Paper 26 - No Plagiarism - URGENT

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Organizational inertia generally falls into one of three categories: the inertia of routine, cultural inertia, and inertia by proxy. Each has di#erent implications for those who wish to reduce inertia or those who seek to gain by attacking a less- responsive rival.

The Inertia of Routine

The heartbeat of any sizable business is the rhythmic pulse of standard procedures for buying, processing, and marketing goods. Its more conscious actions are guided by less rhythmic but still well-marked paths. Even the breathless chase after an important new client, the sizing of a new facility, and the formulation of plans are familiar moves in a game that has been played before. An organization of some size and age rests on layer upon layer of impacted knowledge and experience, encapsulated in routines—the “way things

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are done.” These routines not only limit action to the familiar, they also $lter and shape managers’ perceptions of issues. An organization’s standard routines and methods act to preserve old ways of categorizing and processing information.

The inertia created by standard routines can be revealed by sudden outside shocks: a tripling of the price of oil, the invention of the microprocessor, telecommunications deregulation, and so on. The shock changes the basis of competition in the industry, creating a signi$cant gap between the old routines and the needs of the new regime.

U.S. airline deregulation, inaugurated in 1978, was such a shock. The routines for running airlines and concepts of competition had become set over decades of strong regulation. Deregulation acted to suddenly release many constraints on action, but many of the moves made in the $rst few years were guided by old rules of thumb rather than the realities of the new

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situation. Two years after airline deregulation, I

was asked to help Continental Airlines with some strategy issues, including the purchase of new aircraft. The company had a large "eet of DC-10s, but sought help in thinking through its options in spending an estimated $400 million on new equipment. The CEO, Al Feldman, had just jumped into Continental from the CEO position at Frontier Airlines, where he had been a strong supporter of deregulation.

In the decades of regulation, the government set fares and assigned routes to airlines; competition was more or less limited to image, food, and personal service. The standard unit of production in the airline industry is the available-seat- mile (ASM). Take a seat, lift it to thirty-two thousand feet, and move it one mile and you have produced one ASM. Airline operating costs per ASM fall with the length of a trip because many trip costs are $xed.

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The costs of servicing the aircraft, wear and tear, cleaning, food, and even some crew costs did not depend much on trip length. A 367-mile trip between Los Angeles and Phoenix might cost $0.22 per ASM while a much longer 2,000-mile trip to Detroit might cost only $0.09 per ASM. Congress wanted to promote air travel to small towns, so in the days of regulation the Civil Aeronautics Board (CAB) set fares that were below cost on short routes and forced each airline to "y them. The losses on short routes were covered by the pro$ts on long- haul routes, where the CAB set prices above cost. Of course, the CAB forced each airline to "y a mix of routes.

Working with a small team, I developed a view of the near future of the industry. My analysis was that deregulated fares would shift to more closely parallel costs. Prices and margins on short-haul routes would rise, and they would fall on long-haul routes. The implication was that, with

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deregulation, pro$ts would be made only in two ways: a low-cost operating structure or cleverness in grabbing short-haul routes that did not have enough volume to support vigorous competition. At that time, the dominant feeling in the industry was that low-cost strategies would pull in lots of consumers, but that the business traveler would remain relatively insensitive to price. My thinking was di#erent. Of course business travelers wanted frequent, convenient, comfortable travel, but most business "yers didn’t pay for their travel— their employers did. And employers might be more interested in travel cost than comfort. Business travelers liked comfort, but would their companies pay a premium for it? We thought that falling long-haul prices would make them less willing to do so. I forecast that even as load factors rose, prices and margins would fall.

This point of view directly contradicted the dominant wisdom in the newly

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deregulated industry. Long haul had always been pro$table. Just a few months before, Dick Ferris, United Airlines’ feisty CEO, had given a talk to Wall Street analysts, saying his strategy was to eliminate short feeder routes and “concentrate on the long-haul routes where the bucks are.” He committed United to spending $3 billion to build a new long-haul "eet, centered in Chicago. Brani# International had also reacted to the new era by adding new long-haul routes. I hoped that our analysis would show how Continental could be smarter.

My ideas were not well received by the executive committee. The bottom line, announced from the top, was “You’ve got it all wrong. We have already run a planning model and we know coast-to-coast fares have to rise, not fall. The question is which new equipment we should be buying: Boeing, Airbus, or McDonnell Douglas.”

At moments like this, one is never sure what to think. Perhaps I was missing

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something. What was this “planning model” that was forecasting higher prices on the long hauls? It took a week for me to chase down the model and its forecast. Sure enough, there it was in black and white: current long-haul fares were out of equilibrium and were forecast to rise.

Continental’s “planning model” was a computer program called the Boeing Fleet Planner. The program was provided by Boeing to help airlines make equipment acquisition decisions. Given a route structure and equipment pro$le, it worked out operating costs and spat out predicted $nancial statements. Continental used McDonnell Douglas equipment, but the Fleet Planner program knew the operating characteristics of all major aircraft.

I sat down next to the $nance-o!ce specialist who explained how it worked. To run the program one had to tell it which routes would be "own, project a market share on each, and specify the equipment.

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The program combined this information with operating cost data and computed the cost per ASM on each route. Estimating that 55 percent of seats would be $lled (the load factor), it then added in a 12 percent return on capital and projected a fare. That was the fare that “had to rise, not fall.”

Incredulous, I said, “This is the predicted fare? But it’s just cost plus a markup!”

“We have used this tool for a long time,” the specialist coolly replied. “It has been pretty reliable.”

I was astonished. “What happens to these numbers—where do they go from here?” I asked.

“They go to the CAB, along with a bunch of other stu#, as part of fare planning,” he said.

Continental’s system for projecting airfares for the new era of competition was the same one it had used all during the regulation era to suggest and justify fares in negotiations with the CAB. This projection

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had nothing to do with competition, supply, demand, capacity, or market forces. It took costs and added a markup. It “predicted” what the CAB would do in setting fares. The Boeing Planner was a $ne tool, but it wasn’t a fare predictor unless you had a regulator guaranteeing that you would make a 12 percent return "ying half-full airplanes.

Despite deregulation, the CEO’s animated speeches on how the company had a new, competitive spirit, and an aggressive posture assumed by the senior management group, the company’s planning, pricing, and marketing routines were unchanged from the era of regulation. The new competitive spirit was pure aggressiveness, unalloyed by craft.

It took another month to uncover the dead, yet controlling, hand of another regulation-era rule of thumb. By setting fares to allow the airlines a “fair” 12 percent return on capital, where capital was

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equity plus debt, the CAB had, in e#ect, guaranteed that an airline’s debt interest would always be paid. All a $rm had to do was not deviate too much from the overall norm. Banks had a similar rule about airline debt being a good credit risk. This had a big in"uence on the attitude toward new equipment. When the airlines moved from props to jets, and when they again moved from narrow to wide-body aircraft, billions of dollars were spent on new aircraft, adding tremendous chunks of new capacity. In a normal industry, a surge of new equipment placed in service by all competitors would have forced a crash in prices and major losses. And, in a normal industry, competitors cannot all add capacity at the same time unless there is a remarkable surge in demand. But in the airline business, the CAB lent a hand, propping up prices—and even increasing them—in these periods of overcapacity. Reequipment by the regulated airlines had

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not been a strategic problem. A simple rule su!ced: reequip when everyone else does.

Deregulation meant that the old rules of thumb were obsolete. Go for the long-haul routes, fares will cover total costs, and reequip when everyone else does were not going to work in the future. From 1979 to 1983, the majors kept enacting the old rules. In 1981, United, American, and Eastern together lost $240 million, while all of the shorter-haul carriers (Delta, Frontier, USAir, and so on) made a pro$t. Over the next two decades, only Southwest would be consistently pro$table. In 1984 and ’85, fares on long- haul routes fell 27 percent. On short-haul low-volume routes, fares rose 40 percent, more than covering costs. Our team’s analysis was essentially right. Not rocket science, but counter to the long-standing rules of thumb.

Being right doesn’t always help the decision maker. In Continental’s case, a nasty strike dragged management’s

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attention away from market dynamics. The plan to buy new aircraft was scuttled when fares did not rise and losses mounted. Then, sensing the $rm’s plight, entrepreneur Frank Lorenzo of Texas Air initiated a hostile takeover of the company. Top management couldn’t believe that tiny Texas Air could take over a major airline— it wouldn’t be until the late 1980s that U.S. corporate managements got used to this idea. Frustrated, angry, and su#ering a secret deep depression, Continental CEO Al Feldman shot himself at his desk in August 1981.

In 1982, Frank Lorenzo merged Continental and Texas Air in a reverse takeover. A year later the new company was bankrupt, in part a tactic to separate the equipment from the old union contracts. A new Continental Airlines emerged from bankruptcy in 1986 and soon consolidated with Frontier, People Express, and New York Air. Frank Lorenzo sold his

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interest in 1990.

Inertia due to obsolete or inappropriate routines can be $xed. The barriers are the perceptions of top management. If senior leaders become convinced that new routines are essential, change can be quick. The standard instruments are hiring managers from $rms using better methods, acquiring a $rm with superior methods, using consultants, or simply redesigning the $rm’s routines. In any of these cases, it will probably be necessary to replace people who have invested many years developing and using the obsolete methods as well as to reorganize business units around new patterns of information "ow.

The Inertia of Culture

In 1984, I had a close-up look at one of the epicenters of corporate cultural inertia in that era—AT&T.* As the corporate inventor

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of Unix, which today underlies the open- source Linux and Apple’s Mac OS X operating systems, AT&T should have been a major player, especially with regard to computer communications. Retained as a strategy consultant, I worked with the company on new products and strategies in computing and communications.

The strategic plans I helped formulate at AT&T included developing and bonding key software packages with the AT&T brand name.1 In addition, we planned on making these packages and add-on modules available for sale electronically, over telephone lines, with AT&T “communicating computers.”* Finally, we were interested in developing a simpler version of AT&T’s Unix for the PC platform, one that would begin to support a graphical user interface.

As I developed working relationships at AT&T, some high-level managers let me in on what they saw as an embarrassing

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secret. AT&T wasn’t competent at product development. Yes, the company was the proud owner of Bell Labs; the inventor of the transistor, the C programming language, and Unix; and was a marvelous place that probed deeply into the fundamentals of nature. But there was no competence within AT&T at making working consumer products. One story that was told concerned cellular phones. Starting in 1947, Bell Labs developed the basic ideas underlying mobile telephony. However, the $rst market test, in 1977, had to be undertaken using Motorola’s equipment.

Another story concerned videotex. In 1983, AT&T had a joint venture with the Knight Ridder newspaper chain to test a videotex system (Viewtron). The system would provide news, weather, airline schedules, sports scores, and community information as text on a home TV screen. But Bell Labs had not been able to deliver

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software capable of handling even the light demands of the test market. The software to run the system was instead developed by a small company (Infomart) working under subcontract to Knight Ridder.

My personal lesson in this regard came with respect to the “communicating computer,” a PC tied by a modem to network services. (This was a decade before the Internet came into widespread public use.) I wanted to demonstrate to senior management the potential for selling software via computer. The metaphor was an elevator: $rst "oor games, second "oor utilities, third "oor calculations, and so on. We talked with AT&T Bell Labs about a simple PC-based program to demonstrate this interface. They quoted three million dollars and two years. I suggested a simpler approach and was told by a Bell Labs representative “not to interfere with our design prerogatives.” Frustrated, I wrote the straightforward code for the

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demonstration myself in three weeks. The problem at AT&T was not the

competence of individuals but the culture— the work norms and mindsets. Bell Labs did fundamental research, not product development. The reaction to a request for demonstration code was as if Boeing engineers had been asked to design toy airplanes. Just as in a large university, the breakthroughs of a tiny number of very talented individuals had been used to justify a contemplative life for thousands of others. Through the many decades during which AT&T had been a regulated monopoly, this culture grew and "ourished. Now, with deregulation, competition, and the soaring opportunities in mass-market computing and data communications, this way of doing things was a huge impediment to action. To make matters even worse, the massive inertia of the system was not being countered. With no real understanding of technology, most

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senior managers at AT&T did not comprehend or appreciate the problem. And those few who did had almost no chance of changing the character of Bell Laboratories, a crown jewel of American R & D, a development center that produced Nobel laureates.

The strategy work I did at AT&T in 1984– 85 was a waste. The hard-won lesson was that a good product-market strategy is useless if important competencies, assumed present, are absent and their development is blocked by long-established culture. The seemingly clever objectives I helped craft were infeasible. It would be at least a decade before AT&T slimmed down and gained enough engineering agility to support work on competitive strategy.

Western Electric and most of AT&T Bell Laboratories were spun o# as Lucent Technologies in 1996. Wall Street loved the new company and drove its price from eight dollars to eighty dollars per share

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before a lack of pro$ts became evident and its price collapsed to below one dollar in 2002. French telecommunications equipment maker Alcatel merged with Lucent in 2006. Since the merger, Alcatel- Lucent’s value has declined by 70 percent, largely due to losses in Lucent’s operations.

We use the word “culture” to mark the elements of social behavior and meaning that are stable and strongly resist change. As a blunt and vivid example, Khmer Rouge leader Pol Pot killed one-$fth of the Cambodian population, executed almost every intellectual, burned almost all books, and outlawed religion, banks, currency, and private property, but still did not much alter Cambodian culture. The cultures of organizations are more lightly held than those of nationality, religion, or ethnicity. Still, it is dangerous to think that organizational culture can be changed quickly or easily.

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The $rst step in breaking organizational culture inertia is simpli$cation. This helps to eliminate the complex routines, processes, and hidden bargains among units that mask waste and ine!ciency. Strip out excess layers of administration and halt nonessential operations—sell them o#, close them down, spin them o#, or outsource the services. Coordinating committees and a myriad of complex initiatives need to be disbanded. The simpler structure will begin to illuminate obsolete units, ine!ciency, and simple bad behavior that was hidden from sight by complex overlays of administration and self-interest.

After the $rst round of simpli$cation, it may be necessary to fragment the operating units. This will be the case when units do not need to work in close coordination— when they are basically separable. Such fragmentation breaks political coalitions, cuts the comfort of cross-subsidies, and

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exposes a larger number of smaller units to leadership’s scrutiny of their operations and performance. After this round of fragmentation, and more simpli$cation, it is necessary to perform a triage. Some units will be closed, some will be repaired, and some will form the nuclei of a new structure. The triage must be based on both performance and culture—you cannot a#ord to have a high-performing unit with a terrible culture infect the others. The “repair” third of the triaged units must then be put through individual transformation and renewal maneuvers.

Changing a unit’s culture means changing its members’ work norms and work-related values. These norms are established, held, and enforced daily by small social groups that take their cue from the group’s high- status member—the alpha. In general, to change the group’s norms, the alpha member must be replaced by someone who expresses di#erent norms and values. All

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this is speeded along if a challenging goal is set. The purpose of the challenge is not performance per se, but building new work habits and routines within the unit.

Once the bulk of operating units are working well, it may then be time to install a new overlay of coordinating mechanisms, reversing some of the fragmentation that was used to break inertia.

Inertia by Proxy

A lack of response is not always an indication of sticky routines or a frozen culture. A business may choose to not respond to change or attack because responding would undermine still-valuable streams of pro$t. Those streams of pro$t persist because of their customers’ inertia— a form of inertia by proxy.

As an example, in 1980 the prime interest rate hit 20 percent. With the then- new freedom to create money market

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customer accounts, how did banks respond? Smaller and newer banks seeking retail growth were happy to o#er this new type of high-interest deposit account. But many older banks with long-established customers did not. If their customers had been perfectly agile, quickly searching for and switching to the highest-interest accounts, they would have had to o#er higher-interest accounts or disappear. But their customers were not this agile.

I was a consultant to the Philadelphia Savings Fund Society (PSFS) at the time and asked about its rate structure on deposits. A vice president tried to $nd the brochure describing the higher-interest money market accounts and then gave up. He said, “Our average depositor is a retired person and not that sophisticated. Those depositor funds make up the last giant pool of 5 percent money left on the planet!” What he meant was that he could loan out his depositors’ money and earn 12 percent

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or more, while paying only 5 percent to the depositors. Sure, some depositors would depart, but most would not and the pro$ts on their inertia were enormous. The important implication for competitors was that, at that moment, a rival could poach customers away from PSFS without triggering a competitive response.

In an example from telecommunications, the regional Bell operating companies varied in the number of business customers they served. With the advent of the Internet, which were the $rst to o#er digital subscriber line services? The telephone companies’ primary data o#ering to business had been T1 lines, priced at about four thousand dollars per month and o#ering 1.5 mbps. In 1998, DSL speeds were about one-third of T1 speeds, but DSL prices were one-thirtieth. That is, a customer could replicate a T1 line with three DSLs for one-tenth the cost. Rather than cannibalize their very pro$table T1

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business, telephone companies serving New York, Chicago, and San Francisco just punted—they didn’t o#er DSL. These telephone companies lost about 10 percent of their corporate data business each year to the new-wave carriers (WorldCom, Intermedia Communications, and dozens of digital competitive local exchange carriers, or CLECs), but the very high pro$ts in the T1 business more than made up for the decline.*

Again, the apparent inertia of the telephone companies was actually inertia by proxy, induced because their customers were so slow to switch suppliers, even in the face of dramatic price di#erences. This inertia by proxy fooled hundreds of companies and investors. The fantastic rate of expansion of the “new network” carriers was taken as evidence of competitive superiority, unleashing a frenzy of investment and stock appreciation. When the telephone companies $nally began to

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respond in 2000, the bubble popped. Once real competition began, it was a rout. Not a single CLEC survived.

Inertia by proxy disappears when the organization decides that adapting to changed circumstances is more important than hanging on to old pro$t streams. This can happen quite suddenly, as it did in telecommunications after 1999. Attackers who have taken business away from an apparently sleepy $rm may $nd themselves suddenly without any pro$ts. This e#ect may be magni$ed because the customers who switched away from the inert incumbent are, by self-selection, the most sensitive to a better o#er.

On the other hand, if the attacker has been successful in building bonds of cost and loyalty with newly acquired customers, then the incumbent’s return to a competitive posture may fail to gain back its lost buyers.

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ENTROPY

It is not hard to see entropy at work. With the passage of time, great works of art blur and crumble, the original intent fading unless skillful restorers do their work. Drive down a suburban street and it is easy to spot the untended home. Weeds grow in the garden, paint peels from a door. Similarly, one can sense a business $rm that has not been carefully managed. Its product line grows less focused; prices are set low to please the sales department, and shipping schedules are too long, pleasing only the factory. Pro$ts are taken home as bonuses to executives whose only accomplishment is outdoing the executive next door in internal competition over the bounty of luck and history.

Entropy is a great boon to management and strategy consultants. Despite all the high-level concepts consultants advertise, the bread and butter of every consultant’s business is undoing entropy—cleaning up

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the debris and weeds that grow in every organizational garden.

Denton’s

In 1997, I was retained by Carl and Mariah Denton to look at the overall performance and value of their family company. The company, Denton’s Inc., operated a chain of garden and landscape supply outlets in four states. Denton’s dated back to the 1930s, when a number of separate retailers combined as a way of surviving the Great Depression. Originally serving fairly rural communities, it had, over the years, expanded into exurban areas as well. The twenty-eight retail outlets operated under three separate brand names but were all actually quite similar. Each outlet had a retail store building that sold garden supplies and tools and a large outdoor space that sold plants, trees, soils, and landscaping materials. Denton’s owned

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twenty of its locations outright and leased the remaining eight.

Carl and Mariah Denton were avid gardeners, and their home could have been an advertisement for the company’s products and services. The air was heavy with the scent of "owers, and an arti$cial stream burbled down ledges of stone and rock. Under a large shady oak tree we talked about the company and their desire to “get it in shape” to hand over to their children. They gave me a CD-ROM containing $ve years of $nancial results for each store and the company as a whole.

Digging into the $nancial statements I began to untangle layers of complexity. The main source of confusion was the treatment of capital. The company’s return-on-capital measure for each retail outlet mixed apples and oranges. One location purchased in 1950 had cost $5,000 per acre and one bought in 1989 had cost $95,000 an acre. The computed return-on-investment $gures

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for these locations made the older one look like a huge winner compared with the newer one.2 This way of measuring business performance confounded retailing with real estate investment gains.

To put each location on a comparable basis, I devised a new measure of operating pro$t I called gain to operating (GTO) that adjusted for these di#erences and for various allocations.3 Denton’s best store had a GTO of $1.05 million and its worst had a GTO of negative $0.97 million. That is, closing that store would yield $0.97 million more per year than continuing to operate it. Denton’s whole chain showed a GTO of $0.32 million, a very di#erent picture from the $8 million in net income the accounts showed.

The chart I prepared for Carl and Mariah Denton is reproduced on the following page. To build this chart I ranked outlets in order of their gains to operating, with outlet 1 having the highest and 28 having

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the lowest. The bars show, for each rank, the cumulative gain to operating all of the outlets at that rank or better. Thus, the $rst bar on the left represents the best outlet in the chain—its GTO was $1.05 million per year. The next bar represents the GTO of outlet 1 plus that of outlet 2, a total cumulative GTO of $1.05 + 0.63 = $1.68 million. The third best outlet earned $0.5 million, so the third bar shows the cumulative GTO of outlets 1, 2, and 3 (1.05 + 0.68 + 0.5 = $2.18 million). Outlets 4 through 14 added another $2.5 million to the cumulative total, bringing it up to $4.68 million. But, beginning with outlet 15, negative GTOs begin to drag down the cumulative total. In fact, the negative GTOs of outlets 15 through 28 summed to negative $4.4 million, almost totally canceling out the contributions of the positive GTO stores. As you can see, the number one outlet’s GTO was higher than that of the whole chain of twenty-eight!

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DENTON’S ADJUSTED CUMULATIVE GAIN TO OPERATING (MILLIONS OF $)

Outlets Ranked in Order of Decreasing Gain to Operating

I call this a hump chart. Whenever you can assign pro$t or gain to individual products, outlets, areas, segments, or any other portion of the total, you can build a hump chart. I built my $rst hump chart in an analysis of Western Electric’s pre- deregulation product mix. Since then, I have seen and helped build hump charts for planning military base closings, Sony products, telephone company customers, and a variety of other situations. If there

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are no cross-subsidies, the bars will rise smoothly to a maximum. But if some operations, some products, or some locations are subsidized by others, there will be a true “hump” on the chart—the bars will rise to a maximum and then begin to sag downward as the loss operations pull down the pro$ts of the whole.

If the operations are separable, then a distinct hump, sustained over time, indicates a lack of management. It is a way to see entropy at work. At Denton’s, the cross-subsidies were obscured by the measurement system and institutionalized over time. For example, in addition to the distortions caused by poor measures of space and land costs, Denton’s measured the monthly and annual performance of each location by its “business operations pro$t,” a $gure that omitted employee incentive and bonus payments. Because incentive payments were set each year by corporate management, the logic was that

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they should not be charged directly to each location. But over many years incentive and bonus payments had become close to entitlements and were paid on the basis of total corporate pro$t, creating a subsidy from the more pro$table locations to the less pro$table.

Carl and Mariah were shocked by the hump chart. “You can’t be suggesting that we drop half of the locations,” Mariah said.

“No,” I replied. “But it might make a great deal of sense to close the very worst performing locations. If you do that, and $x the other eight weak locations, you will double total earnings.”

Improving the performance of the weaker locations took two years. The methods were straightforward data-driven management and transfer of best practices. The key at Denton’s was to $gure out why some locations performed better than others. Sales per square foot was a major driver of performance and it turned out to be

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strongly a#ected by location, the closeness of a competing Home Depot, the nursery layout, and the landscaping presentation. Better performing outlets, we discovered, had moved beyond the old-style grid layout and looked more like gardens. Plants were not simply labeled but described in detail along with planting suggestions and ideas about pairings with other plants. Plants were presented in attractive collections, promoting impulse buying. Landscaping supplies were not simply piled up but shown o# in set-piece presentations, again helping customers to visualize how to use these materials at their own homes. Selling activities in the store, garden, and landscaping areas were separated because the knowledge bases of the sales personnel di#ered greatly across these activities.

At the end of two years, Denton’s gain to operating had risen from $100,000 to more than $5 million and its accounting pro$t had doubled. About one-half of the increase

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came from dropping $ve weak outlets and the other half from a best-practices program. None of this improvement came from a deep entrepreneurial insight or from innovation. It was all just management— just undoing the accumulated clutter and waste from years of entropy at work.

Planning and planting a garden is always more interesting and stimulating than weeding it, but without constant weeding and maintenance the pattern that de$nes a garden—the imposition of a special order on nature—fades away and disappears.

General Motors

One of the clearest examples of entropy in business was the gradual decay of the order imposed on the early General Motors by Alfred Sloan. In this decay, one can see the value of competent management by its absence. Indeed, you cannot fully understand the value of the daily work of

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managers unless one accepts the general tendency of unmanaged human structures to become less ordered, less focused, and more blurred around the edges.4

In 1921, Henry Ford held 62 percent of the U.S. automobile market, having built a giant enterprise around the Model T. Ford’s success came mainly from the Model T’s low price, achieved by world-class industrial engineering of each aspect of automobile manufacturing.

General Motors was smaller than Ford and had been assembled through a number of acquisitions. In April 1921, the company’s president, Pierre du Pont, asked Alfred Sloan (then vice president of operations) to undertake a study of “product policy” for the company. At that moment, the company produced ten lines of vehicles that together held about 12 percent of the automobile market. As can be seen in the following diagram, GM’s Chevrolet, Oakland, Oldsmobile, Sheridan,

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Scripps-Booth, and Buick divisions all o#ered automobiles in the $1,800–$2,200 range. None produced a car that competed with Ford’s $495 Model T. Plus, the Chevrolet, Oakland, and Oldsmobile divisions were badly in the red.

Two months later, Sloan presented his product policy to the executive committee. Sloan insisted that “General Motors’ car line should be integral, that each car in the line should properly be conceived in its relationship to the line as a whole.” More speci$cally, he wanted “quality competition

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against cars below a given price tag, and price competition against cars above that price tag.”5 Sloan’s plan not only cut the prices of the cars in the line, it gave each brand a unique range of prices to work within. This new policy dramatically reduced the amount of intracompany competition and product clutter. Under Sloan’s concept, there was no fuzziness or confusion about the di#erence between a Chevrolet, a Buick, and a Cadillac. Look at the diagram on the next page to see the logic and order Sloan’s design imposed.

The executive committee adopted Sloan’s plan, sold Sheridan Motors, and dissolved

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Scripps-Booth. Sloan became president in 1923. Oakland became Pontiac $ve years later. By 1931, General Motors had become the largest automaker and one of the leading corporations in the world. Throughout the 1940s and ’50s, Sloan’s concept became a part of American culture. Walking through a suburban neighborhood, you could tell who lived in each house by the car parked out in front: ordinary people drove Chevrolets, the foreman a Pontiac, the manager a Buick, and the CEO a Cadillac.

Sloan’s product policy is an example of design, of order imposed on chaos. Making such a policy work takes more than a plan on a piece of paper. Each quarter, each year, each decade, corporate leadership must work to maintain the coherence of the design. Without constant attention, the design decays. Without active maintenance, the lines demarking products become blurred, and coherence is lost.

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If the company is fully decentralized, this blurring of boundaries is bound to happen and the original design, based on brands de$ned around price ranges, becomes buried under a clutter of new products. For example, executives running the Chevrolet division knew that they could increase the Chevrolet division’s sales and pro$t by o#ering some higher-priced models. This move might take some business away from Chrysler; it would also take business away from Pontiac and Oldsmobile. Conversely, executives running the Pontiac division saw that they could increase their division’s revenues if they o#ered some lower-priced models, so they pushed in that direction. Like a parent who must resist fourteen- year-olds’ pushing for beer at the party, corporate management’s job is to resist these imprecations and preserve the design. If the design becomes obsolete, management’s job is to create a new way of coordinating e#orts so that the competitive

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energy is directed outward instead of inward.

By the 1980s, Sloan’s design had faded away—a vivid illustration of the power of entropy. General Motors not only had blurred its brands and divisions, it engaged in badge engineering, o#ering essentially the same vehicle under several model and brand names.

More recent administrations worked to reduce the amount of overlap. In 2001, the Oldsmobile division was closed down, a stark recognition that its models had lost any distinction in either style or price. Lawsuits from displaced Oldsmobile dealers made this a very expensive proposition.

The 2008 product lineup at General Motors is shown on the next page, along with competitor Toyota’s product lineup. Because GM’s product mix was much more complex in 2008 than it had been in 1921, the display is restricted to sedans and coupes, omitting SUVs, vans, hybrid engine

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vehicles, and all trucks. Although Oldsmobile no longer existed in 2008, I have projected the price ranges of its models by adjusting its model year 2000 cars for GM’s overall price in"ation over the intervening eight years.

As can be seen, models were clustered around the mass-market $20,000–$30,000 range. In fact, at a price point of $25,500, General Motors o#ered nine vehicles (two Chevrolets, one Saturn, four Pontiacs, and two Buicks). Toyota, by contrast, o#ered two cars at that price.

The loss of coherence in General Motors’ product line dramatically increased the amount of internal competition among its brands. Business leaders tend to see competition as a cleansing wind, blowing away waste and abuse. But the world is not that simple. If you invest in advertising or product development to take business away from a competitor, that may increase the corporate pie. But if you invest to take