Chaos Theory and Decision Making: Why Rule-of-Thumb is Sometimes Better than a Complex Formula

Double-compound-pendulum.gif

Starting the pendulum from a slightly different initial condition results in a completely different trajectory.

Studies from the airline, apparel, and music industries show that forecasts based on simple rules-of-thumb are often better than ones based on complex techniques such as multiple regression.

Complex forecasting methods were compared with tallying (giving all correlated factors an equal weight) and one-good-reason (taking into account only one factor to make the forecast). And the complex forecasting methods could not beat the rule-of-thumb in any of the studied cases.

It follows that we are sometimes better advised to take business decisions based on a rule-of-thumb, or even gut feeling, rather than based on complex analyses and assumption-laden business cases.

Put another way, we should make things as simple as possible, but not simpler. (Albert Einstein, Paraphrased.)

But Why Should this Be? #

It turns out that the higher the level of complexity and uncertainty, and the more we should simplify our forecasts and decisions. In complex contexts such as industry: less is more.

Logic is a powerful tool, but it only works if you feed it with good input: garbage in, garbage out. If you know all the constraints and weights with perfect precision, then you can use logic to find the perfect answer. But when you don’t, which is almost always, there is a good chance that logic will lead you very far astray.

And this does not come from so-called soft social sciences such as economics or psychology. It comes straight from physics: the field that brought us the scientific method and allowed us to put a man on the moon.

A very small cause that escapes our notice determines a considerable effect that we cannot fail to see, and then we say that the effect is due to chance. If we knew exactly the laws of nature and the situation of the universe at the initial moment, we could predict exactly the situation of that same universe at a succeeding moment. But even if it were the case that the natural laws had no longer any secret for us, we could still only know the initial situation approximately. […] And a small error in the [initial conditions] will produce an enormous error in the [final phenomenon].

Henri Poincaré, mathematician, physicist, engineer

The animation at the beginning of this paper clearly illustrates this situation. A double pendulum made of two sections of identical length and weight, with the mass distributed evenly along the length of each section is a much simpler system than most of our industrial businesses in which hundreds of inputs affect interrelated organizations that are spread around the world.

And yet, even a slight imperfection in the initial condition of the pendulum results in a completely different, seemingly chaotic, trajectory.

Why should we expect anything different in the world of industry?

Authors: E. Dib, C. Criado-Perez #

References #
Further Reading #
 
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