The Perils of Prediction

This morning I watched a 1970’s NASA video that envisioned a 10,000-person space city more than a mile in diameter called ‘Taurus’.  I expected a good laugh, but what I found instead was a nearly plausible story of how a space city could be built and sustained.  Food would be grown using abundant sunlight and optimal conditions (no storms or floods) in just 100 acres of farmland. Supplies for building would come from the moon, as it is closer than earth, the difference in gravity and abundance of ‘good material’. The images of life in the space city, were surprising modern, not retro or ‘sci-fi’. Yet for all its plausibility, the prediction that Taurus would be achieved by the year 2000 is laughably off target.



Everything Is Obvious* Once You Know the Answer

Envisioning any future event, even the weather, is fraught with traps.  In his book,  Everything Is Obvious *Once You Know the Answer”, Duncan Watts tells of a management scientist name Steven Schnaars who tried to…

“…. quantify the accuracy of technology-trend predictions by combing through a large collection of books, magazines, and industry reports, and recording hundreds of predicitons that had been made during the 1970s. He concluded that roughly 80 percent of all predictions were wrong, whether they were made by experts or not.”

Watts’ book is dedicated to helping his readers understand why predictions are so difficult. He concludes that the difficulty with prediction is knowing what we should be predicting.  Generally we get it wrong because it’s hard to tell what is most relevant.  In the chapter titled, “The Dream of Prediction”, he writes:

“When I was young, many people believed that the future would be filled with flying cars, orbiting space cities, and endless free time. Instead, we drive internal combustion cars on crumbling, congested freeways; endure endless cuts in airplane service, and work more hours than ever. Meanwhile, Web search, mobile phones, and online shopping — the technologies that have, in fact, affected our lives — came and more or less out of nowhere.”

The key to prediction is understanding what is relevant. It turns out that knowing what is right or wrong is less important than knowing what matters.

Many outcomes seem obvious in retrospect. The difficulty with prediction  is in knowing what predictions really matter.  So many things ‘could’ happen that identifying the important outcomes from the irrelevant is nearly impossible. How would anyone know that terrorists would use boxcutters to hijack a plane, that a 1990’s start up called Google would make it’s investors a fortune?

Knowing what matters is the fundamental insight behind Taleb’s idea of ‘Black Swans’ – rare events that carry great import when they do happen.  There are many unusual events, but not all are very important. According to Watts, it is this fundamental distinction of ‘importance’ that makes future prediction so difficult. In his words, “The apparent obviousness of past events tempt us into thinking that we ought to be able to anticipate which events will be important in the future.’

As marketers, we are routinely asked to predict the future. Our skill in making those predictions does not lie in the ability to say what unlikely events will happen in the future. Rather it relies on our ability to discern what matters to consumers. Knowing what matters  helps us make better predictions because it is a market’s likely response to events that is significant, not the event itself. Many events themselves are fairly obvious and even likely.

Yet predicting the the future precisely is difficult because relevance can be even more difficult to predict than events themselves. After all, it was fairly obvious (in retrospect anyway) that Apple would have introduced another device. But it’s relevance and transformative effect are much more difficult to predict.

The future of Millennial trends and predictions

Making predictions about Millennials is not that difficult. They will grow older, have more income, start families, pay down their debt, take vacations, buy life insurance and worry about sending their children to college. The question is not whether these events will happen, but what will be relevant to them as they make decisions and respond to the inevitable ‘black swan’ events of their lifetimes.