Predicting election results is relatively easy. The problem is well-defined – the candidates are known, the process of choice defined in legislation, the result a matter of public record. The issues lend themselves to probabilistic reasoning – the mathematical properties of sampling populations are well understood. Much the same is true of baseball statistics and poker, two other issues on which Mr Silver (in his book The Signal And The Noise) claims particular insight. Weather forecasting is harder, but we know whether it is raining or not, have extensive data sets, and some – if inadequate – understanding of the processes by which clouds form and winds blow. But most of the problems we face in business and finance are ill-defined and open-ended. We often do not really know the answers even after the event. We cannot envisage the full range of possible outcomes, or the options available. Nassim Nicholas Taleb famously characterised this world as populated by “black swans”, while Donald Rumsfeld mused on “unknown unknowns”.
People crave specific knowledge of the evolution of complex systems, paying good money for the services of clairvoyants and economic forecasters. But such knowledge is rarely available. Nor, even if it were available, would it often be useful. Physicists studying sport have established that many fieldsmen are very good at catching balls, but bad at answering the question: “Where in the park will the ball land?” Good players don’t forecast the future, but adapt to it. That is the origin of the saying “keep your eye on the ball”.
If outcomes are only probabilistic—in the best cases—how am I supposed to plan for the future?
Michael Raynor, author of The Strategy Paradox, argues great strategy can lead to great successes as it did with the iPod but it can also lead to enormous failures as it did with Betamax. If you have to predict the future, a good strategy will often be wrong.
Whether great strategy succeeds or fails therefore depends entirely on whether the initial vision happens to be right or not. And that is not just difficult to know in advance, but impossible.
Raynor argues that the solution to this is to develop methods for planning that account for strategic uncertainty.
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