4 Lessons From Nate Silver's Election Predictions

11/06/2012 11:46 am ET | Updated Jan 06, 2013
  • Inc. Magazine



By Erik Sherman, visit Inc.

Unless you've been safely ensconced in a media-free hideaway, you've probably heard of Nate Silver, the predictive phenom who writes the FiveThirtyEight blog for the New York Times. Controversy has flourished because of the now 86% odds he gives Obama for winning the presidential election.

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A lot of people, including Times conservative columnist David Brooks and MSNBC personality and former politician Joe Scarborough, disliked Silver's air of certainty about what they think is an uncertain process, and said so loudly. Then, of course, came the defense of Silver in other parts of the media.

Put politics aside for the moment. There are some important lessons in this discussion for entrepreneurs who are interested in what you could call "big data." As in predicting elections, in running a business it's easy to follow the path of many partisans and pundits and make fundamental mistakes about how to add up the distribution of risk and spot legitimate opportunities.

Lesson # 1: Prejudice doesn't trump prediction.

The fundamental issue around the current predictive controversy is that critics largely misunderstand what Silver is doing. They might want to believe that you can't use math to predict human action. But I disagree: At any time, you may be able to see trends that give you an insight into what will happen.

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The book Moneyball, which chronicles one baseball club's success in using statistics to cost-effectively run a team, is a perfect example. The talent market in the game was hugely inefficient. Teams put premiums on talents or aspects that satisfied managerial assumptions and prejudices, but that didn't necessarily result in better performance. At the same time, capabilities that showed a statistical impact on the game over time were undervalued.

Don't assume that there are no hidden patterns in your industry or business. What do you think the whole "big data" concept is about?

For the remaining lessons, continue reading at Inc.

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