Applying spreadsheet maths to consumer behaviour is folly

Max Planck, the German theoretical physicist, had a friend who was an economist. “Why don’t you turn your mind to economics, Max?” the friend once asked.

“I couldn’t,” he replied. “The maths is too difficult.”

This is a rather surprising answer. Planck was the father of quantum theory and a mathematician of rare genius. As one contemporary economist remarked, he could have mastered all the mathematical theory in conventional economics in a couple of days. While juggling and playing the piano. So what could he possibly have meant by “too difficult”

What Planck realised, which many economists still don’t, is that there is a degree of complexity to human behaviour, and therefore economics, that simply does not allow for simple mathematical models.
In any system where feedback applies, you enter a completely new level of maths.

Take, for example, one of the simplest feedback devices: the steam regulator. You will have seen these things, typically two brass balls orbiting a central spindle, at any good industrial museum. The idea here is notionally simple. If you want a steam engine to move at a consistent speed, you must have a device which compensates for periods of higher or lower steam pressure. When the engine moves faster, the balls orbiting the spindle move faster too, exerting centrifugal force on a control device, which reduces the supply of steam to the piston. And vice versa.

What could be simpler? Install one and you will enjoy instant equilibrium – or what cyberneticians call homeostasis. In reality the process is never that simple. Long after the death of James Watt, such systems could only be designed by trial and error. A miscalibrated steam regulator could cause the engine to behave erratically, periodically accelerating wildly or slowing to a stop (there are probably parallels here with regulation of financial markets).
Until the mid-19th century, the processes involved were beyond computation. Finally, a series of equations were developed which made some sense of how regulators worked. It was then another couple of decades before they could be practically applied.

The person who developed the equations was James Clerk Maxwell – probably the greatest mathematical genius of his age and ranked by Albert Einstein alongside Newton and Faraday as one of the all-time greats in physics.  So the next time some scrote from the finance department with a B in GCSE Maths wanders into the marketing department and demands that your marketing activity should be more accountable, maybe he is the idiot, not you.

Let’s take the ‘value of a brand’. A brand affects how much you sell of a product, to whom, how often and at what price. But that is not all. It affects your relationship with suppliers, whom you recruit, how hard they work, what they are paid and how long they stay. Most of all, it affects how your competitors behave. So when you are asked to develop a system of marketing where the value of every intervention can be known and evaluated in terms of its precise contribution to your bottom line, the only scientifically valid response is Max Planck’s: “I’m sorry, but the maths is too difficult.”

A simple analogy might be sport – another example of a complex system in a competitive environment. There are certainly cases (Michael Lewis’s book Moneyball describes one) where the use of measurement and big data can uncover biases and irrationalities in the marketplace. These are very useful insights. They suggest what you might sensibly try. But they cannot perfectly predict the result of trying it. In sport there is only one really reliable statistical truth – ‘home advantage’. Even then, people do not fully understand why playing at home yields such a benefit (crowd support? Not needing to travel? Familiarity with the stadium and the pitch?).

They simply know it is true. Perhaps we should not, at times, be afraid to present similarly vague findings: “On the whole, for many businesses in many categories, it is a lot better to be famous than not.” The urge among people trained in finance is to reduce everything to the level of a spreadsheet, as if business were a simple mechanical device. In many parts of business this may be a helpful approach.  If your procurement function reduces the price it pays for coffee cups, this may be treatable as a simple maths equation (though the FT’s John Kay would disagree even with this). But attempting to apply spreadsheet maths to customer behaviour may be a folly.

Next time someone asks you to do this, don’t apologise or bow down: direct them to the Santa Fe institute, where the Nobel Prize winning physicist Murray Gell-Mann is leading a five-year research study into complexity theory. If he finds the maths difficult, it’s fair to say that your finance department will too.

Rory Sutherland is vice-chairman of OgilvyOne