Data Insight, Reputational Risk, and Bill Belichick: Sports Analytics & Business Analytics, Part II
by Brian Timoney
Can everyone immediately cite your worst professional decision?
If you’re 3-time Super Bowl champion and coaching mastermind Bill Belichick, any moderately savvy NFL fan would blurt out “4th and 2“.
Go for it on 4th-and-2 on your own 29 yard line with 2:08 remaining or punt to the Colts and give Peyton Manning the opportunity to march down the field? Given the Colts had only one timeout, a first down would almost guarantee victory.
Belichick went for it; they didn’t make it; the Colts march in from the short distance to win the game.
And by most accounts, the odds were in his favor.
Insight Is Not Cost-Free
So if widely respected championship coach can get crucified for playing the percentages in a non-traditional way (during a regular season game in November), why are you surprised when your precious analytic insights that have even a whiff of the counter-intuitive fail to gain traction?
Statistical reasoning is abstract; middle-management reputational risk is very real, very immediate.
We can all applaud the “democratization of data” and tools that empower analysis-for-everyone. But if that means the status quo is at risk, well then, that’s a whole different conversation. A conversation that’s typically the province of well-dressed, well-paid consultants rather than, say, you the underling who is a bit brighter than the good folks you report to.
Or else it’s the rare don’t-give-a-damn outsider like “The Coach Who Never Punts“.
Probabilistic Thinking In A Binary World
The most entertaining side-show of the 2012 Presidential election was the dust-up between Nate Silver and TV host Joe Scarborough when the latter decried anyone who declared that the race was anything but a 50-50 proposition. Silver, of course, was drawing massive page views at the New York Times with his daily calculations of election probabilities using a large dose of Bayesian methods. The revelation was that putatively intelligent people such as Morning Joe much prefer thinking about outcomes in binary/yes-no/Manichean terms rather than as shifting set of probabilities. Especially when it pertains to a topic in which they are emotionally invested.
So when pitching a middle-manager on workflow improvements that have an 83% chance of success, you think you’re saying “pretty good odds” when in fact what they are hearing is “it might not work.”
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“Moneyball” has become the fashionable pop culture short-hand for analytics-driven decision making: but recall even Brad Pitt and his good looks encountered institutional resistance.
Without Brad’s good looks and Bill’s Super Bowl rings, what are you to do?
Spend as much time analyzing your organization’s culture as its data.
—Brian Timoney