Is It Truly Good to Great, Or Just a Coin Toss?

Posted: June 1, 2010 in Books
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Books like Good to Great are based on survivor bias. Study a bunch of companies that have had an unbroken run of success (By whatever arbitrary criterion you choose. Why 20 years? Why not 21.5 years?) In the universe of all companies, there are bound to be a few that meet your criteria, even though 99 % of companies eventually fail, go out of business, or get bought out. It’s like taking a group of 10000 people and asking them to flip a coin. Every time they flip, you only keep those people that guess right on the coin toss. After a certain number of iterations, there is one person who “successfully” predicted 18 coin tosses in a row (or whatever the number would be). Does that indicate the winner is psychic? After that, you find some arbritrary features that you decide must explain the “success.” Write a book about it, with many compelling – yet just so – stories.

The problem with stories is that they make a great read, convey a point or illustrate with an example. None of these have anything to do with whether there is actually something to be explained in repeated cause and effect terms. The other problem with these books is that they isolate causes of success after the success has occurred, and despite the fact that there is a fair dosage of luck involved (though not always). The resulting advice often appears to be useful on the surface, but there are no real guideposts indicating how to apply it. We’re told that it’s essential to concentrate and adopt the hedgehog approach. What about all the cases where it would have been better to be a generalist? Zen like Level 5 Leadership is the way to go, except that most of the truly exceptional business innovators and leaders are petty tyrants (Jobs, young Gates, etc.). Innovate and be out front, except when you shouldn’t. In fact, for the latter, you could argue that it is the foolhardy thing to do. It’s probably much better to see which way the wind is blowing, and then to bet on a small number of the most likely winners, accepting that you could be totally wrong.

© 2010 Richard Martin

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