Justin Bariso published a fun article in Inc. He wrote about chess grandmaster Maurice Ashley’s favorite approach to problem-solving: working backward.
In other words, Ashley recommends envisioning what you want the chess board to look like near the end of the game. Then, you choose moves that steer you toward that destination.
Note, this approach is different than making the absolute best move right now. You’re not working move-to-move. You’re working with a specific endgame in mind. You might make sacrifices and compromises now, to get to a favorable, well-understood position later.
Working backward doesn’t just help you solve problems. It also helps you create forecasts. It’s something I picked up by watching a lot of sports.
After a big game, I’d inevitably find some article, from some sports reporter, that made the outcome of the game seem inevitable. Of course one team was going to exploit some well-known advantage against an inferior adversary. Why couldn’t we have seen it in advance?
I heard the same thing listening to people who bet on sports. After placing a losing bet, they’d lament that, of course, they should have foreseen the outcome. The team that won was “hot” coming into the game. How could they have missed that piece of information when they placed their bet?
And all of that is nonsense. Nassim Taleb writes about this idea extensively in his book The Black Swan. After the fact, all events seem predictable. But they aren’t.
So I played a little game. Before a big sporting event, I imagined two different outcomes, where each team won once. Then I tried to build an explanation for why each team won. Then I’d decide which explanation seemed more plausible. That’s how I’d predict who would win.
It turns out, spending time thinking in detail about the end game is incredibly helpful. It forces you to remove yourself from the status quo. You have to imagine a new reality, where one of a finite number of outcomes has emerged. As you list the conditions necessary to support that outcome, you get a feel for what seems reasonable.
Practice enough times, and compare against reality after the fact, and you’ll get a good idea of where your biases are. You’ll see how you fool yourself. You’ll see what kinds of variability you tend to ignore.
I described examples from sports above. But the same thing works for forecasting commodity prices. Or stock prices. Or elections.
What would have to happen for the stock market to increase in value by 30% or more this year? What would have to happen for it to fall by the same amount?
We’re living in interesting times. Very few people forecasted the crash in oil prices over the last couple of years. Very few people forecasted Donald Trump winning the Republican presidential nomination. If they had imagined those outcomes in advance, and forced themselves to describe what would had to have happened, they might have discovered their own cognitive gaps.
Next time you choose, or are forced, to make a prediction, don’t just make the prediction. Think about what the world would look like if things went one way versus another. As you zoom out, and imagine the whole environment, you might get a better perspective on how reasonable your expectations are.