity skills within the top management team of your company. We saw how innovative founders often imprinted their organizations with their behaviors. For example, Jeff Bezos personally excels at experimenting, so he helped create institutionalized processes within Amazon to push others to experiment. Similarly, Intuit’s Scott Cook shines at observing, so he pushes observation at Intuit. Perhaps not surprisingly, we discovered that the DNA of innovative organizations mirrored the DNA of innovative individuals. In other words, innovative people systematically engage in questioning, observing, networking, and experimenting behaviors to spark new ideas. Similarly, innovative organizations systematically develop processes that encourage questioning, observing, networking, and experimenting by employees. Our chapters on building the innovator’s DNA in your organization and team describe how you too can actively encourage and support others’ innovation efforts.

Why the Ideas in This Book Should Matter to You

Over the last decade, many books on the topic of innovation and creativity have been written. Some books focus on disruptive innovation, such as Clayton Christensen’s The Innovator’s Dilemma and The Innovator’s Solution. Others, such as Ten Rules for Strategic Innovators (Govindarajan and Trimble), Game Changer (A. G. Lafley and Ram Charan), and The Entrepreneurial Mindset (Rita McGrath and Ian MacMillan), examine how organizations, and organizational leaders, encourage and support innovation. Others look more specifically at product development and innovation processes within and across firms, such as How Breakthroughs Happen (Andrew Hargadon) and The Sources of Innovation (Eric von Hippel). Other books on innovation look at the roles individuals play in the innovation process within companies, such as The Ten Faces of Innovation and The Art of Innovation (both by Tom Kelley of IDEO), or A Whole New Mind (Daniel Pink). Finally, other books like Creativity in Context (Teresa Amabile) and Creativity (Mihaly Csikszentmihalyi) examine individual creativity and, more specifically, theories and research about creativity. Our book differs from the others in that it is focused squarely on individual creativity in the business context and is based on our study of a large sample of business innovators, including some big-name innovators such as Jeff Bezos (Amazon.com), Pierre Omidyar (eBay), Michael Lazaridis (Research In Motion/BlackBerry), Michael Dell (Dell), Marc Benioff (Salesforce.com), Niklas Zennström (Skype), Scott Cook (Intuit), Peter Thiel (PayPal), David Neeleman (JetBlue and Azul airlines), and so on. The premise of our book is that we explain how these big names got their “big ideas” and describe a process that readers can emulate. We describe in detail five skills that anyone can master to improve his or her own ability to be an innovative thinker.

A Disclaimer . . . Sort of

We think it is important to remember three significant points as you read The Innovator’s DNA. First, engaging in the discovery skills doesn’t ensure financial success. Throughout the book, we tell stories of people who were manifestly successful at innovating. We focus on the success stories because we are all more naturally drawn to success than failure. However, in our sample of five hundred innovators, only two-thirds launched ventures or products that met our criteria of success. Many were not successful. The innovators developed the right skills—questioning, observing, networking, and experimenting—that produced an innovative venture or product, but the result was not always a financial success. The point is that the discovery skills we describe are necessary, indeed critical, for generating innovative business ideas, but they don’t guarantee success.

Second, failure (in a financial sense) often results from not being vigilant in engaging all discovery skills. The more financially successful innovators in our sample demonstrated a higher discovery quotient (scored higher on the discovery skills) than less successful ones. If you fail with an innovation, it may be that you didn’t ask all the right questions, make all of the necessary observations, talk to a large enough group of diverse people, or run the right experiments. Of course, it is also possible that you did all these things but an even newer technology emerged or some other bright innovator came up with an even better idea. Or maybe you just didn’t excel at executing on the idea or have the resources to compete with an established firm that imitated your invention. Many factors can prevent a new product or business idea from gaining traction in the market. But the better you are at asking the right questions, engaging in the right observations, eliciting ideas and feedback through networking with the right people, and running experiments, the less likely you are to fail.

Third, we spotlight different innovators and innovative companies to illustrate key ideas or principles, but not to set them up as perfect examples of how to be innovative. Some innovators we studied were “serial innovators,” as they had developed quite a number of innovations over time and appeared motivated to continue doing so. Others benefitted by being in the right place at the right time to make a critical observation, talk to a key person with particularly useful knowledge, or serendipitously learn from an experiment. They made an important discovery once, but they might not necessarily be capable or motivated (perhaps due to financial success) to continue generating innovative ideas. In similar fashion, we have found that innovative companies can quickly lose their innovative prowess, while others can quickly improve it. In chapter 8, we show that Apple’s innovation prowess (as measured by its innovation premium) dropped dramatically after Jobs left in 1984, but then jumped up dramatically a few years after he returned to lead the company. Procter & Gamble was a solid innovation performer before Lafley took the helm, but increased its innovation premium by 30 percent under his leadership. The point is that people and companies can change and may not always live up to our lofty expectations.

Ask yourself: Am I good at generating innovative business ideas? Do I know how to find innovative people for my organization? Do I know how to train people to be more creative and innovative? Some executives respond to the last question by encouraging employees to think outside the box. But thinking outside the box is precisely what employees (and executives) are trying to figure out. We’ve even watched some executives answer the “How do I think outside the box?” question with another equally generic (and unhelpful) answer, “Be creative.”

If you find yourself struggling with actionable answers to these questions, read on to gain a solid grasp of five skills that can make all the difference when facing your next innovation challenge. All leaders have problems and opportunities sitting in front of them for which they have no solution. It might be a new process. It might be a new product or service. It might be a new business model for an old business. In every case, the skills you build by putting into practice the innovator’s DNA may literally save your job, your organization, and perhaps your community. Indeed, we’ve found that if you want to rise to the highest levels of your organization—to a business unit manager, president, or CEO position—you need strong discovery skills. And if you want to lead a truly innovative organization, you likely will need to excel at those skills.

We hope that The Innovator’s DNA will encourage you to reclaim some of your youthful curiosity. Staying curious keeps us engaged and our organizations alive.[3] Imagine how competitive your company will be ten years from now without innovators if its people didn’t find any new ways to improve its processes, products, or services. Clearly, your company would not survive. Innovators constitute the core of any company’s, or even country’s, ability to compete.

How The Innovator’s DNA Unfolds

Like a pocket-sized map in a foreign place, our book serves as a guide to your innovation journey. The first part (chapters 1 through 6) explains why the innovator’s DNA matters and how the pieces can combine into a personalized approach to innovation. We put flesh onto the “think different” slogan by explaining in detail the habits and techniques that allow innovators to think differently. The chapters in part one give rich detail about how to master the specific skills that are key to generating novel ideas—associating, questioning, observing, networking, and experimenting.

The second part (chapters 7 through 10) amplifies the building blocks of innovation by showing how the discovery skills of innovators described in part one operate in organizations and teams. Chapter 7 introduces our ranking of the world’s most innovative companies based on each company’s innovation premium, a market value premium based on investors’ expectations of future innovations. We also provide a framework for seeing how the innovator’s DNA works in the world’s most innovative teams and organizations. We call this the “3P” framework because it contains the discovery-driven building blocks of highly innovative organizations or teams—people, processes, and philosophies. Chapter 8 focuses on building-block number one, people, and describes how innovative organizations achieve maximum impact by actively recruiting, encouraging, and rewarding people who display strong discovery skills—and blending innovators effectively with folks who have strong execution skills. Chapter 9 shows innovative team and company processes that mirror the five discovery skills of disruptive innovators. In other words, innovative companies rely on processes to encourage—even require—their people to engage in questioning, observing, networking, experimenting, and associating. Chapter 10 focuses on the fundamental philosophies that guide behavior within innovative teams and organizations. These philosophies not only guide disruptive innovators but also get imprinted in the organization, giving people the courage to innovate. Finally, for those interested in building discovery skills in yourself, your team, and even the next generation (young people you know), in appendix C we guide you through a process of taking your innovator’s DNA to the next level.

We’re delighted that you’re starting or continuing your own innovation journey. We have watched scores of individuals take the ideas in this book to heart and who describe how they have dramatically improved their innovation skills as a result. They continually confirm that the journey is worth taking. We think you’ll feel the same way once you’ve finished reading about and mastering the skills of a disruptive innovator.

PART ONE

Disruptive Innovation Starts with You

1

The DNA of Disruptive Innovators

“I want to put a ding in the universe.”

—Steve Jobs, founder and CEO, Apple Inc.

DO I KNOW HOW to generate innovative, even disruptive, business ideas? Do I know how to find creative people or how to train people to think outside the box? These questions stump most senior executives, who know that the ability to innovate is the “secret sauce” of business success. Unfortunately, most of us know very little about what makes one person more creative than another. Perhaps for this reason, we stand in awe of visionary entrepreneurs such as Apple’s Steve Jobs, Amazon’s Jeff Bezos, and eBay’s Pierre Omidyar, and innovative executives like P&G’s A. G. Lafley, Bain & Company’s Orit Gadiesh, and eBay’s Meg Whitman. How do these people come up with groundbreaking new ideas? If it were possible to discover the inner workings of the masters’ minds, what could the rest of us learn about how innovation really happens?

Ideas for Innovation

Consider the case of Jobs, who was recently ranked the world’s number-one best-performing CEO in a study published by Harvard Business Review.[1] You may recall Apple’s famous “Think Different” ad campaign, whose slogan says it all. The campaign featured innovators from different fields, including Albert Einstein, Picasso, Richard Branson, and John Lennon, but Jobs’s face might easily have been featured among the others. After all, everyone knows that Jobs is an innovative guy, that he knows how to think different. But the question is, just how does he do it? Indeed, how does any innovator think different?

The common answer is that the ability to think creatively is genetic. Most of us believe that some people, like Jobs, are simply born with creative genes, while others are not. Innovators are supposedly right brained, meaning that they are genetically endowed with creative abilities. The rest of us are left brained—logical, linear thinkers, with little or no ability to think creatively.

If you believe this, we’re going to tell you that you are largely wrong. At least within the realm of business innovation, virtually everyone has some capacity for creativity and innovative thinking. Even you. So using the example of Jobs, let’s explore this ability to think different. How did Jobs come up with some of his innovative ideas in the past? And what does his journey tell us?

Innovative Idea #1: Personal Computers Should Be Quiet and Small

One of the key innovations in the Apple II, the computer that launched Apple, came from Jobs’s decision that it should be quiet. His conviction resulted, in part, from all the time he’d spent studying Zen and meditating.[2] He found the noise of a computer fan distracting. So Jobs was determined that the Apple II would have no fan, which was a fairly radical notion at the time. Nobody else had questioned the need for a fan because all computers required a fan to prevent overheating. Getting rid of the fan wouldn’t be possible without a different type of power supply that generated less heat.

So Jobs went on the hunt for someone who could design a new power supply. Through his network of contacts, he found Rod Holt, a forty-something, chain-smoking socialist from the Atari crowd.[3] Pushed by Jobs, Holt abandoned the fifty-year-old conventional linear unit technology and created a switching power supply that revolutionized the way power was delivered to electronics products. Jobs’s pursuit of quiet and Holt’s ability to deliver an innovative power supply that didn’t need a fan made the Apple II the quietest and smallest personal computer ever made (a smaller computer was possible because it didn’t need extra space for the fan).

Had Jobs never asked, “Why does a computer need a fan?” and “How do we keep a computer cool without a fan?” the Apple computer as we know it would not exist.

Innovative Idea #2: The Macintosh User Interface, Operating System, and Mouse

The seed for the Macintosh, with its revolutionary operating system, was planted when Jobs visited Xerox PARC in 1979. Xerox, the copier company, created the Palo Alto Research Center (PARC), a research lab charged with designing the office of the future. Jobs wrangled a visit to PARC in exchange for offering Xerox an opportunity to invest in Apple. Xerox didn’t know how to capitalize on the exciting things going on at PARC, but Jobs did.

Jobs carefully observed the PARC computer screen filled with icons, pull-down menus, and overlapping windows—all controlled by the click of a mouse. “What we saw was incomplete and flawed,” Jobs said, “but the germ of the idea was there . . . within ten minutes it was obvious to me that all computers would work like this.”[4] He spent the next five years at Apple leading the design team that would produce the Macintosh computer, the first personal computer with a graphical user interface (GUI) and mouse. Oh, and he saw something else during the PARC visit. He got his first taste of object-oriented programming, which became the key to the OSX operating system that Apple acquired from Jobs’s other start-up, NeXT Computers. What if Jobs had never visited Xerox PARC to observe what was going on there?

Innovative Idea #3: Desktop Publishing on the Mac

The Macintosh, with its LaserWriter printer, was the first computer to bring desktop publishing to the masses. Jobs claims that the “beautiful typography” available on the Macintosh would never have been introduced if he hadn’t dropped in on a calligraphy class at Reed College in Oregon. Says Jobs:

Reed College offered perhaps the best calligraphy instruction in the country. Throughout the campus every poster, every label on every drawer, was beautifully hand-calligraphed. Because I had dropped out and didn’t have to take the normal classes, I decided to take a calligraphy class to learn how to do this. I learned about serif and san serif typefaces, about varying the amount of space between different letter combinations, about what makes great typography great. It was beautiful, historical, artistically subtle in a way that science can’t capture, and I found it fascinating. None of this had even a hope of any practical application in my life. But ten years later, when we were designing the first Macintosh computer, it all came back to me. And we designed it all into the Mac. It was the first computer with beautiful typography. If I had never dropped in on that single course in college, the Mac would have never had multiple typefaces or proportionally spaced fonts. And since Windows just copied the Mac, it’s likely that no personal computer would have them.[5]

What if Jobs hadn’t decided to drop in on the calligraphy classes when he had dropped out of college?

So what do we learn from Jobs’s ability to think different? Well, first we see that his innovative ideas didn’t spring fully formed from his head, as if they were a gift from the Idea Fairy. When we examine the origins of these ideas, we typically find that the catalyst was: (1) a question that challenged the status quo, (2) an observation of a technology, company, or customer, (3) an experience or experiment where he was trying out something new, or (4) a conversation with someone who alerted him to an important piece of knowledge or opportunity. In fact, by carefully examining Jobs’s behaviors and, specifically, how those behaviors brought in new diverse knowledge that triggered an innovative idea, we can trace his innovative ideas to their source.

What is the moral of this story? We want to convince you that creativity is not just a genetic endowment and not just a cognitive skill. Rather, we’ve learned that creative ideas spring from behavioral skills that you, too, can acquire to catalyze innovative ideas in yourself and in others.

What Makes Innovators Different?

So what makes innovators different from the rest of us? Most of us believe this question has been answered. It’s a genetic endowment. Some people are right brained, which allows them to be more intuitive and divergent thinkers. Either you have it or you don’t. But does research really support this idea? Our research confirms others’ work that creativity skills are not simply genetic traits endowed at birth, but that they can be developed. In fact, the most comprehensive study confirming this was done by a group of researchers, Merton Reznikoff, George Domino, Carolyn Bridges, and Merton Honeymon, who studied creative abilities in 117 pairs of identical and fraternal twins. Testing twins aged fifteen to twenty-two, they found that only about 30 percent of the performance of identical twins on a battery of ten creativity tests could be attributed to genetics.[6] In contrast, roughly 80 percent to 85 percent of the twins’ performance on general intelligence (IQ) tests could be attributed to genetics.[7] So general intelligence (at least the way scientists measure it) is basically a genetic endowment, but creativity is not. Nurture trumps nature as far as creativity goes. Six other creativity studies of identical twins confirm the Reznikoff et al. result: roughly 25 percent to 40 percent of what we do innovatively stems from genetics.[8] That means that roughly two-thirds of our innovation skills still come through learning—from first understanding the skill, then practicing it, and ultimately gaining confidence in our capacity to create.

This is one reason that individuals who grow up in societies that promote community versus individualism and hierarchy over merit—such as Japan, China, Korea, and many Arab nations—are less likely to creatively challenge the status quo and turn out innovations (or win Nobel prizes). To be sure, many innovators in our study seemed genetically gifted. But more importantly, they often described how they acquired innovation skills from role models who made it “safe” as well as exciting to discover new ways of doing things.

If innovators can be made and not just born, how then do they come up with great new ideas? Our research on roughly five hundred innovators compared to roughly five thousand executives led us to identify five discovery skills that distinguish innovators from typical executives (for detail on the research methods, see appendix B). First and foremost, innovators count on a cognitive skill that we call “associational thinking” or simply “associating.” Associating happens as the brain tries to synthesize and make sense of novel inputs. It helps innovators discover new directions by making connections across seemingly unrelated questions, problems, or ideas. Innovative breakthroughs often happen at the intersection of diverse disciplines and fields. Author Frans Johanssen described this phenomenon as “the Medici effect,” referring to the creative explosion in Florence when the Medici family brought together creators from a wide range of disciplines—sculptors, scientist, poets, philosophers, painters, and architects. As these individuals connected, they created new ideas at the intersection of their respective fields, thereby spawning the Renaissance, one of the most innovative eras in history. Put simply, innovative thinkers connect fields, problems, or ideas that others find unrelated.

The other four discovery skills trigger associational thinking by helping innovators increase their stock of building-block ideas from which innovative ideas spring. Specifically, innovators engage the following behavioral skills more frequently:

- Questioning. Innovators are consummate questioners who show a passion for inquiry. Their queries frequently challenge the status quo, just as Jobs did when he asked, “Why does a computer need a fan?” They love to ask, “If we tried this, what would happen?” Innovators, like Jobs, ask questions to understand how things really are today, why they are that way, and how they might be changed or disrupted. Collectively, their questions provoke new insights, connections, possibilities, and directions. We found that innovators consistently demonstrate a high Q/A ratio, where questions (Q) not only outnumber answers (A) in a typical conversation, but are valued at least as highly as good answers.

- Observing. Innovators are also intense observers. They carefully watch the world around them—including customers, products, services, technologies, and companies—and the observations help them gain insights into and ideas for new ways of doing things. Jobs’s observation trip to Xerox PARC provided the germ of insight that was the catalyst for both the Macintosh’s innovative operating system and mouse, and Apple’s current OSX operating system.

- Networking. Innovators spend a lot of time and energy finding and testing ideas through a diverse network of individuals who vary wildly in their backgrounds and perspectives. Rather than simply doing social networking or networking for resources, they actively search for new ideas by talking to people who may offer a radically different view of things. For example, Jobs talked with an Apple Fellow named Alan Kay, who told him to “go visit these crazy guys up in San Rafael, California.” The crazy guys were Ed Catmull and Alvy Ray, who headed up a small computer graphics operation called Industrial Light & Magic (the group created special effects for George Lucas’s movies). Fascinated by their operation, Jobs bought Industrial Light & Magic for $10 million, renamed it Pixar, and eventually took it public for $1 billion. Had he never chatted with Kay, he would never have wound up purchasing Pixar, and the world might never have thrilled to wonderful animated films like Toy Story,WALL-E, and Up.

- Experimenting. Finally, innovators are constantly trying out new experiences and piloting new ideas. Experimenters unceasingly explore the world intellectually and experientially, holding convictions at bay and testing hypotheses along the way. They visit new places, try new things, seek new information, and experiment to learn new things. Jobs, for example, has tried new experiences all his life—from meditation and living in an ashram in India to dropping in on a calligraphy class at Reed College. All these varied experiences would later trigger ideas for innovations at Apple Computer.

Collectively, these discovery skills—the cognitive skill of associating and the behavioral skills of questioning, observing, networking, and experimenting—constitute what we call the innovator’s DNA, or the code for generating innovative business ideas.

The Courage to Innovate

Why do innovators question, observe, network, and experiment more than typical executives? As we examined what motivates them, we discovered two common themes. First, they actively desire to change the status quo. Second, they regularly take smart risks to make that change happen. Consider the consistency of language that innovators use to describe their motives. Jobs wants to “put a ding in the universe.” Google cofounder Larry Page has said he’s out to “change the world.” These innovators steer entirely clear of a common cognitive trap called the status quo bias—the tendency to prefer an existing state of affairs to alternative ones. Most of us simply accept the status quo. We may even like routine and prefer not to rock the boat. We adhere to the saying, “if it ain’t broke, don’t fix it,” while not really questioning whether “it” is “broke.” In contrast, innovators see many things as “broke.” And they want to fix them.

How do innovators break the status quo? One way is to refuse to be dictated by other people’s schedules. Just glance at an innovative executive’s typical calendar and you will find a radically different schedule compared to less inventive executives. We found that innovative entrepreneurs (who are also CEOs) spend 50 percent more time on discovery activities (questioning, observing, experimenting, and networking) than CEOs with no innovation track record. That translated into spending almost one more day each week on discovery activities. They understand that fulfilling their dreams to change the world means they’ve got to spend a significant amount of time trying to discover how to change the world. And having the courage to innovate means that they are actively looking for opportunities to change the world.

Embracing a mission for change makes it much easier to take smart risks, make mistakes, and most of all, learn quickly from them. Most innovative entrepreneurs we studied felt that mistakes are nothing to be ashamed of. In fact, they are an expected cost of doing business. “If the people running Amazon.com don’t make some significant mistakes,” Jeff Bezos told us, “then we won’t be doing a good job for our shareholders because we won’t be swinging for the fences.” In short, innovators rely on their “courage to innovate”—an active bias against the status quo and an unflinching willingness to take smart risks—to transform ideas into powerful impact.

In summary, the DNA of innovators—or the code for generating innovative ideas—is expressed in the model shown in figure 1-1. The key skill for generating innovative ideas is the cognitive skill of associational thinking. The reason that some people generate more associations than others is partly because their brains are just wired that way. But a more critical reason is that they more frequently engage in the behavioral skills of questioning, observing, networking, and experimenting. These are the catalysts for associational thinking. Of course, the next question is, why do some people engage these four skills more than others? The answer is that they have the courage to innovate. They are willing to embrace a mission for change and take risks to make change happen. The bottom line is that to improve your ability to generate innovative ideas, you need to practice associational thinking and more frequently engage in questioning, observing, networking, and experimenting. That will likely only happen if you can somehow cultivate the courage to innovate.

FIGURE 1-1

The innovator’s DNA model for generating innovative ideas

As innovators actively engage in their discovery skills over a lifetime, they build discovery habits, and they become defined by them. They grow increasingly confident in their ability to discover what’s next, and they believe deeply that generating creative insights is their job. It is not something to delegate to someone else. As A. G. Lafley declared, “innovation is the central job of every leader—business unit managers, functional leaders, and the CEO.”[9]

The Innovator’s DNA

We’ve just told you that the ability to be innovative is not based primarily on genetics. At the same time, we’re using the DNA metaphor to describe the inner workings of innovators, which suggests that it is. Bear with us for a moment. (And welcome to the world of innovation, where the ability to synthesize two seemingly opposing ideas is the type of associating that produces novel insights.) Recent developments in the field of gene therapy show that it is possible to modify and strengthen your physical DNA, for example, to help ward off diseases.[10] Likewise, it is metaphorically possible to strengthen your personal innovator’s DNA. Let us provide an illustration.

Imagine that you have an identical twin, endowed with the same brains and natural talents that you have. You’re both given one week to come up with a creative new business idea. During that week, you come up with ideas alone, just thinking in your room. By contrast, your twin (1) talks with ten people—including an engineer, a musician, a stay-at-home dad, and a designer—about the venture; (2) visits three innovative start-ups to observe what they do; (3) samples five “new to the market” products and takes them apart; (4) shows a prototype he’s built to five people, and (5) asks “What if I tried this?” and “What would make this not work?” at least ten times each day during these networking, observing, and experimenting activities. Who do you bet will come up with the more innovative (and usable) idea? My guess is that you’d bet on your twin, and not because he has better natural (genetic) creative abilities. Of course, the anchor weight of genetics is still there, but it is not the dominant predictor. People can learn to more capably come up with innovative solutions to problems by acting in the way that your twin did.

Discovery Skill Strengths Differ for Disruptive Innovators

To understand that innovative entrepreneurs develop and use different skills, look at figure 1-2. It shows the percentile rank scores on each of the five discovery skills for four well-known founders and innovators: Pierre Omidyar (eBay), Michael Dell (Dell), Michael Lazaridis (Research In Motion), and Scott Cook (Intuit). The percentile rank indicates the percentage of over five thousand executives and innovators in our database who scored lower on that particular skill. A particular skill is measured by the frequency and intensity with which these individuals engage in activities that compose the skill.

FIGURE 1-2

High-profile innovators’ discovery skills profile

As you can see, the pattern for each innovative entrepreneur is different. For example, Omidyar is much more likely to acquire his ideas through questioning (ninety-fifty percentile) and observing (eighty-seventh percentile), Dell through experimenting (ninetieth percentile) and networking (ninety-eighth percentile), Cook through observing (eighty-eighth percentile) and questioning (eighty-third percentile), and Lazaridis through questioning (ninety-sixth percentile) and networking (ninety-eighth percentile). The point is that each of these innovative entrepreneurs did not score high on all five of the discovery skills. They each combined the discovery skills uniquely to forge new insights. Just as each person’s physical DNA is unique, an innovator’s DNA comprises a unique combination of skills and behaviors.

As figure 1-2 shows, innovative entrepreneurs rarely display across-the-board strength in observing, experimenting, and networking, and actually don’t need to. All of the high-profile innovative entrepreneurs in our study scored above the seventieth percentile in associating and questioning. The innovators seemed to hold these two discovery skills more universally. But the innovators we studied didn’t need world-class strength in the other behaviors. It certainly helped if they excelled at one of the four skills and were strong in at least two. If you hope to be a better innovator, you will need to figure out which of these skills you can improve and which can be distinguishing skills to help you generate innovative ideas.

I’m Not Steve Jobs . . . Is This Relevant?

OK, so you’re not Steve Jobs. Or Jeff Bezos. Or any other famous business innovator. But that doesn’t mean you can’t learn from these innovators. You can get better at innovating, even if most of your innovations are somewhat incremental in nature. We’ve seen it happen, and we’ve seen that it can make a difference. We’ve seen a pharmaceutical executive practice a questioning technique (see chapter 3) each day to identify key strategic issues facing his division. After three months, his boss told him that he’d become the most effective strategic thinker on his team. Within six months, he was promoted to a corporate strategic planning job. “I just improved my ability to ask questions,” he told us. We’ve seen MBA students in our classes use the observing, networking, and experimenting techniques to generate entrepreneurial business ideas. One got the idea for launching a company that uses bacteria to eat pollution from networking with someone he met at a neighborhood barbeque. Another observed that the best English speakers in Brazil were people who watched American movies and television. So he launched a company that sells software that helps people learn English by watching movies. Many innovative ideas may seem small, such as a new process for effectively screening job recruits or a better way to build customer loyalty, but they are valuable new ideas nonetheless. And if you come up with enough of them, they will definitely help you advance in your career. The point is this: you don’t have to be Steve Jobs to generate innovative ideas for your business.

Delivery Skills: Why Most Senior Executives Don’t Think Different

We’ve spent the past eight years interviewing scores of senior executives—mostly at large companies—asking them to describe the most novel and valuable strategic insights that they had generated during their careers. Somewhat surprisingly, we found that top executives rarely mentioned an innovative business idea that they had personally generated. They were extremely intelligent and talented individuals who were accomplished at delivering results, but they didn’t have much direct, personal experience with generating innovative business ideas.

In contrast to innovators who seek to fundamentally change existing business models, products, or processes, most senior executives work hard to efficiently deliver the next thing that should be done given the existing business model. That is, they work inside the box. They shine at converting a vision or goal into the specific tasks to achieve the defined goal. They organize work and conscientiously execute logical, detailed, data-driven plans of action. In short, most executives excel at execution, including the following four delivery skills: analyzing, planning, detail-oriented implementing, and disciplined executing. (We’ll say more about these skills later in the chapter and in chapter 8, but for now we need only note that they are critical for delivering results and translating an innovative idea into reality.)

Many innovators realize that they are deficient in these critical skills and, consequently, try to team up with others who possess them. For example, eBay founder Omidyar quickly recognized the need for execution skills, so he invited Jeff Skoll, a Stanford MBA, and Meg Whitman, a Harvard MBA, to join him. “Jeff Skoll and I had very complementary skills,” Omidyar told us. “I’d say I did more of the creative work developing the product and solving problems around the product, while Jeff was involved in the more analytical and practical side of things. He was the one who would listen to an idea of mine and then say, ‘Ok, let’s figure out how to get this done.’” Skoll and Whitman professionalized the eBay Web site, added fixed-price auctions, drove international expansion, developed new categories such as autos, and integrated important capabilities such as PayPal.

The Discovery and Delivery Skills Matrix: How Innovators Stack Up

To test the assertion that innovative executives have a different set of skills than typical executives, we used our innovator’s DNA assessment to measure the percentile rank of a sample of high-profile innovative entrepreneurs (founder CEOs of companies on BusinessWeek’s list of the top one hundred most innovative companies) on both the five discovery skills (associating, questioning, observing, networking, experimenting) and the four delivery or execution skills: analyzing, planning, detail-oriented implementing, and self-disciplined executing. We averaged their percentile rank scores across the five discovery skills to get an overall percentile rank, and then did the same thing across the four delivery skills to get an overall percentile rank. We refer to the overall percentile rank across the five discovery skills as the “discovery quotient” or DQ. While intellectual quotient (or IQ) tests are designed to measure general intelligence and emotional quotient (or EQ) assessments measure emotional intelligence (ability to identify, assess, and control the emotions of ourselves and others), discovery quotient (DQ) is designed to measure our ability to discover ideas for new ventures, products, and processes.

FIGURE 1-3

Discovery-delivery skills matrix

Figure 1-3 shows that the high-profile innovative entrepreneurs scored in the eighty-eighth percentile on discovery skills, but only scored in the fifty-sixth percentile on delivery skills. In short, they were just average at execution. We then conducted the same analysis for a sample of nonfounder CEOs (executives who had never started a new business). We found that most senior executives in large organizations were the mirror image of innovative entrepreneurs: they scored around the eightieth percentile on delivery skills, while scoring only above average on discovery skills (sixty-second percentile). In short, they are selected primarily for their execution skills. This focus on execution is even more pronounced in business unit managers and functional managers, who are worse at discovery than typical CEOs. This data shows that innovative organizations are led by individuals with a very high DQ. It also shows that even within an average organization, discovery skills tend to distinguish those who make it to the highest levels of the organization. So if you want to move up, you’d better learn how to innovate.

Why do most senior executives excel in the delivery skills, but are only above average in discovery skills? It is vital to understand that the skills critical to an organization’s success vary systematically throughout the business life cycle. (See figure 1-4). For example, in the start-up phase of an innovative venture, the founders are obviously more discovery-driven and entrepreneurial. Discovery skills are crucial early in the business life cycle because the company’s key task is to generate new business ideas worth pursuing. Thus, discovery (exploration) skills are highly valued at this stage and delivery (execution) skills are secondary. However, once innovative entrepreneurs come up with a promising new business idea and then shape that idea into a bona fide business opportunity, the company begins to grow and then must pay attention to building the processes necessary to scale the idea.

FIGURE 1-4

The business and executive skill life cycles

During the growth stage, the innovative entrepreneur may well leave the company, either because she has no interest in scaling the idea (which involves boring and routine work, at least to her) or because she does not have the skills to manage effectively in a large organization. Innovative entrepreneurs are often described as poor managers because they lack the ability to follow through on their new business ideas and are often irrationally overconfident in them. Moreover, they are more likely to make decisions based on hunches and personal biases rather than data-driven analysis.[11] Not surprisingly, the conventional prescription for these problems is to replace the entrepreneurs with professional managers—individuals with proven skills at delivering results. At this point in the business life cycle, professional managers who are better equipped to scale the business often replace the entrepreneur founders. When such replacement occurs, however, key discovery skills walk away from the top management team.

With the founder entrepreneur out of the picture, the ensuing growth and maturation stage of the business life cycle begins. In these stages, managers generally make it to the top of the management pyramid through great execution. This may involve generating incremental (sustaining) innovations for existing customers, but the focus is on execution, not building new businesses. Surprisingly few companies in this stage pay systematic attention to the selection or promotion of people with strong discovery skills. As this happens, the lack of discovery skills at the top becomes even more glaring, but it is still not necessarily obvious. (Contrast these common practices with those of Amazon founder Bezos, who systematically asks any new hire, including senior executives, to “tell me about something that you have invented.” Bezos wants to hire people with an inventive attitude—in other words, people like himself.)

Eventually, for most organizations, the initial innovations that created the business in the first place complete their life cycle. Growth stalls as the business hits the downward inflection point in the well-known S curve. These mature and declining organizations are typically dominated by executives with excellent delivery skills. Meanwhile, investors demand new growth businesses, but senior executive teams can’t seem to find them because the management ranks are dominated by folks with strong delivery skills. With discovery skills largely absent from the top management team, it becomes increasingly difficult to find new business opportunities to fuel new company growth. The company once again starts to see the imperative for discovery skills.

In sharp contrast, when entrepreneur founders stay through the growth stage, the company significantly outperforms its peers in growth and profitability.[12] An entrepreneurial founder is far more likely to surround herself with executives who are good at discovery, or who at least understand discovery. Could Apple have built new businesses in music (iTunes and iPod) and phones (iPhone) on top of an older computer business without the return of Jobs? We doubt it.

The key point here is that large companies typically fail at disruptive innovation because the top management team is dominated by individuals who have been selected for delivery skills, not discovery skills. As a result, most executives at large organizations don’t know how to think different. It isn’t something that they learn within their company, and it certainly isn’t something they are taught in business school. Business schools teach people how to be deliverers, not discoverers.

For a moment, consider your company’s track record of rewarding and promoting discovery skills. Does your company actively screen for people who have strong discovery skills? Does your company regularly reward discovery skills through annual performance assessments? If the answers are no, then it is likely that a severe discovery skill deficit exists at the top ranks of management in your company.

Discovery and Delivery Skills Quiz: What’s Your Profile?

To get a quick snapshot of your discovery-delivery skills profile, take the following self-assessment survey (1 = strongly disagree; 2 = somewhat disagree; 3 = neither agree nor disagree; 4 = somewhat agree; 5 = strongly agree). Remember to answer based on your actual behaviors, not what you would like to do.

1. Frequently, my ideas or perspectives diverge radically from others’ perspectives.

2. I am very careful to avoid making any mistakes in my work.

3. I regularly ask questions that challenge the status quo.

4. I am extremely well organized at work.

5. New ideas often come to me when I am directly observing how people interact with products and services.

6. I must have everything finished “just right” when completing a work assignment.

7. I often find solutions to problems by drawing on solutions or ideas developed in other industries, fields, or disciplines.

8. I never jump into new projects and ventures and act quickly without carefully thinking through all of the issues.

9. I frequently experiment to create new ways of doing things.

10. I always follow through to complete a task, no matter what the obstacles.

11. I regularly talk with a diverse set of people (e.g., from different business functions, organizations, industries, geographies, etc.) to find and refine new ideas.

12. I excel at breaking down a goal or plan into the micro tasks required to achieve it.

13. I attend conferences (on my areas of expertise as well as unrelated areas) to meet new people and understand what issues are facing them.

14. I pay careful attention to details at work to ensure that nothing is overlooked.

15. I actively seek to identify emerging trends by reading books, articles, magazines, blogs, and so on.

16. I hold myself and others strictly accountable for getting results.

17. I frequently ask “what if” questions that provoke exploration of new possibilities and frontiers.

18. I consistently follow through on all commitments and finish what I’ve started.

19. I regularly observe the activities of customers, suppliers, or other organizations to get new ideas.

20. I consistently create detailed plans to get work done.

To score your survey:

Add your score on the odd-numbered items. You score very high on discovery skills if your total score is 45 or above, high on discovery if your score is 40–45, moderate to high on discovery if your score is between 35 and 40, moderate to low if you score 29–34; you score low on discovery if your score is 28 or less.

Add your score on the even-numbered items. You score very high on delivery skills if your total score is 45 or above, high on delivery if your score is 40–45, moderate to high on delivery if your score is between 35 and 40, moderate to low if you score 29–34; you score low on delivery if your score is 28 or less.

We have drawn this short survey from a more systematic seventy-item assessment (either a self-assessment or a 360-degree assessment) that we have developed to assess an individual’s discovery skills and delivery skills. You can do this assessment through our Web site at http://www.InnovatorsDNA.com. Should you decide to complete an assessment, you will receive a development guide to walk you through your results and help you design a skill development plan. Your assessment will provide you with your DQ and percentile data for each discovery and delivery skill to compare your scores with the over five thousand executives and innovators in our dataset.

You Can Learn to Think Different

In this chapter, we’ve tried to convince you that creativity is not a just a genetic predisposition; it is an active endeavor. Apple’s slogan “Think Different” is inspiring but incomplete. Innovators must consistently act different to think different. We acknowledge that genetics are at work within innovators, and that some have superior natural ability at associational thinking. However, even if two individuals have the same genetic creative ability, one will be more successful at creative problem solving if he or she more frequently engages in the discovery skills we have identified. By understanding—and engaging in—the five discovery skills, we believe that you can find ways to more successfully develop the creative spark within yourself and others. Read on as we describe how to master the five discovery skills in order to become a more innovative thinker.

2

Discovery Skill #1: Associating

“Creativity is connecting things.”

—Steve Jobs, founder and CEO, Apple Inc.

INNOVATORS THINK DIFFERENTLY (to be grammatically correct), but as Steve Jobs put it, they really just think different by connecting the unconnected. Einstein once called creative thinking “combinatorial play” and saw it as “the essential feature in productive thought.” Associating—or the ability to make surprising connections across areas of knowledge, industries, even geographies—is an often-taken-for-granted skill among the innovators we studied. Innovators actively pursue diverse new information and ideas through questioning, observing, networking, and experimenting—the key catalysts for creative associations.

To illustrate how associations produce innovative business ideas, consider how Marc Benioff came up with the idea for Salesforce.com, now a $13 billion software company. Benioff’s experience with technology and software began when, as a fifteen-year-old, he built a small software company, Liberty Software, writing computer games (like “How to Juggle”) on his Commodore 64. As a computer science and entrepreneurship undergraduate, Benioff worked summers at Apple during the build-up and launch of the first Mac, learning firsthand what it meant to work in a think-different world.

After graduation, Benioff joined Oracle, then a small start-up. By the time Benioff was twenty-five, he was leading Oracle’s entire direct-marketing division and was beginning to see several streams of opportunity emerging on the Internet. “The nature of being successful with software is you always have to be looking for the next thing, so you have to condition your mind to think that way,” Benioff told us. “I’ve seen a lot of different technological shifts over the last twenty-five years, so as I was sitting at my desk at Oracle in the late nineties and watching the emergence of Amazon.com and eBay . . . it felt like something significant was on the horizon.”

Benioff decided it was time to think more deeply about the changing technological landscape—and his own career. So he took a sabbatical that started with a trip to India where he met a variety of diverse people, including spiritual leader and humanitarian, Mata Amritanandamayi (who helped strengthen his commitment to doing well and doing good in business). Benioff’s next stop on this global journey was Hawaii, where he discussed various ideas for new businesses with an assortment of entrepreneurs and friends. While swimming with dolphins in the Pacific Ocean, the fundamental epiphany for Salesforce.com surfaced. He reflected: “I asked myself ‘Why aren’t all enterprise software applications built like Amazon and eBay? Why are we still loading and upgrading software the way that we have been doing all this time when we now have the Internet?’ And that was a fundamental breakthrough for me, asking those questions. And that’s the genesis of Salesforce. It’s basically enterprise software meets Amazon.”

Benioff’s synthesis of novel inputs or association—“enterprise software meets Amazon”—challenged the industry tradition of selling software on CD-ROMs and engaging companies in lengthy, customized (and expensive) installation processes, and instead focused on delivering software as a service over the Internet. That way, the software would be available 24/7, and companies would avoid all the costs and shutdowns associated with ongoing, large-scale IT system installations and upgrades. Given his substantial experience in sales and marketing at Oracle, Benioff felt that providing software services for managing a sales force and customer relations carried huge potential for small and medium-sized businesses that couldn’t afford customized enterprise software. Thus, Salesforce.com was born.

Benioff’s vision emerged from years of significant software industry experience combined with countless questions, observations, explorations, and conversations that ultimately helped him bring together things that had never been connected before. He borrowed elements of the Amazon business model and built a different one based on a software system that companies would pay for as they used it, instead of paying for all of the software systems before they used them (as most software providers did). It was truly revolutionary as it launched an era of “cloud computing” that seems obvious now, but was far from obvious then.

Ever the juggler with a mind hooked on “combinatorial play” (or playing around with new associations), Benioff and his Salesforce.com team have continued the innovation journey. He explained that pre-Salesforce.com, his critical question was “Why isn’t all enterprise software like Amazon?” but post-Salesforce.com, a different question slowly took its place, “Why isn’t all enterprise software (including Salesforce.com) like Facebook?” Benioff and his team hotly pursued the answer and invented Chatter, a new social software application that has been referred to as “Facebook for businesses.” Chatter takes the best of Facebook and Twitter and applies it to enterprise collaboration (think of it as “Facebook and Twitter meet enterprise software,” just as “enterprise software met Amazon” at Salesforce.com’s genesis).

Chatter uses new ways of sharing information such as feeds and groups, so that without any effort, people can see what individuals and teams are focusing on, how projects are progressing, and what deals are closing. It changes the way companies collaborate on product development, customer acquisition, and content creation by making it easy for everyone to see what everyone else is doing. At companies using Chatter, e-mail in-boxes have shrunk dramatically (by 43 percent at Salesforce.com) because the majority of communications are now status updates and feeds in Chatter. “Employees now follow accounts, and updates are automatically broadcast to them in real-time via Chatter,” Benioff told us. “This is the true power of Chatter—bringing to light the most important people and ideas that move our companies forward. I call this social intelligence, and it’s giving everyone access to the people, the knowledge, and the insight they need to make a difference.”

Associating: What It Is

The great innovative entrepreneur Walt Disney once described his role in the company he founded as creative catalyst. By that he meant that while he himself didn’t actually do the drawings for the wonderful animated films or build the giant Matterhorn replica for Disneyland, he did put ideas together in ways that sparked creative insights throughout the company. One day, a little boy was curious about Disney’s job, and Disney vividly recalled the conversation: “I was stumped one day when a little boy asked, ‘Do you draw Mickey Mouse?’ I had to admit I do not draw any more. ‘Then you think up all the jokes and ideas?’ ‘No,’ I said, ‘I don’t do that.’ Finally, he looked at me and said, ‘Mr. Disney, just what do you do?’ ‘Well,’ I said, ‘I think of myself as a little bee. I go from one area of the studio to another and gather pollen and sort of stimulate everybody.’ I guess that’s the job I do.”[1] Not only did Disney spark others’ ideas, he sparked his own as well by putting himself at the intersection of others’ experiences. Over time, Disney’s associational insights—including a string of industry firsts such as joining animation with full-length movies and putting themes into amusement parks—changed the face of entertainment.

Innovative leaders at well-known companies such as Apple, Amazon, and Virgin do exactly the same thing. They cross-pollinate ideas in their own heads and in others. They connect wildly different ideas, objects, services, technologies, and disciplines to dish up new and unusual innovations. “Creativity is connecting things,” as Steve Jobs once put it. He continued, “When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something...they were able to connect experiences they’ve had and synthesize new things.”[2] This is how innovators think different, or what we call associating,[3] a cognitive skill at the core of the innovator’s DNA. In this chapter, we look more deeply into the workings of associational thinking and offer some techniques for developing this cognitive ability.

Associating: Where It Happens

Innovative ideas flourish at the intersection of diverse experience, whether it be others’ or our own. Throughout history, great ideas have emerged from these crossroads of culture and experience. Much like the twelve major streets of traffic converging on the accident-prone circular road surrounding the Arc de Triomphe in Paris, the more diverse our crossroads of experience, the more likely a serendipitous synthesis of the surprising will occur. Put simply, innovators intentionally maneuver themselves into the intersection, where diverse experiences flourish and foster the discovery of new insights. As we mentioned in chapter 1, Frans Johansson coined the term “Medici effect”[4] to describe the spark that occurs in a geographic space or market space where a combination of novel ideas coalesce into something quite surprising. Such Medici effects have occurred throughout history, ancient and contemporary.

For example, historians often refer to the eighth to thirteenth centuries of the Islamic world as the Islamic “renaissance” or “golden age.” Centuries before the Italian Renaissance, Baghdad attracted the best scholars from the Muslim world. Cairo, Damascus, Tunis, and Cordoba were also influential intellectual hubs. Islamic explorers traveled to the edges of the known world and beyond. Mecca served not only as a religious center, but also as a key intersection for multinational merchant traders coming from the far western regions of the Mediterranean to the far eastern reaches of India. This Islamic renaissance produced significant innovations, many of which are relevant today, including the underlying principles and ingredients of lipstick, suntan lotion, thermometers, ethanol, underarm deodorant, tooth bleaching, torpedoes, fireproof clothing, and charitable trusts.[5]

The Medici effect occurred in the Islamic and Italian renaissances, but it has also happened in modern times and in many places around the world. For example, Silicon Valley in the 1960s was anything but silicon. Yet, by the 1970s, all that had changed and technology innovation flourished during its renaissance decades of the 1970s, 1980s, and 1990s. Elsewhere in the world, countries and communities are actively attempting to create their own intersections of people with expertise in different fields to spark creative new ideas. China, for example, has bet substantial resources on its innovation future to the extent that the rest of the world believes that China is on track to become the world’s most innovative country by 2020. In our work with the creative industries and social innovation sectors in China (like so many other sectors as well), we have found that they have dotted the land with artistic and social innovation incubators where ideas see not only the light of day, but the light of practice also.

The Medici effect also crops up in the many so-called “ideas conferences” that are flourishing—conferences such as the World Economic Forum Annual Meeting in Davos, Switzerland; the Aspen Ideas Festival; and TED (Technology Entertainment and Design) conferences, where diverse people join in a conscious attempt to cross-pollinate ideas and perspectives. Let’s explore the power of TED. People go to these conferences to rub elbows and exchange ideas with extraordinary people—those who are well known and those who aren’t. If you’ve never been to TED, take a look at its Web site to get a glimpse of how it creates a Medici effect year after year, and now in geography after geography (from TEDxTelAviv to TEDxRamallah to TEDxYourTown). A few of our personal TED favorites are Sir Ken Robinson questioning the foundation of educational systems, Kaki King experimenting far beyond what a guitar was originally intended to do, and David Gallo observing the incredible surprises of the deep sea (including the unexpected talents of squids). TED’s underlying beauty springs from the intentional diversity of participants and presentations. This diversity forms the foundation for innovators to potentially connect the unconnected.

Innovators in our research not only frequented places like TED, but literally constructed a TED in their heads through an intentional depth and diversity of life experience, creating a personal Medici effect. For them, TED-like conferences were icing on a cake that they had already baked by actively questioning, observing, networking, and experimenting throughout their lives. This incredible foundation of deep and diverse experience fueled their associational thinking far beyond that of noninnovators. Look at PepsiCo chairman and CEO Indra Nooyi’s life to get a glimpse of where her TED in the head comes from.

Nooyi was born to a middle-class family in Madras (now Chennai), where she often sat with her mother and sister “thinking big thoughts”; she played girls’ cricket avidly and was lead guitarist in an all-girl rock band (it’s no surprise that she still performs on stage at PepsiCo events). She finished a multidisciplinary undergraduate degree in chemistry, physics, and math before getting her MBA in Calcutta. Nooyi then worked in the textile industry (Tootal) and consumer products industry (Johnson & Johnson) before getting a master’s of public and private management at Yale. After graduation, she shifted to the consulting industry (Boston Consulting Group) before doing a strategic stint in the electrical power industry (ABB), ultimately arriving at PepsiCo, where she became its first woman CEO.

Nooyi’s diverse professional and personal experience convinced her that people, and especially CEOs, must “be willing to think disruptively.” She did exactly that for the 2010 Super Bowl. Instead of spending $20 million on two sixty-second television ad slots, Nooyi took an entirely different approach, “Pepsi Refresh,” emerging from a question she constantly asks: “How can we do better by doing better?” Pepsi Refresh invites people to submit ideas on how to “refresh” their communities, making them a better place to live. Each month, the Web site accepts a thousand ideas about arts and culture, health, education, and so on. Online voting produces winning ideas, with grants ranging from $5,000 to $250,000. In 2010 alone, PepsiCo allocated $1.3 million each month to Refresh projects based on over 45 million votes cast. Pepsi Refresh’s Facebook numbers also topped 1 million by the end of 2010, and PepsiCo is now rolling out the program globally.

Associating: How It Works

To better grasp how associating works and why some people might excel at it more than others, it is important to understand how the brain works. The brain doesn’t store information as a dictionary does, alphabetically with theater under T. Instead, while theater will associate with T, it will also associate with all of the other knowledge stored in the brain that the brain associates with it. Some associations with theater will seem logical, such as Broadway, showtime, or intermission, while others may be less obvious, such as kissing, acting career, or anxiety (perhaps due to a botched theater performance during high school). The more diverse knowledge the brain possesses, the more connections it can make when given fresh inputs of knowledge, and fresh inputs trigger the associations that lead to novel ideas. Scott Cook, founder and CEO of Intuit, describes these unexpected associations as “powerful and essential supplements to data” when working through a problem. Such analogies (or associations) are critical creative tools to help him generate strategic insights. When the brain is actively absorbing new knowledge, it is more likely to trigger connections between ideas (thus creating a wider web of neural connections) as it toils to synthesize novel inputs. Accordingly, the associating “muscle” can also be developed through the active practice of questioning, observing, networking, and experimenting.

In our research, every high-profile innovator excelled at associating (scoring at the seventieth percentile or higher on the innovator’s DNA assessment), with process inventors showing slightly less associational skill than other inventors (yet still far more than noninnovators). (See figure 2-1.)

FIGURE 2-1

Comparison of associating skills for different types of innovators and noninnovators

Sample items:

1. Creatively solves challenging problems by drawing on diverse ideas or knowledge.

2. Often finds solutions to problems by drawing on solutions or ideas developed in other industries, fields, or disciplines.

Why were all innovators so much better at associating than noninnovators? Our analysis found that the best predictor of excellent associating skills was how often people engaged in the other discovery skills—questioning, observing, networking, and experimenting. For example, Benioff got the initial idea for Chatter as he was asking, “Why isn’t all enterprise software like Facebook and Twitter?” Research In Motion founder Lazaridis got the idea for the BlackBerry at a conference as he listened to someone talk about future trends in wireless data transfers. Starbucks founder Schultz got the idea for Starbucks as he was observing expresso bars in Italy. Disruptive innovators shine best at associating when actively crossing all kinds of borders (geographic, industry, company, profession, discipline, and so on) and engaging the other innovator’s DNA skills.

Finding the right question, making compelling observations, talking with diverse people, and experimenting with the world usually delivers productive, relevant associational insights. In contrast, neglecting the other innovator’s DNA skills usually increases the randomness (and often irrelevance) of a new association or insight, resulting in less impact on the marketplace. For an example similar to the identical twins scenario in chapter 1, consider two innovators independently attempting to surface valuable, new associations. The first person engages actively and regularly in a full range of discovery skills. The second does not. Which is most likely to get relevant, high-impact ideas? Obviously, the first, since she’s been fully immersed in the world of real people facing real challenges while searching for a better solution. No surprise that her associational “ahas” are far more productive than her counterpart’s relatively “random” connections, likely made from the safety and distance of an office chair.

On the Hunt for New Associations

In our work with disruptive innovators, we found several things that best described the dynamics behind their search for new associations. Creating odd combinations, zooming in and out, and Lego thinking allowed them to connect the dots across diverse experiences and ultimately deliver disruptive new business ideas.

Creating odd combinations

Neil Simon’s successful Broadway play and subsequent TV series, The Odd Couple, centered on what life was like when two very different people—a prissy newsman and a sloppy sportswriter—lived together as roommates. The friction between opposite lifestyles often resulted in the most unexpected (and often creative) outcomes. Similarly, innovators often try to put together seemingly mismatched ideas to compose surprisingly successful combinations. They create odd couples, triplets, or quadruplets by consistently asking, “What if we combined this with that?” or “... this, this, and this with that?” They think different by fearlessly uniting uncommon combinations of ideas.

For Lazaridis, connecting ideas across disciplines was something he learned relatively early in life:

When I was in high school, we had an advanced math program and we had a shop program. And there was this great divide between the two departments, and I was in both. And I became, inadvertently, the ambassador between the two disciplines, and saw how the mathematics we were learning in shop was actually more advanced than some of the mathematics we were learning in advanced math because we’re using trigonometry, we’re using imaginary numbers, we’re using algebra, and even calculus in very real, tangible ways. So I was then tasked with bridging the gap and showing how math is used in electronics and how electronics is used in math.

Lazaridis noted that a teacher alerted him to the link between computers and wireless by telling him, “Don’t get too distracted with computer technology because the person that puts wireless and computers together is really coming up with something special.” And so the BlackBerry was born.

Likewise, Google cofounder Larry Page created an odd combination by connecting two seemingly unrelated ideas—academic citations with Web search—to launch Google. As a PhD student at Stanford, Page knew that academic journals and publishing companies rank scholars by the cumulative number of citations each scholar gets each year. Page realized that Google could rank Web sites in the same way that academic citations rank scholars; Web sites with the most links (that were most frequently selected) had more citations. This association allowed Page and cofounder Sergey Brin to launch a search engine yielding far superior search results.

Sometimes the world’s most innovative leaders capture what seem like fleeting associations among ideas and knowledge, mixing and matching quite different concepts. In so doing, they produce the occasional outlandish ideas that may be catalysts for innovative business ideas. EBay founder Pierre Omidyar gave us a recent example of how he came up with a wild idea. He had spoken with consultants who were trying to solve the problem of how to get produce quickly from the farm to consumers in Hawaii before it spoils (the consultants explained that roughly one-third of the produce spoils). The first question Omidyar asked was, “What about the post office? Doesn’t the post office go to everybody’s house six times a week? Why don’t we just mail the head of lettuce?” He then admitted: “It was probably an incredibly stupid idea and there are probably a dozen reasons why it won’t work, but it’s an example of how I put two things together that haven’t been put together before. I understand the post office very well because eBay counts on shipping companies for the business model to work. The post office is an organization that visits every household six times a week! Do you know any other organization that does that? So using those assets in novel ways might be interesting.”

Not everyone would consider putting “fresh produce” and “post office” together, but that’s the kind of thinking that increases the probability of surfacing an innovative new business idea.

Zooming in and zooming out

Innovative entrepreneurs often exhibit the capacity to do two things at once: they dive deep into the details to understand the subtle nuances of a particular customer experience, and they fly high to see how the details fit into the bigger picture. Synthesizing these two views often results in surprising associations. Niklas Zennström (cofounder of Skype) explained this process of zooming in and out based on his own experience: “You have to think laterally. You know, seeing and combining certain things going on at the same time and understanding how seemingly unrelated things could have something to do with each other. You need the ability to grasp different things going on at the same time and then to bring them together. For example, I can look at the bigger picture and also have a very good feel for the details. So I can go between high-level things to really, really small details. The movement often makes for new associations.”

Steve Jobs has mastered zooming in and out to create excellent and often industry-changing products. At one point, when designing the original Mac computer, his team struggled to get the right finish on the plastic. Jobs unblocked the logjam by going to a department store and zooming in on the details of different plastic appliances. He discovered a Cuisinart food processor that had all the right plastic-case properties for producing an excellent case for the first Mac. In other instances, he visited the company parking lot to examine details of different cars to gain new insights about current or future product design challenges. One time, his parking lot excursion revealed a Mercedes-Benz trim detail that helped resolve a metal case-design dilemma.

Jobs is equally adept at zooming out to detect unexpected intersections across diverse industries. For example, as a result of buying and then leading Pixar for over a decade, he acquired a perspective on the entire media industry that was quite different from one he had gained earlier in the computer industry. This produced a powerful intersection of ideas when he returned to Apple. Years of personal negotiation with Disney executives about distribution rights and income for Pixar movies gave Jobs the insight and experience that later helped him create a workable solution to Internet-based music distribution—a solution that escaped senior executives at other computer and MP3 player companies. Jobs’s Pixar experience provided the broad cross-industry perspective that has fueled the invention of several game-changing ideas like iTunes, iPod, iPhone, and most recently, the iPad.

Lego thinking

If innovators have one thing in common, it is that they love to collect ideas, like kids love to collect Legos. Nobel Prize winner Linus Pauling advised that “the best way to get a good idea is to get a lot of ideas.” Thomas Edison kept over thirty-five hundred notebooks of ideas during the course of his lifetime and set regular “idea quotas” to keep the tap open. Billionaire Richard Branson is an equally passionate recorder of ideas, wherever he goes and with whomever he talks. Yet, absolute quantity of ideas does not always translate into highly disruptive ideas. Why? Because “you cannot look in a new direction by looking harder in the same direction,” says Edward de Bono, author of Lateral Thinking. In other words, getting lots of ideas from lots of different sources creates the best of all innovation worlds. Innovators who frequently engage in questioning, observing, networking, and experimenting become far more capable at associating because they develop experience at understanding, storing, and recategorizing all this new knowledge. This is important because the innovators we studied rarely invented something entirely new; they simply recombined the ideas they had collected in new ways, allowing them to offer something new to the market. Questioning, observing, networking, and experimenting helped innovators slowly build larger, richer stocks of building-block ideas in their heads. The more building blocks they acquired, the better they were able to combine newly acquired knowledge to generate a novel idea.

To illustrate, think about a child playing with a set of Lego blocks. The more different kinds of blocks the child uses to build a structure, the more inventive she can become. But the most innovative structures spring from the novel combination of a wide variety of existing Legos, so as the child acquires different Lego sets (for example, combining a Sponge Bob set with a Star Wars set), she gets even better ideas for new structures. Similarly, the more knowledge, experience, or ideas you add from wide-ranging fields to your total stock of ideas, the greater the variety of ideas you can construct by combining these basic knowledge building blocks in unique ways. (See figure 2-2.)

FIGURE 2-2

Why boosting your diverse idea stock increases innovation

Conceptually, as innovators increase the number of building-block ideas, they substantially increase the number of ways they might combine ideas to create something surprisingly new. Combining this with that creatively (building odd combinations) depends on how many unique this and that building blocks people have cached in their heads over time.[a]

a. Mathematically, as the number of different building-block ideas (N) in our heads grows linearly, the potential ways to recombine those ideas grows even faster, or geometrically (by N(N–1)/2).

People with deep expertise in a particular field, who can combine that knowledge with new concepts and ideas unfamiliar to them, tend to be more creative. This is why innovation design firm IDEO tries to recruit people who demonstrate a breadth of knowledge in many fields and a depth in at least one area of expertise. IDEO describes this person as “T-shaped” because the person holds deep expertise in one knowledge area but actively acquires knowledge broadly across different knowledge areas. A person with this knowledge profile typically generates innovative associations in two ways: (1) by importing an idea from another field into his area of deep expertise, or (2) by exporting an idea from his area of deep expertise to one of the broad fields he is exploring where he has shallow knowledge.

For example, a consultant with manufacturing expertise working at Bain & Company happened to visit with hospital administrators after the U.S. government implemented fixed-cost reimbursements to reduce health care costs. The hospital needed new ways to reduce costs, something it hadn’t focused on when the government reimbursed for actual expenses plus a 10 percent profit markup. During the discussion, the Bain consultant—with deep expertise in the manufacturing sector—asked how the hospital managed patient throughput, minimizing the “touches” to the “product” (patient) and speeding its throughput through the “plant” (hospital). These manufacturing-sourced ideas were completely foreign to the hospital, where processes focused on keeping the patient longer to ensure quality care (and kept expenses and profits high). These new ideas from an entirely different industry delivered a dramatic redesign of hospital processes designed to get the patient through the hospital (like a plant) as quickly as possible. Within five years, Bain was working with over fifty U.S. hospitals applying these ideas to reduce costs.

A Safe Place for New Thoughts

After years of building a large stock of ideas through active questioning, observing, networking, and experimenting, innovators often make the most surprising associations. Sometimes an association or idea sparked at the very moment they were engaged in questioning, observing, networking or experimenting (as described in chapters 3 through 6). Equally often, innovators uncovered new ideas while in a relaxed state, without distractions, when they were not “trying” to solve a problem (researchers describe this as “defocusing their attention”). In other words, it rarely happened during a meeting when they were in a focused, convergent thinking mode searching for a solution to a particular problem. Instead, Diane Greene (cofounder of VMWare) told us that “the shower” is a great place to relax and think to get new ideas (a place frequently pitched by many innovators we interviewed, including David Neeleman [founder of JetBlue and Azul] and Jeff Jones [founder of Campus Pipeline and NxLight]). Innovators also unearth new ideas while walking, driving, on vacation, or in the middle of the night (as PepsiCo CEO Nooyi does). Benioff got the key inspiration for Salesforce.com when “swimming with the dolphins.” In addition to hitting the shower, Greene gets some of her best new associations when sailing solo (which she has done since childhood). In short, Greene explained, “You get more creativity by giving yourself the space for ideas to simmer. Ideas come from having a longer time horizon about what you’re thinking about and a broader view of where the idea might be going to go.” The point is that you can sometimes spend too much time deliberately attacking a problem when some creative ideas will only emerge after putting yourself in a relaxed state with no distractions.[6] If all else fails when trying to figure out a problem, go to sleep. Yes, Harvard researchers have found that sleep is a consistent antidote to tunnel vision toward a problem. So when find yourself stuck in a thinking rut, give the problem extra time to percolate by adding some sleep into the mix. On average, that sleep will give you a 33 percent better chance of connecting the unconnected and getting a great new idea.[7]

The best innovators generally knew their safe places and times for generating new ideas. Do you? If not, look for places of transition or relaxation. Some folks find their best ideas early in the morning; others late at night. Whatever works best for you, make sure that you make the time to just meditate and think.

Disruptive innovators force themselves to cross borders (technical, functional, geographical, social, disciplinary) as they engage in the other discovery skills. If we do the same, placing ourselves in midst of bustling intersections of diverse ideas and experiences, exciting associations will naturally happen. The discovery skills of questioning, observing, networking, and experimenting will trigger surprising associations as we exercise them, over and over. Whether pursued out of the office or in a conference room, great associations are more likely to unfold when we create a safe place for them to happen. In time, your capacity to craft creative solutions to problems will become powerful, at work and beyond.

Tips for Developing Associating Skills

To strengthen your capacity to think different and weave together unexpected connections across ideas, consider the following short- and long-term exercises.[8] Most take relatively little time, but when done consistently, they can deliver positive results in generating new ideas. We have found that these exercises can work for creatively solving senior-level strategic problems as well as factory floor–level production challenges.

Tip #1: Force new associations

Innovators sometimes practice “forced associating” or combining things that we would never naturally combine. For example, they might imagine (or force) the combination of features in, say, a microwave oven with a dishwasher. This could deliver an innovative product idea, such as a dishwasher that uses some type of heating technology to clean and sanitize dishes that eliminates water completely. Or in the case of actual appliance companies, EdgeStar produced a countertop-size dishwasher, while KitchenAid went for an in-sink approach. Both are the size of a microwave oven, use limited amounts of water, and wash far faster than a full-size machine.

To practice forced associations, first consider a problem or challenge you or your company is facing. Then try the following exercises to force an association that you normally wouldn’t make:

Pick up a product catalog and turn to the twenty-seventh page. What does the first product that you see have to do with the problem you are thinking about? Does the way it solves a problem for a customer have anything to do with your problem? For example, what if you run across an iPad product in your random page flipping and your work challenge is figuring out how to increase herbal tea sales? Looking at an iPad might spur surprising syntheses, such as creating a novel iPad application to capture the interest of potential customers (or provide a means for current customers to become repeat customers).

Or, open a completely random Wikipedia entry by choosing a random article from the Wikipedia Web menu. A random click might land on boomerang. Perhaps your organization hopes for more appealing product packaging. Bumping into the idea of a boomerang might suggest packaging a customer can return or a self- returning package after the product is used.

Now, back to the challenge you or your company is facing. Try one of these forced association exercises, identify an unrelated random item or idea, and take the time to reflect on what it has to do with your problem. The point is to randomly find things to associate with your problem and work your best to freely (even wildly) make associations, lots of them (remember, lots of associations can lead to great ideas). As you do so, table 2-1 might help organize your insights.

TABLE 2-1

Forcing new associations

Tip #2: Take on the persona of a different company

Follow the lead of TBWA, which often holds a designated “disruption day” to get new ideas.[9] After defining a key strategic question or challenge, TBWA people haul out large boxes full of hats, shirts, and other things from some of the most innovative companies in the world, like Apple and Virgin. They put on the clothing and assume the persona of someone from that company to look at their challenge from an entirely different perspective.

Alternatively, write down a list of companies (in related and unrelated industries) on a stack of index cards (or randomly go down the list of the Fortune 500 or Inc. 100 companies). Use the card stacks to create random pairings of your company with another. Then creatively brainstorm ideas on how the two could create new value through partnership or merger. By combining the strengths of both companies, you may surprise yourself with new products, services, or process ideas.

Tip #3: Generate metaphors

Engage in activities that provoke an analogy or metaphor for your company’s products or services (hopefully escaping from idea ruts), because each analogy holds the potential for seeing things from an uncommon perspective. To illustrate, what if watching TV were more like reading a magazine? (This is how TiVo has changed TV watching; you can start and stop when you want, skip over advertisements, and so on.) Or, what if your product or service could incorporate the benefits of some of today’s hottest products like the Wii or iPhone? What might those new features or benefits be? (See table 2-2.)

TABLE 2-2

Generating metaphors

Tip #4: Build your own curiosity box

Start a collection of odd, interesting things (e.g., a slinky, model airplane, robot, and so on) and put them in a curiosity box or bag (as people in the sixteenth and seventeenth centuries did when they used curiosity cabinets to store interesting objects from around the world). Then, you can pull out unique items randomly when confronted with a problem or opportunity (and if you’re really daring, display them on your office shelves). When traveling (or even at home), visit local second-hand shops and flea markets in a new city to pick up surprising treasures (ranging from a Kuwaiti camel bell to an Australian didgeridoo) that might provoke a new angle on an old problem.

Interestingly, the global innovation design firm IDEO devotes full-time employee effort to finding new things for its “Tech Box.” IDEO designers rely on Tech Box items (each box has hundreds of high-tech gadgets, clever toys, and a wide variety of items) when brainstorming for new ideas, because odd, unusual things often trigger new associations. It may sound silly, but seemingly silly things can provoke the most random associations, literally forcing us out of our habitual thinking patterns.

Tip #5: SCAMPER!

Try Alex Osborn and Bob Eberle’s acronym for insight, SCAMPER: substitute; combine; adapt; magnify, minimize, modify; put to other uses; eliminate; reverse, rearrange. Use any or all of the concepts to rethink the problem or opportunity you are addressing (this is particularly useful when thinking of redesigning a product, service, or process). (Michael Michalko’s Thinkertoys is a useful resource for more details about the SCAMPER method; see table 2-3.)

TABLE 2-3

The Scamper method

Scamper challenge

Invent a new type of wristwatch

Substitute

Use natural wood or rocks instead of steel material.

Combine

Create a space for easy, instant access to medications when the alarm goes off.

Adapt

Use the wristwatch as a reflective mirror when lost.

Magnify, minimize, modify

Make the wristwatch face large enough to be a cup holder.

Put to other uses

Frame the watch as a work of art.

Eliminate

Remove the internal workings of the watch and replace them with a sundial.

Reverse, rearrange

Change the watch hands to go counter-clockwise.
Put the watch face on the inside of the wristband to make the back of the watch the focal point in terms of design and fashion.

3

Discovery Skill #2: Questioning

“Question the unquestionable.”

—Ratan Tata, chairman, Tata Group

“ANY QUESTIONS?” MOST OF us have heard that phrase hundreds, if not thousands of times. Sometimes it comes at the end of a presentation or meeting, and most of us shuffle away because we don’t really think it is an open invitation to question. But other times, you may have real questions—about why things are the way they are and how they might be different—but you don’t ask them. You need to. If disruptive innovators occupied the same room, they would fill the empty space with thought-provoking questions. Why? Because questioning is how they do their work. It is the creative catalyst for the other discovery behaviors: observing, networking, and experimenting. Innovators ask lots of questions to better understand what is and what might be. They ignore safe questions and opt for crazy ones, challenging the status quo and often threatening the powers that be with uncommon intensity and frequency.

Take Orit Gadiesh, the famously inquisitive and inventive chairman of Bain & Company. As a child growing up in Israel, she was fascinated by many things and “always asking a hundred questions.” Her parents also encouraged her to ask questions when called on in class, and she did. So much so that her eighth grade teacher wrote in her yearbook: “Orit, always ask those two questions, and even a third and a fourth question. Don’t ever stop being curious.” When reading this teacher’s comment, Gadiesh realized for the first time that “asking questions was the true way to go.” Later in life, she relied on the same approach to cocreate client insights at Bain, knowing that “asking clients lots of questions is key to generating powerful solutions to problems.”

For example, in the early 1980s, Gadiesh was fresh out of graduate school and new at consulting. She was assigned to help a steel-manufacturing client cut its costs to stay competitive. During her first visit to the plant, she was warned by the over-sixty-year-old CEO that women were “bad luck in the industry.” Undaunted, she pressed forward with the client, asking question after question about why it was doing what it was doing. At the time, there were two ways to make steel, the standard process of pouring it into ingots or, alternatively, continuous casting (then, a new technology), where you literally cast the steel continuously and cut it into slabs.

After reading about the continuous-casting process and sensing its potential, Gadeish visited Japan to observe continuous casting firsthand. She left the country convinced that the new process could create significant value for her client. But the client’s executives and salespeople kept telling her that they couldn’t do it because they had three hundred fifty different products for customers and it was impossible to continuous cast that many products when you have to add other materials to the steel simultaneously. “The client was stubborn, completely convinced that they couldn’t make the change,” she told us.

Here’s where Gadiesh’s questioning skills best tackled the client’s problem. She went to visit customers and started asking questions, “Do you really need three hundred fifty products?” “Why do you need all three hundred fifty products?” Their initial autopilot answer was yes, but as she probed further with additional questions, it became clear that customers didn’t fully grasp the cost advantages that continuous casting offered due to its unique capacity to add other (lower-cost) materials during the steel-casting process. Working with the client and customers, Gadiesh literally went through each of the three hundred fifty products asking, “Why do you have this? What is its core importance?” to fully grasp why they made each thing they made.

Based on the rich information gleaned from asking a series of simple questions about why each product existed, Gadiesh naturally moved from understanding what was to exploring in depth what might be. She moved deeper into disruptive territory by asking fundamental questions such as: “What if we shrink the existing product line by 90 percent?” “What if we cast steel continuously with that sharply reduced product line?” “How might we maximize the addition of cost-saving materials when casting the steel?” Before long, the steel company executives realized that reducing the number of products from three hundred fifty to thirty not only was possible but was the most profitable course of action because it would give them a competitive advantage in the product segments in which they did compete. This allowed them to add other materials like aluminum (thus reducing costs) through a new continuous-casting process, while still meeting most of their key customers’ needs. The client (then a little over a billion-dollar enterprise) built a new production facility and quickly raced ahead of U.S. competitors.

Gadiesh’s ability to generate new insights is largely based on her ability to ask her way into what’s really going on and then push the edge with constant, provocative questions about what might be. At the core, she believes that “when you persist in asking questions throughout life—particularly challenging ones—it’s central to who you are and how you lead.” In fact, she shared with us that in a recent meeting with several heads of state and CEOs, she was curious as to why they weren’t asking more fundamental questions about key policy issues. One CEO confided to her: “When you’re in the room, I don’t have to ask the fundamental questions because I know they’re going to be asked.” Her deeply rooted instinct to ask has helped her successfully guide Bain Consulting for almost twenty years. It’s no wonder then that one of Gadiesh’s key steel industry clients once gave her a hard hat engraved with the phrase “A little light will lead us,” referring not only to her first name, Orit, which means “light,” but also to her light-generating questions that helped transform their business.

What Is “Questioning”?

Questions hold the potential to cultivate creative insights. Einstein knew this long ago as he often repeated the phrase, “If I only had the right question . . . If I only had the right question . . .”[1] No wonder he finally concluded that “the formulation of a problem is often more important than its solution” and that raising new questions to solve a problem “requires creative imagination.” In The Practice of Management, Peter Drucker grasped the same power of provocative questions, observing that “the important and difficult job is never to find the right answers, it is to find the right question. For there are few things as useless—if not dangerous—as the right answer to the wrong question.”[2] Recent research by Mihaly Csikszentmihalyi confirmed these personal convictions by finding that Nobel laureates were far better at achieving breakthroughs once they found the right question to reframe their problem.[3] Our research also found that disruptors rely on crafting the right questions to accomplish their work.

Questioning is a way of life for innovators, not a trendy intellectual exercise. Our research found that not only do innovators ask more questions than noninnovators, they also ask more provocative ones. (Innovators who “strongly agreed” with survey statements such as, “I often ask questions that challenge the status quo,” produced twice as many new businesses than innovators who simply “agreed.”) Among the different types of innovators we studied, product inventors showed the highest reliance on questioning to deliver results, followed by start-up and corporate entrepreneurs and, finally, process innovators. (See figure 3-1.)

FIGURE 3-1

Comparison of questioning skills for different types of innovators and noninnovators

Sample items:

1. Asks insightful “what if” questions that provoke exploration of new possibilities and frontiers.

2. Often asks questions that challenge the status quo.

By asking lots of questions, A. G. Lafley, for example, helped change the game at Procter & Gamble (P&G). Lafley often began conversations or meetings with: “Who is your target consumer here? What does she want? What do you know about her? What kind of an experience does she really want? What does she think is missing today?” Or when working within categories, Lafley often asked, “How well do you understand the different segments of consumers—not so much what we know about them demographically, but psychographically? What do we know about their biggest desires that aren’t met today? What are they most unhappy about today?”

After searching for a deep understanding of what is, Lafley shifted lines of inquiry to powerful what-if questions to help deliver customer-centric innovations. For example, if talking to someone about science and technology or a product need, he asked: “What else is available in the world? Where else might we access what we need? Who across P&G—thinking across our business units or outside of P&G—could help us get what we need in the time frame and cost structure that we want?” Most of all, Lafley was constantly hunting for counterintuitive questions. Instead of asking, “How can we help consumers get floors and toilets clean?” he would query, “How can we give consumers their Saturday mornings back?” He found the latter question far more fruitful for surfacing rich insights about what might be in order to develop new products and services that consumers would want to “hire” to get their jobs done at home. No wonder Lafley’s weekly question to himself is, “What will I decide to be curious about Monday morning?”[4]

How to Ask Disruptive Questions

Innovators constantly question common wisdom. Aaron Garrity, founder of XANGO (an innovative health and nutrition company), put it simply, “I am questioning, always questioning, with a revolutionary mind-set.” Innovators’ provocative questions push boundaries, assumptions, and borders. They leave few rocks unturned when they cultivate the garden. During interviews with disruptive innovators, we noticed not only a high frequency of questions but a pattern as well. They started with a deep-sea-like exploration of what currently is and then rocketed to the skies for an equally compelling search for what might be. Focusing on what is, they asked lots of who, what, when, where, and how questions (as world-class journalists or investigators do) to dig beneath the surface and truly “know the place for the first time” (as poet T. S. Eliot observed). They also invoke a series of what-caused questions to grasp the drivers behind why things are the way they are. Collectively, these questions help describe the territory (physically, intellectually, and emotionally) and provide a launching pad for the next line of inquiry. To disrupt the territory, innovators puncture the status quo with why, why-not, and what-if questions that uncover counterintuitive, surprising solutions. Whether descriptive or disruptive, innovators perpetually invoke powerful questions to help see beneath the surface of everyday action and discover what’s never been.

Describe the Territory

Innovators treat the world as a question mark, rarely working on autopilot and constantly challenging the accuracy of their mental maps about the territory (whether products, services, processes, geographies, or business models). Suspended comfortably between a faith in and doubt of their maps, the best innovators remember that their views of the world are never the actual territory. Intuitively, they rely on a rich assortment of questions to develop a deep understanding of how things really are, before probing intensely into what they might be.

Tactic #1: Ask “what is?” questions

Disruptive innovators leverage a variety of what-is questions to surface unexpected subtleties. For example, Pierre Omidyar’s work as a software architect (before founding eBay) sharpened his what-is questioning skills by focusing on user interfaces and trying to make software less complicated. (His first start-up was a pen-based computing application that attempted to make technology easier to use.) Using a blank-slate approach, Omidyar habitually watches others (for example, clients, customers, or suppliers) and wonders, “What are they really trying to do here?” He then follows up with all kinds of who, what, when, where, and how questions to dig beneath the surface.

Similarly, Dr. William Hunter, product inventor and start-up founder of Canadian-based Angiotech Pharmaceuticals, was intrigued by nontraditional ways that traditional drugs could be used. He ended up inventing the first surgical stent that was coated with a drug to reduce scar tissue (which causes up to a 20 percent failure rate compared to uncoated stents). His insight on coating stents came by changing the question traditional stent producers were asking, “How can we build a better stent?” to a more productive one, “What does the body do to these stents and why do they fail?” His relentless pursuit of the latter question ended up delivering a blockbuster product in the early 2000s.

In hot pursuit of what is, innovators inquire deeply for answers about what is happening right here and right now to gain understanding and empathy for others’ experience. IDEO (and other successful design firms) employs diverse questions about the physical, intellectual, and emotional terrain to obtain a rich three-dimensional view of how end users actually operate. Intuit’s Scott Cook also does this by asking fundamental questions such as, “Where is the real problem?” “What’s the person trying to achieve?” “What’s most important?” and ultimately, “What’s the real pain point?” Innovators like Cook know their questions work when they reveal what is and build empathy for how it feels. Such empathic understanding produces the deep understanding behind better what-caused and what-if questions.

Tactic #2: Ask “what caused?” questions

The next step in understanding the way things are is to ask causal questions to gain insights into why things are the way they are. To illustrate, Mike Collins, founder and CEO of the Big Idea Group (BIG) (a company that finds new product ideas through an inventor network and then launches them), shared an example of how inventors hunt down the real job to be done by understanding better what is really going on in their world. One inventor had pitched a fifteen-minute card game to Collins and his team for potential development and distribution by BIG. Collins felt that the game, as presented by the inventor, wouldn’t crack a tough family-gaming market. But instead of turning the inventor away, Simon Cowell–style, he paused and asked, “What caused you to develop this game?” The inventor quickly replied, by answering a series of implicit who, what, when, where, and how questions, that he had three children (who?) and little time after work (when?) to spend with them at home (where?). He wanted to have fun in the evening with his children (what?), but there was no time for games like Monopoly or Risk. He was in search of a fifteen-minute game that would do the job of connecting him with his children for a quick and enjoyable few minutes at the end of the day.

From Collins’s initial “what caused?” question, a series of answers to implicit who, what, when, where questions emerged that resulted in a successful line of “12 Minute Games” sold through Target. These games did the job many families needed at the end of a busy day or long week, and the insight to that job came by asking questions that gave simple, but critical, insights into what was really going on in the inventor’s life.

Are You Willing to Look Stupid?

So what stops you from asking questions? The two great inhibitors to questions are: (1) not wanting to look stupid, and (2) not willing to be viewed as uncooperative or disagreeable. The first problem starts when we’re in elementary school; we don’t want to be seen as stupid by our friends or the teacher, and it is far safer to stay quiet. So we learn not to ask disruptive questions. Unfortunately, for most of us, this pattern follows us into adulthood. “I think a lot of people don’t ask questions because they don’t want to look stupid,” one innovator told us. “So everyone sits around playing along as if they know exactly what is going on. I see this happen a lot—people go along because they don’t want to be the one to question the emperor’s nakedness [as in the story ‘The Emperor’s New Clothes’].”

The second inhibitor is a concern about looking uncooperative, or even disrespectful. EBay’s Omidyar admitted that others sometimes see him as being disrespectful when he questions their ideas or point of view. How can you overcome these inhibitors? One innovator gave the following advice, “I often preface my questions by saying ‘I like to be the guy that asks a lot of dumb questions about why things are the way they are.’” He says this helps him to detect whether it is safe to ask basic questions (that could seem dumb) or to question the way things are (without seeming uncooperative). The challenge for all of us is that there is a basic element of courage here, in being brave enough to be the one who says. “Wait, I don’t get it. Why are we doing it like this?”

Actually, the more powerful question behind our initial question, “Are you willing to look stupid?” really is, “Do you have sufficient self-esteem to be humble when you ask questions?” Over the years, we have found that great questioners have a high level of self-esteem and are humble enough to learn from anyone, even people who supposedly know less than they do. If this happens, they have learned to live the sage advice of Neil Postman and Charles Weingartner (early advocates of inquiry-based living and learning) where “once you have learned to ask questions—relevant and appropriate and substantial questions—you have learned how to learn and no one can keep you from learning whatever you need to know.”[a]

a. Neil Postman and Charles Weingartner, Teaching as a Subversive Activity (New York: Dell, 1969), 23.

Disrupting the Territory

After describing the territory well enough to thoroughly understand what is, innovators started their search for new, potentially disruptive solutions. They switched gears from descriptive questions to disruptive ones, like why, why not, and what if.

Tactic #3: Ask “why?” and “why not?” questions

Innovators persistently leverage why and why-not questions to acquire critical insights. Jeff Jones, founder of Campus Pipeline (a Web platform that helps universities securely integrate campus communication and resources) and NxLight (an IT tool for simplifying the management of complex intercompany transactions by easily and securely exchanging documents), grasps this fact well, concluding: “Once you discover that asking why in a different way and not being content with what the answer is, it’s interesting what happens. You just have to go a little bit deeper asking questions one or two more times in a different way.” This is exactly what disruptive innovators do to discover new business ideas.

Consider the example of Edwin Land, cofounder of Polaroid.[5] During a vacation with his family, Land took a picture of his three-year-old daughter. She could not immediately see the picture he had taken of her and wanted to know why. And, like most young children, probably asked why more than once. Her simple question pushed Land, an expert in photographic emulsions, to think deeply about the possibilities of “instant” photography. Why couldn’t she see the picture immediately? What would it take for instant photography to be a reality? Within a few hours, the scientist developed the basic insights that would eventually produce instant photographs, a product that would transform his company and disrupt an entire industry. In effect, his child’s naive question challenged industry assumptions and transformed Land’s technical knowledge into a revolutionary product—the Polaroid camera. This industry-changing camera delivered incredible impact between 1946 and 1986, ultimately selling over 150 million units and an even higher volume of expensive film packs for use in the cameras.

Similarly, David Neeleman, founder of JetBlue and Azul airlines, says that one of his strengths “is an ability to look at a process or a practice that has been in place for a long time and ask myself, ‘Why don’t they do it this other way?’ And sometimes I find myself thinking the answer is so obvious that I wonder, ‘Why has no one else ever thought of this before?’” For example, Neeleman’s first start-up was a charter airline called Morris Air. At the time, airline tickets were treated like money; if you lost your ticket, it was like losing cash. This created problems for travelers as they dealt with the challenges of lost tickets and for airlines as they tried to send tickets securely to travelers. One day, an employee was complaining about a ticket problem, prompting Neeleman to ask, “Why do we treat tickets like cash? Is there a better way?” This question sparked an idea, “Why not give customers a code when they buy a ticket that they could give us at the airport with their identification?” This idea led to the creation of e-tickets, an idea that eventually spread throughout the industry after Southwest Airlines purchased Morris Air.

In his most recent venture, Azul, Neeleman asked his senior team, “Why aren’t more Brazilians taking advantage of Azul’s low fares?” Azul’s flights were cheaper than the competition, but his question surfaced the real challenge—getting price-sensitive customers to the airport. Then Neeleman asked, “How much does a cab cost for our typical customer to get to the airport?” The answer was “too much,” potentially 40 percent to 50 percent of the airline ticket cost. So Neeleman searched for lower-cost bus or train alternatives, but they were either nonexistent or too infrequent. This prompted him to then ask, “Why not start our own free bus service to get customers to the airports?” (to take advantage of Azul’s inexpensive fares). Today, passengers book (mostly online) over three thousand bus rides per day to the airport with Azul, the fastest-growing airline in Brazil.

In Asia, Taiichi Ohno, a former engineer at Toyota who is known as the chief architect of the Toyota Production System, put a five-whys questioning process—a technique for asking “what caused” questions—at the core of his innovative production system. The five-whys process requires that when confronted with a problem, one should ask why at least five times to unravel causal chains and come up with innovative solutions. Many of the world’s most innovative companies have adopted variations of the five-whys process to push employees to ask why as they search for a better understanding of what is and new responses to what might be.

Tactic #4: Ask “what if” questions

Meg Whitman of eBay has worked directly with a number of innovative entrepreneurs and founders, including Omidyar (eBay), Niklas Zennström and Janus Friis (Skype and Kazaa), and Peter Thiel and Elon Musk (PayPal). When asked how these folks differ from typical executives, Whitman replied, “My experience is that they get a kick out of screwing up the status quo. They can’t bear it. So they spend a tremendous amount of time thinking about how to change the world. And as they think and brainstorm, they like to ask, ‘If we did this, what would happen?’”

Omidyar is a perfect example. As a systems analyst, he designs end-user interfaces from the ground up with no preconceived way of doing things. To do this, Omidyar probes deeply by asking a series of questions that work from a blank-slate perspective, such as, “What would be the cleanest way to solve it?” He sees himself as “the devil’s advocate in the room saying things like, ‘What if it really didn’t work this way? Or what if we really did do the opposite of this? What would happen then?’”

In sharp contrast to disruptive innovators, delivery-driven executives in our research were far less likely to ask what-if questions that challenged their company’s strategy or business model. Data from our 360-degree survey assessments of executives around the world revealed that most managers do not regularly question the status quo (though they often think they do). They prefer routine to rocking the boat and adhere to the adage, “If it ain’t broke, don’t fix it.” But innovators actively look for things that are “broke” and activate a pattern of what-if questioning to surface new angles of inquiry. One technique that innovators use when imagining the future is to ask what-if questions that either impose constraints or eliminate constraints.

Ask “what if” questions to impose constraints. Most of us constrain our thinking only when forced to deal with real-world limitations, such as shrinking budgets or technology restrictions, but innovative thinkers do the opposite. Google’s Marissa Mayer, vice president of search products and user experience, says: “Creativity loves constraint. People often think of it in terms of artistic work—unbridled, unguided effort that leads to beautiful effect. If you look deeper, however, you’ll find that some of the most inspiring art forms—haikus, sonatas, religious paintings—are fraught with constraints. They’re beautiful because creativity triumphed over the rules . . . Creativity, in fact, thrives best when constrained.”[6]

Questions that artificially impose constraints can trigger unexpected insight by forcing people to think around the constraint. To initiate a creative discussion about growth opportunities at one company in our study, an executive asked this question: “If we were legally prohibited from selling our current products to our current customers, how would we make money next year?” This constraining question led to an insightful exploration of ways the company could find and serve new customers.

Variations of the same question can provoke surprising ideas. For example, you and your team might ask:

1. If the disposable income of our current customers (or our budget) dropped by 50 percent, how would our product or service have to change?

2. If air transportation was no longer possible, how would we change the way we do business?

Asking questions that place constraints on solutions forces out-of-the-box thinking because it ignites new associations. This is precisely what Apple did to come up with the iPod (“What if we created an MP3 player that could fit in a shirt pocket but hold five hundred to a thousand songs?”) and highly successful experience-centered retail stores (“What if we used a regular-sized retail store to sell a very small number of Apple-only products?”

Likewise, Hindustan Lever (Unilever’s business in India) wondered how it could reach millions of potential consumers in small Indian villages where severe constraints existed: no retail distribution network, no advertising coverage, and poor roads and transport. Collectively these constraints challenged its existing business model and produced a fundamental question: “How might we sell products in small villages without any access to traditional distribution networks, advertising, or infrastructure?” The answer ultimately surfaced from direct-selling business models (from companies like Avon). In close partnership with nongovernmental organizations, banks, and the government, Hindustan Lever recruited women in self-help groups across rural India to become direct-to-consumer sales distributors for its soaps and shampoos. The company also provided substantial training for them to succeed as micro-entrepreneurs. (By 2009, the innovative solution in a highly constrained country context produced over forty-five thousand women entrepreneurs selling Hindustan Lever products to three million consumers in a hundred thousand villages.[7]

Ask “what if” questions to eliminate constraints. Great questions also eliminate the constraints that we can unnecessarily impose on our thinking due to a focus on resource allocations, decisions, or technology limitations. To counter this tendency, one innovative CEO finds these questions key to eliminating unwanted sunk-cost constraints: “What if you had not already hired this person, installed this equipment, implemented this process, bought this business, or pursued this strategy? Would you do it today?” Jack Welch often posed the same kinds of questions during his two-decade tenure as GE’s CEO. Questions like these quickly and effectively toss sunk costs (financial and nonfinancial) right out the window.

Another approach to relaxing constraints surfaces in this question: “What if X technology were available to every consumer? How would it change consumer behavior?” With a slight twist on this query, RIM’s Lazaridis likes to look five years ahead. He persistently asks questions such as, “What CPUs will be available? What LCD technology? What keyboard? Mouse?” Once he gets the best answers possible to these questions, he then starts the more predictable graphical and industrial design work on the next generation of BlackBerry products.

After returning to Apple in the mid-1990s, Steve Jobs relaxed constraints by asking, “What would you do if money were no object?” prompting the creation of new products or services.[8] This kind of question assumes that the pursuit of excellence at Apple occurs independent of outside constraints, including customers’ current preferences or the cost of providing exactly what customers might want. Now as a board member at Disney, Jobs pushes the same message further, admonishing people to “dream bigger” as they redesign Disney retail stores to now include one sales area labeled, “WWTD: What Would Tinker Bell Do?”[9]

Questioning Dilemmas for Senior Leaders

When it comes to status quo–challenging questions, leaders (particularly CEOs) face two key dilemmas. The first is that top executives are generally rewarded for generating better strategies or new business models, but they are also punished if they publicly question their firm’s own strategy or existing business model. CEOs are expected to provide answers, not questions, to key external and internal stakeholders. One CEO told us, “If I openly question our strategy or key initiatives, this could create a crisis of confidence within the company. People don’t like that kind of uncertainty.” Senior executives know, as researchers David Krantz and Penelope Bacon do, that “to question an act, belief, or experience runs the risk of disrupting the activity.”[a] When this happens, financial markets worldwide are generally unforgiving and punish such disruptions, at least in the short run.

The second dilemma for leaders is that it’s difficult for people in the organization to ask the top boss questions that challenge the status quo. After all, the CEO may have reached his position by creating the status quo. So while CEOs may be in the best position to ask and respond to questions, they actually face major constraints in asking and receiving questions that challenge the status quo. As a result, it is no small feat for a CEO to create a culture that fosters the kind of questioning that produces innovative outcomes, particularly new businesses and business models.

Many innovative founders and CEOs address the first dilemma by cultivating an informal network of people whom they can question, and who will question them. For example, an innovative CEO at a major multinational firm told us that he has formed an informal, unofficial group of confidantes. “It’s a fairly senior, fairly seasoned set of people who are comfortable throwing out ideas and then forgetting about them if these hunches or speculation aren’t right,” he said. “I can ask any question of these folks and they’ll give me a straight answer.”

Tackling the second dilemma is a little trickier as the challenge can be culturally sensitive. In some country—and company—cultures, you simply don’t question the boss. For example, cross-cultural research suggests that eight in ten Japanese would agree with the following statement about the role of leaders: “It is important for a manager to have at hand the precise answers to most of the questions his or her subordinates may raise about their work.”[b] The result is that Japanese leaders are expected to deliver answers to their people, not questions, particularly status quo–challenging ones. But a company or country culture that fails to encourage questioning sounds the death knell for disruptive innovation. Regardless of the cultural context, CEOs hoping to generate innovative ideas must make clear that leadership requires asking questions that challenge the way things are, even if such practices were established by the CEO on the way to the top!

a. D. L. Krantz and P. Bacon, “On being a naïve questioner,” Human Development 20 (1977): 141–159.

b. N. J. Adler, N. Campbell, and A. Laurent, “In search of appropriate methodology: From outside the People’s Republic of China looking in,” Journal of International Business Studies 20 (1989): 61–74.

Questioning as a Potential Turbocharger

Questions are a critical catalyst to creative insights. Yet, questions alone do not produce innovation. They are necessary, but insufficient. In the absence of active observation, networking, or experimentation, theoretical innovators become what sportswriters in the United States might refer to as armchair quarterbacks. They ask clever questions from the sidelines and may naively believe that one or two magical questions will surface disruptive ideas, but they rarely, if ever, play in the real-life game of innovation.

We found that innovators were more likely to successfully launch innovative products, services, or businesses when they combined an ongoing instinct to formulate and ask the right questions with other innovator’s DNA skills. In other words, leaders who ask questions as they observe discover more than those who don’t. Leaders who ask questions as they network for new ideas discover more than those who don’t. Leaders who ask questions as they experiment discover more than those who don’t. Ultimately, questioning combined with the other discovery behaviors can truly turbocharge your innovation results.

Changing our questions can change the world. The key is constantly creating better questions to see that world through new eyes. When this happens, we will find ourselves living the profound observation that Jonas Salk (discoverer of the first polio vaccine) made that “you don’t invent the answers, you reveal the answers” by “finding the right question.”

We hope our framework for surfacing the right questions can help you along your innovation journey. Start by probing what is and then pursuing what if, particularly what-if questions that impose or eliminate constraints. But remember the framework is not the end, but the means. It is the first step to getting new ideas that might succeed, not a surefire prescription for successful ones. The next three chapters provide further insight into other concrete actions we can take to help improve the questions we ask and, in the end, reveal potentially disruptive solutions to difficult problems.

Tips for Developing Questioning Skills

Innovators not only ask provocative questions, but constantly work at asking better ones. For example, Michael Dell says that if he had a favorite question to ask, everyone would anticipate it, which wouldn’t make it very good. “Instead, I like to ask people things that they don’t think that I’m going to ask them,” he told us. “I kind of delight in coming up with questions that nobody has the answer to quite yet.” To consistently craft better questions, here are a few of our favorite tips.

Tip #1: Engage in QuestionStorming

A few years ago, we stumbled across an incredibly valuable questioning tool. We were teaching a graduate business school class and found ourselves stuck on a particular problem, unable to find any further insight through a typical brainstorming process. One of us suggested taking a time-out from the process and focusing our collective energies on only asking questions about the problem, instead of trying to construct another set of solutions. Much to our surprise, the questions-only approach dug much deeper into the fundamental elements of the challenge and opened everyone’s eyes to a new understanding of the problem.

Since that first questions-only exercise, we have worked with individual executives and teams of executives over the years to develop a process we now call QuestionStorming.[10] We all know about brainstorming, a process in which you get together as a team and brainstorm solutions to a problem. QuestionStorming is similar, but instead of focusing on solutions, you brainstorm questions about the problem.

Here’s how it works. First, as an individual or team, identify a personal, work unit, or organizational problem or challenge to solve. Then write down at least fifty questions about that problem or challenge. (If you’re dealing with a work unit or organizational problem, it is preferable to generate these questions with a team and write all of the questions on a white board for everyone to see.) We suggest a couple of extra rules when doing this as a team: Generate only one question at a time. Have one person write the questions down so that everyone can see and reflect on each question being asked. No one can ask a new question until the last one is completely written down. This helps the group build on prior questions to generate better queries about the challenge. Prod each other to ask a full range of what is, what caused, why and why not, and what if questions during the exercise.

It’s important to follow some other rules. When capturing the questions, discipline yourself or your team to simply ask the question without offering a long preamble as a setup. Ruthlessly facilitate the focus on questioning until you have at least fifty questions (in other words, don’t tolerate answers; simply reinforce the importance of only asking questions about the problem or opportunity). After a possible stretch of initial silence (as your team might struggle to formulate new questions about the issue), most teams engage in an even deeper inquiry about the real root causes of the problem or dimensions of an opportunity to see them in a new light. After listing the questions, prioritize and discuss the most important or intriguing ones in your search for better solutions. You may want to assign an individual or team to attempt to answer the most important questions (probably through observing, networking, or experimenting) before having the group brainstorm solutions.

We have found that individuals who frequently engage in personal QuestionStorming about challenges facing their work unit, organization, industry, customers, suppliers, and so on are more likely to be viewed as creative, innovative, or strategic thinkers. One executive in a large pharmaceutical company started writing down questions for fifteen to twenty minutes each morning before work. Three months later, his boss told him that he had become the best strategic thinker in his business unit. Six months later, he was promoted. Practice does make perfect, or at least better, when it comes to questioning. So if your “questioning muscles have atrophied,” as Ahmet Bozer (Eurasia and Africa Group president at Coca-Cola) recognized after a recent QuestionStorming workshop with his senior team, “it’s time to start exercising those muscles.”

Tip #2: Cultivate question thinking

When identifying problems or challenges, we often describe them as statements. In fact, we often ask groups of executives to identify their top-three challenges. As they wrestle with the task and identify these challenges, they typically frame them as statements. We then give the group an additional five to ten minutes to reformulate their top-three challenges into their top-three questions (about leading innovation effectively, for example). We have found that actively translating statements into questions not only helps sharpen problem statements, but also evokes more personal responsibility for the problems and moves them to take more active next steps in the pursuit of answers.

Tip #3: Track your Q/A ratio

Disruptive innovators we interviewed consistently displayed a high Q/A ratio, where questions (Q) not only outnumbered answers (A) in a typical interaction, but good questions generated greater value than good answers. To check your current Q/A ratio, observe and assess your questioning and answering patterns in a variety of contexts. For example, in the last work meeting you attended or directed, what percent of your comments were questions? Keep a record of your Q/A ratio (percent of comments made that fall into each category) during meetings you attend in the coming week. When reviewing self-observations, you might ask what was your personal Q/A ratio? How many questions did you ask? Work to increase your Q/A ratio by reflecting on what questions were asked and then asking yourself, “What are the questions that aren’t obvious or are not being asked?”

Tip #4: Keep a question-centered notebook

To generate an even richer repository of questions, take time to capture your questions regularly. Richard Branson does this in notebooks “full of questions.” Review the questions periodically to see how many and what kinds of questions you’re consistently asking (or not asking). Table 3-1 can help you see what types of questions you might consider as you observe, network, and experiment to generate new ideas.

TABLE 3-1

Disruptive innovator’s question check-up

As you keep your notebook, take a moment to reflect on the following:

- What are your questioning patterns? What kinds of questions do you focus on?

- What questions yield unexpected insights into why things are the way they are?

- What questions surface fundamental assumptions and challenge the status quo?

- What questions generate strong emotional responses (a great indicator of challenging the way things are)?

- What questions guide you best into disruptive territory?

4

Discovery Skill #3: Observing

“Observation is the big game changer in our company.”

—Scott Cook, founder, Intuit

MOST INNOVATORS ARE intense observers. They carefully watch the world around them, and as they observe how things work, they often become sensitized to what doesn’t work. They may also observe that people in a different environment have found a different—often superior—way to solve a problem. As they engage in these types of observations, they begin to connect common threads across unconnected data, which may provoke uncommon business ideas. Such observations often engage multiple senses and are frequently prompted by compelling questions.

Consider, for example, how Ratan Tata, chairman of India’s Tata Group, gained a powerful insight that inspired the world’s cheapest car, the Tata Nano. Throughout Tata’s life, he had seen thousands of families riding scooters in India. On one very rainy day in Mumbai, India, in 2003, however, he noticed a lower-middle-class man riding a scooter with an older child standing in the front, behind the handlebars. The man’s wife sat sidesaddle on the back with another child on her lap. All four were soaked to the bone as they hurried home. Tata saw with his eyes and listened with his heart to notice what he had previously failed to notice. He asked himself, “Why can’t this family own a car and avoid the rain?” Or, put another way, he thought about a job that needed doing (in this case, the job was to create safe, affordable transportation for a family that could not afford to buy a car, but could buy a scooter).

This singular observation sparked several provocative questions about the possibility of creating an affordable “people’s car.” “The two-wheeler observation [with the family of four piled on the scooter] got me thinking that we needed to create a safer form of transport,” Tata recalls. “My first doodle was to rebuild cars around the scooter, so that those using them could be safer if it fell. Could there be a four-wheel vehicle made of scooter parts?” Tata gathered a small group of engineers to design a low-cost vehicle with four wheels. The initial design had two soft doors with vinyl windows, a cloth roof, and a metal bar as a safety measure. But after seeing the initial designs, Tata and his group concluded that the market wouldn’t want a “half car.”

After several subsequent years of observation and experimentation by the Nano product development team, Tata’s dream became a reality in 2009. Priced at $2,200, Nano was launched as the world’s cheapest car. It generated two hundred thousand orders in the first few months after its launch, and its numerous innovations (including thirty-four patent applications) made it India’s Car of the Year in 2010. Designed with a rear-mounted engine, the Nano can be assembled from kits at dealerships, much like motorcycles are in the United States. This approach may disrupt the entire automobile distribution system in India. And it all started one rainy day in Mumbai when Tata was actively observing on his ride home, rather than simply focusing on his destination.

Tata experienced what some people have referred to as vuja de. Déjà vu, of course, refers to a strong sense that you have seen or experienced something before, even if you haven’t. Vuja de is the opposite—a sense of seeing something for the first time, even if you have actually seen it many times before.[1] Applying the principle of vuja de, Tata was able to “see” what had always been there before but had gone unnoticed or at least had not inspired anyone to act on it.

But Tata’s initial observation—that many lower to middle-income Indians would benefit from being able to purchase an affordable car—is only the part of the story. Let’s examine how Ratan Tata used customer observations to help Tata sell those $2,200 Nanos. As mentioned, he got the idea for the Nano by watching Indian families ride scooters in the rain. He knew that the rural villages of India were a large market for scooters, so he wanted to learn how Tata could sell the Nano in those villages to replace the scooters. So he sent a team out to observe how Indians in the rural areas purchased scooters. The team made some interesting observations that led to a very different way to sell cars in the villages.

First, the team observed that people did their major shopping on Sundays at farmers’ markets or flea markets. There were no permanent scooter or car dealerships. Scooter dealers arrived in a big truck filled with scooters and just stuck them in rows on their allocated piece of ground at the market. People would buy a scooter, get a license, learn how to operate it, and then drive it home that same day. So the Tata team brought in forty Nanos and put them in the open-air market. They quickly found that customers didn’t just walk up, buy a car, and drive it home. First, just as in urban areas, many customers needed financing, so Tata had to offer financing. But in order for people to drive away in a Nano, the team learned that the customer needed to have insurance available on the spot. So Tata had to offer insurance. Even more importantly, the team learned that most customers didn’t have a driver’s license, so Tata had to offer a driver’s education class—and a way to get a license—right there at the market. So Tata ended up providing all these services in sequence so that within two to four hours a customer could pick out a car, have it insured and financed, receive training on how to operate it, get a driver’s license, and finally register the car. Intense observation was the only way Tata could see how to fully meet the needs of a rural Indian who wanted to buy and drive a car.

A Framework for Observing: Look for the “Job” and a Better Way to Do It

IDEO’s Tom Kelley, author of The Art of Innovation, has written that “the Anthropologist’s role is the single biggest source of innovation at IDEO.”[2] Why does he believe this? Anthropologists have developed techniques to study humans in their natural environments and learn from their behavior. Pretending that you are an anthropologist can be especially powerful when you watch someone in a particular circumstance trying to “do a job,” to use Clayton Christensen’s terminology in The Innovator’s Solution. Christensen has argued that customers—people and companies—have “jobs” that arise regularly and need to get done. When customers become aware of a job that they need to get done, they look around for a product or service that they can “hire.” When people have a job to do, they set out to hire something or someone to do the job as effectively, conveniently, and inexpensively as possible. Observing someone in a particular circumstance can lead to insights about a job to be done—and a better way to do it.

Tata’s experience with the Nano illustrates this idea. Ratan Tata’s initial observation of the Indian family on a scooter in the rain led him to realize that the scooter wasn’t doing a very good job at transporting the family in a safe or dry manner. They needed a vehicle like a car that would provide more protection. This led to years of experimenting to create an affordable car that would be within reach of these middle-class families. But just being able to build an affordable car wasn’t enough. To truly put Indian customers in the driver’s seat, Tata needed to provide a set of complementary services that were critical to a customer’s ability to buy a car, finance it, insure it, learn to operate it safely, and then drive it home. Tata’s success was borne of two types of observations: one about the job to be done (transport families safely in a vehicle they could afford) and one about how to actually put a middle-class Indian in the driver’s seat (take the cars to the village markets and provide the necessary services so the customer could operate the vehicle within a single day).

Understanding the Job to Be Done

Every job has a functional, a social, and an emotional dimension, and the relative importance of these elements varies from job to job. For example, “I need to feel like I belong to an elite, exclusive group” is a job for which consumers hire luxury-brand products such as Gucci and Versace. In this case, the functional dimension of the job isn’t nearly as important as its social and emotional dimensions. In contrast, the jobs for which they might hire a delivery truck are dominated by functional requirements. Understanding the functional, social, and emotional dimensions of a job to be done can be quite complex, but may be key to an innovative solution.

For example, we hire schools to educate young people in our society and often criticize them for not doing the job well. The question we typically ask is, “Why aren’t schools performing as well as they should?” Perhaps a key reason we’re dissatisfied with the state of public K–12 education is that we’ve been asking the wrong question. If we asked instead, “Why aren’t students learning?” we might discover things that others do not yet perceive. A key reason why so many students languish unmotivated in school or don’t come to class at all is that education isn’t a job that they are trying to do. They mainly want to feel successful and to have fun with friends, meeting important social and emotional needs each day. No wonder some students drop out of school to hang out in gangs or cruise in cars with friends, since these activities often do the job better than school.

By understanding well the particular social and emotional needs of high school students (the jobs these students want done every day), the MET school, a charter school in Providence, Rhode Island, designed a project-based curriculum where students work together each day on various projects (containing elements of the Montessori method which provides “hands on” interactive learning experiences). This approach gives students an opportunity to have fun with friends while feeling a sense of accomplishment because they can see how their efforts move a project toward completion. They hardly realize they are developing new skills as they complete their tasks on the projects. By better meeting the students’ social and emotional needs, the school motivates students to participate and learn. This illustrates how the jobs-to-be-done framework applies as much to services as to products and how important it is to look beyond the functional job to be done.

In similar fashion, Scott Cook founded Intuit, maker of the popular financial software Quicken and QuickBooks, based on two key observations. The first was a simple observation within his home. He hit on the idea for Quicken by watching his wife work on their finances and hearing her complain about how frustrating and time consuming it was. “She’s got a good mind for math and is quite organized, so she handles the bills for us,” Cook said. “But she frequently complained that it was a waste of time and bookkeeping was a hassle. So it was that observation combined with an understanding of what personal computers could do well and not do well that started Intuit.”

What, we asked Cook, did he mean by separating out what computers “could do well and not do well”? His answer told us something about his observation skills and how he hit on a better way to do the job of managing personal finances. In 1981, he began watching what Apple was doing with its Lisa computer. “I got a buddy of mine who worked at Apple to show me the Apple Lisa before its launch,” he recalled. “The Lisa wasn’t trying to do financial software at all, but that graphical user interface [the mouse and drop-down menus] was amazing.” Following the meeting, he drove to the nearest restaurant and sat down with a pad of paper. He wrote out the various insights that he’d gained from watching the concept of the graphical user interface.

Cook’s observation convinced him that not only could the Lisa perform repetitious financial functions, but that its easy-to-use mouse and drop-down menus would allow the average person to use a computer. He was completely intrigued by the concept of making the items on a computer screen “work just like their real-world counterparts.” (For example, a Quicken electronic check looks just like a paper check.) By building a software program that acted a lot like what people do in their daily lives, Intuit grabbed over 50 percent of market share the year after it was introduced.

Like Cook, we have found that observing is a key discovery skill for most innovators who tend to generate business insights from one of two types of observations:

1. Watching people in different circumstances who are trying to do a job and gaining insight about what job they really want to get done.

2. Observing people, processes, companies, or technologies and seeing a solution that can be applied (perhaps with some modification) in a different context.

Mike Collins (founder and CEO of the Big Idea Group) claims that successful product innovators always have their observation skills turned on. “Observation isn’t just a one-‘aha’ day. Innovators are observing the world around them and asking questions all the time. It’s part of who they are. For other people, it is an untapped skill.” Collins knows what he is talking about. As founder of BIG, a company that uses the American Idol (or Britain’s Got Talent) business model to screen the best ideas of inventors and then take them to market, Collins has worked with over a thousand inventors who are part of the BIG network. We found that product innovators boast the best observing skills among innovators, followed by start-up and corporate entrepreneurs, and finally process innovators. Innovators score at around the seventy-fifth percentile for observing, while noninnovators score at around the forty-eighth percentile. (See figure 4-1.)

FIGURE 4-1

Comparison of observing skills for different types of innovators and noninnovators

Sample items:

1. Gets new business ideas by directly observing how people interact with products and services.

2. Regularly observes the activities of customers, suppliers, or other companies to get new ideas.

How does someone develop the observing skill if it is currently untapped? To discover what innovators do, we asked them, “What makes someone a good observer? How can someone get better at observing?” We have found that observers are more successful at figuring out jobs to be done and better ways to do them when they: (1) actively watch customers to see what products they hire to do what jobs, (2) learn to look for surprises or anomalies, and (3) find opportunities to observe in a new environment.

Actively Watch Customers—and Look for Workarounds

Perhaps the most obvious way to get business insights through observing is to actively watch people as they hire products to do jobs and then see what insights you can gain about the job to be done. For example, Gary Crocker, founder of the medical device firm Research Medical Inc. (acquired by Baxter International), got the idea for some “plumbing” devices that could help surgeons perform heart bypass surgery after observing them do what was very new surgery at the time. He noticed the cardiovascular monitoring catheters that were threaded into the heart to measure blood pressure, but he also noticed that there weren’t any good “plumber tools,” to manage the flow of blood. “There weren’t really big catheters that would take all the blood out of the body and take it into the oxygenator when your lungs and heart are shut down during surgery,” Crocker said. “There wasn’t a well-structured plumbing line. So I thought I could create a product like that. That’s a nice little niche.”

So Crocker eventually left Baxter to start a company that created a variety of specialized devices to control the flow of blood during cardiac surgery. One device, Visuflo with Light Source, addressed the challenges of operating on bleeding sites in beating-heart surgery by blowing a stream of filtered, humidified air onto the suture site to remove unwanted blood flow that compromised the surgeon’s visibility. The device also enhanced visibility by providing an ancillary light source that could be directed into the surgical opening. Without these devices, surgeons would come up with their own ways to get more light into a surgical opening (for example, have a nurse shine a separate light into the opening) or their own techniques to remove unwanted blood flow (for example, trying different suction devices to remove blood). The insights for Crocker’s innovative devices came only after carefully observing the challenges that surgeons faced as they performed cardiac surgery and the workarounds they developed to solve those problems.

The term workaround originated in the IT world where programmers had to “work around” a particular problem in the system. The concept applies equally well to other domains. A workaround is an incomplete or partial solution to a particular job to be done. When you notice a workaround, pay attention, as it might provide clues for how to create an entirely new product, service, or business to do the job.

For example, OpenTable.com is a more comprehensive solution to the workarounds that we typically use when trying to have a great dining experience (the job to be done). The key elements include finding a restaurant that offers the desired quality of food and atmosphere, reserving a table at a convenient time without a wait, and getting a reasonable price for the meal. Finding the right restaurant often involves asking for referrals or reading restaurant reviews. After finding the right restaurant, you then call to make a reservation. If the restaurant doesn’t take reservations or has no reservation available, then you start the process again. You might even simply go to the restaurant early—or possibly send someone to wait in line for you—in order to ensure you get a table or to minimize waiting time. If you are price sensitive, you might look for coupons online or in the newspaper to get a better price for your dining experience. All these activities take time and still don’t ensure a great dining experience.

Chuck Templeton, founder of OpenTable.com, witnessed these workarounds firsthand in 1998 when his wife spent 3.5 hours trying—without any luck—to get reservations at a desirable restaurant when his in-laws visited them in Chicago. So Templeton launched an online app that is essentially your own restaurant concierge service: it allows customers to quickly and easily find a restaurant they might like (by providing insightful reviews and customer ratings), get a reservation at a convenient time (by allowing customers to see table availability and book their own reservation), and even have access to discounted meals (by giving points for meal discounts). Restaurants pay OpenTable $199 per month for the reservation service (to essentially rent a computer terminal and Internet connection) and a $1 fee for every diner who lands at their restaurant through the system. By doing a better job of helping customers have a great dining experience, OpenTable now dominates the dining reservation process in most large U.S. cities and in many others abroad (with over eleven thousand restaurants in its system worldwide).

While watching people trying to do a job to gain insights for new product or service offerings seems straightforward, most company managers spend little time in this simple, commonsense approach. But when companies uncover the hidden needs of the customer through observation (whether it be serendipitous observation, live-in immersion, or video observation), they gain insights that can prove extremely valuable. IDEO’s Kelley reports that when designing a new kids’ toothbrush for Oral-B, IDEO went out in the field to watch kids brush their teeth. What it noticed was that kids’ toothbrushes were just smaller versions of adult toothbrushes, which proved to be a challenge for them to hold and maneuver because they lacked the dexterity of their parents. This led to an innovative design: big, fat, squishy toothbrushes that were much easier for kids to hold and use. The result? Oral-B had the best-selling kids’ toothbrushes in the world for the next eighteen months.

Ten Questions to Ask While Observing Customers

Here are ten questions you should ask while observing customers to better understand the job they want done and how you can offer a product or service that will help them do it better.

1. How do customers become aware of a need for your product or service? Is there a way to make it easier or more convenient for them to find your offering?

2. What do customers really use your product or service for? What job is the customer hiring your product or service to do?

3. What does the customer ultimately consider as the most important features when selecting a final product or service? (If the customer has a hundred points to allocate across all the features he considers important, how would he allocate them?)

4. How do consumers order and purchase your product? Is there a way you can make it easier, more convenient, or less costly?

5. How do you deliver your product or service? Can you do it faster, cheaper, in a completely different way?

6. How do customers pay for your product or service? Is there a way to make it easier or more convenient?

7. What frustrations do your customers have when trying to use your product? Do they use your product in ways you didn’t expect?

8. What do consumers need help with when they use the product?

9. Do customers do things that hurt the longevity or reliability of your product or service?

10. How do customers repair, service, or dispose of your product? Are there opportunities to make this easier or more convenient (or teach the customer how to use the product so it requires less maintenance or to do self-maintenance)?

Look for Surprises

At Intuit, Cook asks his marketing and software engineers to observe customers in their homes as they load and attempt to use Quicken and QuickBooks software. As they watch customers use the product, he asks them “to savor the surprises”—the things that seem unusual or the times when people don’t behave as they are supposed to. For example, Cook tells them: “When you see something unexpected, you need to ask, ‘Why did you do that? Well, that doesn’t make sense. I never expected that.’” Customers often have to find workarounds—meaning they may use the product in unintended ways—and these surprising workarounds often provide clues as to why the current product or service is an incomplete solution. Cook claims that you have to consciously be looking for surprises—the unexpected—because they are typically lost as our minds conform what we see to fit our preexisting beliefs. To battle that tendency, Cook says that “at Intuit we teach our people to ask these two questions as they observe: What is surprising? What is different from what you expected? That’s where true learning and innovation starts.”

The Value of Anomalies in Scientific as Well as Commercial Innovation

Many years ago, Thomas Kuhn, in his landmark book on the history of science, The Structure of Scientific Revolutions, essentially argued that scientific breakthroughs happen—and new and improved theories emerge—when a researcher observes the world well enough to identify and explain an anomaly.[a] The discovery of an anomaly—a surprise—gives scientists the opportunity to revisit a particular theory in an attempt to better understand it. This often leads to a modification or improvement of the theory by understanding and explaining the anomaly. For example, in research on the impacts of technological innovation on the fortunes of firms, early studies concluded that established firms, on average, do well when faced with incremental innovation, but stumble when confronted with radical change. But there were anomalies to this general conclusion. Some established firms successfully implemented radical technology change.

To account for these surprises, Michael Tushman and Philip Anderson (1986) offered a unique, new categorization: competency-enhancing versus competency-destroying technological changes.[b] This resolved many anomalies, yet subsequent researchers continued to uncover new ones that the Tushman-Anderson scheme could not explain. Rebecca Henderson and Kim Clark’s (1990) categories of modular vs. architectural innovations; Clayton Christensen’s (1997) categories of sustaining versus disruptive technologies; and Clark Gilbert’s (2005) threat-versus-opportunity framing each surfaced and resolved anomalies that prior scholars’ work could not account for. Understanding and explaining the anomalies yielded original insights for the researchers.

Kuhn’s bottom line: scientific researchers who seek to reveal and resolve anomalies tend to advance their fields more productively than those seeking to avoid them. Thus, observing anomalies in scientific endeavors is as valuable as observing surprises in commercial endeavors is. Identifying surprises or anomalies—what isn’t what you expected—may be the key to unlock the door to your innovation.

a. Thomas S. Kuhn, The Structure of Scientific Revolutions (Chicago: University of Chicago Press, 1962).

b. Michael L. Tushman and Philip Anderson “Technological Discontinuities and Organizational Environments,” Administrative Science Quarterly, 31, (1986): 439–465.

Rebecca Henderson and Kim Clark, “Architectural Innovation,” Administrative Science Quarterly, vol. 35, no. 1 (1990): 9–30.

Clayton Christensen, The Innovator’s Dilemma (Boston: Harvard Business School Press, 1997).

Clark Gilbert “Unbundling the structure of inertia. Resource versus routine rigidity,” Academy of Management Journal, vol. 48, no. 5 (2005): 741–763.

Noticing the unnoticed calls for a peripheral vision, where innovators habitually surface new ideas by noticing things at the edge of experience (or as an IDEO employee explained, “look for people on the extremes”). For example, Corey Wride founded Media Mouth Inc.—a company providing software that helps you learn to speak a new language by watching movies—after making what seemed to him a surprising observation during an extended trip to Brazil. Wride was conducting training sessions to prepare Brazilians for U.S. graduate school entrance exams like the GMAT. During these trips, he encountered a large number of Brazilians who were eager to practice their English on him to prepare for the TOEFL test. When he found people who were particularly good English speakers, he would often ask them how they learned the language. (He expected those with the best English skills to be individuals who regularly attended one of the many English-learning schools in Brazil. In fact, many of the better speakers did attend these schools, but he later learned that they were not the best speakers of English.)

One evening, he met Julia Trentini, a young woman in her twenties who spoke better English than anyone he had met. He asked her how she had learned English so well. To his surprise, he learned that she had not attended any English school. Instead, she learned by watching American television shows and movies, and then practiced by imitating the phrases and pronunciation of the actors. She watched shows like Friends just for fun and was later surprised to find that she could understand and talk to a group of Americans that she met on the streets of São Paulo. She hadn’t formally studied English at all. Her newfound ability was a happy accident motivated by entertainment. Wride later observed that, like Trentini, other Brazilians with the best English skills also spent significant time watching and imitating American movies. (He learned that most Brazilians prefer to watch American movies in English even when Portuguese audio tracks are available. They prefer the authenticity of the actors’ real voices.) This led to another question: why don’t more Brazilians learn English by watching movies? The answer was that the actors spoke too fast, or used idioms or words that the Brazilians didn’t know or understand.

So Wride, a software engineer by training, devised an ingenious program that would allow a Portuguese speaker to watch virtually any movie in English on her computer and then do four things: (1) slow down the speech of the speaker; (2) select words and hear them pronounced or defined, (3) identify idioms and their meaning in her native language, and (4) insert her own pronunciation into the mouth of the actor so she can hear whether she sounds the same as the actor (hence, the Web site name, MovieMouth.com). Wride’s insight for his business emerged by observing that Brazilians who were supposed to be the best English speakers (those attending the best English training programs) were not the best speakers.

How else can you look for surprises? Leon Segal (an innovation psychologist and former IDEO employee) rightly noted that “innovation begins with an eye,” but it certainly doesn’t have to end there. It’s critical to remember that observations frequently involve more than the eyes. Learning research repeatedly underscores the power of multisensory experience when it comes to seeing something new and making sense of the experience. The more senses we engage as we experience the world, the more we see and remember. As a result, looking for surprises can actually be listening, tasting, touching, and smelling something surprising as well. You may have never heard of Trimpin, but he’s an accomplished musical innovator who has spent a lifetime asking the question, “How can we depart from the traditional orchestra?” He keeps his ears wide open in a constant hunt for new sounds. He says that “as soon as I see something, I hear it.”[3] Trimpin sees the sounds of trolley cable sparks, earthquake-driven tympanis, and other surprising auditory phenomena to create award-winning innovations in the music world. Other innovators also engage a wide range of senses to uncover new business ideas. For example, Howard Schultz started down the path to founding Starbucks when first confronted with the intoxicating smell of Italian espresso bars, and Joe Morton, cofounder of XANGO, got the initial idea for a new health drink in part by tasting mangosteen fruit for the first time in Malaysia (more about this in chapter 5). In sum, remember to engage all your senses as you search the world for surprises.

Change the Environment

Think back to the first time you made a trip to a new country. Or reflect on the first few days that you started working for a new company. Do you remember noticing what was different from what you had seen or experienced before? When entering a new environment, we are far more likely to carefully observe what is going on around us because we automatically seek to understand what is new and different. People who put themselves in new environments and then intensely observe what is happening unearth new ideas.

For example, Starbucks founder Schultz engaged his sensory organs—his eyes, ears, nose, and mouth—when he hit on the idea for his coffee stores. Walking to a trade show in Milan, Italy, Schultz randomly observed what happened in a number of Italian espresso bars. He could tell that the customers were regulars and that the espresso bar “offered comfort, community, and a sense of extended family.” As Schultz continued visiting Italian espresso bars, he had a revelation. “This is so powerful! I thought. What we had to do was unlock the romance and mystery of coffee, firsthand, in coffee bars. It was like an epiphany. It seemed so obvious,” recalled Schultz. “If we could recreate in America the authentic Italian coffee bar culture, it might resonate with other Americans the way it did with me.”[4]

Schultz stayed in Milan for about a week, visiting espresso bars just to observe. He then visited Verona where, losing himself in the streets of the city, he tasted café latte for the first time (he observed a customer order a café latte and, having never before heard of the drink, imitated the customer to see what it was). “Of all the coffee experts I had met, none had ever mentioned this drink. No one in America knows about this, I thought. I’ve got to take it back with me,” he recalls.

How many executives are willing, on a whim, to just take a week getting lost every day in an exploratory journey to observe something of interest and to see where the journey takes them? Without a willingness to actively observe in a new environment, Schultz would never have come up with the ideas that led to Starbucks’s innovative coffee-retailing experience.

Not surprisingly, our research found that innovators were more likely to visit new environments, including traveling to new countries, visiting different companies, attending unusual conferences, or just visiting museums or other interesting places. A. G. Lafley, for example, told us what he learned from his regional assignment in Asia long before becoming CEO of P&G:

Every time I traveled to China, I always went to stores to watch people purchasing our products. Then I went into homes. I always went in the evening because the woman almost always works outside the home. My routine was stores, homes, then the office. It gave me a current snapshot of what was going on. Of course, you can’t generalize from a single qualitative experience, but over five years of doing this regularly, those experiences add up, combined with reading whatever you have access to, as well as the “harder” data. You develop a feel. You become more of an anthropologist because you can’t understand the language. Your power is observation, your listening skills; your ability to read nonverbal cues gets a lot better. Your ability to observe increases. There are so many subtle things to read, understand, react to in a foreign country.

After returning to the U.S. P&G headquarters, he noticed how easy it was to “get lazy because everyone speaks English—you know what they’re going to say and do next.”

Innovators don’t have to go to foreign countries for an immersion experience in a new environment. There is much to be learned by exploring exhibits, museums, zoos, aquariums, and nature. At Daimler, Dieter Gürtler, one of the company’s top engineers, directed a team that focused on building a new aerodynamic concept car. To generate new ideas, he took the team members to a local museum of natural history to watch fish for a day. They were in search of insights that could break the automobile industry’s assumptions about aerodynamics and found a surprising solution in the boxfish. Through direct observation of the fish, as well as conversation with the fish experts, his team worked on mimicking the size and skeletal structure of the boxfish. Ultimately, they produced a concept car that delivered unexpected reductions in weight as well as significant reductions in air drag. As Gürtler put it, “By looking at nature, you come up with ideas you could never have thought of on your own.”[5]

Of course, it isn’t always possible to put yourself in a new environment. Fortunately, a rich source for new ideas often resides right around us in the familiar world of people and places that we think we know well. The problem is that we sometimes miss the obvious new idea in the most obvious of places because we take things for granted and, as a result, we miss opportunities for innovation. As book and New York Times writer Peter Leschak has lamented, “All of us are watchers—of television, of time clocks, of traffic on the freeway—but few are observers. Everyone is looking, not many are seeing.”[6] Acting on autopilot in everyday life automatically starves the brain’s creative capacity.

Observation has the power to transform companies and industries. As Cook told us, “Basic observation is the big game changer in our company.” Effective observation requires putting yourself in new environments. It involves watching customers to see what products and services they hire to help them do their jobs. It involves looking for workarounds—partial or incomplete solutions—that customers use to do those jobs. And it involves looking for surprises or anomalies that might provide surprising insights. As observers identify workarounds and anomalies, and dig deep to understand them, they increase their odds of uncovering an innovative solution to the problems they observe. We encourage you to develop and hone your observation skills and, in so doing, discover how they can be a game changer for you and your company.

Tips for Developing Observation Skills

Tip #1: Observe customers

Hone and sharpen your observing skills by scheduling regular observation excursions to carefully watch how certain customers experience your product or service. (This could be done in fifteen- to thirty-minute increments). Observe real people in real-life situations. Try to grasp what they like and hate. Search for things that make life easier or more difficult for them. What job are they trying to get done? Which of their functional, social, or emotional needs is your product or service not meeting? What is surprising about their behavior and different than expected? Ask the ten questions we suggested earlier in the chapter. In short, become an anthropologist and intensely observe a customer or a potential customer to experience an entire product or service life cycle.

Tip #2: Observe companies

Pick a company to observe and follow. Maybe it is a company you admire such as Apple, Google, or Virgin. It could be a start-up with an innovative business model or disruptive technology. Or it could be a particularly tough, innovative competitor. Treat the company as you would a business school case. Find out everything you can about what the company does and how it does it. If possible, figure out a way to schedule a visit to the company and examine firsthand its strategy, operations, and products to look for cross-pollination opportunities. As you learn new things about it, ask: “Are there any ideas that could be transferred, with some adaptation, to our company or industry? How is this strategy, tactic, or activity relevant to my job, my company, my life? Are there ideas here for a new who, what, or how in my industry?”

Tip #3: Observe whatever strikes your fancy

Set aside ten minutes each day to simply observe something intensively. Take careful notes about your observations. Then try to figure out how what you are seeing might lead to a new strategy, product, service, or production process. When you are out and about watching the world, jot down your key observations and thoughts on a notepad, and review your notes later, after a little time has passed. Keep a small camera (still or video) with you to take pictures of interesting things. The camera can remind you to observe and note what is going on around you. (Amazon’s Bezos confided that he often takes pictures of “really bad innovations” to get ideas for things that might be done better.)

Tip #4: Observe with all your senses

As you observe customers, companies, or whatever, actively engage more than one sense (see, smell, hear, touch, taste). One structured way to do this is through Dialogue in the Dark (a practice developed by Andreas Heinecke) and Dialogue in Silence (a practice developed by Heinecke and his wife Orna Cohen). In these tours by visually or hearing-impaired guides, guests experience darkened or silent environments (ranging from permanent exhibitions to restaurants located throughout the world) and enter a completely different world of either darkness or silence. A less structured approach to engaging your senses is to simply and intentionally become aware of your wider range of senses. For example, pay attention to what you smell next time you’re visiting with customers (as Schultz did in Italy) or eat your next dinner in slow motion, slowly savoring every bite and focusing only on the taste, texture, and smell of the food. Or notice how a product really feels as you touch it (when either using it or trying to understand how it works). As you learn how to observe, pay close attention to any creative insights the experience might trigger. Be sure to capture observations (sights, smells, sounds, touches, and tastes) in your idea journal and explore where the insights might lead you.

5

Discovery Skill #4: Networking

“What a person does on his own, without being stimulated by the thoughts and experiences of others, is even in the best of cases rather paltry and monotonous.”

—Albert Einstein

THINKING OUTSIDE THE box often requires linking the ideas in your area of knowledge with those of others who play in different boxes, who are outside your sphere. Innovators gain a radically different perspective when they devote time and energy to finding and testing ideas through a network of diverse individuals. Unlike typical delivery-driven executives who network to access resources, sell themselves or their companies, or boost their careers, innovators go out of their way to meet people with different backgrounds and perspectives to extend their own knowledge.

Consider what happened when Michael Lazaridis, founder of a small technology company called Research In Motion (RIM), attended a 1987 trade show in search of new ideas. At the time, Lazaridis’s fledgling company had one project: a contract from General Motors to provide technology that would allow large LED display signs on GM’s assembly lines to scroll messages and updates to workers. Lazaridis knew his fledgling company needed more than just one contract and one kind of technology, so he set out to see what new ideas he could uncover.

During the trade show, a speaker from a company called DoCoMo described a wireless data system that it had designed for Coca-Cola. The technology allowed vending machines to wirelessly signal when they needed refilling. (This was early on in the life of personal computers and before people owned cell phones, so sending data wirelessly to a machine was cutting-edge technology.) “That’s when it hit me . . . I remembered what my teacher had said in high school,” recalls Lazaridis. “‘Don’t get too caught up with computers, because it’s going to be the person that puts wireless technology and computers together that’s going to make a big difference.’”

At this moment, Lazardis thought of creating an interactive pager, a product allowing people to wirelessly send data and information to each other. So RIM sold the rights to the LED display sign product to Corman Technologies and focused its full attention on the wireless technologies necessary to create interactive pagers—the precursor to RIM’s blockbuster BlackBerry smartphone. “I realized that’s what I wanted to do,” Lazardis told us, “and since then, that’s all we’ve done. Frankly we’ve never looked back.”

Lazaridis’s experience illustrates the value of talking and interacting with diverse people who can provide unique knowledge and a fresh perspective. What if Lazaridis had never attended the trade show and heard the speaker? Or what if he had not talked with his teacher, who told him to look for ways to put wireless technology and computers together? People who think outside the box often talk to people who play in a different box to get new ideas. Lazardis continues to use idea networking to design future versions of the BlackBerry, talking to all sorts of people to understand technology trends and get new ideas.

What Idea Networkers Do

Some of you may be thinking: “I’m a good networker. But I’m not particularly innovative.” That may well be true. But it’s probably because you are like most successful executives who are what we call resource networkers, rather than idea networkers. Most executives network to sell themselves, to sell their companies, or to build relationships with people who possess desired resources. In contrast, innovators are less likely to network for resources or career progression; rather, they actively tap into new ideas and insights by talking with people who have diverse ideas and perspectives. (See figure 5-1.) Our research on innovators revealed that start-up entrepreneurs and corporate entrepreneurs are slightly better at idea networking than product inventors are, and quite a bit better than process inventors and noninnovators. If you want to launch an innovative new venture, networking is a critical skill, not only for generating new ideas but also for mobilizing the resources to launch new ventures. Overall, innovators score at around the seventy-seventh percentile, whereas noninnovators score around the forty-seventh percentile. (See figure 5-2.)

FIGURE 5-1

Networking differences between discovery- and delivery-driven executives

FIGURE 5-2

Comparison of idea networking skills for different types of innovators and noninnovators

The basic principle of idea networking—as opposed to resource networking—is to build a bridge into a different area of knowledge by interacting with someone with whom you, or people within your primary social networks, typically do not interact. EBay’s Pierre Omidyar told us that he looks for insights in unexpected directions and from people who aren’t experts (as well as experts). “I value ideas from unusual places,” he said. “The cliché would be, rather than talking to the CEO, I would want to talk to someone in the mailroom, something like that. I really look for people that have diverse backgrounds, diverse ways of thinking about things; what I try to do is just be exposed to some different styles of thinking. And I get input from these different directions just in a very open-ended way, not in a directed way.”

To this end, Omidyar and others like him make a conscious effort to meet people with different education backgrounds; who hail from different countries, industries, and business functions; and who are of different ages, ethnic backgrounds, and so forth. For example, Marc Benioff (Salesforce.com) told us about an interesting conversation he had with the State Oracle of Tibet, the official medium who, Benioff said, “was appointed by the Dalai Lama and is basically in charge of innovation for the Tibetan government.” Few of Benioff’s associates in the software industry have had the opportunity to get a different perspective from the State Oracle of Tibet. Innovators intuitively seem to understand that new ideas are often triggered through conversations with individuals who live in a different network of contacts.

University of Chicago sociologist Ron Burt has referred to this type of networking as bridging a “structural hole” or “gap” between different social networks. Burt studied 673 managers in a large U.S. electronics firm and found that those managers who had broader networks of contacts—contacts who were not connected to other managers in the organization—were consistently rated as generating more highly valued ideas.[1] “People with connections across structural holes [gaps in social networks] have early access to diverse, often contradictory, information and interpretations, which gives them a competitive advantage in seeing and developing good ideas,” writes Burt. “People connected to groups beyond their own can expect to find themselves delivering valuable ideas, seeming to be gifted with creativity. This is not creativity born of genius; it is creativity as an import-export business. An idea mundane in one group can be a valuable insight in another.” Burt also found that these “highly valued ideas” pay big dividends: managers with broad networks received more positive performance evaluations, had significantly higher salaries, and received more frequent promotions.

To illustrate how building bridges into different social networks can generate innovative new ideas, consider how Joe Morton, an entrepreneur in the health and nutrition industry, got a billion-dollar idea during a trip to Malaysia. (See figure 5-3.)

FIGURE 5-3

Bridging gaps in social networks to get new ideas

The figure shows Morton’s direct connections to numerous individuals within the health and nutrition industry (depicted by line connections to circles). Morton also spent almost a year living in Malaysia, where he learned about health and nutrition products Malaysians use from folks like Mahathir. (Mahathir represents many people Morton spoke with.) “I had a number of Malaysians tell me about these two local fruits—durian, the king of fruit, which supposedly heated the body up, and mangosteen, the queen of fruit, which cooled the body down and brought it into balance,” Morton told us. “I thought durian smelled horrible, even though Southeast Asians love it. But the mangosteen was delicious. Locals said the husk offered numerous health benefits, including the ability to boost energy, reduce inflammations, and settle an upset stomach.”

Even though Morton had significant experience in the health and nutrition industry, he was not aware of any products in the field using either durian or mangosteen. So he contacted his brother David, who was getting his PhD at the University of Utah medical school, to see if any scientific research had examined health benefits associated with durian or mangosteen. David searched for medical industry research studies about the fruits’ health benefits.

Through David, Morton learned that while there were no medical studies on durian, there were numerous studies that indicated positive health benefits associated with xanthones, polyphenolic compounds found in abundance in mangosteen. These benefits included anti-inflammatory properties, as Mahathir and other Malaysians had suggested. Morton then used this information and his network of contacts in the health and nutrition industry (including cofounders Aaron Garrity and another brother, Gordon Morton) to found XANGO (pronounced “Zango”) in 2002, a company that sells XANGO (mangosteen) juice. With a unique new product and an innovative network marketing approach, it took XANGO only six years to become a $1 billion company.

Morton would never have come up with the idea for mangosteen juice if he hadn’t talked to Mahathir and other locals in Malaysia. Morton bridged a gap between two networks: his health and nutrition network of contacts in the United States and a network of locals in Malaysia who had knowledge of homeopathic herbs and fruits used there. The result: a very successful new product idea.

Like Morton, many innovators claim that by visiting, or preferably living, in a foreign country, they spawned a new idea by talking to a local. When we are in an environment (different country, company, industry, ethnic group, and so on) that is very different from our own, we are more likely to interact with people who are in different social networks. Being in a new environment allows us to ask dumb questions about how and why things work.

This type of networking often produces serendipity. In roughly half the cases we studied where new ideas came through networking, the lucky entrepreneur essentially stumbled onto the idea. We saw this happen with Chris Johnson, cofounder of Terra Nova Biosystems, a company that uses a type of bacteria to eat contaminants in soil, thereby allowing companies to clean up soil in an environmentally friendly way. While attending a July 4th neighborhood barbeque, Johnson met someone who told him about a microbial solution to pollution problems. He contacted the microbiologist who had developed the microbial solution and learned more about how bacteria could be used to eat pollutants. Johnson and his cofounders eventually developed a proprietary process that ensures fast, cost-competitive remediation of a wide range of contaminants in an ecologically safe manner. Johnson’s purpose in attending the barbeque was to socialize, not look for new business ideas—and certainly not to learn about pollution-eating bacteria! But like many innovators, he takes advantage of every opportunity to talk to new people to see what he can learn. This habit produces the novel idea now and again through serendipity. But effective idea networkers also plan to find new ideas by regularly tapping outside experts for ideas, by attending networking events, and by building a personal network of creative confidants.

Tap Outside Experts

We found that purposeful networking was often effective when innovators attempted to reach out to experts in a different field of knowledge. To illustrate, consider the case of Norton, Massachusetts-based CPS Technologies, one of the most innovative companies in the advanced materials industry. CPS has developed highly advanced and innovative ceramic composites, a class of materials superior to conventional ones in a number of ways, including improved thermal conductivity, increased stiffness, and lighter weight. Kent Bowen, founding scientist at CPS, made networking a priority when he hung the following credo in every office of his start-up:

The insights required to solve many of our most challenging problems come from outside our industry and scientific field. We must aggressively and proudly incorporate into our work findings and advances which were not invented here.

One of Bowen’s favorite questions when facing a technical challenge is, “Who else has faced or solved a problem like this before?” He actively looks for people in other fields and disciplines to understand what they do and what they know that might be relevant to his company’s issues. As a result, scientists from CPS have solved numerous complex problems by talking with people in other fields.

For example, CPS’s ceramic composites are made from uniform, submicron materials (aluminum oxide and silicon carbide) that are combined in slurries (an example of a slurry is a mixture like water and cement that eventually makes concrete). Dispersing these submicron materials in a uniform way is critical to making strong, defect-free ceramic products, but the chemistry for doing this had vexed some of the world’s best colloid scientists. After Bowen discovered that photographic film manufacturers dispersed huge volumes of microscopic silver halide particles in very uniform films, CPS contacted a senior polymer chemist from Polaroid, the photographic film manufacturer. The chemist brought new knowledge that helped CPS solve the problem within a few weeks, thereby making the composite much stronger.

The CPS team solved another serious quality problem by talking to “sperm-freezing” specialists. CPS scientists observed that as their ceramic slurries were injected into molds and began freezing, ice crystals formed. These ice crystals were a serious problem because cracks in the composites would originate in the crystals, like cracks in concrete. In a scientific journal report, a CPS engineer discovered that biologists who do artificial inseminations routinely faced the same problem. Experts in sperm-freezing technology knew how to prevent ice crystal growth in cells during freezing. So CPS contacted them, learned their technique, and incorporated it into its manufacturing process. Collectively, these innovations were a stunning success, allowing CPS to produce some of the strongest and lightest ceramic composites ever made. Bowen’s practice of actively seeking out people in other industries and disciplines has been critical to generating innovative ideas.

Despite all the positives of networking with experts in other fields, Intuit’s Scott Cook cautions that sometimes talking to experts isn’t the best way to generate innovations. “Some problems and new business ideas are such a paradigm shift that talking to people reinforces the current paradigm,” cautions Cook. “Some paradigm shifts are, I find, better initiated by watching customers or watching things happen in the marketplace as opposed to talking to experts.” The point is that while getting new ideas and perspectives from experts can lead to innovative ideas, experts are also indoctrinated with a particular perspective that may be incorrect. So remember to ask counterintuitive questions that challenge the so-called experts. Then listen carefully, with a healthy dose of skepticism.

Attend Idea Networking Events

In chapter 1, we noted that Frans Johansson has described cross-discipline connections as the Medici effect, referring to the explosion of creativity during the Italian Renaissance. Richard Saul Wurman, the retired founder of the Technology, Entertainment and Design (TED) conferences, plays the same role as a modern-day Medici, creating a forum where experts in various fields can share cutting-edge ideas. In 1984, Wurman noticed the convergence of technology, entertainment, and design, and created an idea accelerator, where smart people from diverse backgrounds talked about the new projects they were working on. At the annual conference, the speakers and the audience members engage in the annual collision of ideas to create even better ones. TED conferences have evolved into a provocative forum for generating powerful new ideas, as smart individuals with diverse backgrounds connect in a common mind-set to change the world (as Bill Gates put it, “The combined IQ of the attendees is incredible”[2]).

Innovators are likely to frequent idea conferences such as TED, Davos (or other World Economic Forum events), and the Aspen Ideas Festival. Many innovators we interviewed are regular faces at these events (for example, Jeff Bezos regularly attends TED). Such conferences draw together entrepreneurs, academics, politicians, adventurers, scientists, artists, and thinkers from all over the world, who come to present their newest ideas, passions, and projects. Attending a conference that is designed for the exchange and debate of ideas from a variety of fields is likely to create a collision of concepts that can turbocharge your associating skill.

A conference on a topic outside your direct industry and field of expertise can also spark new ideas. One European transportation industry executive we interviewed happened to live next to a conference center in a large city. Even though he walked by the center each day on his way to work, he never ventured in. One day, he noticed a sign for a conference in a completely different industry: beekeeping. For some reason, this theme caught his attention and he wandered in. Much to his surprise, the experience proved invaluable as he applied an idea from beekeeping to come up with an innovative solution to one of his current work challenges. After that, he frequently dropped in on other conferences out of his field just to learn something entirely new.

David Neeleman, founder of both JetBlue and Azul airlines, detected and developed key ideas for JetBlue, such as satellite TV technology at every seat, at-home reservationists, and the hundred-seat JetBlue Embraer jet, through networking at conferences and elsewhere. Says Neeleman: “I always had this gnawing thought in my mind that ‘I’ve got to do something in the seat-back pocket of each plane seat.’ So I talked to a lot of people at a lot of companies about different entertainment options. Then one day, in the early days of JetBlue, I talked to someone who said, ‘Look at this brochure on a company that can do live television on airplanes,’ and I said, ‘That’s it. That’s exactly what we want to do.’”

Not only did Neeleman follow up on the suggestion, he bought LiveTV, the company with the technology to provide satellite TV on airplanes. By purchasing the only company with such technology, he prevented competitors from offering satellite television to their passengers, thereby creating a competitive advantage for JetBlue. Until recently, any competitor who wanted to offer satellite TV to passengers had to purchase it from JetBlue.

When Neeleman was attending a small airline industry conference, someone alerted him to the capabilities of Embraer, an emerging, small plane manufacturer in Brazil. Neeleman immediately scheduled a trip to Brazil to visit Embraer and explore opportunities for JetBlue. During the visit, Neeleman saw the possibility of serving midsize cities with a new hundred-seat Embraer jet, one designed specifically for JetBlue. By offering satellite TV and large comfortable seats, the hundred-seat JetBlue plane would be far more desirable to passengers than the fifty-seat regional jets, and more economical than the larger Boeing and Airbus jets. As part of the deal, JetBlue purchased the Brazilian aircraft maker’s hundred-seat plane-manufacturing capacity for two years. Later, the airline signed a contract with Embraer that prevented it from selling the jet at a price lower than JetBlue had paid.

In addition to attending conferences, some innovators create networking opportunities within their companies. For example, Richard Branson created an idea networking process when founding Virgin Music. He bought an old castle and transformed it into a conversation hub for diverse people from the entertainment industry, including musicians, artists, producers, filmmakers, and otherwise. Branson understands that creating networking opportunities within Virgin produces conversations between people that just might trigger innovative ideas.

Form a Personal Networking Group

We found that many innovators build a small network of people who are their “go to” folks when they want to find or test new ideas. For example, innovative entrepreneurs Jeff Jones (founder of Campus Pipeline and NxLight) and Eliot Jacobsen (RocketFuel Ventures) described how they liked to get together to jam (to use a music or jazz metaphor) to get new ideas. “I have a few people I like to get together with when I’m in need of a boost to my creative juices,” Jones told us. “Eliot Jacobsen is one of my friends that I love to talk to because we just energize each other and build on each others’ ideas.” Jacobsen agreed, saying, “Jeff Jones is one of those people I like to talk to on a regular basis because we just connect in a creative way.”

In similar fashion, we found that many innovators have a small group of creative confidants that they converse with whenever they need some fresh ideas—or someone to challenge their current ideas. Usually this network is relatively small (e.g., fewer than five people), but some innovators have actively created larger networks. One innovative executive told us that over the years he has cultivated a kitchen cabinet of twenty to thirty people from different industries who are his innovation advisers. At least once a year, he picks up the phone and asks his kitchen cabinet, “What’s keeping you up at night?” He says, “Most of them either run companies or are involved in industries in a fairly senior way and they have very specific things to talk about . . . From these diverse conversations I try to piece together trends or directions. There are moments when the pieces just come together and new ideas form with amazing clarity.”

As important as networking is, many senior executives face unique challenges when trying to talk candidly with others about new ideas. After all, intellectual property is at stake, and senior executives often have difficulty challenging the status quo in their organizations because they often created it. “As a CEO, there are few places where you can really publicly talk about fundamental concerns,” one innovative CEO told us. “As a result, I’ve created an unofficial group. It’s fairly senior, fairly seasoned people who are comfortable throwing out ideas and then forgetting about them if these hunches or speculations aren’t right. One thing about being a CEO is that you’ve got to be very careful about what you say in public and whom you involve in these conversations. That’s why networking for ideas, for me at least, is unofficial.” For this reason, it’s important to form a trusted network of confidants, since the issues under discussion are of critical and sensitive strategic value. Building a trusted and diverse idea network is often best accomplished throughout your career, because forming relationships with a diverse set of people takes time and experience. However, if done well, a small personal network of creative confidants can pay significant dividends.

Effective idea networking helps innovators create new processes, products, services, and even business models that deliver positive results. When multiple conversations abound in these networks, a new idea frequently emerges from the insights and refinements gained. Michael Dell put it this way: “I often have a hard time explaining how we innovate at Dell because we do it quite collaboratively, building on each other. Someone will say, ‘Hey, what about this, how about that?’ And by the time you’re done, it’s impossible to say, ‘That’s so-and-so’s idea,’ because you’ve got twenty-seven fingerprints all over the thing.” In the end, idea ownership matters far less than development through the idea networking process.

Networking Sidebar: How Well Do You Take Rejection?

OK, so you’ve already heard about the importance of networking. But if you are like most people, you probably still don’t have any sort of a plan to do it on a regular basis. Meeting new people is easier said than done. So what stops you? To be brutally honest, it may be a lack of confidence that prevents you from reaching out to people you don’t know. You might get rejected. In fact you will get rejected, sometimes when making the pitch for a meeting or conversation, and sometimes after making the pitch. So what can you do to minimize the probability of rejection when making the pitch? Tell the person you want to engage that “I’m interested in your ideas. I’m interested in your perspective.” This taps into his or her desire to help or be viewed as an expert. Most people derive satisfaction from being asked for their opinion and ideas. It’s important to make sure they know you are only interested in their ideas, not their resources.

Once you get the opportunity to exchange ideas with someone, and if you want to keep the door open to future conversations, you have one goal: be interesting. What makes someone interesting? Two things seem to help. First, breadth of experience matters in a big way. If you’ve traveled widely (China, Australia, Italy), experienced widely (Broadway shows, scuba diving), read widely (novels, history, different subjects), or networked widely (“Yes, I know so and so; we met when . . .”), then you increase your chances of being interesting to someone. Second, make sure you perfect your elevator speech on the topic you want ideas about. If you can tell interesting stories about the problem or challenge you are trying to solve, that will spark an interest. Being able to tell short, interesting stories on a variety of topics increases your interesting quotient. Of course, it doesn’t hurt to be funny or witty, but that really takes some practice.

Networking is most likely to spark innovative ideas when you initiate conversations with folks in different social networks. This means talking to people from different business functions, companies, industries, countries, ethnic groups, socioeconomic groups, age groups (eighteen-year-olds and eighty-year-olds), political groups, and religions. Diversity of network breeds diversity of ideas. Attending idea conferences such as TED can be a way to jump-start the diversity of your network. Moreover, when facing a particular problem, ask yourself, “Who else has faced a problem like this before?” and try to talk to those folks.

Tips for Developing Idea Networking Skills

We recommend the following activities to help you practice and strengthen your idea networking skills.

Tip #1: Expand the diversity of your network

List the top-ten people you would typically talk with if you were trying to get or refine a new idea. Go ahead. Make the list right now. How many of those people have a background or perspective that is likely to be very different from yours? For example, how many are teenagers, or how many are older than seventy-five? How many were born and grew up in a different country? How many are from a very different socioeconomic group than yours? If your current idea network either isn’t very large or isn’t very diverse, expand your idea pool by identifying and visiting with people who are the most different from you along some or all of the dimensions shown in table 5-1.

TABLE 5-1

Diversify your idea network

Identify and have a dialogue with people most different from you.

Tip #2: Start a “mealtime networking” plan

Plan to have a meal with someone from a different background at least once each week. Jacobsen, of RocketFuel Ventures, tries to schedule breakfast, lunch, or dinner with someone new every week. “I also frequently meet with people I know who are creative and who I’ve found are helpful in offering a different perspective,” he says. “Networking is important to my success in coming up with new business ideas, and mealtime is for networking.” For ideas on mealtime networking, see Keith Ferrazzi’s book Never Eat Alone.

Tip #3: Plan to attend at least two conferences in the next year

Select one conference that is on a topic related to your area of expertise and one conference on a topic that isn’t. Make an effort to meet new people and get to know what problems and issues they are facing; ask for their ideas and perspectives on problems and issues you are wrestling with.

Tip #4: Start a creative community

Identify a few founding members who you believe are open to discussing new ideas and who you think will stimulate your creative thinking. Decide on a creative place to meet where you can exchange ideas and develop new ones. Meet regularly (at least monthly) to discuss trends and new ideas.

Tip #5: Invite an outsider

Bring in a smart person with a different background (someone from a different function, profession, company, industry, country, age, ethnic group, socioeconomic group) to have lunch with you and your team once each week. Ask the person about your innovation challenges and get his or her perspective on your ideas. Or hold an open house for ideas, inviting two to four people from a variety of perspectives, including nonexperts who are new to a situation, to present their ideas and viewpoints.

Tip #6: Cross-train with experts

Find experts in different functions, industries, or geographic regions, and sit in on their training sessions and meetings to experience their work and world. (For example, marketing managers from Google and P&G traded jobs for a month to gain rich insights into each other’s worlds as well as new ways to challenge fundamental assumptions in the other industry.)

6

Discovery Skill #5: Experimenting

“I haven’t failed . . . I’ve just found 10,000 ways that do not work.”

—Thomas Edison

WHEN MOST PEOPLE hear the word experiment, they think of scientists in white coats running experiments in a lab, or of great inventors like Thomas Edison. Like Edison, business innovators actively try out new ideas by creating prototypes and launching pilot tests. But unlike scientists, they don’t work in laboratories; the world is their laboratory. And beyond just creating prototypes, they try out new experiences and take apart products and processes in search of new data that may spark an innovative new idea. Good experimenters understand that although questioning, observing, and networking provide data about the past (what was) and the present (what is), experimenting is best suited for generating data on what might work in the future. In other words, it’s the best way to answer our “what-if” questions as we search for new solutions. Often, the only way to get the necessary data to move forward is to run the experiment. George Box, former president of the American Statistical Association, reinforces the power of experimentation in framing the future by noticing that, “the only way to know how a complex system will behave—after you modify it—is to modify it and see how it behaves.” This is precisely what experimentation does for disruptive innovators. It provides key data on how well their ideas work in practice and helps them shape revolutionary business models piece by piece.

Experimenting with new business opportunities was, in fact, part of what Amazon.com founder Jeff Bezos did at D.E. Shaw, a Wall Street investment firm. In May 1994, Bezos was exploring the still-immature Internet in his thirty-ninth-floor office in midtown Manhattan. As Bezos was browsing, he came across a Web site that claimed to measure growth in Internet usage. Bezos couldn’t believe his eyes. According to this site, the Internet was growing at a rate of 2,300 percent a year. “It was a wake-up call,” he says. “You have to keep in mind that human beings aren’t good at understanding exponential growth. It’s just not something we see in our everyday life.” What kind of business opportunity might this newfangled thing called the Internet represent?

Bezos began asking a series of questions: What would people buy remotely? What do they prefer to purchase by mail order rather than in a store? After researching the top-twenty mail-order products, Bezos decided that people would buy standard products via the Web—ones that people knew exactly what they were getting. Bezos didn’t see books on the top-twenty list, which was a surprise because books seemed to meet the criteria of a standard product. After a bit of research, he discovered that there are so many books in print that it’s impossible for one book catalog to contain information about them all. Such a catalogue would be far too large and expensive to mail. As Bezos saw it, the Internet was the ideal vehicle for offering such a catalog. He felt he had enough data to run the experiment to see if books could be successfully sold over the Internet.

Within the year, Bezos launched Amazon.com and dubbed it “Earth’s Biggest Bookstore.” Using book wholesaler Ingram to warehouse and ship books, Amazon offered the largest selection of books anywhere, without having made any investment in stores, warehouses, or inventory. But Bezos had bigger dreams than simply selling books. Even before Amazon became profitable, Bezos saw an opportunity for the company to become an online discount retailer, selling a full line of products from toys to TVs. So he made an incredibly risky bet. He decided to build a number of 850,000-square-foot warehouses around the country. The warehouses originally ran at 10 percent capacity. On the announcement, Amazon’s stock tanked; analysts could not understand why the company was abandoning the original “no bricks and mortar” business model.

Today, of course, Amazon is positioned as the leading online discount store, with multiple product lines and efficient warehouse and fulfillment capabilities. More than anything else, Amazon is now a distribution company and virtual mall open to other vendor’s products, a far cry from Bezos’s original business idea. But Bezos isn’t done experimenting with business models. In 2007, Amazon launched the electronic reader Kindle, an experiment that has successfully changed the company again. In addition to being a retailer of other companies’ products, Amazon became the maker of a hot new electronic device (cornering 90 percent of the market until iPad’s launch in 2010). Now Bezos is reinventing Amazon with its cloud computing services (Amazon EC2). Amazon rents data storage and computing power to businesses at extremely low prices by leveraging its huge investment in servers and computing equipment to run its online retailing business. By one estimate, 25 percent of small to medium-sized companies in Silicon Valley are now using Amazon’s cloud computing services.

Where did Bezos’s penchant for experimenting come from? Some of it clearly has its basis in genetics. His tinkering began early when, fed up with sleeping in his crib, he tried to take it apart with a screwdriver. As a twelve-year-old, Bezos desperately wanted a new device called the Infinity Cube, a set of small motorized mirrors that reflected off one another, so that it was like looking into infinity. Bezos was fascinated by this gadget, but it was very expensive. So he bought some mirrors and other parts, and, without any instructions to follow, he constructed his own version of the Infinity Cube. Beyond his natural inclinations to experiment, Bezos credits the annual summers on his grandparent’s ranch for giving him time to hone and develop his experimenting skill. “I really gained confidence in my creative ability by helping my grandfather fix things on his ranch,” he told us. “He often didn’t have the money to fix things, so we’d have to improvise. One time I helped him fix a Caterpillar tractor using nothing but a three-foot-high stack of mail-order manuals. You learn that when one way doesn’t work, you have to regroup and try another approach.”

Bezos’s experience has taught him that experimenting is so critical to innovation that he has tried to institutionalize it at Amazon. “Experiments are key to innovation because they rarely turn out as you expect, and you learn so much,” Bezos told us. “I encourage our employees to go down blind alleys and experiment. We’ve tried to reduce the cost of doing experiments so that we can do more of them. If you can increase the number of experiments you try from a hundred to a thousand, you dramatically increase the number of innovations you produce.”

Three Ways to Experiment

We found that innovators who start new businesses and those who invent new products are the best experimenters. (See figure 6-1.) This is not surprising, since start-up entrepreneurs and product innovators tend to launch something new to the market starting from ground zero (they also score much higher on risk taking). Of all the discovery skills, we found that experimenting was the best differentiator of innovators versus noninnovators, with noninnovators scoring in only the thirty-ninth percentile on experimentation. So if you want to find someone with a penchant for creativity and innovation, evaluating his or her experimenting skills is a great place to start.

FIGURE 6-1

Comparison of experimenting skills for different types of innovators and noninnovators

Sample items:

1. Has a history of taking things apart to see how they work.

2. Frequently experiments to create new ways of doing things.

Most innovators in our study engaged in at least one of three forms of experimentation. (See figure 6-2.) The first is trying out new experiences through exploration, as Steve Jobs did when he stayed at an ashram in India or dropped in on calligraphy classes at Reed College. The second is taking things apart—either physically or intellectually, as Michael Dell did when, at age sixteen, he disassembled a personal computer (more about this later). The third is testing an idea through pilots and prototypes, as BlackBerry inventor Michael Lazaridis did when trying to construct a Star Trek-like force field in high school with wire, electricity, and chemicals. We found that innovators often generated their best ideas when engaged in one of the three different experimenting approaches.

FIGURE 6-2

Three ways that innovators experiment

We typically associate the word experimenting with the last of the three approaches. The classic laboratory approach to experimentation is to test an idea by creating a prototype to see if it will work, just as Edison did so often that he once famously said, “I haven’t failed . . . I’ve just found 10,000 ways that do not work.” But we found that a much broader interpretation of experimenting better reflects how innovators cultivate new ideas. For example, when simply trying out a new experience, you have no explicit intention to test an idea. It’s simply an exploratory journey to see what you can learn. The same can be said for taking things apart, either physically or intellectually. When Dell disassembled his first personal computer, he wasn’t looking to create a new computer or company; he just wanted to see how it worked. Experimenting can also involve launching a pilot or prototype, and then modifying it as you go along. Bezos’s online bookstore didn’t stay where it was after its initial success; it morphed into an online discount retailer, selling a full line of products from toys to consumer electronics. Virgin started out as a record company, but Richard Branson experimented with all types of new businesses, from Virgin Records to Virgin Atlantic to the starry-eyed Virgin Galactic, which plans to carry megarich customers into space. And Apple hasn’t stayed solely a computer company, launching successful products in music (iPod), phones (iPhone), and books (iPad), as well as unsuccessful ones in PDAs (Newton) and digital cameras (Apple QuickTake). The argument that innovators are experimenters is certainly not new; everyone knows that. But what isn’t well understood is the different ways that they experiment to ignite new ideas.

Try Out New Experiences

Many executives view trying out new experiences as a waste of time if the experience is not directly linked to a desired learning outcome. Delivery-driven executives focus on efficiently solving the problem at hand. So if an activity doesn’t have a clear connection to a current deliverable, then they view it as a waste of time. By contrast, discovery-driven executives grasp the idea that trying out new experiences means engaging in interactive learning experiences that may not have any obvious practical application. Indeed, from net present value logic (e.g., the size of the investment made discounted by the time horizon), the return on time invested when using any discovery skill produces a payback that is not only further into the future but also less likely to ever materialize. Jobs never expected that spending time in calligraphy classes would have any practical application or payback. But the calligraphy experience turned out to be a major differentiator for the first Macintosh computer by allowing it to produce documents with beautiful typography.

Innovators understand that diversity of experience allows you to engage in divergent thinking, as you draw on a broader set of ideas when associating. “Of course, it was impossible to connect the dots looking forward when I was in college,” Jobs says. “But it was very clear looking backward ten years later. So you have to trust that the dots will somehow connect in your future . . . believing that the dots will somehow connect down the road will give you the confidence to follow your heart even when it leads off the well-worn path. And that may make all of the difference.”[1] Trying out new experiences may prove worthless from a financial standpoint, but it also might make all the difference when searching for disruptive ideas.

Take, for instance, the example of Kristen Murdock, an entrepreneur who literally figured out how to turn cow pies (manure) into money. Murdock has done this by offering an interesting, if rather disgusting, new product that’s caught interest inside and outside the United States: Cow-Pie Clocks. Not surprisingly, Murdock didn’t just wake up one day and say, “I think I’ll take a bunch of desert-baked cow pies, cover them with glaze, insert a clock in them, and sell them to people who want a truly unique clock.” Rather, while watching her sons ride motorcycles in the desert areas of southern Utah, she stepped over some “interesting looking old petrified cow pies. So I picked one up, smelled it, and it didn’t smell bad; it was really baked,” she said. “I started collecting them and brought them home and put them in the garage. It kind of freaked my kids out.” She had no idea what she would do with them; she just thought they were interesting.

Within a few days, some of them started to disintegrate. So to keep them intact, she applied a glaze and liked what she saw. They were like shiny, petrified pieces of wood, and she thought they were pretty due to the color variations or the interesting rocks embedded in them. Then one night while lying in bed, she hit on the idea to insert a clock into the petrified cow pie and give it away as a gag gift. So she started inserting clocks into the cow pies and giving them to girlfriends with funny sayings, like: “You Dung Good,” or “For all you do, this crap for you.” “None of my girlfriends liked them,” she says. “They hated them . . . they thought it was so sick.” Her big break came after she gave a clock to a relative, who was a friend of entertainer Donny Osmond. Murdock said Osmond called her wanting a clock for himself, so she made one for him. A few weeks later, her relative called and said, “Turn on Donny and Marie,” Osmond’s daily talk show. There, Murdock saw Osmond showing off her clock to a nationwide audience. The calls started to flood in. She quickly set up an Internet business. Each cow-pie clock comes with a display stand and a saying attached such as, “Happy Birthday, You Old Poop.” Murdock will provide whatever saying the customer wants. She has lists of suggestions to choose from, with more coming in continually from customers and friends.

But she didn’t stop there. She kept all of the funny sayings people sent her and created a cow-pie greeting card line. She hired a graphic designer to create a signature cow and cow pie and sold a line of cow-pie greeting cards to Hallmark. The business has been extremely profitable because she gets paid a royalty for the ideas and cow-pie brand, but she doesn’t have to actually print the cards. As in Jobs’s experience with calligraphy, Murdock had no way of knowing that collecting cow pies could lead to any practical application in her life. It all started because she was curious enough to collect a few cow pies while wandering in the desert. Murdock jokingly sums up her success saying, “I’m an entre-manure.”

Innovators like Bezos and Murdock seem to intuitively understand the value that can come from trying out new experiences in new environments. Our research on innovators revealed that one of the most powerful experiments innovators can try out is living and working in different cultures. The more countries someone lives in, the more likely he or she is to leverage that experience to deliver innovative products, processes, or businesses. Individuals who live in a foreign country for at least three months are 35 percent more likely to start an innovative venture or invent a product (each additional country brings additional benefit, though there are diminishing returns after living in two countries). Moreover, if managers try out even one international assignment before becoming CEO, their companies deliver stronger financial results than companies run by CEOs without such experience, roughly 7 percent higher market performance on average.[2] And part of that performance premium comes from the innovation capability that a CEO has acquired by living overseas.

P&G’s A. G. Lafley, for example, spent time as a student studying history in France; later on, he ran retail operations on U.S. military bases in Japan. He eventually returned to Japan as head of P&G’s Asia operations before becoming CEO. His diverse international experience served him well as the leader of one of the oldest and most innovative companies in the world. Similarly, innovator Reed Hastings’s experience working for the Peace Corps in Swaziland continues to influence his innovative strategy and leadership (as founder and CEO) of highly successful Netflix.

In similar fashion, the more industries or companies someone works in, the more likely he or she is to be an innovator. Each additional industry offers an even bigger boost to innovation than living in a foreign country. Working in different company environments helps you develop deep experience with a variety of people, processes, and products. You also learn various ways to solve problems, since each company and industry tends to have distinctive approaches. P&G (led by Lafley) and Google (led by founders Larry Page and Sergey Brin) understand the value of seeing how things work in diverse company environments, which is why these companies orchestrated a three-month swap of employees to see how a very different, but highly successful company operates (more on this in chapter 9). These types of experiences boost a person’s capacity to look at a problem from a variety of angles and perspectives.

Finally, taking the opportunity to learn new skills in different arenas—as Jobs did when learning calligraphy—can boost your innovation capability. For example, Nate Alder (inventor of the Klymit vest) decided to pick up scuba diving during a trip to Brazil. During the scuba certification, he learned about argon gas as an insulator to keep dry suits warm. He thought, “Hey, that’s a cool idea. I wonder if I could put argon gas in a snowboard jacket to keep me warm?” (Alder was a snowboard instructor at the time.) This experience was the catalyst for the creation of the Klymit vest (insulated with argon gas) and a variety of other products using argon gas. As described in chapter 2, innovators tend to be T-shaped in terms of their expertise, with deep knowledge in at least one area and some expertise in a wide variety of knowledge areas. Developing new skills in new areas is a great way to build diversity of knowledge in your head.

In summary, living in a different country, working in a different industry, and learning a new skill are three ways to try out new experiences and boost your creativity. Experimenters seek these types of experiences because they expand the diversity of their knowledge and increase their capacity to innovate.

Take Apart Products, Processes, and Ideas

In 1980, Michael Dell looked forward with great anticipation to his sixteenth birthday. However, he was most excited because his parents had finally agreed to let him purchase his own computer—an Apple II. On the day the computer arrived, Dell was so anxious to get his hands on it that he made his dad drive him down to the UPS office to pick it up. What he did next both shocked and dismayed his parents, but it also proved to be instrumental in his discovery of the “direct from Dell” business model. “After we pulled into my driveway,” Dell recalled, “I jumped out of the car, carried the precious cargo to my room, and the first thing I did was take my new computer apart. My parents were infuriated. An Apple cost a lot of money in those days and they thought I had demolished it. But I just wanted to see how it worked.” Dell’s desire to understand what made his Apple II tick led to a variety of experiments designed to make his computer work better and faster. He bought a variety of components and add-ons to enhance his personal computer, like more memory, disk drives, faster modems, and bigger monitors. He soon learned how to make some money from his “hobby.” “I would enhance a PC the way another guy would soup up a car. Then I would sell it for a profit and do it again,” says Dell. “I was soon going to distributors and buying PC components in bulk to reduce the costs. I remember my mother complained that my room looked like a mechanic’s shop.”

Dell soon gained enough familiarity with the cost of PC components that he acquired an important insight. At the time, an IBM PC sold in a store for around $2,500 to $3,000. But the exact same components could be purchased for $600 or $700, and IBM didn’t own the technology. Dell told us that this raised a critical question in his mind: “Why does it cost five times more to buy a PC in the store than the parts cost?” He realized that he could buy the latest components, assemble them in the exact configuration a customer wanted, and deliver it for far less than the retail price in a store. Thus, the “direct from Dell” business model was born.

Like Dell, many innovators hit on an innovative idea while taking something apart—a product, a process, a company, a technology. For example, Google’s Page is also a tinkerer who likes to deconstruct things. Page’s brother gave him a set of screwdrivers when he was nine years old, which he used to completely take apart every power tool his family had in the house. In similar fashion, Page tinkered with various ideas related to efficiently searching the Web, eventually hitting on the page-ranking idea that searched the Web in a way that was very different from the other search engines at the time. Another experimenter, Albert Einstein, took apart Newton’s theory of time and space intellectually, rather than physically, to come up with his innovative theory of relativity. Einstein is reported to have generated his insights “based purely on thought experiments—performed in his head rather than in a lab.”[3]

In summary, experimenters love to deconstruct—products, processes, ideas—to understand how they work. In the process of taking things apart, they also ask questions about why things work the way they do. This often triggers new ideas for how things might work better.

Test New Ideas Through Pilots and Prototypes

Max Levchin, cofounder of PayPal, majored in computer science during college, where he developed an intense interest in security and encryption technology. In the summer of 1998, Levchin moved to Silicon Valley to pursue his dream of starting a company offering security software. One hot summer day, he decided to drop in on an encryption technology lecture at Stanford University to see if he could spawn any ideas to further his dream. Only six people attended the lecture, so it wasn’t hard to start up a conversation with Peter Thiel, a hedge fund manager who was interested in using encryption technology to secure financial transactions. The two immediately hit it off and decided to start a company based on security software for handheld devices like the Palm Pilot.

The initial idea was to turn the Palm Pilot into a wallet, in which users could secure private information like credit card numbers or passwords. They launched the product with great anticipation but soon learned that the market was quite small, limited to those few users of Palm Pilots who cared about securing private information. So they decided to try out a different business idea: provide software that would allow a Palm Pilot to store money that could be beamed from one Palm Pilot to another.

So Levchin and Thiel developed software that could beam money from one Palm Pilot to another. This business idea caught the attention of some leading venture capital companies in Silicon Valley, leading to PayPal’s first round of financing at Buck’s restaurant, a favorite restaurant for many venture capitalists. PayPal’s investors showed up with $4.5 million preloaded on a Palm Pilot that they beamed to Levchin and Thiel’s Palm Pilot. PayPal seemed to be on its way.

PayPal’s initial growth was rapid, but the market leveled off rather quickly because it was limited to the roughly 3 million handheld (PDA) users in the United States. It didn’t take long before Levchin and Thiel realized another problem with the business model. “The initial idea of beaming money between Palm Pilots was basically a bad idea,” Thiel told us. “I mean, if you have to meet face to face to exchange money, which you had to with the Palm Pilot idea, you could just hand the other guy a check. But in the course of building out this idea, we made midcourse changes that were really interesting.” These midcourse changes were prompted in part by customers who wanted to sync their Palm Pilots to their computers and send money through the Internet to someone else with a computer and Palm Pilot. “We came up with the idea of attaching money to an e-mail,” Thiel recalled. “Since there were 120 million e-mail users in the United States, this made it much more viral. You didn’t have to meet face to face.”

Today, PayPal is the world’s largest processor of e-mail payments, but this never would have happened if its founders hadn’t been willing to constantly experiment and launch earlier versions of the product. Just as the security wallet experiment was a “failure,” the original Palm Pilot experiment also fell on its face. But these critical experiments generated the data necessary for PayPal’s ultimate success.

The PayPal experience is not atypical for innovative entrepreneurs. They realize the importance of experimenting with prototypes and pilots to see what they can learn. Because of their bias for action, they tend to launch products or businesses as quickly as possible, almost as an experiment, to see what the market’s response will be. They like to throw new product, process, and business ideas against the wall to see what will stick. PayPal’s experiments were essentially launched as products to the market, and they generated important data when the products failed to gain traction.

While some innovators seem prone to quickly launch their prototypes directly to the market, others more carefully test and compare competing prototypes to see what works best. Jennifer Hyman and Jennifer Fleiss did this before launching Rent the Runway, a Netflix-type business model for renting designer dresses. During a trip home to New York City, Hyman noticed her sister, Becky—an accessories buyer at Bloomingdale’s—struggling over what to wear for an upcoming wedding. Her sister wanted something stunning, but even though she had a decent salary, every designer dress was too expensive and out of reach. As Hyman watched her sister agonize over what to do, she wondered, “If the Beckys of this world can’t wear a designer dress, what hope is there for the rest of us?” She also thought that designers had a problem as well. “If designers can’t get their pieces into the hands of young, fashionable women,” she thought, “they are going to have a difficult time building their brands.” Hyman’s simple observation of a common ritual (finding a dress for a special occasion) in a familiar place (home) with a familiar person (her sister) produced an uncommon insight. Why not modify the Netflix business model and apply it to high-end fashion? Instead of purchasing designer dresses, women could rent the designer dresses online for that special occasion, for only one-tenth the cost.

So Hyman and Fleiss set up some experiments to test their idea. They bought a hundred dresses from designers like Diane von Furstenberg, Calvin Klein, and Halston and ran three experiments. The first was on the Harvard University campus; they rented dresses to Harvard undergrads, letting young women try on the dresses first. The pilot was an unqualified success. Women not only rented the dresses but returned them in good condition. This experiment demonstrated that there was a market for renting dresses and that renters would return them in good shape. But would women rent dresses they couldn’t try on? To answer that question, they set up another experiment, this time on the Yale campus, allowing women to see the dresses before renting, but not allowing them to try them on. Although fewer women rented, the pilot proved successful. Finally, they took photos of dresses and ran a test in New York City where women rented a dress only from PDF photos and descriptions of how they fit. This experiment would tell them whether they could truly use a Netflix model of renting over the Web, or whether they must open stores where women could see and try on dresses. The final experiment showed that roughly 5 percent of women looking for special occasion dresses were willing to try the service, enough to demonstrate the viability of renting over the Web. And that’s how Rent the Runway launched. It has proved very successful, with over six hundred thousand members and roughly fifty thousand clients trying the service in the first year. Trying different experiments was critical to designing a successful business model. As Hyman told us, “Our revenue growth is amazing. This is a dream come true.”

As we studied innovators and their experiments, one thing we noticed was that the amount of experimenting required to gain new insights is almost the inverse of the amount of prior questioning, observing, and networking they had done. In other words, if you haven’t done much questioning, observing, or networking (or haven’t done them well), then you will have to run more experiments to gain the insights required to move forward. For example, Rent the Runway’s experiments were able to be carefully crafted to generate the right data because of years of observations that Hyman, in particular, had made of the needs of young women attending special events. (Hyman had worked for years at Starwood Hotels where she launched programs to meet the needs of wedding parties and honeymooners; she also worked at WeddingChannel.com and IMG, one of the world’s top firms for female models.) As a result, she had a deep knowledge of the needs of fashion-oriented young women, special events, and designers and designer clothing. This allowed her and Fleiss to design better experiments to test their ideas.

The bottom line is that if you ask salient questions, observe salient situations, and talk to more diverse people, you will likely need to run fewer experiments. And the experiments you do run will be better designed to generate the data you need to take the next step. Random experimentation occurs when you know very little from your questions, observations, and networking conversations.

In the end, we’ve learned that even when you’ve effectively questioned, observed, and networked, persistent experimentation is likely to be important for generating disruptive insights. Virtually every disruptive business that we studied evolved over time—through a series of experiments—into a business model that changed an industry. Some experiments were accidental. For example, Herb Kelleher of Southwest Airlines told us that the original low-cost airline entrant stumbled onto its quick-turnaround capability when financial pressures forced the company to service its routes with three planes instead of the four it had originally planned to use. It had to either cancel flights or figure out a way to fly a four-plane schedule with three planes. This led management to develop a new set of practices for turning the plane around as quickly as possible, eventually leading to a fifteen-minute plane turnaround. This innovation completely changed Southwest’s strategy and business model, as well as its bottom line.

Similarly, IKEA never intended to have knockdown kit furniture (disassembled furniture in flat parcel boxes) as a central feature of its low-cost furniture retailing model. A serendipitous experiment early on in the company’s history yielded an important insight. After completing a photo shoot for a furniture catalog, a marketing manager found not all the furniture fit back into the trucks. When a photographer suggested that they take the legs off the table and then slide the table into the truck, the lights went on: Ikea could knock down almost all its furniture to reduce shipping costs and make the customer the final assembler. This small experiment was critical to IKEA’s business model as a global furniture retailer.

Innovators engage in three types of experimenting to generate data and spark new insights: trying out new experiences, taking things apart, and testing ideas by creating prototypes and pilots. Although questioning, observing, and networking are excellent for providing data about the past and present, experimenting is the best technique for generating data on what might work in the future. In other words, it’s the best way to answer what-if questions. Innovators also understand that by asking salient questions, observing salient situations, and talking to the right people, you will likely need to run fewer experiments. This reduces the cost and time associated with experimenting. Finally, innovators understand—and accept—that the majority of their experiments will not turn out as planned (and indeed may turn out to be a colossal waste of time), but they know that experimenting is often the only way to generate the data required to ultimately achieve success.

Tips for Developing Experimenting Skills

To strengthen your experimenting skills, you will need to consciously approach your work and life with a hypothesis-testing mind-set. We recommend the following activities to practice and strengthen your experimenting skills.

Tip #1: Cross physical borders

Visit (or even better, live in) a new country or some other new environment, such as a different functional area within your company or a new company in a different industry. Acquire a passport mind-set to break free of common routines. Explore the world by engaging in new activities. Join new social or professional activities beyond your normal sphere, attend a lecture by someone whose work you’re unfamiliar with, or visit an unusual museum exhibit. When you try out these new activities, ask yourself questions to help produce new insights from the experience, such as: “If my work team were here, what could we learn from this experience that would lead us to do something new? If I were going to replicate one thing (product, process, and so on) from this environment in my everyday environment, what would it be?” Work to cross one border at least once every month.

Tip #2: Cross intellectual borders

Take out a new annual subscription to a newspaper, newsletter, or magazine from an entirely different context (or to help save trees, intentionally and regularly search the Web for country, industry, or profession information about areas distant from your own). If you live in the United States or France, consider reading a publication from China, India, Russia, or Brazil. If you work in the oil and gas industry, read a publication from the hospitality industry. If you are trained in marketing, read a publication related to engineering or operations.

Tip #3: Develop a new skill

To gain new perspectives, create a plan to develop some new skills or acquire new knowledge. Look for opportunities in your community to take classes in acting or photography, or get some basic training in mechanics, electronics, or home building. Try out new physical activities like yoga, gymnastics, snowboarding, scuba diving, or even sky diving (if you are brave enough). Check out the menu of courses at your local university and sign up for classes that sound interesting to you, ranging from history to chemistry to calligraphy. Or closer to home, identify another function in your company, whether it be marketing, operations, or finance, and see if you can learn how that function works in your company.

Tip #4: Disassemble a product

Look through your house for something that no longer works, or go to a junkyard or flea market to buy a few things that you can easily take apart. (This is especially fun to do with your kids.) Search for something that you’ve always been interested in but have never taken the time to explore. Set aside a block of time to take the objects apart piece by piece and search for new insights into how they were designed, engineered, and produced. Draw or write about your observations in a journal or notebook.

Tip #5: Build prototypes

Identify something that you would like to improve. What would it look like if you changed it? Build a prototype of your new, improved invention from random materials in your house or office, or go on a shopping spree to obtain odd things that might work well in the prototype. Play-Doh (the children’s modeling clay) is a great medium for creating prototypes. If you are feeling adventurous and want to splurge, you may even want to buy a three-dimensional printer that produces objects on demand (according to your design).

Tip #6: Regularly pilot new ideas

Gordon Moore, the cofounder of Intel, once recalled that, “most of what I learned as an entrepreneur was by trial and error.” Engage in frequent pilot tests (small-scale experiments) to try out new ideas and to see what you learn from doing something differently than you’ve done before. You, too, can become an experimenter when you embrace learning through trial and error, but you must have the courage to fail and learn from your failures. Make up your mind to plan and carry out a pilot test of an idea you have at work during the next month.

Tip #7: Go trend spotting

Actively seek to identify emerging trends by reading books, articles, magazines, Web links, blogs, and other sources that specifically focus on identifying new trends. Read material written by individuals you believe excel at identifying trends and seeing what’s next. Try reading the work of Kevin Kelly (executive editor of Wired and author of New Rules for the New Economy), Chris Anderson (editor in chief of Wired and author of The Long Tail and Free), or another author who is looking into the future. Then think about how these trends might lead to an interesting experiment with regard to a new product or service. Figure out a way to creatively conduct that experiment.

PART TWO

The DNA of Disruptive Organizations and Teams

7

The DNA of the World’s Most Innovative Companies

“Fast-growth companies must keep innovating. Companies are like sharks. If they stop moving, they die.”

—Marc Benioff, founder and CEO, Salesforce.com

IN THIS BOOK’S first six chapters, we described how innovative people think differently and act differently to generate creative ideas for new products, services, processes, and businesses. Now we shift our attention to answering the question: how do companies comprising many people build the code for innovation? Without a doubt, executives worldwide face this critical question as they try to build innovation capabilities within their companies to generate growth opportunities. Before addressing this question, though, let’s look at two other equally important ones. First, which companies are truly the most innovative and should serve as models of innovation? Second, does having an innovation capability (and a reputation for innovation) turbocharge a company’s market value?

In 2005, BusinessWeek began creating a list of the world’s one hundred most innovative companies. It based this list on a Boston Consulting Group survey of executives who voted on the companies. (See table 7-1 for the BusinessWeek top twenty-five innovative companies from 2005 through 2009.) A quick look at the list shows Apple at number one and Google at number two. OK, intuitively that sounds right. But based on the methodology, the list is largely a popularity contest based on past performance. Do General Electric, Sony, BMW, and Toyota really deserve to be on the list of most innovative companies today?

TABLE 7-1

BusinessWeek list of most innovative companies (2005–2009)

To answer these questions, we decided to develop our own list of innovative companies based on expectations of future innovations. We thought the best way to do this would be to see whether investors—voting with their wallets and purses—could give us insight into which companies they believe are most likely to produce new products, services, or markets.

We teamed up with HOLT (a division of Credit Suisse that had done a similar analysis for The Innovator’s Solution) to develop a methodology for determining what percentage of a firm’s market value could be attributed to its existing products, services, and markets. If the firm’s market value was higher than the cash flows attributed to its existing businesses, then the company shows an innovation premium. This is the proportion of a company’s market value that cannot be accounted for from cash flows of its current products and businesses in its current markets. Investors give this premium because they expect companies to come up with profitable new products or markets (for details on how to calculate the premium, see the endnote).[1] It is a premium that every executive and every company would like to have.

So how does the BusinessWeek top twenty-five stack up using our methodology? Our analysis reveals a different ranking order. (See our ranking in table 7-1 based on the average innovation premium over five years.)[2] Our research puts Amazon at number one (with a premium of 57 percent), Apple at number two (a premium of 52 percent), and Google at number three (a premium of 49 percent)—results that are reasonably similar to the BusinessWeek list. But take a look at the bottom five. Samsung (–29 percent), Sony (–28 percent), Honda (–27 percent), Toyota (–26 percent), and BMW (–26 percent) generate cash flows from existing businesses that are actually higher than their current market value. In other words, investors are not anticipating growth from new innovative products or services and, worse, they’re expecting that these firms’ existing businesses will likely shrink or have profit levels drop.

As we analyzed these results in greater detail, we realized that investors not only cared about whether companies could produce innovations, but also cared about whether they could generate profits from new products and services. For example, Sony (number nine on the BusinessWeek list) and Samsung (number twelve on the list) have historically produced innovations in the consumer electronics industry, but recently investors haven’t seen large profits from them and don’t expect to in the future. However, competitor Nintendo (number seventeen on the BusinessWeek list) has an innovation premium of 26 percent, which means Nintendo not only has done a better job of generating profits from past innovations (such as the Wii), but is expected to do so in the future, giving it a much higher ranking on our list. Automakers BMW, Toyota, and Honda rank low on our list not because they won’t innovate going forward, but because they will face severe challenges generating any profits from their innovations. Not only will these companies continue to fight emerging existing competitors (such as Korea’s Hyundai and China’s Chery), but a slew of brand-new competitors coming into the market, including battery-powered carmakers Tesla and Coda.

Given the differences described, we decided to generate our own list of most innovative companies based on their innovation premium. (See table 7-2.) We focused on large public companies (more than $10 billion in market value), since the BusinessWeek list likewise focused on large companies. Our ranking revealed that, looking into the future, Salesforce.com is ranked number one (Benioff’s disruptive cloud computing company, featured in chapter 2), followed by Intuitive Surgical (makers of the da Vinci system of surgical robots, which we will describe later). These companies are right up there with Amazon, Apple, and Google, which ranked three, five, and six, respectively. Do Salesforce.com and Intuitive Surgical deserve to be at the top of the list? Investors seem to think so. Salesforce.com not only has led the charge with cloud computing but has also introduced the AppExchange—which Forbes called the “iTunes of Business Software” and which won awards from the Software & Information Industry Association, SD Times, and others. The AppExchange offers more than a thousand applications for businesses in much the same way that the iPhone offers a multitude of applications for consumers. Moreover, Salesforce.com recently unveiled Chatter, a new social software application seen as “Facebook for businesses.” Chatter takes the best of Facebook and Twitter and applies it to enterprise collaboration (as we describe in chapter 2).

TABLE 7-2

The world’s most innovative companies (ranked by innovation premium)

Source: HOLT and The Innovator’s DNA LLC.

Intuitive Surgical (number two) is an equally impressive innovator, having introduced robotic-assisted surgery to the world. For many surgeries—like prostate surgery—Intuitive’s da Vinci system has become the modus operandi in most operating rooms. But someday it could also play a major role in military surgical units. A surgeon in London could use it to operate on an injured soldier in any of the world’s military hot spots. The $1.5 million da Vinci system allows surgeons to operate using three-dimensional visualization and four robotic arms that work with a precision that most surgeons cannot duplicate. This results in smaller incisions, fewer mistakes, shorter recoveries, and reduced hospitalization costs.

India’s Hindustan Lever (number seven) not only has been a consumer products innovator but, as described in chapter 3, has also used an innovative network-marketing approach to sell its products through thousands of underprivileged rural women throughout India. This has allowed Hindustan Lever to sell in over 135,000 villages and become the most trusted Indian brand—used by two out of three Indians. The U.K.’s Reckitt Benckiser Group (number eight) has been an innovation powerhouse with roughly 40 percent of revenue in recent years coming from innovations launched in the prior three years. Many ideas come through networking with outsiders via its IdeaLink Web site where it lists jobs that need to be done and requests solutions. The company is currently hunting for “methods for detection of parasites and other parasite eggs” among other things. Denmark’s Vestas Wind Systems (number eleven) recently won the “Innovation Cup” as the country’s most innovative company. It is the world’s leading supplier of wind power solutions and has spawned a number of innovations, including floating foundations for wind power stations at water depths of over thirty meters.

We believe our list better identifies the current and future innovators and is consistent with A. G. Lafley and Ram Charan’s argument that: “An innovation is the conversion of a new idea into revenues and profits . . . In fact, there is no correlation between the number of corporate patents earned and financial success. A gee-whiz product that does not deliver value to the customer and provide financial benefit to the company is not an innovation. Innovation is not complete until it shows up in the financial results.”[3]

If you agree with this statement, you probably prefer our ranking to BusinessWeek’s.

The DNA—People, Processes, and Philosophies—of Innovative Companies

Drawing on a sample of companies that lead both lists, we dove deeply into the practices of some of the world’s most innovative companies. We relied on both lists as models of innovation and emphasized those that appear in each (e.g., Amazon, Apple, Google, P&G) and those on the innovation premium list that may not be as well known globally for innovation (e.g., Salesforce.com; Intuitive Surgical; Hindustan Lever; Reckitt Benckiser).

We started by asking innovative founders at some of these firms, like Amazon’s Bezos or Salesforce.com’s Benioff: What makes your firm so innovative? What happens inside your firm that results in innovative new products, services, processes, or businesses? The first insight to emerge from these interviews is that founder innovators typically imprint their organizations with their own innovator’s DNA. To illustrate, Bezos described how he surrounds himself with people at Amazon who are inventive. He asks all job candidates: “Tell me about something that you have invented.” He adds, “Their invention could be on a small scale—say, a new product feature or a process that improves the customer experience, or even a new way to load the dishwasher. But I want to know that they will try new things.” When the CEO asks all job candidates whether they’ve ever invented anything, it sends a powerful signal that invention is expected and valued. “I also look for people who believe they can change the world,” Bezos told us. “If you believe the world can change, then it’s not a stretch to believe you can be a part of it.”

He also talked about the importance of experimentation processes (as we described in chapter 6), stating that, “I encourage our employees to experiment. In fact, we have a group called Web Lab that is charged with constantly experimenting with the user interface on the Web site to figure out improvements for the customer experience.” Finally, he discussed the importance of culture, saying that most company’s big errors are “acts of omission” instead of acts of “commission.” “It’s the opposite of sticking to your knitting. It’s when you shouldn’t have stuck to your knitting and you did,” says Bezos. So he encourages people at Amazon to ask “why not?” when considering whether to launch something new. “It’s very fun to have a culture where people are willing to take these leaps. It’s the opposite of the ‘institutional no.’ It’s the institutional yes. People at Amazon say, ‘We’re going to figure out how to do this.’”

To sum up: Bezos looks for people with an inventive attitude like his. He personally experiments as a way to generate innovative ideas, so he’s created processes at Amazon that encourage and support experimenting by others. And he asks why not and is willing to take leaps (as he did leaving D.E. Shaw to start Amazon; he certainly did not “stick to his knitting” when he made that career decision). Not surprisingly, this philosophy has become part of the culture at Amazon in which others are also expected to ask why not and take leaps.

Our observations at Amazon and other highly innovative companies confirm insights about the genesis of organizational culture made by MIT’s Edgar Schein in his classic work Organizational Culture and Leadership. Schein argues that organizational culture arises during the early stages of an organization when it faces particular problems or must accomplish particular tasks. For example, the challenge might be: “How do we develop a new product?” or “How do we deal with this customer’s complaint?” In each instance, organization members responsible for resolving the problem sit down and decide on a method for resolving it. If the method works successfully, the organization likely uses it again and again when faced with similar problems and it becomes part of the organization’s culture (a taken-for-granted way for how the organization addresses certain problems). If it does not work well, the organization’s leaders will devise a different method for solving the problem and continue to search until a method successfully solves it. As any particular method for solving a problem is profitably used over and over, it becomes part of the culture. Not surprisingly, Schein observes that a company founder has a significant influence on the methods chosen to solve the organization’s early challenges. Ultimately, if the founder’s methods for reaching solutions work reliably and successfully, they come to be taken for granted for accomplishing particular tasks in the company. It is through the repeated, successful application of the founder’s initial solutions that they become embedded in the organization’s culture.

The point, of course, is that the DNA of innovative organizations likely reflects the founder’s DNA. As we talked to innovative founders about creating innovative organizations and teams, they repeatedly discussed the value of populating the organization with people who are like them (in other words, innovative), processes that encourage the innovative skills they depended on (e.g., questioning, observing, networking, experimenting), and philosophies (a culture that encourages everyone to innovate and take smart risks). Our observations of other companies on our most innovative list revealed the same thing. This led us to develop a set of working hypotheses about the DNA of innovative organizations that we put into a 3P framework of innovative organizations.

People

First, we found that innovative companies were often led by founder entrepreneurs, leaders who excelled at discovery and who were not bashful about leading the innovation charge. In fact, key leaders of these companies showed a higher discovery quotient than leaders of less innovative companies (more on this in chapter 8). We also found that highly innovative companies had stronger discovery skills in all management levels and each functional area of the organization. They also monitored and managed the appropriate mix of decision makers’ discovery and delivery skills throughout the innovation process (from ideation to implementation). Finally, they often had created a senior-level position focused on innovation, which is what Lafley did when he hired Claudia Kotchka as vice president for design, innovation, and strategy. Put simply, these companies were filled on average with far more people who excelled at the five discovery skills described in chapters 2 through 6, and they were wiser than less innovative companies about the strategic use of discovery-driven people.

Processes

Just as inventive people systematically engage their questioning, observing, networking, and experimenting skills to spark new ideas, we discovered that innovative organizations systematically develop processes to encourage these same skills in employees. Most innovative companies construct a culture that reflects the leader’s personality and behaviors. For example, Jobs loves to ask “what if” and “why” questions and so do Apple employees. Lafley has devoted hundreds of hours to observing customers, just as anthropologists observe tribes, and has put specific processes in place for observing customers at P&G. Benioff is a great networker, and at Salesforce.com he introduced Chatter and other networking processes to help employees network both inside and outside the company for unusual ideas. As an exceptional experimenter himself, Bezos has tried to institutionalize experimentation processes at Amazon that allow employees to go down blind alleys in pursuit of new products or processes. By creating organizational processes that mirror their individual discovery behaviors, these leaders have built their personal innovator’s DNA into their organizations.

Philosophies

These organizational discovery processes are supported by four guiding philosophies that imbue employees with the courage to try out new ideas: (1) innovation is everyone’s job, (2) disruptive innovation is part of our innovation portfolio, (3) deploy lots of small, properly organized innovation project teams, and (4) take smart risks in the pursuit of innovation. Together, these philosophies reflect the courage-to-innovate attitudes of innovative leaders. They believe innovation is their job, so they constantly challenge the status quo and aren’t afraid to take risks to make change happen. To illustrate, the most innovative companies don’t relegate R&D to one unit. Instead, virtually everyone, including the top management team, is expected to come up with new ideas, which results in a democratization of innovation efforts. The notion that everyone should innovate and challenge the status quo is supported by a risk-taking philosophy, such as IDEO’s “fail soon to succeed sooner.” The remarkable companies we studied not only show a tolerance for failure; they see failure as impossible to avoid and a natural part of the innovation process. Moreover, since they believe that everyone can be creative, they work hard to keep units small so that each employee feels empowered and responsible for innovating (Amazon’s Bezos employs a “Two Pizza Team” rule, meaning that teams should be small enough—six to ten people—to be adequately fed by two pizzas).

In sum, our interviews and observations revealed that innovative companies build the code for innovation right into the organization’s people, processes, and guiding philosophies (the 3P framework that comprises the DNA of innovative organizations.) (See figure 7-1.)

FIGURE 7-1

People, processes, and philosophies in the world’s most innovative companies

Of course, the devil is in the details in making the 3P framework real to employees. Many organizations say that they have innovative people and that they encourage innovation through the company’s processes and guiding philosophies. But they can be clueless about how to embed them deeply into the organization’s culture. In this chapter, we have identified some of the world’s most innovative companies and provided a framework to help you see how creative organizations do it.

How Innovative Is Your Organization or Team?

To get a quick snapshot of your organization or team’s innovation profile, take the following short survey (1 = strongly disagree; 2 = somewhat disagree; 3 = neither agree or disagree; 4 = somewhat agree; 5 = strongly agree). Remember to answer based on the people, processes, and philosophies that actually exist within your organization or team, not what you would like them to be.

People

1. Our organization or team has leaders with a well-known track record for generating innovative ideas for new processes, products, services, or businesses.

2. Our organization or team actively screens for creativity and innovation skills in the hiring process.

3. Evaluating an employee’s creativity or innovation skills is an important part of the performance appraisal process within our team or organization.

Processes

4. Our organization or team frequently engages in brainstorming to generate wild or very different ideas by drawing analogies from other products, companies, or industries.

5. Our organization or team encourages team members to ask questions that challenge the status quo or conventional ways of doing things.

6. Our organization or team cultivates new ideas by giving people frequent opportunities to observe the activities of customers, competitors, or suppliers.

7. Our organization or team has instituted formal processes to network outside the company to find new ideas for processes or products.

8. Our organization or team has adopted processes to allow for frequent experiments (or pilots) of new ideas in search of new innovations.

Philosophies

9. Our organization or team expects everyone to offer creative ideas for how the company should change products, processes, and so on.

10. People in our organization or team are not afraid to take risks and fail because top management supports and rewards risk taking.

To score your survey:

Add up your total score for all ten questions. Your team or organization scores very high on the innovator’s DNA if the total score is 45 or above; high if the score is 40–45; moderate to high if the score is between 35 and 40; moderate to low if the score is 30–34; low if the score is below 30. The short survey is drawn from a more systematic organization or team assessment available from the authors; for more information, see http://www.InnovatorsDNA.com.

As we mentioned at the beginning of this chapter, chapters 2 through 6 focused primarily on how individual innovators do their work. In this chapter, we’ve suggested that the innovator’s DNA has some clear organizational analogs and applications. We think there are equally compelling applications to teams at work (where the principles apply as they do with individuals and organizations). We believe this because the boundaries between what an organization is and what a team is are becoming increasingly blurred in our fast-paced world where organizations like Vodafone start entirely new business units with twelve people. Is that an organization or a team? We see it as a classic case of both, since an organization is a collection of teams, and the innovator’s DNA works well in each. In the three chapters that follow, we describe in detail how innovative organizations and teams build the code for innovation into their people, processes, and philosophies.

8

Putting the Innovator’s DNA into Practice: People

“Innovation distinguishes between a leader and a follower.”

—Steve Jobs

EVERY DAY, your executive actions may be the most powerful signal to your organization and team that innovation truly matters. Our interviews with dozens of senior executives of large organizations revealed that in most cases, they did not feel personally responsible for coming up with innovations. They only felt responsible for “facilitating the process” to make sure someone in the company was doing so. But in the world’s most innovative companies, senior executives like Jeff Bezos (Amazon), Marc Benioff (Salesforce.com), and A. G. Lafley (Procter & Gamble) didn’t just delegate innovation; their own hands were deep in the innovation process.

As we showed in chapter 1, leaders of highly innovative companies scored around the eighty-eighth percentile in discovery skills (an overall discovery quotient of 88 percent), but only around the fifty-sixth percentile in delivery skills. When asked about their lower delivery-skill scores, innovative executives typically responded that they didn’t have the time or didn’t want to spend the time on execution tasks. Their focus was innovation, so they actively engaged in questioning, observing, networking, and experimenting, which had a powerful imprinting effect on their organization and team. Because innovators excelled at the innovator’s DNA skills, they valued them in others, so much so that others within the organization felt that reaching top executive positions required personal innovation capability. This expectation helped foster an innovation focus throughout the company.

By contrast, a sampling of top executives without a personal innovation track record revealed that, on average, they scored at around the sixty-eighth percentile in discovery skills, but roughly the eightieth percentile in delivery skills. (See figure 8-1.) They were clearly above average in discovery, but it wasn’t their distinctive competence. Basically they were delivery-driven executives who had moved up the management pyramid by executing and delivering results. Since they were role models for advancement, others marching up the management ladder were selected for a similar skill set. As a result, the entire management team of less innovative organizations displayed a lower discovery quotient.

FIGURE 8-1

Discovery-delivery skills matrix

Apple’s performance under Jobs, compared to other leaders, powerfully illustrates this concept. (See figure 8-2.) From 1980 to 1985 during Jobs’s initial tenure at Apple, the company’s innovation premium was 37 percent. However, during the 1985–1998 period without Jobs, Apple’s innovation premium dropped to an average of –30 percent. Apple quit innovating and investors lost confidence in Apple’s ability to innovate and grow. When Jobs returned and restructured his senior management team with more discovery-driven capacity, Apple started to innovate again. It took a few years to get back on track, but between 2005 and 2009, Apple’s innovation premium jumped to 52 percent.

FIGURE 8-2

Innovation premium for Apple Inc.

Why Innovative Leaders Make a Difference

In chapter 1, we described how Jobs got key ideas for the Macintosh computer (mouse and GUI interface) during his pivotal visit to Xerox PARC. He recalled “being shown a rudimentary graphical user interface. It was incomplete, some of it wasn’t even right, but the germ of the idea was there. Within ten minutes, it was so obvious that every computer would work this way someday.”[a] Jobs was so impressed that he took his entire programming team on a tour of PARC and returned to Apple laser-focused on developing a personal computer that incorporated and improved on the technologies they saw at PARC. Jobs assembled a team of brilliant engineers, gave them the needed resources, and infused the Macintosh team with a vision of what was possible. That’s what an innovative leader does.

In stark contrast, the executive team at Xerox lacked the discovery skills necessary to exploit technologies developed in their own company. As PARC scientist Larry Tesler observed, “After an hour looking at demos, they [Jobs and Apple programmers] understood our technology and what it meant more than any Xerox executive understood after years of showing it to them.”[b] Jobs agreed with Tesler, saying, “Basically they were copier heads that just had no clue about a computer or what it could do. And so they just grabbed defeat from the greatest victory in the computer industry. Xerox could have owned the entire computer industry today.”[c] No wonder Tesler left PARC and joined Apple. Innovators want to work with and for other innovators. Moreover, companies with innovative leaders are much more likely to devote the resources required to pursue potentially revolutionary ideas.

a. “1994 Rolling Stone Interview of Steve Jobs,” http://holykaw.alltop.com/ 1994-rolling-stone-interview-of-steve-jobs

b. Robert X. Cringely, Triumph of the Nerds, PBS documentary, New York, 1996.

c. Ibid.

In similar fashion, P&G performed well as an innovative company before Lafley became CEO in 2000, as evidenced by the 23 percent average innovation premium from 1985 to 2000. However, Lafley’s innovation focus boosted P&G’s innovation capability and delivered a 35 percent innovation premium, on average, during his 2001 to 2009 tenure. (See figure 8-3.)

FIGURE 8-3

Innovation premium for Procter & Gamble

Lafley, and other innovative leaders we studied, very consciously set the example by modeling innovation behaviors to help make them matter to others. “Lafley always gets out in marketplaces and wants consumer interactions,” says Gil Cloyd, a member of his top management team and former chief technology officer. “He’s genuinely curious about it. This becomes important because it’s not just role modeling of something you’d like, but it’s an infectious curiosity to discover how we can provide an ever more delightful experience for our consumers, improving lives in yet another way.” By simply watching Lafley’s everyday actions and noticing how much time he personally spent generating new ideas, his team (and organization) “got it” about innovation. Lafley also demonstrated that innovation is just not an individual game but, in the end, a powerful team effort. “You remember the times when nobody knew what to do and you came through with something that people didn’t think you could come through with or when you create something that people didn’t think could be created,” Lafley observed. “When this happens in our company, it’s never one person. It’s always a group . . . Getting everybody in the same boat, rolling in the same direction, that is really what’s fun. Especially when you win.”

These innovation premium data on CEO impacts at Apple and P&G reflect a key finding in our research that if top executives want innovation, they need to stop pointing their fingers at someone else and take a hard look at themselves. They must lead the innovation charge by understanding how innovation works, improving their own discovery skills, and sharpening their ability to foster others’ innovation. Moreover, they must actively populate their team and organization with enough high-discovery-quotient individuals to truly make innovation a team game.

Building a Team and Organization with Complementary Skills

While ensuring that your organization is populated with folks who are good at the five discovery skills is important, we don’t want to leave the impression that discovery-driven people are all that matters in a team or organization. The fastest way for an organization to die is to stop executing. Discovery-driven leaders need the delivery-driven skills of people who excel at execution. Not only do effective leaders of innovative teams understand their own constellation of discovery and delivery skills, they actively balance their weaknesses with other people’s strengths.

Complementary Discovery Skills Can Boost Innovation

We accidently discovered something about the composition of highly innovative teams after Ross Smith, director of Windows Core Security at Microsoft, and Dan Bean, a member of the Microsoft Defect Prevention (DP) team, called us to discuss team innovation. Smith was managing roughly seventy teams (ranging from four to eight people) working on various issues related to Window’s security. He had observed that one of those teams, the six-person DP team, had been the most innovative for the past five years. The team had pioneered a number of innovations, but perhaps the most valuable were clever “productivity games” for enticing users to give feedback on key Microsoft products.

For instance, the DP team members created whimsical games that presented each of the Windows dialogues in a different language for native speakers. To get feedback, they sent the game to the thousands of Microsoft employees who spoke a language other than English, from Chinese to Slovakian. When playing the game, users received a colored electronic pen for highlighting language errors and dragging them to a “no good” bucket (for which they gained extra points). They could also type in comments when dragging errors to the bucket. “These productivity games had huge impact,” Smith told us. “We saved millions of dollars and improved quality to a level that we’ve never seen before.”

Smith wanted to better understand why this particular team showed greater innovation results than some other teams staffed with equally talented software engineers. One answer, Smith believed, was that the DP team had developed a high level of mutual trust through active, focused effort. Another important ingredient—first noticed by team member Bean—was that team members seemed to possess complementary discovery skills. We tested and confirmed Bean’s hypothesis with our 360-degree innovator’s DNA assessment.

Specifically, we found that each team member excelled at a different discovery skill. Smith excelled at associating, Bob Musson at questioning, Bean at questioning and observing, Joshua Williams at networking, and Harry Emil at experimenting. Thus, the team displayed a collective discovery aptitude that was extremely high, thanks to team members’ complementary discovery skills. In short, the team achieved higher synergies in discovery because team members brought different novel inputs to the team through different discovery skills. “All I know,” says Bean, “is that the discussions we have in this team are the most creative and stimulating I have run into at Microsoft. And that makes it really fun to work in the team.” It also didn’t hurt that team leader Smith, according to team members, is someone who “trusts his people,” “encourages folks to come up with new ideas and take risks,” “values independent thinkers,” “encourages and inspires new ideas,” and “evangelizes the work of others and has a tendency to downplay his own contribution.” In short, Smith has done exactly what a good leader does to create a safe space for others to innovate (more on this in chapter 9).

Beyond Microsoft, we noticed similar patterns in other highly innovative teams. When complementary discovery skills exist, the rich skill diversity increases the team’s overall ability to innovate. Thus, the team’s capacity to generate new ideas consistently outstrips the ability of either any individual team member or another team when team members excel at the same discovery skill (e.g., networking is the primary source of new ideas for all team members). Moreover, when different team members shine at different discovery skills, they can learn more from each other, creating further innovation synergies.

For example, during the highly successful 1990 to 2005 run at Dell Computer, Michael Dell engaged in a frequent tug of war between discovery and delivery with then president Kevin Rollins. Dell recalled:

I gave Kevin a Curious George stuffed animal. The Curious George is for Kevin to ask questions, to be a little more inquisitive. Kevin responded by giving me a toy bulldozer driven by a little girl with a huge smile on her face. Sometimes I’ll get really excited about an idea and I’ll just start driving it. Kevin put the bulldozer on my desk, and it’s a signal to me to say “Wait a second, I need to push it a little more and think through it for some others and kind of slow down on this great idea that I’m working on.” We don’t use them that much, but they’re subtle little jokes between us.

Rollins acknowledged that Dell and he played different roles, telling us, “Michael simply owns more of the entrepreneurial juice stuff. He has an idea a day, an hour. In big companies, you can’t do an idea a day. I’m the governor of the innovation engine.”

Similarly, eBay’s Pierre Omidyar was aware that he was strong at discovery but weak at execution. Identifying this need for stronger execution skills on his team, he invited Jeff Skoll, a Stanford MBA, to join him. “Jeff and I had very complementary skills,” Omidyar told us. “I’d say I did more of the creative work developing the product and solving problems around the product, while Jeff was involved in the more analytical and practical side of things. He was the one who would listen to an idea of mine and then say, ‘OK, let’s figure out how to get this done.’” Omidyar grasped the power of complementary skills when building a top management team at eBay.

The takeaway from these stories is that successful innovation as a team requires the ability to generate novel ideas and the ability to execute those ideas on the team. Both skills sets are necessary. Smart leaders know this and consciously think about team composition, making sure the team is balanced enough in terms of discovery and delivery skills. Figure 8-4 shows discovery and delivery skills temporarily “in balance” on a team. But remember that perfect balance is not necessarily the perfect solution.

FIGURE 8-4

Balancing discovery and delivery skills in a team or company

Sometimes discovery skills should weigh more heavily on a team or throughout an organization (particularly during the founding stage of an organization or if the team is charged with product development, marketing, or other business development tasks). At other times, delivery skills are relatively more important, and those skills should be given greater weight on the team (during growth or the mature stage of a business, or in functional areas related to operations and finance). In figure 8-5, we show the average desirable team profile for different types of high-performing teams in organizations (assuming each team averages about the seventieth percentile across both skill sets).

FIGURE 8-5

Desired skills composition in different types of teams

People in product development and marketing teams should score, on average, higher on discovery than delivery skills (though having some team members who excel at execution might work best). In contrast, people on finance and operations teams should score, on average, higher on delivery than discovery skills (again, it’s not a bad idea to have a few folks strong at discovery in the mix). The trick is first knowing who has what skills and then figuring out how to combine complementary strengths within a team to generate ideas with impact.

The relative importance of discovery and delivery skills on a particular team also varies with the team’s particular role in the innovation funnel (or innovation cycle). For example, at BIG, a company that uses the business model of the American Idol TV show to find inventors and bring their products to market, CEO Mike Collins wants a different mix of discovery and delivery skills at each stage of the innovation funnel.

Stage one at BIG is “idea generation,” when his organization actively looks for innovative ideas from inventors around the world. His company engages in “big idea hunts” through road shows in different cities, Internet and newsletter solicitations, and connections with professional inventor groups. Over time, BIG has developed a network of professional inventors that it taps not only for their own product ideas, but also for BIG’s clients. BIG makes money from taking inventor’s ideas to market and by using its inventor network to come up with new product ideas for specific clients wanting new product ideas from outside their companies. In effect, companies outsource new product development to BIG just as they outsource innovative product designs to IDEO.

During stage two, called “winnowing,” Collins invites (and pays) individuals with strong discovery skills to participate on a panel to listen to inventors’ ideas and evaluate whether a new product idea shows market potential. Over time, he’s learned that the panel works best when it includes people with strong discovery skills, because they see beyond the initial idea in search of ways to improve it. “On one occasion, we were evaluating ideas for new toys, and we asked a senior merchandising executive from a major toy retailer to participate on the panel,” Collins told us. “But he was useless because all he could do was analyze why an idea wouldn’t work. He was all about execution, and at the idea stage, you need people who can find creative ways to make an idea work.” Collins’s experience suggests that the first two stages of the innovation funnel need people very strong at discovery, but these skills become less critical in stages three and four.

Stage three is the “refinement” stage when the idea is tested to see whether it works in the marketplace. Designers and engineers collaborate to help design and build product prototypes. Marketers assess whether a sizable market exists for the product. Manufacturing specialists (often in China) analyze the product’s cost at different unit volumes. These tasks require stellar execution skills first and foremost. However, even at this stage, Collins and others with strong discovery skills serve a critical role in searching for innovative adaptations to the product, making it even more desirable to customers.

Stage four is the “capture value” stage when the product launches to the market. While this stage centers mostly on delivery in terms of manufacturing, marketing, distributing, and selling the product, discovery skills can still generate value as BIG searches for innovative ways to manufacture, market (brand), distribute, and sell (price) the product. “You can find ways to innovate at any stage of the innovation process,” says Collins. In fact, BIG is quite innovative in this final stage of the innovation funnel, using a wider variety of distribution channels for its inventor-produced pipeline of products than a typical company.

To illustrate, BIG’s early search for new product ideas was in the product category of toys. Once BIG had gone through the first three stages of sourcing and developing a new toy idea, it then would face the question: what is the best way to capture value from this product (e.g., manufacture, market, sell)? Some new toy products fit well with Toys “R” Us, the retailer you would normally think about as the best way to distribute new toys. In these cases, BIG might source production from China and let Toys “R” Us take it from there. However, rather than just rely on Toys “R” Us or Walmart (the big-box toy retailers in the U.S.), BIG found that some new toy ideas were better suited for the Learning Company, Basic Fun, the National Geographic catalog, QVC, Brookstone (toys for adults), or numerous other channels. It also licensed toy ideas to Hasbro, Mattel, or other toy manufacturers that were better positioned to take a particular toy to market due to their particular resources and processes. In short, BIG was far more innovative in the final stage of the innovation funnel compared to a toy company like Mattel, which basically took all its toys to big-box retailers like Toys “R” Us or Walmart. The point is that, while you might need more discovery skills at the early stages of the innovation process, you should deploy (or at least sprinkle) people with strong discovery skills throughout every team in the organization—and at every stage of the innovation funnel.

The Value of Complementary Human, Technical, and Business Expertise

Making sure that innovative teams possess complementary discovery and delivery skills matters, but making teams multidisciplinary—comprised of individuals with deep expertise in different disciplines—also matters in company innovation. To illustrate, consider how IDEO, the hottest innovation design firm in the world (it has won twice as many Industrial Design Excellence Awards as any other firm) staffs innovation design teams. These are teams explicitly charged with creating an innovative product design or new service concept.

In general, IDEO works to create multidisciplinary teams comprised of individuals who are T-shaped in terms of expertise: deep in one area of expertise with shallow expertise in multiple areas of knowledge (as described in chapter 2). Of course, as a design firm, all IDEO teams have a team member with significant design expertise. However, IDEO teams also search for individuals with expertise that falls in one of three domains: “human factors” expertise (to determine the desirability of an innovative idea), “technical factors” expertise (to assess the technical feasibility of an innovative idea), and “business factors” expertise (to evaluate the business viability and profitability of an innovative idea).

First, IDEO includes a human-factors expert on the team, someone with a background in one of the behavioral sciences such as anthropology or cognitive psychology. This person provides insight into the desirability of a new product (or service) from the user’s perspective. The human-factors person orchestrates in-depth observations of customers to understand the job to be done and to acquire deep user empathy. For example, when designing a product or service for people in wheelchairs, the human-factors person might make sure that people on the team spend one day experiencing the world as someone in a wheelchair would. By gaining insight and empathy into the user experience, the human-factors person brings insight into the desirability of an innovative new design. This perspective is particularly important in early stages of designing a new product or service.

A Lack of Business Innovation May Stifle Technology Innovation

A few years ago, Clayton Christensen received a visit from a few technology executives at 3M who expressed frustration that innovations weren’t getting to market because of a lack of innovation on the business side. 3M has long been known for innovation, and Christensen knew the company well as a result of several onsite visits to grasp how innovation works there. During his visits, he found that 3M’s research and development arm applied the innovation principles described in this book. It hired people with deep and varied expertise, connected discovery-driven people with varied technology expertise, and had philosophies that encouraged innovative behavior.

So what was the problem the 3M team brought to Christensen? They showed him a gift bag that was unlike anything he had ever seen. If you looked at the bag straight on, it was a beautiful purple color. If you looked at it at a different angle, it was pink. Inside it was bright white. By using technologies that allowed polymers to absorb or repel wavelengths, the team created a gift bag that could literally change colors. This seemed remarkable, but the team was far from elated. “The corporation doesn’t want to take it to market,” they said. “The market’s not big enough.”

From Christensen’s view, this was an amazing gift bag. The market for these types of bags must be huge. Indeed, the world market for gift bags and boxes is in the billions, but profit margins in the gift-bag segment are only 30 percent, he was told. 3M’s typical profit margins are 55 percent, and the treasury didn’t typically fund product launches with lower margins. This led to the question, what if the team just raised the price on the bags to reach the target margin of 55 percent? The response was that if the price increased, the market would shrink so much (to a small niche) that it wouldn’t be big enough for 3M to pursue.

The challenge was finding a way to profitably take this innovative product to market. But 3M didn’t pursue innovation on the business side as much as it did on the technology side. It had created rules about launching products and didn’t expect innovation on the business side of how it decided to fund or not fund the launch of a new product.

We’ve observed this challenge elsewhere. Companies relegate innovation to the R&D unit where people should innovate, but those on the business side should just execute and skip the same innovation challenge. The result (in 3M and other companies) is that a lack of business innovation can easily stifle technology innovation. Not surprisingly, this can deflate folks in the R&D side of the business. Moreover, the company can miss disruptive opportunities that it wouldn’t miss if it could only innovative a bit more in how it manufactures, distributes, markets, prices, or allocates resources to a product.

The technical-factors person brings deep expertise in various technologies that the team might employ in the design of a new product or service. This person likely comes from an engineering or science background. This expertise is important in order for the team to grasp what technologies are feasible for use in a particular new product or service design. Technical expertise is particularly critical after the team has clearly identified the user’s needs (the job to be done) and then is searching for and deciding on technologies to provide the optimal solution.

Finally, the business-factors person brings the expertise necessary to figure out whether an innovative new product or service design will prove viable in the market. This person likely has a business background, such as a master’s degree in business administration (MBA) with expertise in operations, marketing, or finance. Naturally, this expertise becomes more relevant in the later stages of the innovation process when a team must determine the optimal way to manufacture, distribute, promote, and price the product for profitability.

By staffing teams with complementary expertise, IDEO can better look at problems from a variety of angles and discover a new product or service that is desirable, feasible, and viable. No wonder it generates so many successful innovations.

Like IDEO, Apple spurs innovation by filling its ranks with people who possess various different types of expertise. “Part of what made the Macintosh great was that the people working on it were musicians, and poets, and artists, and zoologists, and historians, who also happened to be the best computer scientists,” says Jobs. “The reason Apple is able to create products like the iPad is because we always try to be at the intersection of technology and liberal arts, to be able to get the best of both.”[1] The key point is that innovative companies select a mix of people who possess not only complementary discovery and delivery skills, but also different expertise and diversity of backgrounds to look at problems through multiple lenses.

In summary, the most innovative companies in the world have leaders who understand innovation at a deeply personal level. They lead the innovation charge with a high discovery quotient and regularly contribute innovative ideas to the company. As one executive with a delivery-driven boss complained to us, “you can’t be all about execution and expect people to be innovative. It just doesn’t work that way.” Innovative companies find novel ways to hire discovery-driven people who have a track record of innovation and a strong desire to change the world. Having a larger number of discovery-driven people lays the foundation for strong innovation synergies as discovery- and delivery-driven folks interact well enough to learn from and support each other. Innovative teams (and companies) perform best when discoverers honestly appreciate the pivotal role of those with strong execution skills (and vice versa), especially in teams staffed with folks possessing complementary skills. Finally, innovative companies hire and staff teams with people who possess different types of expertise (preferably with a T-shaped profile) so that the team or organization can view and solve problems from very wide angles.

9

Putting the Innovator’s DNA into Practice Processes

“We don’t care if you give us a toothbrush, a tractor, a space shuttle, a chair; we want to figure out how to innovate by applying our process.”

—David Kelley, founder, IDEO

OUR RESEARCH ON THE WORLD’S most innovative companies reveals that the DNA of innovative organizations mirrors the DNA of innovative individuals. Just as inventive people systematically engage in questioning, observing, networking, and experimenting to trigger new ideas, innovative organizations develop processes that encourage these same skills in employees. They also rely on systematic processes to find people with strong discovery skills who thrive in environments that embrace their use of those skills. As described in chapter 7, organizational processes reflect a response to recurring tasks that when used frequently become taken-for-granted recipes to solve particular problems. However, for processes to help organizations generate innovations (e.g., new process, product, service, or business ideas) systematically, they must be widely understood and employed throughout an organization (not just by an innovative founder or a small number of highly innovative people). In this chapter, we first discuss how innovative organizations find people who excel at discovery, and then we examine the processes that encourage—even require—employees to question, observe, network, and experiment.

How Innovative Organizations Find Discovery-Driven People

Leaders of highly innovative organizations understand the critical need to attract creative people if the company hopes to build a cadre of innovators at all levels. “In most things in life, the dynamic range between average quality and the best quality is, at most, two-to-one.” Steve Jobs discerned. “But, in the field that I was interested in—originally hardware design—I noticed that the dynamic range between what an average person could accomplish and what the best person could accomplish was 50 or 100 to 1. Given that, you’re well advised to go after the cream of the cream. That’s what we’ve done. A small team of A+ players can run circles around a giant team of B and C players. That’s what I’ve tried to do.” So how do highly innovative companies find employees that rate A+ for innovation? They look specifically for people who:

1. Show a track record that demonstrates strong discovery skills (for example, they have invented something).

2. Possess deep expertise in at least one knowledge area and show breadth in a few others (for example, the T-shaped knowledge profile of innovators we discussed in chapter 2).

3. Display a passion to change the world and make a difference.

Clearly, if companies want innovative ideas from employees, they should screen for innovation potential in the hiring process. Most companies rarely do it but highly innovative ones do. They explicitly screen candidates for creativity and innovation skills as part of the new-hire process. For example, at Virgin (number sixteen on the BusinessWeek list), Richard Branson has made innovation one of six key characteristics the company evaluates when screening new employees. To get hired at Virgin, you must demonstrate a “passion for new ideas,” you must “make your creativity apparent,” and you must show “a track record of thinking different.” Virgin describes its people as “easy to spot. They act in unusual ways, as it’s the only way they know how. But it’s not forced—it’s natural. They are honest, cheeky, questioning, amusing, disruptive, intelligent, and restless.” By looking for people who are cheeky, questioning, amusing, disruptive, intelligent, and restless—and show a track record of thinking different—Virgin increases the probability of having a crew of innovators at every level.

Google (number two on the BusinessWeek list; number six on our list) has developed a variety of innovative techniques to find job candidates both bright and curious. To illustrate, Google came up with a Google Labs Aptitude Test (GLAT), a twenty-one-question test that is a somewhat tongue-in-cheek way of screening for new employees. Some questions focus on evaluating quantitative ability (one question: “How many different ways can you color an icosahedron with one of three colors on each face?” Hint: the answer is 58,130,055). Others are designed to test for creativity and a sense of humor: “In your opinion, what is the most beautiful math equation ever derived?” Another says: “This space left intentionally blank. Please fill it with something that improves on emptiness.” People who lack the patience for such frivolity do not apply. People who both understand the question and find it amusing and challenging are exactly the kind of people Google wants to hire.

Another innovative technique for finding qualified and creative job candidates is Google Code Jam. Launched in 2003, Google Code Jam is a timed problem-solving contest (tournament) where all participants compete online to solve the same problems under the same time constraints. The prize for winning? $10,000 and a job offer from Google. In fact, in Google’s Code Jam 2006, it awarded jobs to the top twenty finalists. Of course, being a top-twenty finalist is no small feat, considering twenty-one thousand people from all over the world competed in the contest. Through use of the tournament, Google effectively screens twenty-one thousand worldwide applicants for jobs in a matter of days with a format that is almost entirely automated. The fact that winners of Code Jam have come from Russia, Poland, and China shows that Google is attracting global talent (entrants for Code Jam 2010 came from 125 countries). While the early qualifying rounds largely test an individual’s speed in solving computer programming problems, the final challenge phase, conducted with the a hundred finalists at Google’s headquarters, asks the participant to demonstrate more innovative thinking; each contestant attempts to crack the programming code of the other participants. This process has been very successful at helping Google find highly talented programmers who are passionate about programming and about wanting to work for Google.

A consistent theme within the most innovative companies was hunting for people who had invented something, held deep expertise in a particular knowledge area, and demonstrated a passion to change the world through excellent products and services. Amazon sends a powerful signal to any potential new hire that it expects and values invention by questioning them about something they have invented. IDEO (frequently in Business Week’s top 25 most innovative, but not on our list because it is a private company) looks for people with deep expertise, whether in psychology, anthropology, design, engineering, or whatever, in part because it demonstrates that they are passionate about something. Apple looks for A+ talent by explicitly looking for people with a demonstrated track record of excellence. “We wanted entrepreneurs . . . high energy contributors who defined their previous role in terms of what they contributed and not what their titles were,” said Sharon Aby, a former recruiter at Apple. “The main quality: expectation of excellence . . . As recruiters, we didn’t settle. I fought with some managers who wanted to fill a role quickly to get a project moving, but if it took six months to find the best, they’d have to wait. We looked for people who were excited to create new things. Our motto was, ‘Surprise me.’”[1]

Processes That Mirror the Discovery Skills of Disruptive Innovators

Highly innovative companies have a culture that reflects the leader’s personality and behaviors. In other words, innovative leaders often imprint personal behaviors as processes within the company. Here are some examples of how innovative leaders institutionalize processes to encourage questioning, observing, networking, and experimenting throughout their organizations.

Processes Can Turn “B” Players into “A” Players (and Vice Versa)

Jobs says Apple always goes for A+ players. Great advice—but doesn’t every company try to do this? What if you can’t attract A+ players though? And even if you can get them, does this ensure that they will perform? An intriguing study by Harvard’s Boris Groysberg, Ashish Nanda, and Nitin Nohria provides some interesting answers to these questions.[a] They studied the performance of stock analysts over time, particularly “star” performers who moved to a different company. Star stock analysts were identified by rankings provided by Institutional Investor (rankings based on criteria such as earnings estimates, stock selection, and written reports). Analysts with higher rankings delivered more accurate stock forecasts, and their reports produced bigger stock price impacts. The same star analysts who moved to an investment firm with less effective processes and resources though, experienced an immediate decline in performance that persisted for at least five years. Star analysts who moved between two firms with equivalent processes and resources also exhibited a performance drop, but only for two years. Thus, a firm’s resources and processes play an important role in star analysts’ performance. The researchers found that some firms, like Sanford Bernstein, were far more successful at growing stars because of key processes established to train, mentor, and support analysts. These findings are consistent with a study of 2,086 mutual fund managers that reported that 30 percent of a mutual fund’s performance could be attributed to the individual and 70 percent was due to the manager’s institution.

Most of us possess an instinctive faith in talent and genius, but it isn’t just people who make organizations perform better. The organization—its processes and philosophies—can also make people perform better. Companies can turn B people into A performers—or worse, A people into B performers—depending on its innovation processes and resources.

a. Boris Groysberg, Ashish Nanda, and Nitin Nohria, “The Risky Business of Hiring Stars,” Harvard Business Review (May 2004).

Discovery Process #1: Questioning

By now, virtually anyone working in a manufacturing environment has heard of lean manufacturing or, as it is known in the automobile industry, the Toyota Production System (TPS). The now-famous system was a leapfrog innovation over the mass-production techniques pioneered by Henry Ford. While Toyota (number four on the BusinessWeek list) certainly stumbled on quality in 2009, the original innovation propelled Toyota to become the global automotive leader in both revenues and profits for decades. Taiichi Ohno, a former engineer at Toyota who is known as chief architect of TPS, put a five-whys questioning process at the core of his innovative production system. Many of the world’s most innovative companies have adopted variations of the process.

The five-whys process requires that when confronted with a problem, ask yourself why at least five times to unravel causal chains and spark ideas for innovative solutions. To illustrate, in 2004, Bezos was visiting an Amazon fulfillment center with his leadership team. During the visit, he heard about a safety incident when an associate had seriously damaged his finger on a conveyor belt. When Bezos learned of the incident, he walked to the whiteboard and began to ask five whys to get at the problem’s root cause:

Question 1: Why did the associate damage his thumb?

Answer: Because his thumb got caught in the conveyor.

Question 2: Why did his thumb get caught in the conveyor?

Answer: Because he was chasing his bag, which was on a running conveyor.

Question 3: Why was his bag on the conveyor and why was he chasing it?

Answer: Because he placed his bag on the conveyor, but it then turned on by surprise.

Question 4: Why was his bag on the conveyor?

Answer: Because he used the conveyor as a table for his bag.

Question 5: Why did he use the conveyor as a table for his bag?

Answer: Because there wasn’t any place near his workstation to put a bag or other personal items.

Bezos and his team determined that the likely root cause of the associate’s damaged thumb was needing a place to put his bag but not having one around he used the conveyor as a table. To eliminate further safety incidences, the team provided portable, lightweight tables at the appropriate stations and additional safety training to alert associates about the dangers of conveyor belt work. While this innovation was minor, one Amazon member, Pete Abilla, said it was a transforming experience “that I carry with me to this day.” Abilla went on to describe several things that he learned.

1. “Bezos cared enough about an hourly associate and his family to spend time discussing his situation.

2. He properly facilitated the five-why exercise to arrive at a root cause: he did not blame people or groups (no finger pointing allowed).

3. He involved a large group of stakeholders, demonstrated by example, and arrived at a root cause (solution).

4. He is the founder and CEO, yet he engaged in the dirt and sweat of his employees’ situation.”

“In that simple moment, he taught all of us to focus on root causes,” says Abilla. “He demonstrated by example the importance of questioning.”[2] If Bezos were the only one to use the five-whys method, then it wouldn’t be a process at Amazon that consistently contributes to innovations. Instead, Amazon teaches the five-whys questioning process in training programs, and employees frequently rely on it when problem solving.

Our observations of Apple (number one on the BusinessWeek list; number five on our list) suggest that while it isn’t formalized, you could almost say the company uses a five what-ifs process as it brainstorms ways to wow customers. The iPad might never have been created had it not been for Jobs and his leadership team asking effective what-if questions. If they had asked, “How can we build a better e-book reader for the iPhone?” the innovative iPad might never have been created. Instead, Jobs reportedly asked, “Why isn’t there a middle category of device, in between a laptop and a smart phone? What if we build one?”[3] The what-if question sparked a discussion about a middle category that would have to be far better than either a smartphone or laptop in doing some key tasks like browsing the Web, enjoying or sharing photographs, and reading e-books. Consistently asking what-if questions is a key part of the culture at highly innovative companies.

Discovery Process #2: Observing

One company that turned keen observations into gold is medical robot maker Intuitive Surgical (number two on our list). Fred Moll, a surgeon turned entrepreneur, used his firsthand observations as a surgeon to develop robots that can perform surgery. Moll licensed some technology from SRI, a company that had worked on a Pentagon-funded project to bring the operating room to the battlefield without putting surgeons in harm’s way. The key was to ensure that robots could precisely mimic what surgeons wanted robots to do.

To refine the da Vinci robot prototype, Moll and Robert Young (an electrical engineer and founder of Acuson, a maker of ultrasound devices) mounted forty sensors along the joints of the flexible “master” joysticks. The sensors register the surgeon’s hand movements, which are conveyed as digitized information to a computer and recalculated as wrist, shoulder, and elbow positions thirteen hundred times a second. Those movements are transmitted electromechanically to robotic arms and then to the “slave” handles that manipulate the surgical instruments. Moll’s intent was for the robots to be precise, but he knew that surgeons lack perfect hand control. So the computer filters out hand tremors, making the da Vinci robot extremely precise. Even more important, Intuitive Surgical’s product developers continue to observe surgeons to create new da Vinci system tools, allowing medical robots to assist in doing more and different types of surgeries.

Keyence Corporation (number twenty-three on our list), a Japanese company that specializes in factory automation devices such as electronic sensors, makes sure that 25 percent of the devices it sells every year are new products and more advanced than anything rivals can offer. New product ideas surface mostly from the hands-on experience of seven thousand salespeople who proactively head to the production floors of some fifty thousand customers. Salespeople are required to spend hours observing customer manufacturing lines to gain insights into their problems. By watching the production lines of instant noodle makers, Keyence learned that noodle quality was compromised because they were manufactured at variable thicknesses. So Keyence developed laser sensors that could measure noodles to 1/100th of a millimeter. Instant noodle makers now depend on these sensors to keep noodle thickness consistent. Each year, thousands of observations like these by salespeople lead to hundreds of new factory automation devices for customers.

Beyond observing customers, our leading innovators also find ways to observe other companies’ practices to spark new ideas. For example, in 2008, Google and P&G (number six on the BusinessWeek list; number eighteen on our list) did an employee swap to spur innovation, despite the fact (or perhaps because of the fact) that the companies are quite different (P&G is a consumer products giant that spends $9 billion on advertising each year but very little online, whereas Google is an online search giant that makes most of its money through online advertising). Roughly two-dozen human resource and marketing employees spent weeks sitting in on each other’s training programs and meetings where business plans got hammered out. The initiative allowed for up-close observation of each other’s practices—with some interesting results.

For example, when Google observers watched P&G launch an ambitious new promotion for its Pampers line (using actress Salma Hayek), they were stunned to learn that Pampers hadn’t invited any “mommy bloggers”—women who run popular Web sites about child-rearing—to attend the press conference. “Where are the bloggers?” Google staffers asked in disbelief. In response, Pampers invited more than a dozen mommy bloggers to visit P&G’s baby division, where they toured the facilities, met diaper executives, and got a primer on diaper design. The bloggers claimed to have drawn anywhere from a hundred thousand to 6 million visitors to their Web sites.

Another result of the swap was an online campaign inviting people to make spoof videos of P&G’s “Talking Stain” TV ad and post them to YouTube. The original ad for Tide to Go stain-removing pens, aired during a Super Bowl, shows a job candidate being drowned out by a talking stain on his shirt that babbles nonsense every time he tries to speak during the interview. Spoof campaigns can be risky because people might post something rude about your product or not participate at all. But with guidance from Google, P&G provided prospective spoofers a tool kit of official logos. In the end, 227 spoofs turned up, and a few were good enough to air on TV. The campaign was so successful that Tide plans to use more consumer-generated content in the future.

IDEO’s David Kelley best summed up the importance of observing processes: “Asking questions of people who were there, who should know, often isn’t good enough. It doesn’t matter how smart they are, how well they know the product or opportunity. It doesn’t matter how many astute questions you ask. If you’re not in the jungle, you’re not going to know the tiger.”

Discovery Process #3: Idea Networking

Not surprisingly, innovative companies, like innovative people, are also great idea networkers. They develop formal and informal networking processes to facilitate knowledge exchanges both outside and inside the company.

Internal Networking

Most companies have processes for sharing ideas among employees, but innovative companies take it to the next level. One popular internal networking process at innovative companies comes from the American Idol model for finding new ideas. Basically, this process involves challenging employees to generate and submit innovative ideas, which a panel of judges screens and selects. For example, Google holds an “Innovator’s Challenge” four times each year. In this competition, employees submit ideas for top management review; winning ideas receive the resources necessary to maintain momentum. Google also has a process for sharing new ideas internally that facilitates networking. Marissa Mayer, director of consumer products and a champion of innovation at Google, holds regular brainstorming sessions during which engineers have ten minutes to pitch new ideas. Mayer and a group of a hundred others discuss the idea. These sessions try to build on the initial idea with at least one new complementary idea per minute.[4] They have an established process for deciding which projects are refined enough to present to the company founders (though they do not reveal the process).

Innovation at Google is very democratic; it lets market forces determine which ideas move forward and which don’t. Once projects and ideas post to an internal electronic idea board, individuals throughout the company rate the ideas and provide feedback. Employees can also choose to spend 20 percent of their time working on projects of their own choosing. Google executives believe that the market forces inside the company are strong enough to reward good ideas and punish bad ones, much as the “real” market would if the ideas were actually developed and launched. Google also facilitates internal networking through free food. Google Cafe provides tasty, healthy, free lunches and dinners (prepared by the Grateful Dead’s former chef Charlie Ayers) to employees. “The free food at Google serves an important function beyond giving employees access to good, healthy food,” Gagan Saksena, a former software engineer at Google, told us. “It’s totally possible for you to be sitting by someone who has been working in an area that you were not interested in. And then suddenly a discussion with that person may trigger some new ideas for both of you.”

External Networking

Over the last few years, companies have increasingly looked outside their own walls for new ideas. The term open market innovation has been used to describe this phenomenon. When Lafley became CEO in 2000, he established a goal of increasing the percentage of P&G’s new product ideas through external sources from 10 percent to 50 percent. By 2006, 45 percent of new product ideas came from external sources, and P&G had reduced its R&D from 4.8 percent of sales to 3.4 percent of sales, while launching hundreds of products based on externally sourced ideas. The company experienced this growth in external idea generation through its Connect + Develop (C&D) initiative. Through C&D processes, P&G teams work with independent researchers, other companies, and sometimes even competitors to generate ideas.

P&G employs a number of different processes to gather ideas from these external sources. For example, the company uses NineSigma and InnoCentive, third-party matchmakers that link companies like P&G with outside technology. These companies help P&G prepare technical briefs describing problems it is trying to solve and then anonymously sends these briefs to thousands of researchers around the world. The process brings P&G into contact with people providing solutions on a contract basis. C&D has helped P&G develop many new products such as Swiffer WetJet, Olay Daily Facials, Crest Whitestrips, Iams Dental Defense, Mr. Clean AutoDry, and Max Factor Lipfinity.

Consumer products giant Reckitt Benckiser (RB) (number eight on our list) has seen similar results using its IdeaLink Web site where it lists its “most wanted” jobs that need to be done and requests solutions. For example, RB launched Finish Quantum, a new dishwasher detergent designed to provide maximum clean and shine. The driving force behind Quantum’s “clean and shine” performance is three highly active chemical agents that are normally incompatible. The challenge was to combine them in a single product but hold them apart. Working closely with external experts, RB developed an innovative polymer system and processing technique to create a dissolvable shell with three chambers that separate each agent until it’s needed.

Beyond networking for solutions to particular technical problems, RB also networks with entrepreneurs to help launch entirely new products using RB brands. RB does this by actively licensing its brands to entrepreneurs or companies with access to sales channels or product competencies that RB believes will add value to the equity of its brands. If an entrepreneur has a good new product idea, RB promises to complete the evaluation process and give a decision on licensing within three months. Through processes like these, RB’s innovation pipeline is so full that a new product launches or a product formula changes every eight hours. No wonder CNBC named CEO Bart Becht the European business leader of the year in 2009.

Discovery Process #4: Experimenting

Companies with high innovation premiums also institutionalize experimentation. For example, Monsanto’s (number nine on our list) premium results from creating genetically engineered seeds that make crops drought resistant and immune to herbicides and insects. It’s even working on making a lettuce with the crunch of iceberg and the nutrients of romaine, and heart-healthy soybeans with omega-3 (fish) oil. Its biotech crops come out of the same genetic engineering revolution that produced companies like Genentech and Amgen.

How does Monsanto do it? One secret is innovative software that allows for digital experimentation with seed genetics. Monsanto uses software, which it calls the “molecular breeding platform,” to accelerate plant production to bring higher yields and herbicide resistance. This custom software—with the help of robotics and data visualization capabilities—tracks terabytes of information about plants down to the genotypes of individual seeds. Instead of spending years in planning and trial and error, Monsanto can use these digital planting experiments to predict good and bad crops and quickly get the information to researchers. Experimentation has been key to producing innovative seeds that have captured 90 percent of the U.S. soybean crop and 80 percent of corn and cotton crops.

Like Monsanto, Beiersdorf Group (number fourteen on our list), maker of Eucerin and a host of other skin-care products, invests considerable resources in experimenting with new products—and has done so since 1911 when it first launched Nivea facial creme. Beiersdorf develops most products at its Hamburg research center, the largest and most advanced of its kind in Germany (and perhaps the world). The research center’s work is symbolized by the unusual architecture of the auditorium—known by resident researchers as the “philosopher’s stone”—that is modeled on the structure of a skin cell.

The Hamburg research center incorporates a test center where it tries out the effectiveness and tolerance of new skin products on some six thousand volunteers every year. The test center contains dozens of bathrooms and examination rooms with technology that can measure even the smallest changes in skin-cell structure. This facility enables testers to use products under real-life conditions, and Beiersdorf researchers to carefully monitor and document the effectiveness of various products. In one case, Beiersdorf discovered that testers weren’t getting the necessary UV protection from sunscreen because they weren’t applying it properly and, in most cases, they applied far too little. By experimenting with customers using sunscreen (and by using an innovative method by which the amount of UV protection on the skin is made visible and can be measured), Beiersdorf researchers made adjustments in consumer education and the products themselves to help customers achieve optimal protection.

Of course, customer experiments happen only after Beiersdorf runs its own experiments. It tests each raw material and each combination of substances—including full cosmetic formulas—using special methods to ensure that they pose no health threat and are compatible with skin. It does this by testing cell cultures, as opposed to animal testing (typical in other companies). Beiersdorf’s experimenting processes help it launch between 150 to 200 new products and apply for 120 to 150 new patents each year.

Amazon’s Bezos also imprinted his penchant for experimenting on his company. “You need to do as many experiments per unit of time as possible,” says Bezos. “Innovation is part and parcel with going down blind alleys. You can’t have one without the other. But every once in a while, you go down an alley and it opens up into this huge, broad avenue . . . it makes all the blind alleys worthwhile.” One way Amazon conducts small experiments is by offering a pilot product or service to half of its customers and compares their response to the other half. In similar fashion, Google has institutionalized experiments by using “beta” labels to release products early and often for public trials, allowing Google to quickly get direct customer feedback. It pursues innovation by having hundreds of small teams pursue—and pilot—new projects simultaneously. No wonder Google creates so many innovative new product and service offerings.

Combining Discovery Processes to Produce Innovations

Although we can deploy innovators’ DNA skills as separate processes to spark new ideas within teams or organizations, we can also use them in a connected way as a system. Innovation design firm IDEO does just that in teams. Kelley attributes IDEO’s success at innovating to its team processes. “We’re experts on the process of how you design stuff,” Kelley says. “We don’t care if you give us a toothbrush, a tractor, a space shuttle, a chair; we want to figure out how to innovate by applying our process.”[5] So what processes does IDEO rely on to innovate? IDEO teams start with a questioning process, move to observing and networking processes to gather data about their initial questions, and conclude with an experimenting process where innovative ideas emerge and evolve through rapid prototyping. In 1999 the late-night news show Nightline highlighted how IDEO used these processes to completely redesign a shopping cart in five furious days. Today, IDEO takes the same approach in its quest for more innovative products and services with a variety of clients. For example, the processes formed the core of IDEO’s recent work with Zyliss, a maker of kitchen products, to completely redesign its kitchen gadget line, from cheese graters to pizza cutters to mandolines (slicers).

Process #1: Questioning

The IDEO project team began its quest for an innovative cheese grater (or pizza cutter, or mandoline) by asking a series of diverse questions to better understand the problems associated with using traditional cheese graters. What are the problems with cheese graters? What don’t people like about existing cheese graters? How important is safety? What other things do people want to grate with a cheese grater? Who are the “extreme users” of cheese graters (highly skilled and highly unskilled users) and how do their needs differ? As far as kitchen gadgets go, extreme users are cooks and chefs (those using kitchen gadgets for hours each day) as well as first-time or rare users of kitchen gadgets, such as college students, children, or the elderly.

While IDEO teams didn’t use our QuestionStorming method per se (see chapter 3), the team’s initial process looked very similar and centered on asking questions to better understand what to look for as they shifted to the data-gathering phase of observing and networking. As the team members asked questions, they wrote them on small sticky notes to easily rearrange and prioritize them. Matt Adams, a project leader at IDEO, told us, “By having the right questions, it becomes clearer how you might go about answering those questions.” Then IDEO teams gained a much better sense of “what to ask, how to ask it, and what kinds of people to ask” as they moved to the next processes, observing and networking.

Process #2: Observing

This phase involved sending the IDEO design team members out into the field where they observed and documented customer experience firsthand. “Our process is to go in and try to really understand the people that you are designing for,” says Kelley. “We try and look for a latent customer need, a need that’s not been seen before or expressed in some way.”[6] So the Zyliss team spent hours and hours observing various product users, particularly extreme users, in Germany, France, and the United States, trying to intuit what they were thinking and feeling. They took photos and videos of customers using kitchen gadgets to document what they noticed.

Through observations, the team captured many problems with using traditional kitchen gadgets. For example, they saw that traditional cheese graters easily clogged, were hard to clean, and often required considerable dexterity for safe use. They noticed that the mandoline, a slicer well beloved by advanced cooks, presented severe safety hazards due to extremely sharp blades being exposed. They looked for ways to optimize ergonomics (ease of use), cleanability, and functionality. For example, they carefully observed hand and arm movements to make subtle adjustments in handle shape or tool angle for tremendous ergonomic benefit.

Process #3: Networking

As IDEO team members observed, they also talked to as many product users as they could about kitchen gadgets they were using. In particular, they visited with users while they were operating a particular kitchen gadget, because this is when users are most likely to offer ideas or insights about things they like and hate about it. They especially like to talk to “experts” (e.g., full-time professional chefs or highly competent home cooks). They are the most demanding and difficult-to-please users and often have great product improvement suggestions.

Through unscripted conversations, IDEO team members gained critical insights for designing novel kitchen gadgets. They tried to gain deep empathy to the point that they could champion a particular user, such as a chef. They tried to understand what she loves, what her challenges are, and what’s really important to her, so they could share that person’s story later with other team members. Peter Killman, a project leader at IDEO, says that during the observing and networking phase, IDEO teams “go out to the four corners of the earth and come back with the golden keys of innovation.”[7] Those keys, observation and idea networking, help unlock the doors to innovative ideas.

Process #4: Brainstorming Solutions and Associating—the Deep Dive

The next phase involved bringing all the insights acquired through observation and interviews back to a brainstorming session that IDEO calls a “Deep Dive.” During the Deep Dive brainstorming session, everyone openly shared all the acquired knowledge during the data-collection phase (called “downloading”). It’s basically a storytelling session with lots of details about individual lives, in which team members capture insights, observations, quotes, and details, and share photos, videos, and notes.

The team leader facilitated the discussion, but there are no real titles or hierarchy at IDEO. Status comes from creating the best ideas, and everyone gets an equal opportunity to talk. After they shared ideas, the team members brainstormed design solutions to the problems they’ve witnessed. To actively support associational thinking during the brainstorming phase, IDEO maintains a Tech Box at every office (full of a fantastic range of odd, unrelated things from model airplanes to Slinkies). They spread the items out in front of the team to stimulate associational thinking as they brainstorm innovative product designs.

Process #5: Prototyping (Experimenting)

The final phase was “rapid prototyping,” in which designers built working models of the best kitchen gadget ideas that emerged from the brainstorming session. Kelley describes the value of a prototype as follows: “You know the expression ‘a picture is worth a thousand words.’ Well, if a picture is worth a thousand words, then a prototype is worth about a million words . . . Prototyping is really a way of getting the iterative nature of this design going through feedback from others. If you build a prototype, other people will help you.”[8]

IDEO took its kitchen gadget prototypes to a variety of different product users—from chefs to college students to children—for feedback. For example, the new cheese grater design has a large drum to grate cheese as it rolls and can grate more cheese (or chocolate or nuts) with less cranking. An optimized, clog-resistant tooth pattern provides maximum grating with minimal resistance for older users and people with small hands. The foldable and opposable hand crank makes for efficient drawer storage and for easy use by right- and left-handed users. These innovations are refined with each new prototype because IDEO “builds to think and thinks to build,” as Matt Adams put it. Taking the prototype out for a test drive is the fastest way to get great feedback on new product ideas.

Systematically using an iterative process of questioning, observing, networking, and prototyping, IDEO successfully generates one new innovative design after another. IDEO’s processes encourage, support, and expect innovation from everyone on the team. It’s no surprise then that John Foster, head of talent and organization at IDEO, believes that “leadership is a group outcome,” especially innovative leadership.

Our research shows that the DNA of innovative organizations mirrors the DNA of innovative individuals. Just as inventive people systematically engage in questioning, observing, networking, and experimenting behaviors to spark new ideas, innovative organizations and teams systematically develop processes that encourage and develop these same skills in employees. Moreover, as the IDEO example demonstrated, they systematically combine these processes into an overall process for generating novel solutions to problems. By creating organizational processes that mirror their individual discovery behaviors, innovative leaders can build their personal innovator’s DNA into their organizations.

10

Putting the Innovator’s DNA into Practice: Philosophies

“Innovation is deeply ingrained in all of the nooks and crannies of our culture.”

—Jeff Bezos

WHAT FOUNDATIONAL PHILOSOPHIES permeate the world’s most innovative companies? To tackle this question, we first explored the inner world of their entrepreneurial founders and senior executive teams. We asked about the philosophies and beliefs that kept their personal innovator’s DNA skills in perpetual motion. The most frequent answer was, “I don’t know. It’s just the way I am.” They simply took it for granted that innovation was their job, not someone else’s. It was a core part of who they were. They devoted significant time and energy to hunting down new ideas. They pursued a range of innovative results, from incremental to disruptive, and didn’t see themselves as taking extreme risks in the process.

Not surprisingly, the same innovators worked equally hard to infuse a parallel set of taken-for-granted philosophies deep into every nook and cranny of their company’s culture (just as Bezos did at Amazon). They recognized that a culture is most powerful when widely shared and deeply held. So how did they do this? They knew that their own innovation example was an important first step to building a highly innovative company. They also realized it was impossible to personally lead or participate in every team and that they would have limited direct contact with most employees (especially as their companies grew). As such, they worked hard to instill a deep, companywide commitment to innovation. Not only did their companies pay attention to picking innovative people and putting innovative processes into place, they also lived by a set of key innovation philosophies.

Here’s what innovative entrepreneurs and executives told us about their innovation philosophies. We heard that innovation is everyone’s job. We learned that disruptive innovation is part of their company’s innovation portfolio. We found out that having lots of small project teams, properly organized, is central to the way their companies took innovative ideas to market. Finally, we realized that they do take more risks than other companies in the pursuit of innovation, but they take actions that mitigate those risks, thereby turning them into “smart risks.” These four philosophies permeate the world’s most innovative companies and are not only expressed through words but punctuated powerfully through reinforcing actions.

Philosophy #1: Innovation Is Everyone’s Job, Not Just R&D’s

Innovation is obviously R&D’s job. We’ve never seen any company question this. However, we have witnessed significant debate in companies around the world about whether innovation is everyone’s job. In one organization, we watched the chairman and CEO pitted against each other on this issue. The chairman was convinced that everyone should innovate, while the CEO took the opposite stance, believing that only R&D or consumer marketing should spend energy on innovation. While this debate raged at the top, the company launched a new initiative to focus everyone on spending some of their workweek discovering new products, services, and processes. It was no surprise that few employees jumped at the chance to innovate until they saw senior-level executives settle their debate.

In rejecting the limiting belief that innovation is R&D’s job alone, leaders of highly innovative companies—such as Jobs, Bezos, and Benioff—work hard to instill “innovation is everyone’s job” as a guiding organizational philosophy. When Jobs returned to Apple after a twelve-year hiatus, he launched the “Think Different” advertising campaign. The ad paid tribute to a wide range of innovators saying, “Here’s to the crazy ones. The misfits. The rebels. The trouble makers . . . the ones who see things differently. They’re not fond of rules. And they have no respect for the status quo . . . they change things. They push the human race forward.”

The Emmy award–winning Think Different campaign was hailed as one of the most innovative of all time, largely because it inspired people. What most people don’t realize, though, is that the campaign targeted Apple employees as much as its customers. “The whole purpose of the ‘Think Different’ campaign was that people had forgotten what Apple stood for, including the employees,” said Jobs. “We thought long and hard about how you tell somebody what you stand for, what your values are, and it occurred to us that if you don’t know somebody very well, you can ask them, ‘Who are your heroes?’ You can learn a lot about people by hearing who their heroes are. So we said, ‘Okay, we’ll tell them who our heroes are.’” To reestablish Apple’s innovativeness, Jobs knew that every employee needed this message: “Our heroes are innovators. We stand for innovation. If you want to work at Apple, we expect you to be an innovator who wants to change the world.”[1]

The Think Different campaign is just one of many things Jobs has done to send the message to Apple employees that innovation is their job. He once urged the original Macintosh development team to innovate by saying, “Let’s make a dent in the universe. We’ll make it so important that it will make a dent in the universe.”[2] More recently, he encouraged Disney employees to “dream bigger” (as the largest single shareholder of The Walt Disney Company stock, Jobs has a vested interest in Disney being innovative). These bold statements send a clear message to employees: we expect each of you to innovate.

Of course, bold actions must follow bold statements to reinforce the message. P&G’s Lafley pursued the “we innovate” philosophy when he remarked, “The P&G of five or six years ago depended on eight thousand scientists and engineers for the vast majority of innovation. The P&G we’re trying to unleash today asks all hundred thousand-plus of us to be innovators.” To reinforce his commitment to organizationwide innovation, he actively solicited ideas from throughout the company, and if the concept showed promise, he put it into development. For example, Lafley backed a successful hair-care product line for women of color because a few African American employees explained to him that existing products didn’t work well and “we can do better.” P&G did better, launching a successful new line, Pantene Pro-V Relaxed & Natural. Lafley’s actions set the tone for a we-innovate philosophy to take hold. Yet, key leaders’ personal actions alone are not enough. We saw that highly innovative companies, compared to typical companies, reinforce this philosophy by giving people more time and resources to innovate.

Creating a Safe Space for Others to Innovate

Establishing an “innovation is everyone’s job” philosophy requires creating a safe space for others to take on the status quo. Researchers call this “psychological safety,” in which team members willingly express opinions, take risks, run experiments, and acknowledge mistakes without punishment. “If you foster an environment in which people’s ideas can be heard,” says Azul and JetBlue founder David Neeleman, “things naturally come up.”

Many leaders think they encourage others to develop and use their discovery skills, but in reality colleagues often don’t see it that way. On average, team leaders in our research thought they were significantly better at encouraging discovery activities in others than did their managers, peers, or direct reports. (This sounds a bit like the “better-than-average” effect where over 70 percent of us see ourselves as above average in leadership ability and only 2 percent view ourselves as below average. Clearly, this data shows room for improvement. See figure 10-1.)

FIGURE 10-1

Leading innovation: perceptions of self vs. others

How do leaders build a safe space for others to innovate? The most important first step to creating a safe space is to encourage questions. At Southwest Airlines, Kelleher creates a safe space by soliciting challenging questions from direct reports, as well as others. “I just watch, I listen,” he says. “And I want them to ask me tough questions.” Another innovative leader encouraged everybody, even veterans, to ask why on a daily basis, because “they stop using their minds; they’ve moved into this execution mode and stop asking questions.”

Another key to encouraging others’ innovation efforts is to cheer them on when they use their discovery skills. One senior executive excelled at generating new ideas, but expressed intense frustration with team members failing to do the same. An innovator’s DNA 360-degree assessment helped her better grasp what was going on. The data revealed that she had not created a safe space to innovate. Compared to all other assessors, she consistently rated her team members far lower than anyone else (her evaluation put her direct reports at the thirty-fifth percentile on their discovery skills, while her direct reports ranked each other—with confirming evidence from other peers in the company—at around the sixty-fifth percentile).

Why did she do this? Two explanations surfaced during a team-building workshop we conducted. First, she liked her ideas more than others’ and often devalued their creative ideas. Second, even though she talked about the importance of creativity, she praised and rewarded delivery skills with her everyday actions. This attention to successful execution, combined with her dismissing others’ new ideas, led some team members to change their behavior when around her. They were innovative elsewhere, but flicked the switch off in her presence.

This leader’s challenge is not uncommon. Dan Ariely’s research in The Upside of Irrationality shows a simple cognitive bias that causes all people to do this all the time. Ideas that are “not invented here” are always suspect because people tend to discount or ignore evidence from sources they don’t know or trust, which is especially true if the idea contradicts an existing belief or something they already favor. This bias creates a real leadership challenge that innovative leaders conquer by demonstrating an authentic commitment to hearing and supporting others’ ideas. Collectively, these actions help establish a widely shared and deeply held belief that innovation is everyone’s job.

Give People Time to Innovate

As we mentioned in chapter 1, founder CEOs on our list of most innovative companies spent almost 50 percent more time on discovery behaviors than did CEOs of typical companies. Innovative leaders know innovation doesn’t just happen, but requires a significant time commitment. Consequently, they do what other companies do not: budget more human and financial resources to innovation activities. For example, Google reinforces the “innovation is everyone’s job” philosophy with its 20 percent project rule, when it encourages engineers to spend up to 20 percent of their time (the equivalent of one day a week) working on pet projects they choose. Even Brin, Page, and Schmidt try to adhere to the 20 percent rule. Management does not specify how to use time, but projects must receive a green light, and employees must account for their time. Moreover, since projects are reported and documented, they wind up on an intracompany idea-sharing forum for companywide input and vetting, which leads to collaboration. Others within Google who learn about the idea may contribute a portion of their 20 percent time to help nurture an idea. Several highly successful projects have come from 20 percent projects—including Gmail, Google News, AdSense (contextual ads that generate advertising revenues), and Orkut (a popular social networking site in Brazil). Roughly half of Google’s new product launches in recent years emerged from 20 percent time projects. The 20 percent project rule visibly symbolizes that management believes everyone can and should innovate.

Like Google, 3M has long been known for a similar 15 percent rule, and at P&G, some employees said they were encouraged to devote 75 percent of their time working “in the system” (e.g., executing tasks) and 25 percent working “on the system” (e.g., discovering new and better ways to execute). Other companies, such as Apple and Amazon, give no explicit time allocation, but regularly ask employees to run experiments and work on innovation projects. Alternatively, Atlassian Labs (an innovative Australian-based company that makes software development and collaboration tools) employs a unique variation of the 20 percent innovation time rule. It conducts an annual “FedEx” day when all software developers devote twenty-four hours nonstop to generating new product ideas. Developers work intensely to build a viable “FedEx Shipment Order” that sufficiently details a new idea for others to review. Twenty-four hours later, Atlassian holds a “FedEx Delivery” day when developers rapidly prototype and then demonstrate new software ideas for others in the company. This annual innovation effort has proved highly successful, as developers experience more fun and growth in their work and ultimately help product managers fill in product holes with new options.

Consider where your company stands on this innovation philosophy. One acid test that we’ve used to see whether an organization has successfully ingrained this innovation philosophy into its culture is to walk in and ask a random group of a hundred employees (selected from the top to the bottom and across every function or geography) these questions:

1. Does your organization expect you to innovate in your job?

2. Is innovation an explicit part of your performance reviews?

In highly innovative organizations, 70 percent or more of the employees respond with a resounding yes. Innovating is an obvious, taken-for-granted component of their everyday work.

Establishing an “Innovation Is Everyone’s Job” Philosophy

Our exploration of the world’s most innovative companies suggests that the “innovation is everyone’s job” philosophy gains greater organizational traction and visibility when:

1. Top leaders actively innovate, and everyone sees or hears about it.

2. All employees receive real time and real resources to come up with innovative ideas.

3. Innovation is an explicit, consistent element of individual performance reviews.

4. Companies allocate at least 25 percent of human and financial resources to platform or breakthrough innovation projects.

5. Companies incorporate innovation, creativity, and curiosity into their core values, in word and deed.

Philosophy #2: Disruptive Innovation Is Part of Our Innovation Portfolio

Beyond encouraging all employees to spend time on innovation tasks, highly innovative companies also allocate a greater percentage of both human and financial resources to innovation projects. They spend more dollars on R&D and initiate more innovation projects compared to similar sized companies in the same industries. Such concrete investments signal an organization’s real commitment to innovation.

Of course, most organizations invest in R&D to pursue new products or services. However, we would describe over 90 percent of their innovation projects as “derivative,” producing very incremental improvements to existing products (e.g., next-generation products or services) based on established technologies that are well known to the company (and usually its customers).[3] For example, Sony’s introduction of the game console PS3—which outperforms the PS2 by providing superior graphics, a Blu-ray player, and Internet connection—is a derivative project. Sony has added features to an existing product to make it more appealing. But it has failed to create a new platform of products, thereby pulling in a whole new segment of customers, or an entirely new market.

In contrast, companies design disruptive innovation projects to establish entirely new markets by offering a unique value proposition through more radical technologies. (Technologies become more radical by incorporating entirely new components—compared to established products—and offering new linkages among components within a new product architecture.) Sony’s Walkman was disruptive because it opened up a fundamentally new market by offering a music device that was far more portable than any other music device. The Walkman was based on new miniaturized components and new linkages (interfaces) between those components. Apple took a similar leap forward with iPod and iTunes that, compared to Walkman, were based on very different components and product architecture to open up portable music to a far larger customer group. Over 95 percent of iPod buyers had never used an Apple computer and over 80 percent had never used a portable music device. That is opening up an entirely new market. The iPhone is also disruptive, not so much because the technologies employed were so different (though some were), but because it had a very different architecture (one button, touch screen) and because of the “App store,” which allowed the device to do so many more jobs than a typical cell phone. Amazon’s Kindle e-reader and cloud computing services represent similar disruptive innovations by opening up completely new markets.

Finally, sandwiched between derivative and disruptive innovations are what Steve Wheelwright and Kim Clark refer to as “platform” innovation projects (see figure 10-2; note that Wheelwright and Clark use the term “breakthrough” projects to refer to what we have called “disruptive” projects).[4] We see Apple’s MacBook Air laptop as a platform innovation project because it’s different enough to be viewed as a new product category but fails to open an entirely new market as the iPod did, since most MacBook Air users are already users of small laptops or other Apple computers. Moreover, the technologies behind MacBook Air are a bit less radical than for breakthrough products like the iPod and iTunes. (Of course, we can always debate the degree to which any given product is based on radical technologies [new components, new linkages among components] or whether it opens up a new market by offering a value proposition markedly different from other products.)

FIGURE 10-2

Aggregate project planning: a framework for prioritizing a company’s innovation projects

Steven C. Wheelright and Kim B. Clark, “Creating Project Plans to Focus Product Development,” Harvard Business Review, March–April 1992, 10–82.

For us, the framework in figure 10-2 illustrates how innovative companies consciously allocate a significantly greater proportion of people and resources to platform and breakthrough (disruptive) innovation projects. For example, Google uses a 70-20-10 rule for allocating engineering efforts, including the 20 percent project time granted to technical staff. Google devotes 70 percent of engineering time to expanding and developing derivative products within the core business, that is, Web search and paid listings; 20 percent to projects designed to “extend the core,” such as Gmail or Google Docs; and 10 percent to build “fundamentally new businesses,” such as the Nexus One phone (its first device), a new collaborative tool called Wave, free Wi-Fi service in San Francisco, or Google Editions (its own e-book store). From our perspective, the 70-20-10 prioritization maps well with Wheelwright and Clark’s “derivative,” “platform,” and “breakthrough” innovation project categories. Google’s prioritization demonstrates a willingness to invest in platform and breakthrough innovation projects. “We will not shy away from high-risk, high-reward projects because of short-term earnings pressure,” wrote Page in a letter to shareholders at Google’s IPO. “For example, we would fund projects that have a 10 percent chance of earning a billion dollars over the long term. Do not be surprised if we place smaller bets in areas that seem very speculative or even strange.”[5]

Similarly, Apple and Amazon allocate significant resources to platform and breakthrough innovation projects (though they don’t appear to follow any specific resource-allocation guidelines). As far as we can tell, Apple was the only computer manufacturer to allocate real resources to pursue a music business, a phone business, and a digital camera business (the Apple QuickTake, which failed). These businesses were certainly not direct computer derivatives. As an online retailer, Amazon has devoted significant resources to create an e-reader product, the Kindle—which cleared the way for a new product category—and more recently, a cloud computing service. These products unlocked entirely new markets for Amazon, but rarely without deep resistance. Bezos explained, “Every new business we’ve engaged in has initially been seen as a distraction by people externally, and sometimes internally. They’ll say, ‘Why are you expanding outside of media products? Why are you entering the marketplace business with third-party sellers?’ We’re getting these questions right now with our new web infrastructure services: ‘Why take on these new web developer services?’”[6] Yet, Bezos and Amazon press forward in their habitual pursuit of breakthrough business ideas.

To summarize, innovative companies invest more absolute time and resources in platform and breakthrough innovation projects. The acid test of whether an organization has adopted a philosophy of pursuing more than just derivative innovation projects is to ask: what percentage of your innovation projects is devoted to platform or breakthrough innovations? If this percentage is small, less than 5 percent, the company is unlikely to be very innovative and certainly wouldn’t be seen that way by investors. If this percentage is at least 25 percent, the company shows tangible signs of buying into Jobs’s advice to “dream bigger” by actively pursuing more disruptive innovations.

Philosophy #3: Deploy Small, Properly Organized Innovation Project Teams

Every new product or service idea needs a vehicle to take it from inception to the marketplace. A small project team (e.g., breakthrough, platform, or derivative) is the vehicle in most innovative companies. Smart leaders know that the way to empower individuals to innovate is to organize them into very small work units with big goals where individual and team performance is visible. Amazon employs a “Two Pizza Team” philosophy, meaning that teams should be small enough (six to ten people) to be adequately fed by two pizzas. By keeping teams small, Amazon can work on a larger number of projects, thereby allowing its teams to go down more blind alleys searching for new products or services.

In similar fashion, Google engineers typically work in teams of only three to six people. Chairman Schmidt explains the intention: “We try to keep it small. You just don’t get productivity out of large groups.”[7] The result is an empowered, flexible organization with small teams pursuing hundreds of projects, an approach that Schmidt claims “let[s] a thousand flowers bloom.”[8] With hundreds of small team projects developing new ideas, it is little wonder that Google can create so many new product offerings.

Providing the right structure and right mix of skills for these project teams is also critical. Many organizations fail with innovation projects, especially breakthrough ones, because they fail to understand a basic organizing principle: the more radical the innovation, the more autonomy the project team will require from the organization’s existing functions and structure. To illustrate, a company’s least radical projects are “derivative,” meaning that they typically involve incremental improvements to components or features. For example, Sony designers and engineers who are very familiar with the PS3’s components and architecture will likely develop the next generation of its PS3 game console (we’ll call it the PS4). Most likely they will modify or improve existing components, for example, improved graphics, more storage, more convenient online gaming. Maybe they’ll add a new component, for example, the ability to digitally record TV shows as a DVR/TiVo does. The best type of team for this sort of derivative innovation project is a functional team in which engineers who specialize in each type of component work to innovate at the component level. Alternatively, they might use a lightweight team that primarily comes from the game console group but includes a light allocation of engineering resources from other functional areas within Sony.

But imagine that Sony wants to develop an iPad-like device that possesses features that leapfrog iPad (let’s call it the sPad). If Sony attempts to develop the new sPad device within the PS3 engineering group, the new device will likely reflect the knowledge and technology of an existing Sony game console. The same would be true if the Sony computer engineering group or the Sony TV group developed the device. To get something more radical, Sony would be better off pulling folks from each of these areas (and perhaps elsewhere) into a heavyweight team or autonomous business unit. A heavyweight team enables members to transcend the boundaries of their functional organizations. Heavyweight teams are co-located and led by a manager with significant clout. Members bring functional expertise to the team, but their primary loyalty and innovation mind-set must move beyond the limited interests of their functional group. For that reason, they become part of a real team (and not just a group of people who happen to meet together), possessed by a compelling collective responsibility to figure out a better way—new processes, new knowledge—to meet the project’s goals.

In some cases, the innovation project differs so radically from a company’s existing offerings that it requires an entirely different business model (e.g., to serve different customers using different technologies). Then it makes sense to create a fully autonomous business unit to pursue the breakthrough innovation opportunity. For example, when Amazon decided to pursue and then launch a cloud computing service business, it created an autonomous business unit because the new opportunity demanded an entirely different business model from its online discount retailing business.

The bottom line? Allocating resources to lots of platform or breakthrough innovation projects will not pay off if project teams don’t have the right level of autonomy to do their work. The more radical the innovation project, the more autonomy and the more diversity the project team requires. Remember, disruptive innovation demands a team staffed with folks displaying a broad diversity of knowledge in order to generate more radical ideas.

Philosophy #4: Take “Smart” Risks in Pursuit of Innovation

Most companies push platform and breakthrough innovation projects off the table as strategic priorities because derivative projects leverage existing competencies more effectively. They view the success of derivative projects as more certain and less risky. To counter this dysfunctional resource-allocation dynamic, highly innovative companies exploit a fourth innovation philosophy to soundly back up the first three: “Take smart risks in the pursuit of innovation.”

Breakthrough innovations require risk taking to make them happen. Long ago, Edwin Land, inventor of the Polaroid technology and camera, noticed that the most essential part of creativity is “not being afraid to fail.” For innovators—and innovative companies alike—mistakes are nothing to be ashamed of. They are an expected cost of doing business. “You do enough new things and you’re going to bet wrong,” says Bezos. “But if the people running Amazon don’t make some significant mistakes, then we won’t be doing a good job for our shareholders because we won’t be swinging for the fences.”

How Smart Is Your Company or Project Team about Risk Taking?

To judge your organization’s propensity to take risks and learn from failure, reflect on the following questions:

- Does your organization encourage people to take risks in order to learn from them?

- Does your organization reward people for learning from failures? Or is punishment its default response?

- Can you name at least one successful innovation when your company celebrated learning from at least one failure to make the innovation ultimately work?

- Has your company built a higher-than-average discovery quotient in its people to ensure against the inherent risks of disruptive innovation?

- Do your company’s top managers understand that they need to take risks and fail frequently in order to innovate?

IDEO’s slogan “fail often to succeed sooner” frames a fundamental philosophy behind its success as the world’s leading innovation design firm. It posts the phrase companywide to remind employees that if they aren’t failing, they aren’t innovating (see chapters 8 and 9 for more about IDEO’s people and processes). Virgin’s Branson also acknowledges the “ability to fail” as a core value. “It is impossible to run a business without taking risks,” he says. “The very idea of entrepreneurship . . . conjures up the frightening prospect of taking risks and failing.”[9]

Of course, innovative companies like IDEO and Virgin aren’t trying to fail. They just know that when a company tries out lots of new ideas, some won’t work. That’s the very nature of pushing the envelope. But they’re smart enough to recognize the difference between good and bad failures. Good failures at Google have two defining characteristics: (1) you know why you failed and have gained knowledge relevant to the next project; and (2) good failures happen fast enough and aren’t big enough to compromise your brand. As Google’s leaders have acknowledged, “we’re going to try things, and some things aren’t going to work. That’s okay. If it doesn’t work, we’ll move on.”[10]

Apple echoes the same philosophy. “One of the hallmarks of the [Apple] team, I think, is this sense of looking to be wrong,” says Jonathan Ive, principal designer of the iMac and senior vice president of industrial design. “It’s the inquisitiveness, the sense of exploration. It’s about being excited to be wrong because then you have discovered something new.”[11] By embracing failure as a vehicle for learning, innovative companies embolden their employees to try new things. Companies would do well to embrace, as a company slogan, the innovation philosophy of creativity researcher and author Sir Ken Robinson: “If you’re not prepared to be wrong, you’ll never come up with anything original.”[12]

But we emphasize that the innovative companies we studied were wrong less often. Why? Because they took smarter risks by hiring and developing discovery-driven people and institutionalizing processes that support people’s questioning, observing, networking, experimenting, and associating (as we recommended in chapters 8 and 9). Imagine that your company wants to invest in a new disruptive innovation project. What if you could assemble a dream team of innovators to pursue the project, including Jobs (Apple), Bezos (Amazon), Benioff (Salesforce.com), Kelley (IDEO), Lazaridis (RIM), Lafley (P&G), and Gadeish (Bain & Company)? Would you invest in their innovation project? Our guess is yes. Somehow pursuing disruptive innovations with this type of team feels less risky (than doing it with a more common delivery-driven management team) because these folks boast strong discovery skills and understand the behaviors (and processes) required for generating a successful disruption. No wonder the risk seems more calculated with them. The actual risk is low because putting the right people and innovation processes into place increases the probability of success (and decreases the probability of taking disastrous steps).

The financially successful innovators in our study demonstrated a higher discovery quotient (stronger discovery skills) than less successful ones. We see the same equation at work in the world’s most innovative companies. Innovation failure (in a financial sense) often results because companies fail to consistently engage all discovery skills. They likely don’t ask all the right questions, don’t do all of the necessary observations, don’t talk to enough diverse people, or don’t run the right experiments to reduce the inherent risks of innovating. Quite the reverse is true for our dream team filled with innovators who know from experience that fully leveraging their innovator’s DNA actually reduces the likelihood of failure. Similarly, making sure that your organization pays careful attention to putting the right people, processes, and philosophies in place takes out an insurance policy that tones down the risks associated with innovation.

Highly innovative companies live by a set of key innovation philosophies that instill a deep, companywide commitment to innovation. First, these companies make clear that innovation is everyone’s job. Second, they make sure that disruptive innovation is an important part of the company’s innovation portfolio. Third, they create lots of small project teams and endow them with the right people, structure, and resources to power new ideas to market. Finally, they knowingly take risks in the pursuit of innovation. But they mitigate the inherent risks associated with innovation by deploying the right people and processes in their teams and by providing the right structure so that teams have proper autonomy levels. Ultimately, innovative companies rely on these philosophies to create a culture that not only ignites new ideas, but takes them to market. When this happens, people work in a company culture that helps them answer the following four questions with a hearty yes:

- Philosophy #1:In your company, is innovation everyone’s job?

- Philosophy #2:Is disruption part of your company’s innovation portfolio?

- Philosophy #3:Are small project teams central to taking innovative ideas to market?

- Philosophy #4:Does your company take smart risks in the pursuit of innovation?

Conclusion: Act Different, Think Different, Make a Difference

“Care about something enough to do something about it.”

—Richard Branson, founder, Virgin Inc.

BY THE END of our eight-year research project on some of the most innovative people and companies in the world, we came to believe that if individuals, teams, and organizations want to think different, they must act different. Now that you’ve nearly finished The Innovator’s DNA, we wonder where you stand. Do you believe that if you act different, you can think different? That if your organization acts different, it can think different as well? We hope so, because the innovator’s journey, individually or collectively, can often feel like a road “less traveled.” Yet, the road is worth taking because it just might make “all the difference” in your life and the lives of many others.

Mastering the five discovery skills of disruptive innovators and demonstrating the courage to innovate are what we’ve tried to share in this book. Doing so requires practice, personally, professionally, and organizationally (for a road map of how to master the five discovery skills, and even how to build them in the next generation, see appendix C). Consistent practice produces mastery, and mastery makes for new habits or, in organizations, new capabilities. By developing heavy-duty discovery skills, we really are different. We act different, think different, and by doing so we can make a concrete difference.

Of course, there are a variety of ways to leverage your discovery skills to make a difference. Ideally, you will uncover a big, disruptive idea, initiating meaningful change in many lives. Certainly, Bezos, Jobs, Benioff, and other innovative entrepreneurs have had an immense impact on the world. Their organizations employ hundreds of thousands of people, and their products influence—and most would say improve—the lives of hundreds of millions. No wonder many of these business innovators moved from disrupting industries to seeking an even greater impact by aiming their attention and resources (including innovator’s DNA skills) at some of the toughest world challenges, such as poverty, education, and disease.

Take a look at Salesforce.com, where Benioff built a company to not only disrupt the entire enterprise software industry, but also to make a difference wherever it operates. He did this through a 1-1-1 philosophy where 1 percent of all employees’ time, 1 percent of all its products, and 1 percent of all its equity go toward improving communities and promoting compassionate capitalism. As Benioff puts it, he’s in the “business of changing the world.” His approach relies on hundreds of thousands of employee hours and millions of dollars to tackle problems ranging from sanitation to homelessness. Benioff is not alone in taking on tough issues. Bill and Melinda Gates, Richard Branson, and many others do the same in their own shape and form.

On a smaller scale but a highly similar focus, we have also worked with social innovators around the world who rely on innovator’s DNA skills to create profound solutions to some of society’s most difficult problems. For example, Andreas Heinecke founded a for-profit social enterprise, Dialogue in the Dark, when working as a newspaper journalist in Germany. Heinecke’s boss had brought a blind coworker to his desk and asked him to teach the person how to become a journalist. Heinecke had no idea how to approach the situation, but quickly threw himself into the task of figuring out how to make it work, in part because he had less than perfect hearing. Heinecke not only helped his blind colleague to become a journalist but, in the process, used his innovator’s DNA skills to found Dialogue in the Dark, which hires blind experts to take sighted visitors into a world of complete darkness for one to three hours. (Our assessment showed Heinecke as exceptional at idea networking and questioning.) Heineke observed that to better understand and appreciate blind people, you must experience the world as they do.

To date, over 6 million visitors in thirty different countries have experienced the exhibitions where people learn to navigate through parks and across streets, and to eat in completely dark spaces. Dialogue in the Dark also conducts very successful leadership development sessions at companies and conferences, including the World Economic Forum Davos events. (We regularly collaborate with Heinecke to produce “Innovator’s DNA in the Dark” experiences that deliver a unique and profound learning context for cultivating the innovator’s DNA skills with companies like the leading logistics firm in the Middle East, Aramex, to the world’s leading art business, Christie’s.) Dialogue in the Dark is now one of the largest worldwide employers of blind people (hiring and training over six thousand so far). All this was triggered because Heinecke decided to focus his persistent questions and conversations on a search for new ways to create jobs for the blind and to overcome barriers in all walks of life.

In the end, most of us will likely make a difference through many minor (derivative) innovations. An idea with impact might be a new process for hiring that helps your company find more talented people (such as Google’s Code Jam tournament described in chapter 9). It might be a new approach to marketing your company’s products (such as P&G’s new use of bloggers and customer-generated content described in chapter 9). Or it might be building a business model based on the premise that for every pair of shoes sold, the company will give away one pair, as Blake Mycoskie did when he founded TOMS Shoes (after traveling to Argentina in 2006 and seeing so many children with foot diseases because they lacked shoes).

Clearly, the process of creative discovery can be difficult, but the rewards far outstrip the challenges. Being a creator is exciting, and to author or coauthor an idea that leads to a new product, service, process, or business energizes. Being an innovator is psychologically and emotionally gratifying in a way that money simply isn’t, even though the financial rewards of successful innovation can be significant. Mark Ruiz, co-founder of MicroVentures and finalist for the Entrepreneur of the Year Philippines 2010 award, admitted the same when he told us, “even though I’m an entrepreneur, what drives me is not really the money. What really drives me is a deep sense of mission and purpose. I just see problems that are screaming for new and innovative solutions.” Ruiz works nonstop to build new venture after new venture to take on these problems in his home country, the Philippines.

Ruiz and all the other disruptive innovators we encountered while working on this book take seriously the questions, “If not you, who?” “If not now, when?” They do not sit still. They are physically active, always asking questions, observing, networking, and experimenting. Others can actually “see” their discovery skills at work because their innovation work is far from sedentary. Judi Sandrock, CEO of the Branson Centre for Entrepreneurship, told us that she lives by the question, “How do I do this now?” and works tirelessly to help emerging entrepreneurs in South Africa do the same. In his path-breaking research on risk and uncertainty, economist Frank Knight saw innovative entrepreneurs as a class of individuals with the “disposition to act” in spite of the uncertain context in which they operated. We heard this over and over from various innovators, including Virgin’s Branson who lives by, “Screw it, Let’s do it,” and Skype’s Zennström, who made the following analogy between action and entrepreneurial success:

Say that you have one of those reality shows on TV and you drop a bunch of people in the middle of a desert island. The winner is the person who gets to the shore the quickest. Some people try to analyze where they are, which direction to go. Some of them say, “Let’s climb up a tree or a rock or hillside and maybe we can see further and figure out what is the best direction to go.” They will spend time planning and analyzing how to find the best direction to go. But some other people will just look around, follow their intuition, and start running in a direction.

If there are a lot of people that have been dropped on the island, I can almost guarantee that whoever starts climbing up the tree to start analyzing where he is and which direction to go will not win the competition. Why? Because there are a few other maniacs who will follow their intuition and just start running. They’re much more likely to get to shore quicker. The point is: if you have a good gut feeling for which general direction to go, then you should just run as fast as you can.

Zennström’s challenge: act and figure it out as you go. That way, you get valuable feedback by acting, and you get even better feedback by fully engaging your innovator’s DNA skills along the way. But act now or it may be too late. Windows of opportunity exist for capturing the full value from any innovative business idea. No wonder successful innovators move fast to implement an idea before its window closes.

In the end, innovation is an investment—in yourself, in others, and if you’re a senior manager or emerging entrepreneur, in your company. Whether you’re working at the top of an organization or as a technical specialist at the bottom, eBay’s Whitman advises everyone “to have the courage to plant acorns before you need oak trees.” Innovation is all about planting acorns (ideas) with less than complete confidence that each will grow into something meaningful. The alternative, however, is little or no growth when no acorns emerge as trees. By understanding and reinforcing the DNA of individual innovators within innovative teams and organizations, you can find ways to more successfully develop not just growth saplings but the real oak trees of future growth. As you continue your innovation journey, let your life speak^2 the final line from Apple’s Think Different campaign: “The people who are crazy enough to think they can change the world are the ones who do.” So just do it. Do it now!

Appendix A: Sample of Innovators Interviewed

Interviewees

Name

Company

Innovative aspect of company [*]

Nate Alder

Klymit

Among the first to offer Klymit Kinetic vests and jackets insulated with noble (argon) gases.

Marc Benioff

Salesforce.com

Among the first to offer online/on-demand CRM/Salesforce Automation Software.

Jeff Bezos

Amazon.com

Among the first online book retailers; developed online fulfillment capabilities.

Mike Collins

Big Idea Group

Intermediary between product inventors and innovative product-buying companies/distribution channels.

Scott Cook

Intuit

Among the first to offer personal finance and tax software Quicken and TurboTax.

Gary Crocker

Research Medical Inc.

Introduced disposable medical products for beating-heart surgeries to reduce excessive blood loss and visualization visibility problems for surgeons.

Michael Dell and Kevin Rollins

Dell Computer

Developed direct-to-customer sales model in PCs, allowing for mass customization.

Orit Gadeish

Bain & Co.

Bill Bain founded Bain & Company, but Gadeish is known to have initiated innovative ideas in numerous client engagements.

Aaron Garrity and Joe Morton

XANGO

Among the first to offer juice and other nutritional products using mangosteen and a network marketing approach.

Diane Greene

VMWware

Among the first to offer virtualization software technology allowing virtual servers and desktops to host multiple operating systems and multiple applications locally and in remote locations.

Andreas Heinecke

Dialogue in the Dark

A social enterprise that hires blind experts to take “sighted” novices visitors into a world of complete darkness for various training and educational purposes.

Jennifer Hyman and Jenny Jennifer Fleiss

Rent the Runway

Among the first to offer designer dresses for rent over the Internet.

Eliot Jacobsen

Freeport.com; Lumiport

Among the first to launch a free ISP with unique reach to local retailer community; helped launch Lumiport, a topical light for acne treatment.

Josh James and John Pestana

Omniture

Among the first to develop and deploy Web analytics software.

Jeff Jones

NxLight; Campus Pipeline

Among the first to offer a digital offering to campus allowing users to access data remotely.

A. G. Lafley

Former CEO, Procter & Gamble

Initiated major organizational process changes at P&G to focus the company on innovation, including the “Connect and Develop” process that has been a major source of new product introductions.

Mike Michael Lazaridis

Research In Motion

Developed “BlackBerry,” a handheld wireless communication device that has frequently been first with new technologies.

Kristen Murdock

Cow Pie Clocks and greeting cards

Invented the “Cow-Pie Clock,” a clock embedded in a glazed cow pie with a funny saying attached (e.g., “Happy birthday, you old poop”).

David Neeleman

Morris Air; JetBlue; Azul

Pioneered ticketless air travel at Morris Air, Live TV at Jet Blue, and free bus travel to the airport at Azul Airlines in Brazil.

Pierre Omidyar; Meg Whitman

eBay

Launched online auction site facilitating person-to-person auctions.

Ratan Tata

Tata Group Chairman

Ratan’s father founded Tata, but Ratan initiated the Tata Nano project, which led to the Tata Group’s launching of the world’s cheapest car.

Peter Thiel

PayPal

Among the first to offer financial services over the Internet. With Max Levchin, developed software that essentially attached money to an e-mail.

Corey Wride

Movie Mouth

Movie Mouth is building an interactive, Web-subscription application that has an embedded media player accessing copyrighted media, such as DVDs and CDs, on the local machine, and remote content from the Web.

Niklas Zennströom

Skype

Used “supernode” technology to place calls via the Internet and deployed a unique viral marketing approach.

* We use the wording “among the first” to launch a product or service offering because we have not verified that the company was indeed the first to offer the product or service. However, the innovators we interviewed claimed that this was their original idea and they were not simply imitating another company’s offering.

Appendix B: The Innovator’s DNA Research Methods

Our research project consisted of two phases: (1) an inductive study of innovators compared with noninnovators, and (2) a large sample study comparison of roughly eighty innovators and roughly four hundred noninnovator executives (we later expanded this to a larger sample). We conducted exploratory interviews with a sample of roughly thirty innovative entrepreneurs and a similar number of senior executives in larger organizations (see a subsample of innovators we interviewed in appendix A). The goal of our interviews with innovators was to understand when and how they personally came up with creative ideas on which they built new innovative businesses. We asked questions such as:

1. What was the most valuable strategic insight or novel business idea that you generated during your business career? Please describe the details of the idea. (For example, how was the idea novel and how did you come up with it?)

2. In your opinion, do you have any particular skills that are important to helping you generate novel business ideas? How did those skills influence your ability to generate strategic insights or novel business ideas?

To get an outside perspective, whenever possible we also interviewed senior executives who were well acquainted with the innovative entrepreneur. For example, we interviewed Dell CEO Kevin Rollins about Michael Dell and former eBay CEO Meg Whitman about eBay founder Pierre Omidyar, Skype founder Niklas Zennström, and PayPal founder Peter Thiel.

Through the interviews, we identified four behavioral patterns—questioning, observing, networking, and experimenting—that were more pronounced in innovators and which seemed to trigger associational thinking. These four behavioral skills and one cognitive skill comprise the five discovery skills that we discuss in the book.

We then developed a set of survey items to measure the frequency and intensity with which a person engaged in questioning (six survey items), observing (four survey items), experimenting (five survey items), and idea networking (four survey items). Response options ranged from 1 or strongly disagree to 7 or strongly agree. We also conducted an exploratory and confirmatory factor analysis (EFA) to uncover the underlying factor structure of the nineteen items measuring the behaviors.

We then conducted a negative binomial regression to test the relationship between the four discovery behaviors and starting innovative ventures. The results showed that observing, networking, and experimenting were significantly correlated with starting an innovative new business (and questioning was significant when combined with one of the other three behaviors). The four behavioral patterns were also significantly correlated with each other—with correlations typically greater than 0.50—suggesting that an individual who engages in one of the behaviors is more likely to engage in some level of the other behaviors. Results were stronger when each of the behaviors was used in combination with another behavior. Full details of the initial study can be found in: Jeffrey H. Dyer, Hal B. Gregersen, and Clayton M. Christensen, “Entrepreneur Behaviors, Opportunity Recognition, and the Origins of Innovative Ventures,” Strategic Entrepreneurship Journal 2 (2008): 317–338.

Appendix C: Developing Discovery Skills

Years ago, Arnold Glasow, an entrepreneur and humorist, concluded that “improvement begins with I.” We couldn’t agree more. The focus of this appendix is to suggest how you might personally improve your discovery skills—associating, questioning, observing, networking, and experimenting.

Developing Your Discovery Skills

To develop your skills, we provided a number of practical tips in chapters 2 through 6. To decide which tips make the most sense to follow, we suggest that you take five steps: (1) review priorities to see where you spend your time, (2) assess your discovery skills systematically, (3) identify a compelling innovation challenge that matters, (4) practice your discovery skills ruthlessly, and (5) get a coach to support your ongoing development efforts. When combined, these steps can help you—and your team—build the relevant innovation skills required to make a bigger, better impact at work and beyond. (If you also want to build your team’s discovery skills, take the steps outlined , but focus your development work on your team.)

Step 1: Review priorities

Consider how you typically spend your time at work. We suggest dividing your core tasks into three broad categories: discovery, delivery, and development. Discovery focuses on innovation and includes actively engaging the five discovery skills in search of new products, services, processes, and/or business models. Delivery is all about producing results, analyzing, planning, executing, and implementing strategies. Finally, development centers on building your capabilities and those of others (primarily direct reports, if you are a manager). This task includes selecting the right people for your team and training them well in the innovator’s DNA skills.

Now, look at your calendar for a typical workweek. What percent of your time do you personally spend on each task—discovery, delivery, and development? You may want to answer this question by filling out the chart in table C-1, using the following simple process. First, make your best guess about how you currently spend your time (the “today” column). Second, record your best judgment about where you think you should be spending your time (“tomorrow”), given your team’s purpose and your company’s strategy. Third, calculate the difference or “gap” between today and tomorrow for each category.

Next, focus primarily on the gap. Is it large? Negative? Positive? Or neutral? If the gap is zero, you’re spending the time and energy that you think you should on discovery. However, a negative gap reflects a need to devote more time to discovery activities to improve your ability as a discovery-driven leader.

Innovative CEOs and founder entrepreneurs spend roughly 50 percent more of their typical week on discovery activities than noninnovative CEOs and entrepreneurs do. So if you aren’t devoting at least 30 percent of your time to discovery, you probably aren’t leading the innovation charge. Creative problem solving takes time, so increase the amount you spend on discovery to have a bigger impact on innovation.

TABLE C-1

Tracking your time spent

Step 2: Assess your discovery skills

After reflecting on your time spent (discovery versus delivery), get a more refined, specific sense of your discovery and delivery skill strengths and weaknesses. You can gain an idea of your performance on these skills through the brief self-assessment in chapter 1. You can also visit http://www.InnovatorsDNA.com to take a more comprehensive online self-assessment or a 360-degree online assessment (which provides feedback from your manager, peers, and direct reports) to capture a better sense of your strengths and weaknesses.[1] These assessments can prove valuable in helping you answer: “What is my everyday discovery versus delivery orientation? In which discovery skills am I strongest? Which ones do I want to develop? In which delivery skills am I strongest? Which delivery skills do I need to develop?”

Step 3: Identify a compelling innovation challenge

After assessing your strengths and weaknesses in discovery and delivery, the next step is to find a specific, current innovation challenge or opportunity so that you can practice your discovery skills. This challenge might range from creating a new product or service, reducing employee turnover, or coming up with new processes that reduce costs by 5 percent in your business unit. With your innovation challenge clearly in mind, develop a plan to practice some of the discovery skills as you search for creative solutions.

Step 4: Practice your discovery skills

We propose that you work on your questioning skills first, since innovation often starts with a compelling question and innovative teams have a culture that supports questioning. Write down at least twenty-five questions about your innovation challenge and conduct a QuestionStorming activity (or other questioning tips) with your team, as outlined at the end of chapter 3. A personal habit of asking questions helps create a safe space for other team members to also ask questions.

After strengthening your capacity to question, identify your strongest skill among observing, networking, and experimenting and seek to practice it as you tackle your innovation challenge (unless it’s so strong that more practice provides diminishing returns; in that case, working on a weaker discovery skill may be a better development option). Again, refer to each of the chapters about these skills (chapters 4 through 6) for suggestions about improving them. Involve your team as much as possible in whatever discovery skill you are working on (observing, networking, or experimenting) as you search for a solution to your challenge. Finally, engage in frequent brainstorming sessions (alone and with your team) to practice associating (see chapter 2 for tips on associating).

Step 5: Get a coach

Innovation is habit forming or, rather, innovation requires forming new habits regarding the five discovery skills. Our friend Stephen Covey, author of The 7 Habits of Highly Effective People, might call this book The Innovator’s DNA: The Five Habits of Highly Creative People. How can you increase the probability that if you try out the new skills suggested, you will turn them into new habits? One place to start is asking someone to serve as your creative mentor or coach—someone who can motivate and coach you while you work on developing new behavioral patterns. Personal change is difficult, and asking someone you respect to help with the change effort is an important step (getting one person engaged in the change process will bump up your success rate 15 percent to 20 percent). The coach can be a boss, peer, professor, classmate, or even someone you live with (you might practice these skills with other family members as you attempt to creatively solve problems at home). But whomever you pick, make sure he or she is someone you can trust to give you honest feedback and suggestions. A creative mentor and coach can make a big difference in helping improve your creativity skills.

Master the Five Skills of Disruptive Innovators

Mastery of any skill comes by practicing specific elements of that skill. For example, world-class athletes, musicians, or managers break down a skill into very specific parts of their “game.” Then they practice these minute elements relentlessly. For a golfer, it might mean short putts on the green, over and over for days until she masters one small element of the swing. Concert pianists do the same with a small part of a musical piece. Practice over the course of weeks, months, and years ultimately provides mastery of not only one skill, but a set of skills.

The disruptive innovators in our research did precisely this, either consciously or unconsciously. They practiced skills relentlessly, on almost anyone or anything they interacted with. The mystery of innovation is far less mysterious when people practice the innovator’s DNA skills regularly so the skills become new habits. This takes time and self-discipline. So start with realistic expectations and actively allocate time to improving your discovery skills. Most of all, remember that your personal development efforts send a serious signal to your team and organization about how high innovation ranks in your priorities and how important it might become to theirs.

Developing Discovery Skills in the Next Generation

The most important innovation work any of us might do is within the four walls of our home, the boundaries of our neighborhood, or the classrooms of our local schools. Why? Almost all the disruptive innovators we interviewed mentioned at least one adult in their lives who paid personal attention to their innovation skills and helped nurture them as they grew into adulthood. That’s why we think it’s so important for adults to honor and amplify young people’s discovery skills worldwide.

Consider Steve Jobs’s life. Early on, his father set aside part of his workbench for Jobs to experiment on mechanical things. Later, Jobs’s neighbor, Larry Lang, taught him (and other interested neighborhood kids) a lot about electronics by building Heathkits together (products like transistor radios that were purchased in do-it-yourself kits). In retrospect, Jobs realized that building Heathkits with a neighbor and exploring things on his father’s workbench ultimately gave him an understanding of what lurked inside a finished product. More importantly, Jobs acquired the sense that “things were not mysteries” and, as a result, he also gained “a tremendous level of self-confidence” about mechanical and electronic things.

Jobs was not the only fortunate one when it came to developing the next generation of disruptive innovators. Jeff Bezos’s grandparents played an equally powerful role in fostering his experimentation skills during the summers on their Texas farm. Richard Branson’s mother supported his curiosity to carry on a family legacy of discovering new terrain. Orit Gadiesh’s parents and schoolteachers not only tolerated her questions, but valued them. In short, disruptive innovators had one or more adults play a key role in keeping their natural innovator’s DNA alive beyond childhood. You can play that same important role with a future generation of innovators.

Developing Discovery Skills in Homes and Neighborhoods

What better place to start building the five skills of disruptive innovators than in our homes and neighborhoods? If you take on this challenge to “send the elevator down,” as entrepreneur (and founder of Ariadne Capital) Julie Meyer put it, and bring up a new generation of disruptive innovators, here are a few concrete, helpful tips.

Associating Skills

1. One game you can play, particularly when traveling in the car, is called, “What’s the connection?” Two people each think of a random word. A third person is the player. Once they decide on random words, each of the first two people announces his or her word. The third person must then create a logical connection between the two words, but try to be creative in doing so. For example, the words pickle and stitches might be connected with: “We make sour faces when getting stitches at the hospital and when we bite into a sour pickle.” Similarly, the board game TriBond (distributed by Mattel) gives you three word clues and asks you to figure out what they have in common. (You can also try out the game at http://www.TriBond.com, where there’s a new combination of three words to connect every day.)

2. Search for books that foster associational thinking. One of our favorites is Not a Box. The main character, a rabbit, tries to convince readers that boxes are not boxes. Instead, boxes might be anything, if we let our imaginations run wild (ranging from a race car to a spaceship). After one of us read Not a Box to a three-year-old grandchild, he discovered him sitting in a box later that day. It was not a box, but a pirate ship! If you enjoy reading creative books with children, a few others are: Harold and the Purple Crayon (by Crockett Johnson,), Ish (by Peter Reynolds), The Anti-Coloring Book (by Susan Striker and Edward Kimmel).

Questioning Skills

1. When most children come home from school, parents often ask: “How was your day?” or “Did you learn anything interesting today?” The second question is better than the first (in terms of insights gained), but what if you regularly asked your child (or neighbor’s child): “What questions did you ask today?” “What questions did other children ask today? “What questions didn’t you have time to ask today?” Then listen; really, really listen. You may be surprised by what you discover. (You may also want to take a moment to watch What Is That?, a short video by MovieTeller films about how a father’s and son’s questions powerfully affect each of them).

2. Whenever you face a family, school, or community problem or challenge that needs a solution, try using a modified version of our QuestionStorming approach with young people. Kids don’t have the patience to brainstorm fifty questions, but they usually have the patience to brainstorm ten questions. For example, suppose you have a problem with your child not doing chores or homework. Asking just ten questions together about the “problem” can often yield interesting insights. For example, you might ask, “Why isn’t science interesting to you?” “What can I do to be helpful?” Your child might ask, “Why do I need to know science?” “Why is science so important to you?” This process of asking questions about a problem can often trigger ideas or insights that will lead to novel solutions.

Observing Skills

1. Give children a chance to see you at work. You never know what surprises they might have by joining you for a day. Pay attention to what they notice as they enter your world; become a fly on the wall and watch the world through their eyes as they try on the likely new, adult world of work. For Jon Huntsman Jr., going to his father’s workplace when he was eleven years old altered the course of his life. He was visiting his father, who worked as a special adviser to President Nixon, at the White House. While there, he met Henry Kissinger, who was on his way to a secret meeting in China. When young Jon asked Kissinger where he was going, Kissinger replied, “China.” Until then in Jon’s life, China had not been a real place with real people. But hearing that one word from someone who was actually going to China sparked a lifelong interest. Huntsman later studied Asian history and Asian languages in school. In total, he spent fifteen years learning Mandarin and spoke it fluently as the U.S. Ambassador to China.

2. Take frequent walks in old places and new ones. Take a child on a walk and look at the experience through her eyes. What does she see? Hear? Taste? Touch? Smell? You may be surprised at what you’ve never noticed before. Watch carefully for what surprises her; it just might surprise you as well. When traveling or living in new places, do the same, especially in moments of transition (just arriving or just leaving) when we sometimes see things that otherwise remain invisible. Keep a journal together that captures your observations. How to Be an Explorer of the World (by Keri Smith) is a great guide for adults and children who are interested in making better observations of the world.

Networking Skills

1. You can start building networking skills with young people by occasionally bringing a work (or even family) problem to them and asking for their opinion. Explain that problems are best solved when you get a variety of people looking at them from multiple perspectives. If they express interest in the problem, you might even invite them to join you as you bring the same problem to someone else with a different background. This becomes a powerful example of the importance of networking for ideas and demonstrates a process for doing it.

2. Occasionally, whenever you face a family, school, or community problem or challenge, think about inviting a focus group of three or four people with different backgrounds to give their perspectives on how to best solve the problem. This could involve a dinner invitation or drinks and refreshments to accompany the discussion.

3. If you have young people in your home, do some idea networking together by socializing with a diversity of people. For example, pick a person from a different country, different ethnic group, different religion, different age, or unusual occupation and invite him or her to a meal with your family. Explore together how other people live and see the world.

Experimenting Skills

1. Conduct experiments at home or in your neighborhood and discuss them with children. For example, Bill Dyer (a sociologist and father of Jeff Dyer) placed an ironed white shirt on the floor of the central walkway in his home. He watched for two days as his children carefully stepped around it, as no one bothered to pick it up. He then discussed with his children why they didn’t think to pick up the shirt and, more broadly, what they viewed as their responsibilities around the house. On another occasion, he swapped a teenage son for a neighbor family’s teenage son for a week. After the week, the two families got together to discuss what each boy, and each family, learned from the experience.

2. Take a young person to a junkyard or flea market to find something to take apart. Pick something for yourself at the same time. Take the items home and dismantle them together to see what new insights emerge about how and why things work. One father and son did this with an old airplane engine. The experience sparked a future aviation career, as the young boy grew up to become a pilot.

3. Engage young people in prototyping efforts. Select a product you’d like to improve (or imagine a new one) and design and construct a crude prototype together. Children love the chance to create something new, particularly if Play-Doh is involved; you never know what new feature of the prototype they might discover.

4. Take your child on a trip to a foreign country (or even a “foreign” part of your hometown) with the explicit goal of experimenting with everything new. Try out new foods, customs, and local products and services. If possible, live in a home to experience life as a local. Try out as many new interactive experiences as possible.

Final Call for Action

What is our final call for action? Adopt a young innovator! Find at least one child (your own, a relative’s, or a neighbor’s) and help that young person appreciate and strengthen his innovation skills. Every child deserves at least one adult who values her innovation skills, at least one adult who listens to her honest questions. As Dr. Seuss knew so well, “Unless someone like you cares a whole awful lot, nothing is going to get better. It’s not.” If we don’t collectively nurture the next generation of disruptive innovators, who will? There are far too many children in need for any adult to slack off when it comes to nurturing the next generation. If we collectively do this task well, many young people will grow up acting different, thinking different, and, in the end, making a difference in a world bursting with complex, challenging problems. Naively perhaps, we believe in the power of one, that one adult honoring one child’s innovation skills can make all the difference in building a new generation of disruptive innovators. That is our hope.

Notes

Introduction

1. IBM, “Capitalizing on Complexity: Insights from the Global Chief Executive Officer Study,” May 18, 2010.

2. Jeffrey H. Dyer, Hal B. Gregersen, and Clayton Christensen, “Entrepreneur Behaviors, Opportunity Recognition, and the Origins of Innovative Ventures,” Strategic Entrepreneurship Journal 2 (2008): 317–338.

3. Todd Kashdan, Curious?: Discover the Missing Ingredient to a Fulfilling Life (New York: Harper Collins, 2009).

Chapter 1

1. M. T. Hansen, H. Ibarra, and U. Peyer, “The Best Performing CEOs in the World,” Harvard Business Review, January–February 2010.

2. J. Young and W. Simon, iCon: Steve Jobs, The Second Greatest Act in the History of Business (Hoboken, NJ: John Wiley & Sons, 2005), 37.

3. Ibid., 38.

4. Ann Brashares, Steve Jobs: Thinks Different (New York: Twenty-first Century Books, 2001).

5. Steve Jobs, commencement address, Stanford University, 2005.

6. Marvin Reznikoff, George Domino, Carolyn Bridges, and Merton Honeyman, “Creative Abilities in Identical and Fraternal Twins,” Behavior Genetics 3, no. 4(1973): 365–377. For example, the researchers gave them the Remote Associations Test (RAT), where they would present twins with three words and ask them to find a fourth word linking the three; they also gave them the Alternative Uses Test, where they would ask the subjects to brainstorm as many alternative uses for a common object—like a brick—and code how many total and divergent responses the subjects provide.

7. See K. McCartney and M. Harris, “Growing Up and Growing Apart: A Developmental Meta-Analysis of Twin Studies,” Psychological Bulletin 107, no. 2 (1990): 226–237.

8. Other studies that have found that nurture trumps nature as far as creativity goes include: F. Barron, Artists in the Making (New York: Seminar Press, 1972); S. G. Vandenberg, ed., Progress in Human Behavior Genetics (Baltimore: Johns Hopkins Press, 1968); R. C. Nichols, “Twin Studies of Ability, Personality and Interest,” Homo 29 (1978), 158–173; N. G. Waller, T. J. Bouchard, D. T. Lykken, A. Tellegen, and D. Blacker, “Creativity, Heritability, and Familiality: Which Word Does Not Belong?” Psychological Inquiry 4 (1993): 235–237; N. G. Waller, T. J. Bouchard Jr., D. T. Lykken, A. Tellegen, and D. Blacker, “Why Creativity Does Not Run in Families: A Study of Twins Reared Apart,” unpublished manuscript, 1992. For a summary of research in this area, see R. K. Sawyer, Explaining Creativity: The Science of Human Innovation, 2nd ed. (New York: Oxford University Press, forthcoming).

9. A. G. Lafley and Ram Charan, The Game Changer (New York: Crown Business, 2008).

10. Indeed, the goal of “gene therapy” is to insert new genes into an individual’s cells to replace a genetic defect with a properly functioning gene.

11. L. W. Busenitz and J. B. Barney, “Differences between Entrepreneurs and Managers in Large Organizations: Biases and Heuristics in Strategic Decision-Making,” Journal of Business Venturing 12 (1997): 9–30.

12. R. C. Anderson and D. M. Reeb, “Founding Family Ownership and Firm Performance: Evidence from the S&P 500,” The Journal of Finance, 58, no. 3 (June 2003): 1301–1327. This study found that companies led by the CEO founder were 29 percent more profitable (net income to assets) and had 21 percent higher market valuations. These results cannot be attributed to the fact that founder-led companies are smaller and more likely to grow (they controlled for size and age) or are in more attractive industries (they controlled for industry). The authors conclude that “founders bring unique, value-adding skills to the firm that result in superior accounting performance and market valuations” (p. 1317).

Chapter 2

1. Walt Disney Company, 1965 Annual Report.

2. Gary Wolf, “Steve Jobs: The Next Insanely Great Thing,” Wired, wired.com/wired/archive/4.02jobs_pr.html (accessed November 10, 2009).

3. We prefer the term associational thinking to pattern recognition because the latter term seems to suggest that there is an identifiable pattern innovative entrepreneurs recognize. As innovators described how they discovered or recognized ideas for innovative new ventures, it seemed to us that while they connected disparate ideas together, they often did not necessarily recognize a pattern, or even recognize that it would be a viable business opportunity. They often discovered that things fit together through trial and error and adaptation.

4. While Frans Johansson coined the term “The Medici Effect” for his bestselling book, we prefer a less time and place bound version of the term. Hence, we use the “Innovation Effect” when referring to places past, present, and future where a powerful convergence of different ideas generate substantial innovative results. Historically these were geographic spaces that promoted intersections between people with different backgrounds and knowledge. Today these can be geographic places or virtual market spaces that are designed to foster connections between people with different knowledge.

5. In short, the Medici effect was not limited to the Medici family or the renaissance period in Florence, Italy. Instead, the Medici effect was simply a specific example of the common experience within science and elsewhere that innovations often result at the intersection of disciplines.

6. Mihaly Csikszentmihalyi, Creativity (New York: Harper Perennial 1996).

7. “Leslie Berlin, “We’ll Fill This Space, but First a Nap,” New York Times, September 28, 2008.

8. If you want books chock-full of ideas about how to connect ideas more creatively, pick up either of Michael Michalko’s books, Cracking Creativity or Thinkertoys. They’re exceptional.

9. Bill Taylor, “Trading Places: A Smart Way to Change Your Mind,” Harvard Business Review Blog, March 1, 2010.

Chapter 3

1. Quinn Spitzer and Ron Evans, Heads You Win: How the Best Companies Think (New York: Simon and Schuster, 1997), 41.

2. Peter Drucker, The Practice of Management (New York: Wiley, 1954), 352–353.

3. Mihaly Csikszentmihalyi, Creativity (New York: Harper Perennial 1996).

4. Karen Dillon, “Peter Drucker and A.G. Lafley want you to be curious,” October 8, 2010, http://blogs.hbr.org/hbr/hbreditors/2010/10/ what_will_you_be_curious_about.html.

5. Land not only created the Polaroid camera, but held 532 other patents for a variety of scientific and commercial purposes (a patent output second only to Thomas Edison).

6. Marissa Ann Mayer, “Turning Limitations into Innovations,” BusinessWeek, Feburary 1, 2006, http://www.businessweek.com/innovate/ content/jan2006/id20060131_531820.htm.

7. Rekha Balu, “Strategic Innovation: Hindustan Lever Ltd.,” FAST Company, May 31, 2001, http://www.fastcompany.com/magazine/ 47/ hindustan.html.

8. Alan Deutschman, “The once and future Steve Jobs,” October 11, 2000, http://www.salon.com/technology/books/2000/10/11/ jobs_excerpt.

9. Brooks Barnes, “Disney’s Retail Plan Is a Theme Park in Its Stores,” New York Times, October 13, 2009.

10. Since our serendipitous discovery of QuestionStorming, we have since learned that others also stumbled across similar practices (e.g., Jon Roland, Questorming (http://www.pynthan.com/vri/questorm.htm); or Marilee Goldberg, The Art of the Question (New York: Wiley, 1997).

Chapter 4

1. Bob Sutton, a professor at Stanford, has used this expression, but Tom Kelley of IDEO says he’s also heard that it originated with the comic George Carlin.

2. Tom Kelley, The Art of Innovation (New York: Doubleday, 2005), 16.

3. http://www.wired.com/magazine/tag/trimpin/, November 12, 2009.

4. Howard Shultz and Dori Jones Yang, Pour Your Heart Into It: How Starbucks Built a Company One Cup at a Time (New York: Hyperion, 1997), 51–52

5. Ethan Waters, “Cars, Minus the Fins,” Fortune, July 9, 2007, B-1.

6. See http://www.nytimes.com/1991/01/27/books/notes-from-a-more-real-world.html?src=pm.

Chapter 5

1. Ron Burt, “Structural Holes and Good Ideas,” American Journal of Sociology 110, no. 2 (September 2004): 349–399.

2. See http://www.ted.com/pages/view/id/47.

Chapter 6

1. Steve Jobs, Stanford Commencement Speech, June 12, 2005.

2. M. Carpenter, G. Sanders, and H. Gregersen, “Bundling Human Capital: The Impact of International Assignment Experience on CEO Pay and Multinational Firm Performance,” Academy of Management Journal 44, no. 3 (2001): 493–512.

3. Walter Isaacson, Einstein (New York: Simon and Schuster, 2007), 2.

Chapter 7

1. How the innovation premium is calculated:

Step 1: In assessing a company’s current valuation, HOLT determines the next two years of cash generation from existing businesses for each firm based on the consensus estimate of earnings and revenues by analysts. The consensus estimate of earnings and revenues is based on the median of the combined estimates of carefully screened analysts covering a public company as selected by Institutional Brokers Estimate System [I/B/E/S]). Benchmarks for historical periods (as are used in the innovation premium) use actual reported profitability and reinvestment rates as the starting point for the cash flow forecasts.

Step 2: HOLT then projects future free cash flows over the next 38 years from existing businesses based on fade algorithms developed from an analysis of historical cash flows from over 45,000 firms and more than 500,000 data points. The concept of fade embodies the common-sense notion that competition is the one enduring constant in free markets (à la Schumpeter’s “creative destruction”) and that technological change and changing market dynamics all militate against the persistence of excessively high returns (this is consistent with prior research that consistently shows a “regression to the mean” effect with regard to firm profitability).

The fade algorithm for a given company is based on the following:

a. The forward two-year consensus estimate of ROI level. Firms with higher levels of profitability and ROI maintain higher returns into the future. However, the historical experience of most firms shows a “regression to the mean” effect, meaning that high ROIs will gradually fade toward the average ROI of firms in the economy. The higher the current level of profit, the faster the expected decline. (Firms will tend to maintain their rank order; however, the spread between the top and bottom performers tends to narrow.)

b. Historical ROI volatility (over the previous five years). The greater the volatility of ROI historically, the faster the firm’s ROI tends to fade toward the average of all firms going forward. Firms with consistent and stable ROI are more likely to maintain a consistent ROI into the future.

c. A company’s reinvestment rate. The faster a company’s recent growth and the greater the amount of cash it has reinvested, the faster the firm’s ROI will fade toward the mean profitability of firms in the economy. It’s hard enough for a management team to maintain high levels of financial performance; doing this while also growing rapidly is even more difficult.

Step 3: The difference between the company’s total enterprise value (market value of equity plus total debt) and this value of existing business constitutes the innovation premium, expressed as a percentage of the enterprise value.

While HOLT’s fade algorithm is based specifically on the historical and future projected performance of the given firm, it may appear to reflect sector identification or industry position. To the extent that firms in an industry or sector share the characteristics of ROI level, variability, and reinvestment, the pattern of fade will also be similar. There is also an apparent correlation between a company’s fade expectations and its position in the industry, since most industry leaders have higher and more stable rates of ROI and, having been through their growth phase in achieving their leadership position, no longer need to grow at above-average rates.

We require at least 10 years of financial data for a given firm in order to be considered on our list of most innovative companies. We also use a “research and development” screen requiring that companies make some investment in R&D. Also, to control for size differences, we include only those with a market value greater than $10 billion. In very rare cases when a company derived more than 80 percent of their revenues from a single high economic growth market (e.g., India, China), we assumed a small portion of the company’s innovation premium [5 percent of the difference in growth] was derived from domestic market growth rather than entering new products, services, or markets. Accordingly, we made a slight downward adjusted to the firm’s innovation premium, but this only made a minor change in a firm’s ranking and did not move any companies on, or off, the list. The innovation premium shown in the tables in this chapter reflect a weight average innovation premium over five years with the weighting as follows: most recent year (30%), years 2–4 (20%), year 5 (10%).

2. Our ranking must exclude private companies like Virgin (#16 on the BusinessWeek list) and Tata (#25) because they do not have publicly traded stock and report financial results.

3. A. G. Lafley and R. Charan, Game Changer (New York: Random House, 2008), 21.

Chapter 8

1. As quoted in Carmine Gallo, The Innovation Secrets of Steve Jobs (New York: McGraw-Hill, 2011).

Chapter 9

1. Carmine Gallo, The Innovation Secrets of Steve Jobs (New York: McGraw-Hill, 2011), 31.

2. http://www.shmula.com/987/jeff-bezos-5-why-exercise-root-cause-analysis-cause-and-effect-ishikawa-lean-thinking-six-sigma.

3. Gallo, The Innovation Secrets of Steve Jobs, 96.

4. Google’s Culture of Innovation, Innoblog, November 14, 2005, http://www.innosight.com/blog/index.php?/archives/36-Googles-Culture-of-Innovation.html.

5. Nightline, “Deep Dive” video, February 9, 1999.

6. David Kelley interview at Stanford University’s business and design school, August 21, 2006, http://sites.google.com/site/wyndowe/ iinnovateepisode3:davidkelley,founderofideo

7. Nightline, “Deep Dive” video.

8. David Kelley interview, August 21, 2006.

Chapter 10

1. Steven Levy, The Perfect Thing: How the iPod Shuffles Commerce, Culture, and Coolness (New York: Simon & Schuster, 2006), 118.

2. Jeffrey S. Young, Steve Jobs: The Journey Is the Reward (Glenview: IL: Scott Foresman and Company, 1988), 176.

3. The categorization of innovation projects as “derivative,” “platform,” or “breakthrough” comes from the Aggregate Project Planning framework introduced by Steven C. Wheelwright and Kim B. Clark. See: “Using Aggregate Planning to Link Strategy, Innovation, and the Resource Allocation Process,” HBS N9-301-431 (Boston: Harvard Business School Publishing, 2000).

4. The concept of aggregate project planning was first introduced in Steven C. Wheelwright and Kim B. Clark, “Creating Project Plans to Focus Product Development,” Harvard Business Review, March–April 1992, 10-82.

5. Larry Page and Sergey Brin, “Letter from the Founders: ‘An Owner’s Manual’ for Google Shareholders,” Google Inc., Form S-1 Registration, April 29, 2004, 1, via Thomson Research/Investext, http:// research.thomsonib.com.

6. “The Institutional Yes. An interview with Jeff Bezos,” Harvard Business Review, October 2007.

7. David Vise and Mark Malseed, The Google Story (New York: Delacorte Press, 2005), 256.

8. John Battelle, The Search: How Google and Its Rivals Rewrote the Rules of Business and Transformed Our Culture (New York: Penguin Group, 2005), 141.

9. See http://www.virgin.com/aboutvirgin/allaboutvirgin/richard replies/ default.asp.

10. Keith Hammonds, “How Google Grows . . . and Grows . . . and Grows,” FastCompany.com, http://www.fastcompany.com/online/69/ google.html, March 2003.

11. Jonathan Ive, “Lessons On Designing Innovation,” interview, Radical Craft Conference, Art Center College of Design, Pasadena, CA, March 25, 2006.

12. Ken Robinson with Lou Aronica, The Element (New York: Penguin, 2009), 15.

Appendix C

1. These online assessments also provide a development guide with your customized assessment report to help you understand your strengths and potential areas of improvement with regard to your discovery skills and delivery (execution) skills. The development guide also helps you build a skill development plan to leverage your strengths and improve on any major weaknesses that could derail your career.

Acknowledgments

Almost a decade ago the innovator’s DNA research project started to take shape and evolved through the contributions of hundreds, even thousands, of people from around the world. Each of us feels deep gratitude for the colleagues who played critical roles in advancing our ideas much further than they might otherwise have gone. We thank many of them individually below, but many others played a pivotal role in moving this project forward and ultimately bringing it to a conclusion.

No doubt this book would not have been possible without the gracious gift of time given to us by so many disruptive innovators who shared insights into the personal characteristics that helped them innovate. While we interviewed close to a hundred such innovators, we give special thanks to the following: Nate Alder (Klymit), Marc Benioff (Salesforce.com), Jay Bean (ah-ha.com; OrangeSoda, Inc.), Jeff Bezos (Amazon.com), Mike Collins (Big Idea Group), Scott Cook (Intuit), Gary Crocker (Research Medical, Inc.), Michael Dell and Kevin Rollins (Dell Computer), Orit Gadeish (Bain & Co.), Aaron Garrity and Joe Morton (XanGo), Diane Greene (VMware), Andreas Heinecke (Dialogue in the Dark), Jennifer Hyman and Jenny Fleiss (Rent the Runway), Eliot Jacobsen (Freeport, Inc.; Lumiport), Josh James and John Pestana (Omniture), Jeff Jones (NxLight; Campus Pipeline), A.G. Lafley (Procter & Gamble), Mike Lazaridis (Research in Motion), Kristin Murdock (Cow-Pie Clocks and Greeting Cards), David Neeleman (JetBlue; Azul), Pierre Omidyar and Meg Whitman (eBay), Mark Ruiz (Hapinoy), Ratan Tata (Tata Group), Peter Thiel (PayPal), Corey Wride (Movie Mouth), and Niklas Zennström (Skype).

Lisa Stone, assistant to Clayton Christensen, worked hard to coordinate many aspects of the project, but most of all she excelled at setting up interviews with high-profile innovators. While this might sound straightforward, it was at times a Herculean task to coordinate the schedules of four busy people across three continents. Thanks, Lisa, for making miracles happen.

We would also like to extend special thanks to Michael McConnell of HOLT (a section of Credit Suisse), who conducted the research we used to calculate the innovation premium for the companies we analyze in the book. Michael’s thoughtful guidance and careful analysis made our ranking of the world’s most innovative companies possible. We cannot thank him (and HOLT) enough for his expertise and insights.

When the writing finally came to a close, we reached out to several innovators and best-selling authors who gave their valuable time to carefully read the manuscript and provide us with feedback. For those efforts we’d like to thank Marc Benioff, A.G. Lafley, Stephen Covey, and Scott Cook.

At Harvard Business Review Press many people extended themselves throughout the life of the project to make this a better book. Melinda Merino, our editor, listened intently to our original pitch and took it forward with vision and commitment. We appreciate her thoughtful guidance on the book’s structure and content, as well as her unwavering support and encouragement. More than once her optimism came through with a cheery voice and a warm smile that kept the creative ideas flowing and the manuscript moving along. At Harvard Business Review, Sarah Cliffe gave us valuable feedback and guidance on our original HBR article, “The Innovator’s DNA.” Bronwyn Fryer, our HBR editor and later a freelance editor who worked with us on the book, was indispensable in making our writing more coherent. She constantly pushed us to make the ideas within each chapter more interesting, compelling, and accessible—and she did it with exceptional speed and professionalism. As the book moved into production and marketing, many others played key roles in sustaining the energy behind our ideas and keeping us focused on key deadlines. In particular, Jen Waring, Courtney Cashman, Julie Devoll, and Alex Merceron fully leveraged their professional skills in handling every aspect of the manuscript.

Beyond Harvard Business Review Press, two organizations and their people were especially helpful in making this book a reality. At Innosight, Scott Anthony, Mark Johnson, and Matt Eyring worked tirelessly with us to shape our ideas for practical use by leaders around the world. Their efforts helped keep the ideas solidly on the ground where the greatest good can be done. Similarly, at Stern+Associates, Danny Stern and his team were exceptional at helping us frame the ideas for an even broader audience—and, we hope, maximum impact.

From Jeff Dyer

When we started this project almost ten years ago, I had no idea of the joyful, but challenging, journey before me. The innovator’s DNA research has opened my eyes to the fact that all of us can make creative contributions towards a better world. I would first like to acknowledge my sage and insightful coauthors, Hal Gregersen and Clayton Christensen, who have taught me much and have made this book possible. In particular, Hal excels at asking great questions and stepping back to look at the big picture; Clay is a master at theorizing and knowing how to use “the case” to make theory interesting and practical. Moreover, they are both great friends and wonderful human beings.

The data collection effort for this book has been immense, and I have many research assistants to thank who have worked untold hours to make this manuscript possible. I would especially like to thank Nathan Furr, Mihaela Stan, Melissa Humes, Ryan Quinlan, Jeff Wehrung, Nick Prince, Brandon Ausman, Jon Lewis, Stephen Jones, Andrew Checketts, and James Core. In addition, I would like to thank Spencer Cook for developing the tools to capture individual assessment data on our website, as research without data is not possible. Thanks also to Greg Adams for his expert analysis of the data that was used to test hypotheses in our Strategic Entrepreneurship Journal article, “Opportunity Recognition, Entrepreneur Behaviors, and Origins of Innovative Ventures.” I would also like to recognize and thank the scores of MBA students at Brigham Young University who took my Creative Strategic Thinking course and interviewed innovative entrepreneurs as part of their class projects. Their work—and the interview transcripts they provided—was invaluable in helping us to understand the processes by which innovators discover new business ideas. Corey Wride, one of those MBA students, was particularly helpful in reading the manuscript and offering very useful suggestions. The transcriptions of all of the innovator interviews, including the ones conducted by Hal, Clay, and me, were done by Nina Whitehead and her staff, who always managed to meet my ASAP deadlines. Indeed, all of the staff members that support me at Brigham Young University are terrific and deserve my thanks, especially my assistants Holly Jenkins, Stephanie Graham, and Stephen Powell. I also must extend my heartfelt thanks to Dean Gary Cornia and the other deans at the Marriott School at Brigham Young University for the research funding that has supported this project over the last ten years.

I must also acknowledge the contribution of my parents, Bill and Bonnie Dyer. My mother has been a constant source of love and support throughout my life. My father was an amazing example to me in every aspect of life; but for this book, in particular, I thank him for teaching me that it’s okay to ask questions.

Finally, I owe a deep debt of gratitude to my wife Ronalee and my children, Aaron, Matthew, and McKenzie, who have always supported me on this project despite the fact that it has taken a great deal of my time and attention. Ronalee, especially, deserves recognition for always taking such great care of our children and me—we are all greatly blessed because of her love. So thanks, Ronnie—the book is finally done.

From Hal Gregersen

For me the innovator’s DNA speaks deeply about the genesis of ideas with impact. Now at the project’s end, it’s rewarding to reflect on the ideas and actions of others that have shaped my innovation journey. Let’s start with parents.

My father was a master at many things, ranging from the repair and maintenance of anything mechanical to playing the clarinet, saxophone, and bass with such intensity and mastery that his feet often tapped out the beat in his sleep. My mother was equally adept at making music with the flute and piano, but more important, she always paid attention to what wasn’t being said when others spoke. Her inquisitive ears and eyes reflected a heart in search of, and then in service of, hidden needs. Thank you, Mom and Dad, for constantly questioning the world (albeit from different angles) and passing that legacy on to your children.

Shifting from home to school, one teacher stands out above all in terms of unbridled curiosity—J. Bonner Ritchie. I worked with him intensely during my master’s program, where he single-handedly rewrote the maps in my mind by constantly confronting my worldviews. Put simply, Bonner personified the innovator’s DNA long before we ever put these ideas onto paper. His unsettling questions, uncanny observations, and unusual dexterity with metaphor lifted my own sense of inquiry to an entirely different level. For that gift, Professor Bonner, thank you.

After finishing my PhD, I started a twenty-year search to understand what makes great global leaders great. That search, however, was certainly not a solo effort. Many colleagues in the academic world and executives in the business world played an important role in the hunt. In particular, Stewart Black, as well as Mark Mendenhall, Allen Morrison, and Gary Oddou, demonstrated unbridled inquisitiveness in our work (and friendships)—just as we had discovered global leaders doing in theirs. To each I give heartfelt thanks, professionally and personally.

During the 1990s and early 2000s, I experienced a perfect incubator at BYU for uncovering some of the early innovator’s DNA ideas—especially around questioning and curiosity. These inklings took shape and took hold in discussions with colleagues across the campus, especially Gary Cornia, Matt Holland, Curtis LeBaron, Lee Perry, Jerry Sanders, Michael Thompson, Greg Stewart, Mark Widmer, Dave Whetten, and Alan Wilkins, along with a cadre of exceptional research assistants including Cyndi Barrus, Chris Bingham, Bruce Cardon, Jared Christensen, Ben Foulk, Melissa Humes Campbell, Spencer Harrison, Mark Hamberlin, Julie Hite, Marcie Holloman, Rob Jensen, Jayne Pauga, Alex Romney, Laura Stanworth, and Spencer Wheelwright. On the administrative side, Holly Jenkins always excelled at supporting this work and was a joyous breath of fresh air when things seemed deceptively heavy.

Crossing the Atlantic to teach at the London Business School and then INSEAD shifted my role in the innovator’s DNA project onto a truly global trajectory. INSEAD’s tagline, ”The Business School for the World,” is much more than marketing hype. Colleagues, administrative support, and executive education participants come from every corner of the earth. Numerous innovation and entrepreneurship-focused colleagues from each campus (Fontainebleau, Singapore, and Abu Dhabi), including Phil Anderson, Henrik Bresman, Steve Chick, Yves Doz, Soumitra Dutta, Charlie Galunic, Morten Hansen, Mark Hunter, Quy Huy, Roger Lehman, Will Maddux, Steve Mezias, Jürgen Mihm, Mike Pich, Subi Rangan, Gordon Redding, Loïc Sadoulet, Filipe Santos, Manuel Sosa, James Teboul, Ludo Van der Heyden, Hans Wahl, and Luk Van Wassenhove have been exceptional at nurturing insight-laden conversations. Administrators in the dean’s office—Frank Brown, Anil Gaba, Dipak Jain, and Peter Zemsky—and in the organizational behavior area—Paul Evans, Martin Gargiulo, and Herminia Ibarra—have been equally generous in their support of the innovator’s DNA research. In addition, several INSEAD research grants have been pivotal in moving the research along at critical stages, and coaches from the INSEAD Global Leadership Center have debriefed numerous Innovator’s DNA 360 Assessments with consistent professionalism. Other INSEAD support staff have been truly helpful to the project, while personal assistants Jocelyn Bull, Melanie Camenzind, and Sumy Manoj have played a key role in keeping my work (and often my life) on track over the years. Finally, many thanks to at least a couple thousand INSEAD executive education participants (executives, entrepreneurs, and social entrepreneurs) who contributed key insights about the innovator’s DNA over the years and provided reams of critical research data.

In the business, government, and social enterprise world, many executives were particularly generous with their time and talents related to nurturing my evolving insights on innovation. Stefan Bauer at Eli Lilly has been a dedicated collaborator and constant source of wisdom and insight when it comes to understanding what innovation is and how to make it happen. His ideas and his life have helped transform my own. Similarly, Schon Beechler, an academic, consultant, and executive coach, has done the same while working with me on numerous innovation-centered projects, ranging from recent professional development workshops on questioning at the Academy of Management to ongoing research with Teach for America about its teachers’ innovation skills. Others include David Breashears (filmmaker, photographer, adventurer); Larry Kacher at ADIA; Fadi Ghandour at Aramex; Edward Dolman, Steven Murphy, Lisa King, Karen Deakin, Gillian Holden, and Naomi Graham at Christie’s International; Ahmet Bozer and Stevens J. Sainte-Rose at Coca-Cola; Andreas Heinecke, Orna Cohen, and Meena Vaidyanathan at Dialogue in the Dark; Mark Ruiz at Hapinoy; Pat Stocker at Marriott; David Daines and Denice Jones at Nu Skin; and Dave Ulrich, Wayne Brockbank, and Norm Smallwood at RBL (Results-Based Leadership).

Now I give deep thanks to my incredible coauthors, Jeff and Clay, for their contributions to this book and to my life. When Jeff joined BYU, he brought along his father’s “institution builder” mentality. Jeff not only worked tirelessly to support colleagues’ creative efforts in the strategy group; he reached beyond the strategy world to collaborate with me on an experimental MBA class, Creative Strategic Thinking. We hoped to merge a strategic perspective on how companies innovate with a psychological perspective on how individuals innovate. This merger created a perspective-changing classroom experience that continues on, with Jeff at the helm. The unexpected side benefit of that course was an increasing level of collaboration around where innovative ideas come from and how they successfully move forward. Our collaboration has been powerful, both professionally and personally. Jeff’s capacity to craft clear ideas and to exert discipline onto a project when it might otherwise drift is exceptional. These gifts proved invaluable during a decade that rocked the Gregersen family in many unexpected and difficult ways. Through it all, Jeff not only kept the project on track, but even more important, he provided steady personal support in the midst of difficult life challenges. I will always be grateful to him for his professional excellence and his personal friendship.

Almost ten years ago I first met Clay Christensen. I still remember the conversation as though it were yesterday. We talked in depth about the transforming power of questions in our lives, at home and at work. It was a dialogue steeped with insight and a bit of a precursor to the disruptive questions—in a good way—that Clay would come to pose throughout the project. However, little did any of us know that Clay (and his family) would tackle a series of serious health challenges in the coming years: his heart attack, then cancer, and then a stroke. Each took a heavy toll on Clay’s health, and with each he faithfully clawed his way back to well-being. Through it all, I stand amazed at his capacity to continue taking on work and to do so with his characteristic kindness. When I discussed innovator’s DNA ideas with Clay—whether he was in good health or fighting to recover—he more often than not would reset a theoretical framework for the book or a chapter that almost always made it better. His passion for theory and his capacity for building good theory left indelible marks on the innovator’s DNA. No wonder he’s the author of disruptive innovation. Most of all, I express gratitude to Clay that during his own physical challenges he still found the time to supply energy-giving support and insight into my own family’s ups and downs.

Finally, my gratitude comes full circle back to home. Our grandchildren Elizabeth, Madysen, Kash, Brookelynn, and Stella endlessly surprise me with innocent nuggets of insight about the subtle and often unseen nuances of life. Our children Kancie, Matt (and Emily), Emilee (and Wes), Ryan, Kourtnie, Amber, Jordon, and Brooke continue to roam the world (literally and symbolically) in pursuit of ideals and actions that make a difference. Collectively and individually, their resilience through difficult times inspires and encourages my own hope in a brighter future—and with good reason. Almost ten years ago my wife, Ann, bravely took on the frightening challenges of breast cancer. Unfortunately, two years later, physicians acting on automatic pilot completely misdiagnosed the rapid return of her cancer and, as a result, she passed away suddenly and perhaps unnecessarily (raising profound questions for which there will likely not be clear answers in this life). Out of that tragedy, though, another miracle walked into my life: Suzi, who grabbed my hand and heart to start a global journey that neither of us expected. We married and later left the United States to experience more cultures and people than I ever thought the world could dish up. Living and traveling with Suzi always includes unplanned excursions that create wonder, awe, and, at the core, a restoration of the heart. On those journeys it’s inspiring to watch her completely engaged with sketching and painting her keen observations of the world. Her counterintuitive take on life and her deeply intuitive sense of direction are solid anchors in my sometimes topsy-turvy world. Indeed, “forever and always” have taken on even deeper meaning as we face the joys and sorrows of earthly experience (including Suzi’s own experience with breast cancer). What a gift it is to be married to your best friend. Nothing better—especially when so much time and energy went into writing this book. So thank you, Suzi, for joining me on the journey and infusing it with such joy. I have never seen blue like that before.

From Clayton M. Christensen

I feel the same sense of gratitude to the many individuals Jeff and Hal have already mentioned. I add to these my wife Christine, who takes over most things when writing a book takes over my life.

In addition I wish to thank the hundreds and hundreds of managers—some senior executives, but most in the middle ranks, who also taught us profound lessons about how to be innovators—because they have repeatedly failed at it. Few of these managers will find their names in this book despite the fact that they shaped our thinking profoundly. But I hope that they hear their voices within its pages—not attributed, unfortunately, because there literally are too many to mention. Great theories only emerge from work in which researchers repeatedly try to find anomalies that the theory can’t explain—which is why I am so thankful for those who were willing to explain to us why things don’t always work as expected.

I am grateful for the opportunity Jeff and Hal gave me to work on their team. Hal taught me the value of asking the right questions. Jeff taught me how to get the right answers. My role on our team was to stand in the coach’s box by third base. I would wave Hal and Jeff on to home plate, chapter after chapter. I hope that we can play again.

About the Authors

Jeff Dyer is the Horace Beesley Professor of Strategy at the Marriott School, Brigham Young University, and adjunct professor of strategy at the University of Pennsylvania’s Wharton School. Dyer holds a PhD in Management from UCLA. He is the only strategy scholar in the world to have published five times in both Strategic Management Journal and Harvard Business Review. The impact of his work is evidenced by the fact that he was recognized by Essential Science Indicators as the fourth most cited management scholar and seventeenth most cited overall scholar (1996–2006) in the combined fields of management, finance, marketing, operations, and economics. His Oxford book, Collaborative Advantage, was awarded the Shingo Research and Professional Publication Award.

Dyer, a former Bain & Company manager, regularly gives speeches, consults, and conducts training programs in the areas of innovation and strategy. His past clients include Baxter International, Boeing, Ford, Kraft, General Electric, Johnson & Johnson, and Medtronic.

Hal Gregersen is a Professor of Leadership at INSEAD, where he pursues his vocation of executive teaching, coaching, and consulting by researching how leaders discover new ideas, develop the capacity to realize those ideas, and deliver high-impact results. He holds a PhD from the University of California, Irvine. Before joining INSEAD, he taught at the London Business School, Dartmouth’s Tuck School of Business, and Brigham Young University. He also served as a Fulbright Fellow at the Turku School of Economics in Finland.

Gregersen has coauthored many books, including It Starts with One: Changing Individuals Changes Organizations, and has published over fifty scholarly articles. Putting this research into practice, he consults with senior teams, conducts workshops, and delivers keynote speeches with global clients, including Adidas, Aramex, Cemex, Christie’s, Coca-Cola, Daimler, IBM, Intel, LG, Lilly, Marriott, Nokia, Sanofi-Aventis, Twinings, and the World Economic Forum. He also works with social enterprises such as Teach for America, Dialogue in the Dark, and Room 13 to help build the next generation of leaders. Traveling the world, he pursues a lifelong avocation—photography—as part of a global community of social entrepreneurs committed to creating positive change through the arts.

Clayton M. Christensen is the Robert and Jane Cizik Professor of Business Administration at Harvard Business School. He is regarded as one of the world’s foremost experts on the management of innovation and technological change. Christensen holds a BA in economics from Brigham Young University; an MPhil in economics from Oxford University, where he studied as a Rhodes Scholar; and MBA and DBA degrees from Harvard Business School, where he graduated with highest honors as a George F. Baker Scholar. His publications on the management of technological innovation have received numerous academic awards, including the McKinsey Award and the Global Business Book Award. One of his most recent articles, “How to Measure Your Life,” published in the Harvard Business Review, won the 2010 McKinsey Award. In addition to his academic pursuits, Christensen is the founder of three successful companies: CPS Technologies, Innosight LLC, and Rose Park Advisors. During the administration of President Ronald Reagan, he served as a White House Fellow.