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Discuss with your colleagues your assessment and the implications of this case study from the Harvard Business Review as it relates to the issue of Management Research.Develop and post your proposed guidelines or how and when research should be used by management. whyhardnosedexecutives.pdf Unformatted Attachment Preview www.hbr.org Managers often make significant business decisions based on little more than convincing book jacket blurbs. They should hold themselves—and the experts—to a higher standard. Why Hard-Nosed Executives Should Care About Management Theory by Clayton M. Christensen and Michael E. Raynor Reprint R0309D Managers often make significant business decisions based on little more than convincing book jacket blurbs. They should hold themselves—and the experts—to a higher standard. Why Hard-Nosed Executives Should Care About Management Theory COPYRIGHT © 2003 HARVARD BUSINESS SCHOOL PUBLISHING CORPORATION. ALL RIGHTS RESERVED. by Clayton M. Christensen and Michael E. Raynor Imagine going to your doctor because you’re not feeling well. Before you’ve had a chance to describe your symptoms, the doctor writes out a prescription and says, “Take two of these three times a day, and call me next week.” “But—I haven’t told you what’s wrong,” you say. “How do I know this will help me?” “Why wouldn’t it?” says the doctor. “It worked for my last two patients.” No competent doctors would ever practice medicine like this, nor would any sane patient accept it if they did. Yet professors and consultants routinely prescribe such generic advice, and managers routinely accept such therapy, in the naive belief that if a particular course of action helped other companies to succeed, it ought to help theirs, too. Consider telecommunications equipment provider Lucent Technologies. In the late 1990s, the company’s three operating divisions were reorganized into 11 “hot businesses.” The idea was that each business would be run largely independently, as if it were an internal entrepreneurial start-up. Senior executives pro- harvard business review • september 2003 claimed that this approach would vault the company to the next level of growth and profitability by pushing decision making down the hierarchy and closer to the marketplace, thereby enabling faster, better-focused innovation. Their belief was very much in fashion; decentralization and autonomy appeared to have helped other large companies. And the startups that seemed to be doing so well at the time were all small, autonomous, and close to their markets. Surely what was good for them would be good for Lucent. It turned out that it wasn’t. If anything, the reorganization seemed to make Lucent slower and less flexible in responding to its customers’ needs. Rather than saving costs, it added a whole new layer of costs. How could this happen? How could a formula that helped other companies become leaner, faster, and more responsive have caused the opposite at Lucent? It happened because the management team of the day and those who advised it acted like the patient and the physician in our opening vi- page 1 of 9 Why Hard-Nosed Executives Should Care About Management Theory Clayton M. Christensen is the Robert and Jane Cizik Professor of Business Administration at Harvard Business School in Boston. Michael E. Raynor is a director with Deloitte Research and a professor at the Richard Ivey School of Business in London, Ontario, Canada. This article elaborates on a central theme of their forthcoming book, The Innovator’s Solution (Harvard Business School Press, 2003). gnette. The remedy they used—forming small, product-focused, close-to-the-customer business units to make their company more innovative and flexible—actually does work, when business units are selling modular, self-contained products. Lucent’s leading customers operated massive telephone networks. They were buying not plug-and-play products but, rather, complicated system solutions whose components had to be knit together in an intricate way to ensure that they worked correctly and reliably. Such systems are best designed, sold, and serviced by employees who are not hindered from coordinating their interdependent interactions by being separated into unconnected units. Lucent’s managers used a theory that wasn’t appropriate to their circumstance—with disastrous results. Theory, you say? Theory often gets a bum rap among managers because it’s associated with the word “theoretical,” which connotes “impractical.” But it shouldn’t. A theory is a statement predicting which actions will lead to what results and why. Every action that managers take, and every plan they formulate, is based on some theory in the back of their minds that makes them expect the actions they contemplate will lead to the results they envision. But just like Monsieur Jourdain in Molière’s Le Bourgeois Gentilhomme, who didn’t realize he had been speaking prose all his life, most managers don’t realize that they are voracious users of theory. Good theories are valuable in at least two ways. First, they help us make predictions. Gravity, for example, is a theory. As a statement of cause and effect, it allows us to predict that if we step off a cliff we will fall, without requiring that we actually try it to see what happens. Indeed, because reliable data are available solely about the past, using solid theories of causality is the only way managers can look into the future with any degree of confidence. Second, sound theories help us interpret the present, to understand what is happening and why. Theories help us sort the signals that portend important changes in the future from the noise that has no strategic meaning. Establishing the central role that theory plays in managerial decision making is the first of three related objectives we hope to accomplish in this article. We will also describe how good theories are developed and give an idea of how a theory can improve over time. And, fi- harvard business review • september 2003 nally, we’d like to help managers develop a sense, when they read an article or a book, for what theories they can and cannot trust. Our overarching goal is to help managers become intelligent consumers of managerial theory so that the best work coming out of universities and consulting firms is put to good use—and the less thoughtful, less rigorous work doesn’t do too much harm. Where Theory Comes From The construction of a solid theory proceeds in three stages. It begins with a description of some phenomenon we wish to understand. In physics, the phenomenon might be the behavior of high-energy particles; in business, it might be innovations that succeed or fail in the marketplace. In the exhibit at right, this stage is depicted as a broad foundation. That’s because unless the phenomenon is carefully observed and described in its breadth and complexity, good theory cannot be built. Researchers surely head down the road to bad theory when they impatiently observe a few successful companies, identify some practices or characteristics that these companies seem to have in common, and then conclude that they have seen enough to write an article or book about how all companies can succeed. Such articles might suggest the following arguments, for example: • Because Europe’s wireless telephone industry was so successful after it organized around a single GSM standard, the wireless industry in the United States would have seen higher usage rates sooner if it, too, had agreed on a standard before it got going. • If you adopt this set of best practices for partnering with best-of-breed suppliers, your company will succeed as these companies did. Such studies are dangerous exactly because they would have us believe that because a certain medicine has helped some companies, it will help all companies. To improve understanding beyond this stage, researchers need to move to the second step: classifying aspects of the phenomenon into categories. Medical researchers sort diabetes into adult onset versus juvenile onset, for example. And management researchers sort diversification strategies into vertical versus horizontal types. This sorting allows researchers to organize complex and confusing phenomena in ways that highlight their most meaningful differences. It is then possible page 2 of 9 Why Hard-Nosed Executives Should Care About Management Theory Prediction Formation of a theory: A statement of what causes what and why Confirmation Categorization Anomaly Observation and description of the phenomenon harvard business review • september 2003 Copyright © 2003 Harvard Business School Publishing Corporation. All rights reserved. to tackle stage three, which is to formulate a hypothesis of what causes the phenomenon to happen and why. And that’s a theory. How do researchers improve this preliminary theory, or hypothesis? As the downward loop in the diagram below suggests, the process is iterative. Researchers use their theory to predict what they will see when they observe further examples of the phenomenon in the various categories they had defined in the second step. If the theory accurately predicts what they are observing, they can use it with increasing confidence to make predictions in similar circumstances.1 In their further observations, however, researchers often see something the theory cannot explain or predict, an anomaly that suggests something else is going on. They must then cycle back to the categorization stage and add or eliminate categories—or, sometimes, rethink them entirely. The researchers then build an improved theory upon the new categorization scheme. This new theory still explains the previous observations, but it also explains those that had seemed anomalous. In other words, the theory can now predict more accurately how the phenomenon should work in a wider range of circumstances. To see how a theory has improved, let’s look at the way our understanding of international trade has evolved. It was long thought that countries with cheap, abundant resources would have an advantage competing in industries in which such resources are used as important inputs of production. Nations with inexpensive electric power, for example, would have a comparative advantage in making products that require energy-intensive production methods. Those with cheap labor would excel in labor-intensive products, and so on. This theory prevailed until Michael Porter saw anomalies the theory could not account for. Japan, with no iron ore and little coal, became a successful steel producer. Italy became the world’s dominant producer of ceramic tile, even though its electricity costs were high and it had to import much of the clay. Porter’s theory of competitive clusters grew out of his efforts to account for these anomalies. Clusters, he postulated, lead to intense competition, which leads companies to optimize R&D, production, training, and logistics processes. His insights did not mean that prior notions of advantages based on low-cost resources were wrong, merely that they didn’t adequately predict the outcome in every situation. So, for example, Canada’s large pulp and paper industry can be explained in terms of relatively plentiful trees, and Bangalore’s success in computer programming can be explained in terms of plentiful, low-cost, educated labor. But the competitive advantage that certain industries in Japan, Italy, and similar places have achieved can be explained only in terms of industry clusters. Porter’s refined theory suggests that in one set of circumstances, where some otherwise scarce and valuable resource is relatively abundant, a country can and should exploit this advantage and so prosper. In another set of circumstances, where such resources are not available, policy makers can encourage the development of clusters to build process-based competitive advantages. Governments of nations like Singapore and Ireland have used Porter’s theory to devise cluster-building policies that have led to prosperity in just the way his refined theory predicts. We’ll now take a closer look at three aspects of the theory-building process: the importance of explaining what causes an outcome (instead of just describing attributes empirically associated with that outcome); the process of categorization that enables theorists to move from tentative understanding to reliable predictions; and the importance of studying failures to building good theory. Pinpointing Causation In the early stages of theory building, people typically identify the most visible attributes of the phenomenon in question that appear to be correlated with a particular outcome and use those attributes as the basis for categorization. This is necessarily the starting point of theory building, but it is rarely ever more than an important first step. It takes a while to develop categories that capture a deep understanding of what causes the outcome. Consider the history of people’s attempts to page 3 of 9 Why Hard-Nosed Executives Should Care About Management Theory fly. Early researchers observed strong correlations between being able to fly and having feathers and wings. 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 of flight. When these researchers categorized the world in terms of the most obvious visible attributes of the phenomenon (wings versus no wings, feathers versus no feathers, for example), the best they could do was a statement of correlation—that the possession of those attributes is associated with the ability to fly. Researchers at this stage can at best express their findings in terms of degrees of uncertainty: “Because such a large percentage of those with wings and feathers can fly when they flap (although ostriches, emus, chickens, and kiwis cannot), in all probability I will be able to fly if I fabricate wings with feathers glued on them, strap them to my arms, and flap hard as I jump off this cliff.” Those who use research still in this stage as a guide to action often get into trouble because they confuse the correlation between attributes and outcomes with the underlying causal mechanism. Hence, they do what they think is necessary to succeed, but they fail. A stunning number of articles and books about management similarly confuse the correlation of attributes and outcomes with causality. Ask yourself, for example, if you’ve ever seen studies that: • contrast the success of companies funded by venture capital with those funded by corporate capital (implying that the source of capital funding is a cause of success rather than merely an attribute that can be associated with a company that happens to be successful for some currently unknown reason). • contend that companies run by CEOs who are plain, ordinary people earn returns to shareholders that are superior to those of companies run by flashy CEOs (implying that certain CEO personality attributes cause company performance to improve). • assert that companies that have diversified beyond those SIC codes that define their core businesses return less to their shareholders than firms that kept close to their core (thus harvard business review • september 2003 leaping to the conclusion that the attributes of diversification or centralization cause shareholder value creation). • conclude that 78\% of female home owners between the ages of 25 and 35 prefer this product over that one (thus implying that the attributes of home ownership, age, and gender somehow cause people to prefer a specific product). None of these studies articulates a theory of causation. All of them express a correlation between attributes and outcomes, and that’s generally the best you can do when you don’t understand what causes a given outcome. In the first case, for example, studies have shown that 20\% of start-ups funded by venture capitalists succeed, another 50\% end up among the walking wounded, and the rest fail altogether. Other studies have shown that the success rate of start-ups funded by corporate capital is much, much lower. But from such studies you can’t conclude that your start-up will succeed if it is funded by venture capital. You must first know what it is about venture capital—the mechanism—that contributes to a start-up’s success. In management research, unfortunately, many academics and consultants intentionally remain at this correlation-based stage of theory building in the mistaken belief that they can increase the predictive power of their “theories” by crunching huge databases on powerful computers, producing regression analyses that measure the correlations of attributes and outcomes with ever higher degrees of statistical significance. Managers who attempt to be guided by such research can only hope that they’ll be lucky—that if they acquire the recommended attributes (which on average are associated with success), somehow they too will find themselves similarly blessed with success. The breakthroughs that lead from categorization to an understanding of fundamental causality generally come not from crunching ever more data but from highly detailed field research, when researchers crawl inside companies to observe carefully the causal processes at work. Consider the progress of our understanding of Toyota’s production methods. Initially, observers noticed that the strides Japanese companies were making in manufacturing outpaced those of their counterparts in the United States. The first categorization efforts were di- page 4 of 9 Why Hard-Nosed Executives Should Care About Management Theory Unfortunately, many management researchers are so focused on how companies succeed that they don’t study failure. rected vaguely toward the most obvious attribute—that perhaps there was something in Japanese culture that made the difference. When early researchers visited Toyota plants in Japan to see its production methods (often called “lean manufacturing”), though, they observed more significant attributes of the system—inventories that were kept to a minimum, a plant-scheduling system driven by kanban cards instead of computers, and so on. But unfortunately, they leaped quickly from attributes to conclusions, writing books assuring managers that if they, too, built manufacturing systems with these attributes, they would achieve improvements in cost, quality, and speed comparable to those Toyota enjoys. Many manufacturers tried to make their plants conform to these lean attributes—and while many reaped some improvements, none came close to replicating what Toyota had done. The research of Steven Spear and Kent Bowen has advanced theory in this field from such correlations by suggesting fundamental causes of Toyota’s ability to continually improve quality, speed, and cost. Spear went to work on several Toyota assembly lines for some time. He began to see a pattern in the way people thought when they designed any process— those for training workers, for instance, or installing car seats, or maintaining equipment. From this careful and extensive observation, Spear and Bowen concluded that all processes at Toyota are designed according to four specific rules that create automatic feedback loops, which repeatedly test the effectiveness of each new activity, pointing the way toward continual improvements. (For a detailed account of Spear and Bowen’s theory, see “Decoding the DNA of the Toyota Production System,” HBR September–October 1999.) Using this mechanism, organizations as diverse as hospitals, aluminum smelters, and semiconductor fabricators have begun achieving improvements on a scale similar to Toyota’s, even though their processes often share few visible attributes with Toyota’s system. Moving Toward Predictability Manned flight began to be possible when Daniel Bernoulli’s study of fluid mechanics helped him understand t ... Purchase answer to see full attachment