“Prediction is very difficult,” the old chestnut goes, “especially about the future.” And for years, social science agreed. Numerous studies detailed the forecasting failures of even so-called experts. Predicting the future is just too hard, the thinking went; HBR even published an article about how the art of forecasting wasn’t really about prediction at all.
That’s changing, thanks to new research.
We know far more about prediction than we used to, including the fact that some of us are better at it than others. But prediction is also a learned skill, at least in part — it’s something that we can all become better at with practice. And that’s good news for businesses, which have tremendous incentives to predict a myriad of things.
The most famous research on prediction was done by Philip Tetlock of the University of Pennsylvania, and his seminal 2006 book Expert Political Judgment provides crucial background. Tetlock asked a group of pundits and foreign affairs experts to predict geopolitical events, like whether the Soviet Union would disintegrate by 1993. Overall, the “experts” struggled to perform better than “dart-throwing chimps”, and were consistently less accurate than even relatively simple statistical algorithms. This was true of liberals and conservatives, and regardless of professional credentials.
But Tetlock did uncover one style of thinking that seemed to aid prediction. Those who preferred to consider multiple explanations and balance them together before making a prediction performed better than those who relied on a single big idea. Tetlock called the first group foxes and the second group hedgehogs, after an essay by Isaiah Berlin. As Tetlock writes:
The intellectually aggressive hedgehogs knew one big thing and sought, under the banner of parsimony, to expand the explanatory power of that big thing to “cover” new cases; the more eclectic foxes knew many little things and were content to improvise ad hoc solutions to keep pace with a rapidly changing world.
Distinguish as sharply as you can between the known and unknown. ...
Adopt the outside view and put the problem into a comparative perspective that downplays its uniqueness and treats it as a special case of a wider class of phenomena.
Answers & Comments
“Prediction is very difficult,” the old chestnut goes, “especially about the future.” And for years, social science agreed. Numerous studies detailed the forecasting failures of even so-called experts. Predicting the future is just too hard, the thinking went; HBR even published an article about how the art of forecasting wasn’t really about prediction at all.
That’s changing, thanks to new research.
We know far more about prediction than we used to, including the fact that some of us are better at it than others. But prediction is also a learned skill, at least in part — it’s something that we can all become better at with practice. And that’s good news for businesses, which have tremendous incentives to predict a myriad of things.
The most famous research on prediction was done by Philip Tetlock of the University of Pennsylvania, and his seminal 2006 book Expert Political Judgment provides crucial background. Tetlock asked a group of pundits and foreign affairs experts to predict geopolitical events, like whether the Soviet Union would disintegrate by 1993. Overall, the “experts” struggled to perform better than “dart-throwing chimps”, and were consistently less accurate than even relatively simple statistical algorithms. This was true of liberals and conservatives, and regardless of professional credentials.
But Tetlock did uncover one style of thinking that seemed to aid prediction. Those who preferred to consider multiple explanations and balance them together before making a prediction performed better than those who relied on a single big idea. Tetlock called the first group foxes and the second group hedgehogs, after an essay by Isaiah Berlin. As Tetlock writes:
The intellectually aggressive hedgehogs knew one big thing and sought, under the banner of parsimony, to expand the explanatory power of that big thing to “cover” new cases; the more eclectic foxes knew many little things and were content to improvise ad hoc solutions to keep pace with a rapidly changing world.
Answer:
What helps in making predictions reliable?
How to Make Accurate Predictions
Unpack the question into components.
Distinguish as sharply as you can between the known and unknown. ...
Adopt the outside view and put the problem into a comparative perspective that downplays its uniqueness and treats it as a special case of a wider class of phenomena.
Explanation: