Good Strategy Bad Strategy: The Difference and Why It Matters

by Richard P. Rumelt

When looking at costs, include the buyer’s costs of searching for the product, evaluating it, traveling to buy it or waiting for it to arrive, switching to it, i...

The other way to grab the high ground—the way that is my focus here—is to exploit a wave of change. Such waves of change are largely exogenous—they are mostly beyond the control of any one organization. No one person or organization creates these changes. They are the net result of a myriad of shifts and advances in technology, cost, competition, politics, and buyer perceptions. Important waves of change are like an earthquake, creating new high ground and leveling what had been high ground. Such changes can upset the existing structures of competitive positions, erasing old advantages and enabling new ones. They can unleash forces that may strengthen or radically weaken existing leaders. They can enable wholly new strategies. An exogenous wave of change is like the wind in a racing boat’s sails. It provides raw, sometimes turbulent, power. A leader’s job is to provide the insight, skill, and inventiveness that can harness that power to a purpose. You exploit a wave of change by understanding the likely evolution of the landscape and then channeling resources and innovation toward positions that will become high ground—become valuable and defensible—as the dynamics play out.

Modern patterns of advertising, retailing, and consumer branding were developed—hundreds of famous brands, such as Kellogg’s, Hershey’s, Kodak, Coca-Cola, General Electric, Ford, and Hunt’s, date from this era. Most of the foundations of what we now see as the “modern world” were put in place, and great still-standing industrial empires were established. All of this took place in the fifty years between 1875 and 1925. Now, look at another, more modern, period of fifty years. Since I was born in 1942, television has reshaped American culture, jet air travel has opened the world to ordinary people, the falling costs of long-distance transport have generated a rising tide of global trade, retail stores the size of football fields now dot the landscape, computers and cell phones are ubiquitous, and the Internet has made it possible to work, seek out entertainment, and shop without leaving home. Millions can instantly tweet about their evanescent likes and dislikes. Yet, all in all, the last fifty years’ changes have had a smaller impact on everyday life and the conduct of business than did the momentous changes that occurred from 1875 to 1925. Historical perspective helps you make judgments about importance and significance.

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For instance, look at the amazing success of Cisco Systems. It sits right on the interface between telecommunications and computing—a position that everyone thought would be the big battleground between AT&T and IBM. And yet, instead of a battle of titans we have this upstart grabbing the business. “As you said, the critical barrier to becoming a major player in telecommunications equipment and computing has been scale,” I continue. “Yet, Cisco Systems, started by two university staff members, has broken right through the scale ‘barrier.’ It has grabbed the inter-networking equipment market right out from under the nose of giants like IBM, AT&T, Alcatel, NEC, and Siemens. And Matra. How has that happened?”

Jean-Bernard Lévy shakes his head. He has a different slant on the issue. “We have had Matra engineers working on inter-networking equipment. The basic principles are well understood. Yet we cannot seem to replicate the performance of Cisco’s multi-protocol network routers.” “Are there key patents?” I ask. “There are patents, but they aren’t the crucial thing,” he replies. “The heart of the Cisco router is firmware—software burned into read-only memory or implemented in programmable arrays. Cisco’s product embodies, perhaps, one hundred thousand lines of code that is very skillfully written. It was created by a very small team—maybe two to five people. That chunk of very clever code gives the product its edge.”

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A router, I knew, was really just a small computer—it used microprocessors, memory, and input-output ports to manage the flow of data over a digital network. Its performance had little to do with the specific microprocessors, memory, and logic chips inside it. After all, everyone in the industry had access to similar chips. The part of the Cisco router that is so hard to duplicate was the software. Well … no, it was the skill embodied in the software that was so hard to duplicate.

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DISCERNING THE FUNDAMENTALS The work of discerning whether there are important changes afoot involves getting into the gritty details. To make good bets on how a wave of change will play out you must acquire enough expertise to question the experts. As changes begin to occur, the air will be full of comments about what is happening, but you must be able to dig beneath that surface and discover the fundamental forces at work. Leaders who stay “above the details” may do well in stable times, but riding a wave of change requires an intimate feel for its origins and dynamics.

It seems obvious in hindsight. Both the rise of software’s importance and the computer industry’s deconstruction had a common cause: the microprocessor. Yet these connections were far from obvious in the beginning. Everyone in high tech could see the microprocessor, but understanding its implications was a much more difficult proposition. Let me share with you a personal view of some of the steps along that path.

Software’s Advantage How had software become such a sharp source of advantage? The answer is that millions of microprocessors, in everything from PCs to thermostats, bread machines to cruise missiles, meant that their programming determined the performance of these devices.

Design always involves a certain amount of trial and error, and hardware trials and errors are much more costly. If a hardware design doesn’t work correctly, it can mean months of expensive redesign. If software doesn’t work, a software engineer fixes the problem by typing new instructions into a file, recompiling, and trying again in a few minutes or a few days. And software can be quickly fixed and upgraded even after the product has shipped. Thus, software’s advantage comes from the rapidity of the software development cycle—the process of moving from concept to prototype and the process of finding and correcting errors. If engineers never made mistakes, the costs of achieving a complex design in hardware and software might be comparable. But given that they do make mistakes, software became the much-preferred medium (unless the cutting-edge speed of pure hardware was required).

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Intel made processors, other firms made memory, others made hard drives, Microsoft made systems software, and so on. Computers were assembled by mixing and matching parts from competing manufacturers. Grove was dead-on in understanding that “not only had the basis of computing changed, the basis of competition had changed too.”2 Still, as a strategist, I wanted to know more. Why had the computer industry deconstructed itself and become horizontal? Andy Grove wrote, “Even in retrospect, I can’t put my finger on exactly where the inflection point took place in the computer industry. Was it in the early eighties, when PCs started to emerge? Was it in the second half of the decade, when networks based on PC technology started to grow in number? It’s hard to say.”3 I was puzzled over the cause of the computer industry’s deconstruction. Then, about a year later, the reason snapped into focus. I was interviewing technical managers at a client firm and one said that he had formerly been a systems engineer at IBM. He then explained that he had lost that job because modern computers didn’t need much systems engineering. “Why not?” I asked without thinking. “Because now the individual components are all smart,” he answered. Then I saw it.

The modularization of the computer industry came about as each major component was able to contain its own microprocessor—each part became “smart.”

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Smart components operating within a de facto standard operating system meant that the job of systems integration became almost trivially simple. The skills at systems integration that IBM and DEC had built up over decades were no longer needed. That was why my engineer-informant had lost his job. With the glue of proprietary systems engineering no longer so important, the industry deconstructed itself. Modules did not have to be custom designed to work with every other part. To get a working system, customers did not have to buy everything from a single supplier. Specialist firms began to appear that made and sold only memory. Others made and sold only hard drives or keyboards or displays. Still others made and sold video cards or game controllers or other devices.

Today, there are many academic researchers who look at the computer industry and see a network of relationships, each one a channel whereby one firm coordinates with another. The idea of a network especially enchants modern reductionist sociologists who count connections among people, skipping over the old-fashioned hard-to-quantify questions about content and meaning. However, dwelling on this network of weak relationships confuses the background with the absent foreground. What is actually surprising about the modern computer industry is not the network of relationships but the absence of the massively integrated firm doing all the systems engineering—all of the coordination—internally. The current web of “relationships” is the ghostly remnant of the old IBM’s nerve, muscle, and bone.

🙌🏾 these patterns repeat themselves from industry to industry.

The story of how Cisco Systems came into being and how it came to beat the giants vividly demonstrates the power of using waves of change to advantage. The particular waves Cisco used were the rise of software as a critical skill, the growth in corporate data networking, the shift to IP networks, and the explosion of the public Internet.

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Working with industry-wide or economy-wide change is even more advanced than particle physics—understanding and predicting patterns of these dynamics is difficult and chancy. Fortunately, a leader does not need to get it totally right—the organization’s strategy merely has to be more right than those of its rivals. If you can peer into the fog of change and see 10 percent more clearly than others see, then you may gain an edge.

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To aid my own vision into the fog of change I use a number of mental guideposts. Each guidepost is an observation or way of thinking that seems to warrant attention.

Guidepost 1—Rising Fixed Costs The simplest form of transition is triggered by substantial increases in fixed costs, especially product development costs. This increase may force the industry to consolidate because only the largest competitors can cover these fixed charges.

Guidepost 2—Deregulation Many major transitions are triggered by major changes in government policy, especially deregulation. In the past thirty years, the federal government has dramatically changed the rules it imposes on the aviation, finance, banking, cable television, trucking, and telecommunications industries. In each case, the competitive terrain shifted dramatically.

When price competition took hold, these subsidies diminished fairly quickly, but the newly deregulated players chased what used to be the more profitable segments long after the differential vanished. This happened because of the inertia in corporate routines and mental maps of the terrain, and because of poor cost data. In fact, highly regulated companies do not know their own costs—they will have developed complex systems to justify their costs and prices, systems that hide their real costs even from themselves. It takes years for a formerly regulated company, or a former monopolist, to wring excess staff expense and other costs out of its system and to stop its accountants from making arbitrary allocations of overhead expenses to activities and products. In the meantime, these mental and accounting biases mean that such companies can be expected to wind down some product lines that are actually profitable and continue to invest in some products and activities that offer no real returns.

Guidepost 3—Predictable Biases In seeing what is happening during a change it is helpful to understand that you will be surrounded by predictable biases in forecasting. For instance, people rarely predict that a business or economic trend will peak and then decline. If sales of a product are growing rapidly, the forecast will be for continued growth, with the rate of growth gradually declining to “normal” levels. Such a prediction may be valid for a frequently purchased product, but it can be far off for a durable good.

Predicting the existence of such peaks is not difficult, although the timing cannot be pinned down until the growth rate begins to slow. The logic of the situation is counterintuitive to many people—the faster the uptake of a durable product, the sooner the market will be saturated.

Along the same lines, in 1998 many pundits were predicting the emergence of global megacarriers that would dominate world communications. Such companies, foreshadowed by the Concert Communications Services joint venture between AT&T and British Telecom, would offer global seamless carriage of data over complex managed intelligent networks. Of course, it turned out that there is no more reason for one company to own networks all over the world than there is for UPS to own all the roads on which its trucks travel.