NFL big data blitz: Don't punt; go for it!
American football can be perplexing to the uninitiated because of its complexity compared to the rest of the world's true football. However, that complexity does have an upside. It creates plenty of opportunities to generate statistics with which to evaluate the game.
Source: Peter McCarthy/Flickr
Statistics relating to one area of the game, punting, seem to indicate that football coaches are consistently making poor decisions by ignoring convincing data, thus hurting their team's chances of winning. A study of this issue sheds some light on why company managers similarly might be making poor decisions that undermine their businesses' chances of improving profits.
Here's the main idea: During football games there are usually many opportunities to kick the ball back to your opponent when you fail to achieve a first down. But there's statistical evidence showing such a strategy leads to fewer wins for a given team. So why do teams punt?
One explanation is tradition. Teams have almost always punted on fourth down, except at key moments, usually late in the game when a team is behind. In business situations, that translates to explaining a failed decision as: "We've always done things this way."
A more insidious answer comes from www.advancednflstats.com: "... coaches are thinking more about their job security than their team's chances of winning. Coaches know that if they follow age-old convention by kicking and lose, then the players get most of the blame. But if they defy convention and go for the 1st down and fail, even if it was the best decision, they'll take all the criticism."
As one critic of punting on fourth down noted, there's a bias by top management to favor logic over information. It's an article of faith that "... managers who fail to maximize profits for the owners of their firms are likely to be fired and replaced by ones who do. Thus the case for firm maximization rests much more on logical argument than empirical evidence."
There are three lessons for business here. First, don't punish managers who make the best decisions on the best data, but don't always succeed. Such a move will discourage future good decision-making.
Second, while established, well-understood business processes can benefit a company, if data show them to be flawed, eliminate or change them, no matter how comfortable workers are with them.
And third, if you have managers who fail to apply data to their decision making and then push the blame on workers when those decisions prove wrong, it's time to sack those managers.
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