John Kay: A wise man knows one thing – the limits of his knowledge
Money and Finance

John Kay: A wise man knows one thing – the limits of his knowledge


John Maynard Keynes, who never tried to conceal that he knew more than most people, also knew the limits to his knowledge. He wrote “about these matters – the prospect of a European war, the price of copper 20 years hence – there is no scientific basis on which to form any calculable probability whatever. We simply do not know.”

And Keynes was right. He published these observations in 1921, and 20 years later Britain was engaged in a desperate, and unpredictable, struggle with Germany.

But lesser men find prognostication easier. I have been looking at some of the models people use, in both the public and private sectors to predict events.

The models share a common approach. They pose the question: “How would we make our decision if we had complete knowledge of the world?” With such information you might make a detailed assessment drawing together many different pieces of relevant information on matters such as costs, benefits, and consequences.

But little of this knowledge exists. So you make the missing data up. You assume the future will be like the past, or you extrapolate a trend. Whatever you do, no cell on the spreadsheet may be left unfilled. If necessary, you put a finger in the air.

Models are often useful in illuminating complex problems and quantification is an essential part of decision making. But good models are simplifications, not black boxes whose workings are incomprehensible even to their operators. The relevant model is always specific to the task at hand and there is no objective method of determining the right tool to employ in any particular case. If you do not know the answer to a question, the right response is not to make a number up, but to rethink and frame an alternative question that is capable of being answered.

We do great damage by claiming to know things that are not known, by asserting certainty in the face of uncertainty and ambiguity, and by attaching a veneer of rationality to decisions that have in fact been made on other, rarely articulated, grounds. The paradoxical result is all too obvious. The public sector and large bureaucratic organisations appear as paragons of good decision making process and exemplars of bad decisions.





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