It’s been almost 15 years since Moneyball was published, but its repercussions are still being felt through baseball. Bloomberg’s republishing today of an August 2014 article on Jeff Luhnow, Houston’s data analytics guru, discusses how he implemented Moneyball-like innovations – first for Saint Louis, then for Houston.
Sports Illustrated went even further earlier in 2014, declaring the Astros the 2017 World Series champions in an especially impressive act of clairvoyance.
Teams in baseball relying on “big data” continue to show benefits when it is properly implemented and adhered to. This help for mid- or low-tier teams can narrow the gap against the “big money” teams who have much larger wallets and thus a larger margin for error.
In media also, big data is being used to narrow the gap between smaller and larger media properties, whether used to drive better targeting, higher ROI of advertising, or developing programming. But as with baseball, data doesn’t guarantee outcomes – human choices and dumb luck can negate all the predictive data.
There is also the consideration that baseball is pretty much a series of one v. one interactions – the pitcher v. the batter; the outfielder v. the ball in flight; the infielder throwing to another player. It is unlike football, where to have a successful play, you need the line to block; the quarterback to throw; the receiver to run his route; and all of that is being done with the other team trying to interfere.
Media is much more like football than baseball; it is a complex interaction of many factors that boil down to whether a consumer is watching your commercial on the program you bought it on (or watching your program on your subscription service). So while big data can certainly address many issues, the humans in the loop will still be important for many years yet.
David Tice is the principal of TiceVision LLC, a media research consultancy.
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