For the past 20 years, the theory of disruptive innovation has been enormously influential in business circles and a powerful tool for predicting which industry entrants will succeed. Unfortunately, the theory has also been widely misunderstood, and the "disruptive" label has been applied too carelessly anytime a market newcomer shakes up well-established incumbents. In this article, the architect of disruption theory, Clayton M. Christensen, and his coauthors correct some of the misinformation, describe how the thinking on the subject has evolved, and discuss the utility of the theory. They start by clarifying what classic disruption entails-a small enterprise targeting overlooked customers with a novel but modest offering and gradually moving upmarket to challenge the industry leaders. They point out that Uber, commonly hailed as a disrupter, doesn't actually fit the mold, and they explain that if managers don't understand the nuances of disruption theory or apply its tenets correctly, they may not make the right strategic choices. Common mistakes, the authors say, include failing to view disruption as a gradual process (which may lead incumbents to ignore significant threats) and blindly accepting the "Disrupt or be disrupted" mantra (which may lead incumbents to jeopardize their core business as they try to defend against disruptive competitors). The authors acknowledge that disruption theory has certain limitations. But they are confident that as research continues, the theory's explanatory and predictive powers will only improve.
Much of the strategy and management advice that business leaders turn to is unreliable or impractical, say the authors, because those who would guide us underestimate the power of chance. Raynor and Ahmed undertook a statistical study of 25,000 companies--those that had traded on U.S. stock exchanges at any time from 1966 to 2010. They measured performance according to return on assets--a metric, they reasoned, that reliably reflects managerial efforts rather than simply changes in expectations, which are the primary driver of shareholder returns. Out of that 25,000 they identified 344 companies they deem exceptional: 174 Miracle Workers, whose ROA fell in the top 10% of all companies studied, and 170 Long Runners, whose ROA fell in the top 20% to 40%. For purposes of comparison, they also identified companies that were Average Joes. After repeatedly trying and failing to isolate measurable behaviors that were consistently relevant to success, the authors shifted their emphasis away from what these companies did to hypotheses about how they thought. They realized that the choices these companies had made were consistent with three seemingly elementary rules: (1) Better before cheaper--in other words, compete on differentiators other than price. (2) Revenue before cost--that is, prioritize increasing revenue over reducing costs. (3) There are no other rules--so change anything you must to follow Rules 1 and 2.
Studies that examine high-performing companies to unearth the secrets of their success have a critical flaw: Very few of those companies are truly remarkable. Data analysis reveals that most owe their success to luck, not smart practices. That puts the prescriptions of success studies in a whole new light.
Voice over Internet protocol (VoIP) is beginning to disrupt plain old telephone service (POTS). Ron Close has been offered the job of heading Bell Canada's nascent VoIP business. Bell is Canada's largest telco and supplier of POTS. The case provides a platform for discussing a disruptive innovation (VoIP) and its implications for an incumbent player. Ron Close explains how Bell addressed the technology challenge, and its managerial and organizational consequences in an available video, product 7B06M009.
Theory often gets a bum rap among managers because it's associated with the word "theoretical," which connotes "impractical." But it shouldn't. Because experience is solely about the past, solid theories are the only way managers can plan future actions with any degree of confidence. The key word here is "solid." Gravity is a solid theory. As such, it lets us predict that if we step off a cliff we will fall, without actually having to do so. But business literature is replete with theories that don't seem to work in practice or actually contradict each other. How can a manager tell a good business theory from a bad one? The first step is to understand how good theories are built. They develop in stages: gathering data, organizing it into categories, highlighting significant differences, then making generalizations explaining what causes what, under which circumstances. For instance, professor Ananth Raman and his colleagues collected data showing that bar code-scanning systems generated notoriously inaccurate inventory records. These observations led them to classify the types of errors the scanning systems produced and the types of shops in which those errors most often occurred. Recently, some of Raman's doctoral students worked as clerks to see exactly what kinds of behavior cause the errors. From this foundation, a solid theory predicting under which circumstances bar code systems work and don't work is beginning to emerge. Once we forgo one-size-fits-all explanations and insist that a theory describes the circumstances under which it does and doesn't work, we can bring predictable success to the world of management.
What was it Wayne Gretzky said about why he was so good at hockey? He just skated to where the puck was going next. Executives and investors wish they could do so, too--to sense where profits are going next. Following a six-year study of profitability patterns, the authors have developed a model for doing just that. In the early stages of a product's evolution, companies compete on the basis of performance. And because they can't make substantial improvements in product performance unless the entire value chain is housed under one organizational roof, it works best if companies are vertically integrated. But as the underlying technology improves to meet the needs of most customers, companies begin to compete on the basis of convenience, customization, price, and flexibility. At that point, vertical integration is no longer an advantage--in fact, it quickly becomes a disadvantage. Different links in the industry value chain become modular, and the chain subsequently fragments. In either stage, most profitability goes to the companies that own the interdependent links in the value chain--the places where everyone's still vying to satisfy their customers with ever-better product functionality. Initially, that's the makers of the proprietary products aimed at the end-use consumers. But as those products become standardized, profitability shifts to the makers of components, and as components themselves become standardized, it can shift further back in the value chain. That's predictable, but it causes a problem for incumbents. As their products become commodities and profits decline, pressure from investors to maintain ROA causes them to spin off asset-intensive units that design and manufacture components--the very places where profits are heading.
Conventional wisdom holds that a company's divisions should be given almost total autonomy--especially under conditions of uncertainty--because they are closer to emerging technologies, customers, and competitors than corporate headquarters could ever be. But research from Michael Raynor and Joseph Bower suggests that the corporate office should be more, not less, directive in turbulent markets. Rapid changes in an industry make it difficult to predict where and when synergies among divisions might emerge. With so many possibilities and such uncertainty, companies can't afford to sacrifice their ability to flexibly execute business strategy. Corporate headquarters must play an active role in defining the scope of division-level strategy, the authors say, so that divisions do not act in ways that undermine opportunities to collaborate in the future. Through an examination of four corporations--Sprint, WPP, Teradyne, and Viacom--the authors challenge traditional approaches to diversification in which a company's divisions are either related (they share resources and collaborate) or unrelated (they compete for resources and operate as stand-alone businesses). They argue that companies should adopt a dynamic approach to cooperation among divisions, enabling varying degrees of relatedness between divisions depending on strategic circumstances. The authors offer four tactics to help executives manage divisions dynamically.
From 1992 to 1997, CIBC CEO Al Flood and head of investment banking John Hunkin integrate the struggling investment bank, Wood Gundy, with CIBC's corporate bank. The impact and interaction of organization design, compensation schemes, and communication initiatives are explored.
By 1997 the turnaround of CIBC's troubled investment bank, Wood Gundy, and its integration with corporate banking activities was complete. Marketplace results were encouraging, but scuttled mergers and tumultuous succession issues made the future uncertain.
From 1992 to 1997, CIBC CEO Al Flood and head of investment banking John Hunkin integrate the struggling investment bank Wood Gundy with CIBC's corporate bank. The impact and interaction of organization design, compensation schemes, and communication initiatives are explored. A rewritten version of an earlier case.