We’re going to talk about investors. First, though, we’ll set the stage with a few relevant words about the United States Congress. No, not those words.

The United States government was designed with a system of checks and balances. They work very well. So exquisitely is Congress balanced that it has become immobile. Which, incidentally, an economist might call an “optimal” position. That’s because motion in any direction would apparently produce an outcome so awful that Congress will not allow it. If no other position is preferable, then the current position must therefore, by definition, be optimal. Which must mean something is wrong with economists, but at least they have a sense of humor.

Anyway. If Congress suffers from a surplus of balances, then it seems to me that investors suffer from a surplus of checks. I don’t mean checks in the sense of here, let me write you a check. I mean checks in the sense of due diligence, verification, and oversight. Not that there’s anything wrong with that, except for when they are all along the lines of making sure you don’t overpay for your berth on the Titanic.

Some time ago I attended a meeting of investors, of whom I was not one. They filled a large room and listened to pitches from passionate entrepreneurs, of whom I was also not one. The entrepreneurs all sounded highly competent, knowledgeable, and professional. They knew their markets, their products, and their prospects.

I listened to the thirty or so questions asked by the investors following the entrepreneurs’ presentations. The questions dealt with checks as in due diligence, verification, and oversight. That’s fine: if I’d chosen to invest, I’d have wanted to be sure everything was legitimate too. But that’s what every question was about. Every question was a request for a reason to believe that giving you a great deal of my money would be a wise move. Not a single question dealt with what could go wrong. What if, for example, a company already in a market wanted to squash the entrepreneurial intruder? What if an applied-for patent is denied?

We humans are basically optimistic and energetic. We imagine things, we want things, we make things happen. I’m that way too; one doesn’t start one’s own business otherwise. But being an optimist doesn’t mean looking only for reasons to believe. An optimist is not the person who leaps off a 50-story building and says, after plummeting 49 stories, “so far, so good.”

Strategy development often combines reasons to believe with ambition; that is, the laudable desire to do well and get ahead. In combination — reasons to believe and ambition — we get advocacy. I’m right, this is why I’m right, and this is why we should do things my way. That’s how we get ahead. That’s how we inspire action. That’s how we make progress.

We don’t want to become check-happy, like the investors, nor do we want to become balance-happy, like Congress. At least I hope not. So, let’s hearken back to the olden days of yore when we took tests and had to answer questions like these:

Checks are to balances as advocacy is to:
A. Optimism
B. Optimal
C. Optical
D. Optional
E. Stress tests

Yes, stress tests: business war games, strategy simulations, what-if analysis, sparring-partner equivalents, corporate contrarians, etc. Techniques advocated by conditional optimists who know something can go wrong. After all, if an unexpected threat (or opportunity) can come out of left field, it is good to look in that direction before committing to a new strategy or investment, or even to the status quo.

One last point. If stress-testing a strategy (or a government policy) demonstrates that it will produce really nasty results, that’s not a good enough reason to reject it. First, we must compare the results of the stress test to the outcomes we’d get under the status quo. If we get better results with the new strategy (or policy) than we’d get without it, then, really nasty as it is, we should switch to it. Even better, look for an even-better strategy (or policy).

The Wall Street Journal reported today that Google’s shares went up more than 8% because profit and revenue growth weren’t “as bad as some had feared.”

Google’s results? Profits up 26%, revenue up 31%. Google is on track to earn profits of about $5 billion on revenue over $20 billion in 2008. I agree, it doesn’t sound bad enough to fear.

Let’s put those numbers in perspective. At that rate of growth, Google will be equal to the rest of the entire American economy in 30 years or so. (If the economy continues to shudder, it won’t take that long.) Another six or seven years, it’ll equal the non-Google gross world product. A few more years and there they are at the gross galactic product. How do I know? I just extrapolate Google’s technological capabilities as blithely as I extrapolate their financial statements. By the time I’ve shuffled off to the Oort Cloud or whatever the airlines would call my final destination, you’ll be able to prove me right or wrong with a Google search for extra-terrestrial business intelligence.

If Google regains the magical 39% growth rate that would allay investors’ fears, you can shave about five years off those numbers. I can see why people would be so eager to restore that growth: who wants to wait another five years for world domination?

Obviously my numbers are not “accurate” even though I based them on real data about the American and world economies and calculated them to n decimal points. But any imprecision in that 30-year timeline is quite immaterial to this essay, or to anything else for that matter.

With the possible exception of the universe itself, nothing sustains a rate of growth forever because nothing grows forever. However, the expectation, the demand, the requirement that each year be bigger and better than the previous leads us to deceive ourselves. It leads us to overreach, cut corners, build houses of cards, and do “whatever it takes” to “make the numbers.” Not unlike the genesis of the financial crisis I described in It’s Working!, and not unlike the analytic circle I described in Self-fulfillment.

Let’s take a step back. So far in this essay I have heroically slaughtered a dragon that we all know doesn’t exist. We all know growth eventually slows. No one expects Google to dominate the world; after all, there has to be room for Wal-Mart, big pharma (which, having begun on this path a while ago, is a few years ahead of Google in struggling to maintain growth), Toyota and/or Tata, and whatever devices let us text-message one another.

But even though we all know growth eventually slows, we don’t want it or expect it to slow today. We’ll talk about tomorrow tomorrow; today we’re talking about my money. If you don’t stay on a roll, I’ll hammer your stock. And my friends and I can do it, thanks to our world of instantaneous information-plus-noise, imperfect analysis, and twitchy trigger fingers.

Knowing that, management reasonably wants to maintain or enhance performance. That’s not inherently bad; it’s how capitalism is supposed to work. But management has little clear guidance on when their efforts go from building up to propping up to puffing up. When did airlines’ cost-cutting go from sensible to fiscally and physically dangerous? When did Detroit’s price-cutting go from occasionally expedient to perennially desperate? When did pharma’s infatuation with blockbuster drugs go from delightful jackpot to essential lifeline?

The problem is not that 39% growth won’t last forever. The problem is not that stock prices rise and eventually fall. The problem is that, judging by results, we often act ineffectively when growth slows. When we push too hard to keep the growth going, we create a bubble that ends up like the financial crisis. When we squeeze too hard to keep costs down, we starve the investment we need to run the business in the future. (One can make a case that we are doing exactly that with the country’s infrastructure.) When we polish our numbers too hard to make everything look peachy, we create new expectations that are even harder to satisfy.

The issue is what we colloquially call denial, as in the refusal to look hard at potentially bad news and take appropriate action. Much, perhaps most, of that denial is not willful; the generally accepted tools that strategists use (e.g., spreadsheets, forecasts, benchmarks) have built-in filters that prevent potentially bad news from reaching strategists’ eyes. (See, for instance, the discussion of accounting-based spreadsheets in With All This Intelligence, Why Don’t We Have Better Strategies?) Plus, denial is strongly reinforced by the rewards we lavish upon those who succeed, by the tickets to “away” we lavish on those who don’t, and by the tomorrow-is-like-today habit that makes us expect the good times to last a little longer.

We don’t always fall into such traps, of course. As I noted in It’s Working!, Viacom bought Blockbuster for $11.6 billion in 1994, and, after a series of losses, “split it off” in 2004 for $2.7 billion (both numbers are in 2007 dollars). The flip side is that someone else sold it for $11.6 billion and didn’t own it as its value went down to its current market value of about $300 million. [Update: in January 2010, Blockbuster's market value was below $100 million.]

The best way I know to reduce denial is for people to live through the bad situation. For instance, it’s one thing to tell a person that he or she won’t live forever, and it’s quite another thing for that person to live through a potentially deadly event.

I was fortunate enough to live through a flight with the mid-air explosion of an engine: fortunate both in that I was alive and uninjured and in that I was lucky to have had the experience. I’m not recommending that we blow up lots of engines at five thousand feet so more of us can enjoy growth experiences. What I’m saying is that it was a cheap (for me) way to learn an important lesson.

That’s the key: a cheap way to learn an important lesson. The military does it with war games; lawyers do it by arguing in front of mock juries; actors do it by rehearsing. As they get more intense and immersive, movies are arguably getting closer to being simulations, although they’re presented almost entirely in the third person. Interestingly, the exploding-engine incident was a learning experience for me but not for the pilots of my aircraft. Luckily for me, they’d already had their learning experiences in flight simulators! Which is exactly the point.

In business, the cheap way to learn important lessons is through business war games and strategy simulations, especially because they make it possible to turn the clock back and what-if a different move by you or your competitors. I won’t go into detail here about them because other materials say enough and because this essay isn’t specifically about business war games and strategy simulations. Based on my experience, I’ll just say this (which I believe would be echoed by other professional war-gamers):

• It is possible to overcome common psychological and analytic biases that unintentionally distort our thinking. Add books about social psychology and numeracy to your reading list.
• Every business I’ve seen has found better options. Sometimes they’re much better. Usually they’re surprises. You have to look for them. Start by asking what could make your current strategy fail.
• Solving strategy problems rarely requires getting more decimal points. It almost always requires thinking differently.
• Thinking differently doesn’t happen automatically or overnight. After all, each of us has spent a lifetime practicing our current ways. But thinking differently is possible.
• Perhaps the most-insightful, -useful, and -important part of thinking differently is asking what if.
• Improving your thinking is the fastest, cheapest, and highest-leverage way to improve your business’ performance.

We’re all getting experience now by living through the current financial crisis. Unfortunately, unlike a war game or simulation, we don’t get to turn the clock back and prepare a better strategy. Unfortunately too, without the opportunity to what-if the situation, what we will learn from it depends on how we perceive and interpret it.

So, if you’re not lucky enough to be prospering at Google, what should you do amid the extraordinary market decline and the extra pressure to perform? Here are two things not to do: Panic and deny. Here are two of the generic things others might urge you to do: Get back to basics or hunker down to wait it out. And here’s what you should do first: Outthink your competitors.

See also Do Not Overtighten.

My thanks to RJB, who inspired two of my favorite phrases in this essay.

Data mining is the unleashing of massive computer power on massive consumer databases to look for patterns that managers can use to build sales and spend more efficiently. The work takes place with silicon, copper, and iron oxide, but it depends first on carbon: on how we humans think. If we believe, for instance, that demographics drive purchases, then we program our computers to look for correlations between demographic characteristics and purchase behavior.

Given enough data and computing, we will find correlations. Some of the correlations may be true in the sense that they are not random. Some will be false in the sense that they are random; they slip in because we will get false positives if we test enough potential correlations. But the important thing is that the computer thought as we (the human programmers) thought; in this case, to look for demographic connections.

And then self-fulfillment happens. Say the data mines reveal that people with characteristic X tend to buy more of a product than do people with characteristic Y. So we market more to those with characteristic X and less to those with characteristic Y, and guess what? Sales go up among X’s and down among Y’s. It looks like our analysis worked, but what happened is that our actions made it work: a finding (possibly random) triggered positive action, the action stimulated happy results, the happy results confirmed the finding. Should we credit the finding or the clear, focused action? The issue isn’t data mining per se. We could make the same points about self-fulfilling managerial truisms such as “invest in your fast-growing products.”

That an analysis may be self-fulfilling or have its genesis in beliefs doesn’t make the analysis wrong. On the other hand, the happy results don’t mean the analysis was right.

Update. Recommended: Jason Zweig’s article “Data Mining Isn’t a Good Bet For Stock-Market Predictions,” in the Wall Street Journal, August 8, 2009.

I’m a simulations kind of guy, and not just for business. In this essay I’m going to talk about both business and crisis simulations.

A large pharmaceuticals company in Europe used a business war game to help them develop their strategy for a product launch. We divided their management groups into teams to role-play the competitors, and we set up three teams to play their own business. Why three teams for their own business?, they asked. They thought the strategy decision for their own business was pretty clear.

As it turns out, the three home-team teams came up with three very different strategies. That was a major insight from the war game: they didn’t know they had (at least) three options. It was premature to fine-tune an “obvious” strategy (which wasn’t so obvious after all).

I’ve seen similar behavior in crisis simulations. Here’s a true story from an actual simulation conducted by a company I co-founded a few years ago, Crisis Simulations International.

A bomb has gone off in an American city, severely damaging a key bridge, hurling cars into the river below and derailing a train. The train was carrying poisonous chlorine gas, among other things. You are the mayor. You don’t know if the chlorine is leaking. You don’t know if another bomb has been planted, ready to kill rescue workers. You don’t know whether to believe confused, contradictory, maddeningly incomplete reports flooding in from all directions. Simulated TV broadcasts are blaring. Fleeing people may quickly gridlock the city, making it impossible for rescuers to get through. You have a variety of decisions to make. Many lives, the safety of your city, and your political career are at stake.

At key points during the simulation we asked 100 assembled experts, in real time, what they would decide for the simulated mayor, police chief, fire chief, and so on. They would have several starkly different options at each decision point, such as whether or not to pull back rescuers when a suspicious box was discovered near ground zero. The experts had electronic devices that let them vote quickly and anonymously.

The 100 experts were nowhere near unanimous on any of the questions we posed. On one question, the experts split almost exactly evenly on the four possible decisions.

Let’s leave aside the disturbing question of crisis preparedness. Instead, let’s mention three points about the experts’ decisions.

1. Each of them selected what he or she thought was right.
2. Most of the other experts disagreed.
3. Someone else, making assumptions about what others had decided, would probably assume wrong.

People do make assumptions about what others will decide. The people actually going through the computer-based simulation are usually in the same room, and yet they don’t talk to each other about how to coordinate their decisions! They make their decisions based on what they think others will do, and the odds are distressingly high that they’ll be wrong.

It doesn’t take much time to find out the things you can do that you didn’t know you could do. The whole business war game took just one day, and the crisis simulation took a few hours. You don’t even have to run a business war game or a crisis simulation to get benefits like those. (See, there’s something else you can do that you might not know you could do.)

• Broaden your view before you talk about specific action. Ask questions such as what you would do if you discovered your first choice was placed completely out of bounds.
• Treat the word “obvious” not as validation but rather as a warning flag. Or perhaps as an opportunity flag, because you may uncover an option that your competitors haven’t seen.

By the way, it doesn’t have to be grim and serious. In my experience, management groups do their best work when they’re having fun with a challenge.

First store in the 1980s, hundreds now. Compound annual growth of 70% for the last ten years, the ability to undercut Wal-Mart and Target on price, a glowing article in Business Week in 2006, another on ABC News in May 2008, and a website that says “[our business] significantly impacts whole communities, rejiggers shopping patterns, alters local economies, and sometimes even changes lives for the better.” Heady stuff.

So how do they look halfway through 2008? Here’s what the Wall Street Journal said on July 9: “Steve & Barry’s to File for Chapter 11.” (Update: They did file.)

How do we respond to such a story? When they were flying high, we respected, perhaps envied, maybe even emulated their energy and vision. What do we learn from their dire straits?

We could say it’s the economy, except that, as the Journal said, “[their] deep-discount model was built to thrive in a difficult economic environment.” We could say they made mistakes, except that they appeared to be doing things right for decades. We could say those guys were stupid, except they weren’t. We could say their industry is so verydifferent from ours, except that an awful lot of industries are suffering these days.

Steve & Barry’s isn’t so different from your business and mine, and Steven Shore and Barry Prevor aren’t so different from you and me. They’re smart. They’re educated. They’re professionals. They’re motivated. They’re experienced. They showed guts and commitment, and they succeeded for a long time, and they may continue to succeed. And they, like us, are vulnerable. The question is, vulnerable to what?

It’s easy to say that businesses are brought down by the economy, but that really doesn’t explain much. Why are businesses brought down by the economy, especially businesses designed specifically to thrive in a difficult economic environment? It’s not as though we’ve never had a tough economy before, and it’s not as though there’s rocket science involved. More specifically and more importantly, why are businesses run by smart, educated, successful, motivated, experienced, gutsy, committed people brought down by the economy?

Many business-strategy errors in many industries — we’re going beyond Steve & Barry’s now — happen not because people are stupid or misinformed. On the contrary, they happen because people are smart and well-informed. We suffer the unintended consequences of being smart in the wrong ways and informed about the wrong things. Some examples:

• A clever business model (smart) may unconsciously rely on a perfect storm of good events to succeed (unintended consequence).
• A make-it-happen culture of leadership (smart) makes it difficult or even career-dangerous to speak up about danger ahead (unintended consequence)
• A desire for success and certainty makes us ignore genuine risks; plus, we borrow from the future to make our numbers today.
• A desire for good (as in accurate and rosy) forecasts and data makes us focus on precision and trend lines, neither of which fit in times of serious change.
• Affection for growth and market share makes us play chicken with equally desperate competitors and makes us unrealistic about prices.
• Relying on typical management tools makes us vulnerable to the shortcomings in those tools, such as spreadsheets that take neither competitors nor customers into account.
• Confidence makes us act and overconfidence makes us fail; it can be hard to distinguish the two, especially when we’re moving fast and believe our strategy is working.

I will expand on those themes in future essays. For now, let’s just note that the good news is that every one of those forces, unlike the economy, is under management’s control. In other words, we can do something about it.