Honey, We Shrunk The Industry Again

Honey, We Shrunk The Industry Again: Another War Game About Automobiles, by Mark Chussil

Why “again”? Because this isn’t the first time. See also Honey, We Shrunk The Industry, published in Competitive Intelligence magazine, July/August 2009.

A business war game. Five automaker teams: Ford, GM, Hyundai, Toyota, Volkswagen. Three market segments. Two years. One set of consumer judges, one set of investor judges. Fascinating results, again.

The automaker teams were smart and they wanted to win. Yet collectively their decisions subtracted roughly $15 billion of simulated profits from the industry over two years.

It appears that company-centric financial approaches (what are our costs, how much capacity should we mothball) instead of competitive analysis (what will our competitors do, how will consumers respond) led to those problems. In effect, the automaker teams worked by the book, but the book didn’t work.

The good news: Anyone who’d gone through the war game would be less likely to make those mistakes in real life. They would have a competitive advantage.


On September 30, 2009, the front line in the automobile wars could be found in a conference room at Northrop Grumman outside Washington, DC. That’s where a group of 20 strategists converged to war-game the industry. Sponsored by the Greater DC chapter of the Society of Competitive Intelligence Professionals and facilitated by me, the war-game used a simplified version of ACS’ ValueWar™ strategy simulator, customized for the auto industry.

The war-game exercise was designed to demonstrate war-gaming, not to solve the problems of the auto industry. After all, the industry’s problems took decades to build, and it would take our talented strategists more than three hours to fix them all. That said, it was fascinating to see many of the industry’s woes reenacted — and understood — in those three hours. Moreover, the strategists saw for themselves how war-gaming provides a new look at businesses people know well.

War games are not about a consultant or guru dispensing advice to eager supplicants. They are about business strategists living through future scenarios in fast forward and discovering lessons for themselves. They are about strategists making the most of their knowledge, expertise, and creativity. They are about smart people teaching themselves. War games make it possible in a way that conventional strategy development does not.

Why A Business War Game?

Business war games provide a new look at businesses we already know by having us role-play competitors and customers in addition to ourselves, by having us compete as well as compute, by having us encounter action and reaction rather than assume bigger and better. They let us explore and stress-test in a safe environment, where mistakes mean oops instead of ouch.

We can think of business war games as being the highest of three levels of competitive inquiry.

  • “What do you think they will do?” This is a basic competitive-analysis question. It explicitly treats competitors as “them.” Strategists, being human, tend to view “them” as less capable than “us.” In practice, answers to this question are often extrapolations of competitors’ past actions.
  • “What would you do if you were them?” This question is a major improvement because it encourages the strategist to look through competitors’ eyes. It greatly reduces wishful thinking. Brainstorming or scenario-planning programs may use this question, assuming that they explicitly consider competitors.
  • “You are them. You want to win. Go!” This is what happens in a business war game. Strategists don’t only look through competitors’ eyes; they walk in competitors’ shoes. Business war games tap human competitiveness and desires to win. They make tough sparring partners out of genial colleagues. The sparring partners find the flaws in their company’s strategy just as real competitors will. And so strategies get stress tests second only to real life.

The Design Of The Automobile War Game

Teams, segments, judges, and decisions

We divided the war game participants into five automaker teams: Ford, GM, Hyundai, Toyota, and Volkswagen. For the purpose of this war game, these teams/companies competed in three USA market segments:

  • Big Tough (roughly SUVs). In the game, this segment was slowly shrinking.
  • Slick Style (roughly upscale sedans). This segment was steady.
  • Cool Green (roughly eco-friendly vehicles). This segment was slowly growing.

Why five teams? Not to be flip, but three would have been too few for participants to experience the richness of the industry and seven would have been too many to handle in the time we had. Similarly, one segment would have been too few and five too many. Three made for manageable tasks and complexity. Of course, there’s nothing about war gaming that forces those limits. I’ve run war games with eight competitors and with ten segments, and I’ve designed simulation software that can handle dozens of competitors in scores of segments.

We had two judge teams too, representing consumers and investors. The automaker teams would find it difficult to win the war game by creating unidimensional customer-satisfaction or shareholder-wealth strategies. They would have to make real-world tradeoffs.

In addition to excluding some competitors and market segments, we excluded decisions regarding labor, pensions, healthcare, debt service, dealers, government regulations, and suppliers.  We did that for reasons of time and complexity. For the same reasons we limited the game to decisions for pricing, marketing, production, and capacity. That may sound like a short list — real business war games may allow strategists to work with many strategy levers — but it was more than enough to simulate the dilemmas and debacles that real automakers face in real life.

In addition to making pricing and other decisions, the automaker teams presented marketing pitches to the consumer judges and business pitches to the investor judges. The judges’ assessments joined the teams’ decisions in the simulator, which did the arithmetic to estimate demand, sales, profits, and market share.

Calculating outcomes

We used a computer-based strategy simulator, calibrated for the five automakers and the three market segments, to calculate the demand, sales, market shares, and profit consequences of the teams’ strategies. The model took into account common-sense connections like the following. Some of those connections work similarly in other industries, and some don’t.

  • Customers have choices. If you invest in marketing or product improvements that customers like, and if you do it better than your competitors, then demand for your autos will rise. If you sit on your laurels, demand is likely to fall.
  • Some customers are loyal and will buy again from the same automaker. Other customers are not loyal and will make conscious purchase decisions.
  • Price affects both demand and the bottom line. Demand, through customer purchase decisions. The bottom line, by rippling through revenue and costs.
  • You decide how much to produce before you find out how much customers want to buy. You cannot sell more than you produce.
  • If an automaker cannot satisfy demand, some customers will buy from its competitors (if they have produced enough cars). Other customers will not buy at all if the car they want is unavailable.
  • Production capacity costs money. An automaker can save some money by mothballing capacity. However, mothballing will limit what it can produce, and mothballed capacity cannot be brought back on line quickly.
  • And more.

There is much more to say about simulation design, customization to industries, and other aspects of business war-gaming, but we won’t say it here. (See other articles and essays on this website.) What’s important is that it is possible to simulate and war-game virtually any industry. My colleagues and I have conducted war games with management in dozens of industries, from airlines to vaccines, on six continents.

About accuracy

All in all, the simulator estimated outcomes pretty well, and definitely better than conventional company-centric analyses. “Estimated” is an important word. We didn’t pretend that this simulator was “accurate” (no analysis of the future is). However, it was definitely realistic and directionally correct, which makes it highly useful for evaluating and stress-testing strategy moves.

Accuracy in future-looking simulations is a fairly complex subject and bigger than I’ll treat here. I’ll just say this. No matter what, strategists will make decisions. The relevant question is not whether a simulation is accurate. The relevant question is whether a strategist can make a better decision with a simulation than without. Oh, and I’ll also say this. There is always a model in strategy decisions. It may be in someone’s head, it may be in a spreadsheet, it may be in a simulator. Choose your model consciously.

Publicly available information and realistic estimates

The war game used publicly available information and realistic estimates as the basis for strategizing and simulating. Nothing proprietary or mysterious, nothing contentious. As in most business war games, the action and the insights come from strategists’ thinking, behavior, assumptions, and decisions, not from decimal points or obscure factoids.

Two rounds (year 1 and year 2) and three hours

The auto teams made decisions about their company’s pricing, marketing, production, and capacity mothballing. They made those decisions for year 1 and we fed their decisions into the simulator. We shared key year-1 results with the teams before they completed their year-2 decisions. They made their decisions for year 2 and we simulated those results too. All, including a debriefing, in three energetic hours (very fast for a business war game).

A level playing field

The five automakers we chose for the war game didn’t start from equal positions and they didn’t have equal resources. We took that into account in the scoring process to ensure that every automaker team had an equal opportunity to win.

It helps for the teams participating in a war game to know there will be a winner because it taps the competitive emotions that affect real-life decision-making. During the business war games we’ve run for real business situations, we’ve seen a company’s own people cheer when they, role-playing the competition, beat their own company! That’s good for the same reason that a boxer wants to practice with a tough sparring partner.

The hard part: Strategic thinking

Competitive strategy is often likened to chess for its complexity and to poker for its competitive interplay. It’s tougher than chess and poker, though, because in competitive strategy the contestants make their moves simultaneously instead of sequentially. You make your strategy decisions before you know your competitors’ strategy decisions.

Take, for instance, this war game.  If you know your competitors will focus on the Slick Style segment and cut production in the Big Tough segment, it’d be reasonable for you to do the reverse. Problem is, simultaneous moves means you don’t and won’t know that. You have to commit to your moves before you know what your competitors will do. (That’s why it’s so helpful to find clues with competitive intelligence and what-if analysis.) It’s a classic and difficult problem, and it affected the automakers in the war game. Here are some of the consequences and the lessons we can draw from them.

Lessons From The War Game

We’ve  run this war game before (June 2009), with SCIP Oregon. We can run it again, too. Contact ACS at info@whatifyourstrategy.com if you’re interested.

Some of the lessons we observed in the previous war game are similar to those from the DC war game, and some are different. The differences are important because they show there’s more than one set of possible strategies and outcomes. The similarities are important because they reveal how strategists commonly think.

These lessons cite various numbers from the simulation. As I said, the numbers are not “accurate.” However, they are sensible and meaningful, and none of the lessons below would materially change if the numbers were off by considerable amounts.

Do not use any information or analysis presented here to make investment or other weighty decisions about the auto industry!

Lesson 1. History isn’t all it used to be

It always happens: strategists tend to think in terms of where they were last year and then adjust up or down. It’s related to a phenomenon that psychologists call “anchoring.” More importantly, it’s due in part to assumptions that there is some kind of static, steady-state, or equilibrium position, assumptions that are reinforced by trend-line and other analyses.

This war game was no exception. Teams went into exquisite calculations with decimal-point precision, figuring out this year in terms of last year plus or minus.

As a result, the Toyota team produced fewer cars than it could have sold. How many? Across the three segments, over 1.2 million in year 1 and 1.3 million in year 2. At prices around $25,000 per car, that means roughly $30 billion in revenue left on the table each year.

The Toyota team wasn’t alone. The GM team was short 581,000 Big Toughs in year 2; there goes $15 billion, more or less. Ford and GM were short 164,000 Slick Style and 260,000 Big Tough cars, respectively, in year 1. Hyundai was low by 138,000 Slick Styles in year 2, which amounts to over 10% of their total sales.

Those shortfalls became unearned bonuses for the automakers who produced more cars than consumers wanted to buy. In other words, automakers who had extra cars to sell were able to sell some to disappointed customers of the out-of-stock automakers. For instance, GM picked up Slick Style sales roughly equal to Hyundai’s shortfall.

Why didn’t the automaker teams know better? Arguably not because they didn’t have enough time, because teams that have hours to develop strategies do the same thing. Definitely not because they were stupid, misinformed, or indifferent, because they were smart, well-informed, and motivated. Why, then? Partly because it’s not the way strategy development usually works. Partly because it’s really hard: it requires analyzing multiple moving parts, including competitors, consumers, production and segment allocations, price, mothballing, marketing spending, and resulting sales. And partly because few people have experience with that kind of systems thinking. All of which are reasons why war games are so surprising and so useful.

Lesson 2. Don’t forget the consumer

In my experience with business war games, teams usually pander to consumers. They promise the earth, they promise the moon, they try to outdo each other by offering shiny baubles and promising elysian delights at bargain prices.

Not this time. Even though I urged the teams several times to produce advertisements to appeal to consumers, and even though I told the teams that reactions from the consumer judges would greatly influence their sales, the teams’ presentations focused almost entirely on the investor judges. There was a minor battle for supremacy of slogans, but that was about it for consumers.

It showed up in the judges’ questions. A consumer judge asked over and over, “Why should I buy a car from you?”

It showed up in the judges’ ratings. On a 0-10 scale, where 0 means not good and 10 means not bad, the average investor ratings were 5.9 in year 1 and 6.9 in year 2. Consumer ratings were 5.1 and 4.8, respectively.

And it showed up in the teams’ results. In year 2, Ford made 1.3 million vehicles it couldn’t sell. They also had low ratings from the consumer judges. The low ratings from the consumers translated into low demand. Low demand in itself doesn’t hurt, but it does when combined with high production and heavy fixed costs for capacity, which is what Ford faced. If Ford had sold those cars, it might have broken even.

GM would have faced a similar fate except it didn’t overproduce quite so much. It only made about 690,000 cars it couldn’t sell, which also represented the difference between a major loss and breakeven.

Volkswagen was hurting too. They had 245,000 leftovers in year 2 (up from 98,000 in year 1). A smaller number, but it was the highest leftover percentage in the game: 51% of the cars made by Volkswagen went unsold.

Meanwhile, Toyota sold out, and Hyundai almost sold out. Toyota was strongly profitable in year 2, and Hyundai was a short drive away from making money. Those were the automakers the consumers liked most and that didn’t over-produce.

Lesson 3. Numbers aren’t only about numbers

Even though we’ve got a bunch of numbers here, the numbers aren’t the point. The point is about the way the teams competed. All of the teams did some things right. All the teams made mistakes, some costing tens of billions of dollars in actual costs or opportunity costs. But the interesting part is where the numbers came from. The numbers — sales, shortfalls, and profits — are, of course, results of doing things right, and of mistakes.

The numbers in the teams’ decisions are expressions of their thinking. The decisions reflected the teams’ predictions and assessments of what moves would work for them. They prioritized their time to focus on investors instead of consumers not because they thought that was a bad idea, but because they thought it was a good idea. They spent $X on marketing because they believed $X was the right amount to spend on marketing, not because they believed $X was the wrong amount. If they thought different decisions would have worked better, they would have made those decisions.

  • Speaking about marketing, the teams held their marketing expenses very close to where those expenses began. I don’t know why, other than perhaps taking a budget-oriented perspective: if I overspend I’ll get in trouble, if I underspend I’ll get less next year. (I’ve seen that in other business war games too, where we told participants that they could spend whatever they wanted and all of them kept within a few percentage points of their previous spending.) There were some tweaks, as with prices, but the changes were, in effect, noise.
  • The teams focused efforts on the numbers rather than on consumer appeal (i.e., the ads they were encouraged to create), yet the latter could have had tremendous impact. (We could say that the problem wasn’t that some overproduced, it was that they undersold.) Not so dissimilar to what strategists face in real life: huge focus on the numbers and planning, less on blue-sky thinking. It makes incumbents vulnerable to upstarts. Why, after all, is it even possible for upstarts to gain a toehold against incumbents? Incumbents have, or at least can have, all the advantages. The only advantage an upstart can have is thinking differently, and thereby acting differently.
  • The calculations some teams recorded for mothballing decisions suggest that the teams were trying to optimize a financial statement rather than to create a competitive strategy. An interesting (at least to me) question is whether it’s better to have a shortfall or to expand capacity to ensure that no demand goes unsatisfied. A strong argument can be made that many woes are due to a desire never to leave money on the table. People can lose a lot of money trying not to leave behind a little bit of money. I’m not saying that a company should go one way or the other. I am saying that there is often a hidden assumption that we should (and can) match supply to demand, and it’s good to notice and challenge hidden assumptions from time to time.

True, the teams didn’t have much time to formulate their strategies. Still, the way they chose to spend their limited time reflects what they believed to be important.

Lesson 4. It’s not enough to be smart

The people participating in our war game were really smart. Those who have participated in other war games were also really smart. The problem is, it’s not enough to be smart. None of us is able to do all the arithmetic in our heads. I’m not saying that any team made mistakes; then again, we all know that no one is always right. Plus, we know that individuals can make rational decisions that, in combination, produce undesired results.

The thing is, when it comes to strategy it’s even hard to tell when an individual or a team is smart. Say you got terrific results. How much of that is because you did something smart and how much is because someone else did something not smart? How much of your decisions were due to luck and how much to thoughtful analysis? How do you know if the same moves will work next year? It can be hard to resist the automatic conclusion that our strategy is working.

We say that people learn from experience. The trick is to get experience where it’s cheap, and to get lots of it. Business war games are cheap, plentiful experience. Cheap, because you’re not playing with real money and real careers. Plentiful, because you can test multi-year strategies in a few hours. With computer simulations, you can test them in a few seconds.

Lesson 5. Define “winning”

The auto team that scored best on profits was Toyota. (That’s a statement about the Toyota war-game team as well as the Toyota brand itself. By no means was Toyota predestined to be big and profitable in the war game.) GM had the biggest overall market share, but Toyota was within rounding error of them. It appears that Toyota had a winning strategy. Appears. However, they were the team that had by far the biggest capacity shortfall in both years. Over two years that team could have sold over 2,500,000 more vehicles. They could have sold roughly $60 billion more.

Other tidbits:

  • Toyota gained by far the most share, despite their shortfalls. They wouldn’t have if they had mothballed more capacity.
  • Ford took it on the chin. They might not have if they had built less and mothballed more, or if they had impressed the consumer judges more.
  • Volkswagen lost a little share. Hyundai gained a bit. GM pretty much held still.

So, did the Toyota team do well (highest profits, biggest share gain) or did they do badly (biggest opportunity lost)? Hard to know. But we do know that it would be hard to see the situation with a conventional spreadsheet, and it was easy to see in a war game with a strategy simulator.

Conversely, the simulation had the Toyota team’s competitors pick up much of what the Toyota team left behind. In effect, the Toyota team’s mistake became a gift that inflated the other teams’ results and that made them look better than their decisions warranted.

Lesson 6. To find better strategies, look again

Of course the teams might have come up with better strategies if they’d had more time. More importantly, the teams would probably have come up with better strategies if we had the time to turn back the clock and try a second round of strategizing.

In the real business war games I’ve conducted, disappointments from the first rounds are essential to getting people’s attention and stimulating people’s creativity. The second set of simulations are where the best strategy ideas come up. Just think: if you’d participated in this business war game, and you knew all these lessons (and more), wouldn’t that help you develop a much better strategy?

Ever see a Fortune 500 company turn on a dime? I have. It’s with the process similar to the one we ran, with those second or third rounds. The key is to get quickly and persuasively to the second or third rounds.

Incidentally, my colleagues and I are strategy agnostic. We don’t come in with a favorite strategy. I for one don’t even care what strategy the company ends up adopting. What I do care about, and I care about this deeply, is the quality of the company’s strategic thinking and decision-making. I don’t care if the right answer for your company is to zig or to zag. I care a lot about helping you find the right answer, whatever it turns out to be.

And In Conclusion

As obvious as those lessons may appear now, they were not obvious before the war game. Corollary: what appears obvious before a war game often turns out to be a really bad idea. That lesson and its corollary are the rule, not the exception, in real business war-gaming.

Business war-gaming and strategy simulations are big subjects and we’ve just scratched the surface. I urge you to learn more about them. Qualitative or quantitative, formal or informal, big or small, facilitated by you or outsiders… business war games help strategists make much better strategy decisions.

Thanks, and congratulations

My thanks to the Greater DC Chapter of SCIP, especially to August Jackson and Jeff Trexel, for inviting me to present the automobile industry business war game.

My thanks to the intrepid strategists who gave their all to the automobile industry for three hours. It was a huge challenge, and you rose to the occasion with intelligence, critical thinking, and humor. You brought great ideas, open minds, and good cheer to the event. Well done.

Congratulations to the Top Strategists on the top-scoring team, Toyota, and to the judges who asked great questions as consumers and investors. Honorable mention to the Hyundai team, which was within a decimal point of Toyota.

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