Political prognosticator and analytics guru Nate Silver rose to national fame by correctly predicting elections. But in 2016, Silver joined almost every other analyst by projecting a victory for Hillary Clinton over Donald Trump. Was Silver’s good luck over?
Cognitive Bias and the “Failure” of Data
Actually, Silver’s estimate for the 2016 election was closer to correct than almost anyone else’s. He saw Clinton as a heavy favorite, but still gave Donald Trump a roughly one-in-three shot of winning. But the world didn’t remember that part of the projection once the election results came in. They just remembered the part Silver got wrong. Nobel Prize winner Daniel Kahneman has an explanation: cognitive bias.
Kahneman studied how people make decisions and judgments, and he quickly discovered that they don’t make any sense. People like to think of themselves as logical and rational, but they mostly use logic to justify believing whatever they want to believe anyway. And one thing people absolutely love to believe is that the future is certain. Human minds loathe uncertainty. Uncertainty breeds anxiety and fear—sometimes paralyzing fear. So when given a number like “one in three” or “ninety percent,” they subconsciously convert the odds to “yes” or “no.”
This cognitive bias is often very useful. You probably never consider the statistical chance that you’ll be run over by a bus because if you did, you might never leave the house. It’s far easier, and probably mentally healthier, to treat the risk of bus accidents as a 0. But the tendency to round probabilities up or down can be disastrous in the business world.
Have you told your boss that there’s a 90% chance you’ll make the sale? If the deal didn’t go through, you were probably in a bit of hot water. Has a supplier ever told you her product’s failure rate was less than 1%? You’d probably be pretty mad if your order was a dud. The problem with both of those statements of probability is that they do a poor job of communicating risk. They invite the mind’s cognitive bias to take over and convert the estimate into a certainty. When that certainty turns out not to be so certain, it feels like a broken promise.
That’s why the world decided Nate Silver was wrong. They had rounded up the probability of a Clinton victory to a guarantee. When Trump won, it felt like Silver had broken his word. His failure wasn’t in the data—it was in the way he communicated the risk.
The lesson here is that quoting numbers won’t save you.
Don’t just toss out percentages—put them in context. Visualizations are one useful technique. If a product will fail one time in a hundred, a graphic with 99 white shapes and one black shape gets the message across far more effectively than the numbers. Analogies are also effective. A 90% probability? That’s about the same as the chance that an NFL kicker will make a 32-yard field goal. Anchoring the numbers to a familiar context creates a lasting impression. It forces the mind to acknowledge uncertainty.
In business and life, people care about honesty. But if your goal is to be trustworthy, it’s not enough to state the facts. You have to make those facts sink into others’ minds. When it comes to probabilities and risks, that task is taller than it looks.