Searchlight

Don't overvalue predictive ability of data-crunching

Karen Goulart, Senior Features Writer

Albert Pujols is no Pablo Picasso. No offense intended to Pujols -- for what it's worth, I don't think Picasso could've pulled off three MVP seasons. But it seems pretty clear that Pujol's genius, unlike Picasso's, has a shelf life. And that's pretty much the point I'm looking to make in this week's Searchlight.

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Karen Goulart

In this this week's lead item, MIT Sloan fellow Michael Schrage applies the famous data-crunching analytics of Moneyball to businesses outside the wide, wide world of sports. He asks his readers if they really believe that "a 50-year-old marketer with a terrific track record is immune from the same economic and analytic forces affecting the career of a 40-year-old pro athlete who was a two-time all-star?"

For me, the whole Moneyball mantra -- that a person's potential can be based on hard numbers and carefully constructed algorithms -- stands up well enough when we're talking about ballplayers. We can map and analyze and calibrate athletic performance and make predictions about how an individual's performance might impact the outcome of a well-understood exercise -- like a ballgame. Mapping the human brain, as recent news from the White House suggests, however, remains for the most part uncharted territory. What's the algorithm for measuring creativity? Picasso codeveloped cubism while in his 20s and 30s. In his 80s, the world would later realize, he discovered neo-expressionism. And he had a few creative ideas in between.

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Unlike in athletics, where one's body of work relies on one's literal body, in "real world" professions, the physical body is not necessarily the rate-limiter. If I'm New England Patriots owner Robert Kraft and I don't want to pay Tom Brady the way I used to pay him, that makes some sense. Tom Brady at 35 (while pretty damn good) is not Tom Brady at 25. But the people in your company, the ones who are still here not only because they're loyal, but because they too are damn good, are arguably going to be better at 35 than 25 and better still at 45. Presumably they're still here because they've been adding value to your business over the years, becoming team leaders, sharing their knowledge, innovating and doing good work. Using analytics to gauge the usefulness of employees on an age curve to predict how much they'll help your business seems a reasonable exercise to Schrage, who writes, "Think of it as Six Sigma predictive analytics for talent." Sure, think about it -- but given how little we know about what makes our brains tick, I'd hold off on sending HR a list of rejects.

If you're tired of sports analogies, this week's Searchlight also includes Amazon's next step in its plan to take over the world, call-center cyberattack nightmares, the unsettling new Facebook Home and more.

  • Moneyball analytics is great for sports, but does it work in the business world?
  • It would be nice to hear that some people still opt to reach out by phone these days, except that in this case, the people reaching out are trying to extort money from you as part of some scary telephony denial-of-service attacks.
  • Data scientists participating in a contest have created an algorithm that helped commercial airlines reduce flight delays. I may not fully understand you, big data, but I love you.
  • If you haven't perfected mobile security or your BYOD policy, you're not alone. This is, of course, cold comfort when you realize you're in the company of the U.S. Army.
  • Going forward, you might not have to worry so much about employees in your business going rogue and downloading Dropbox. The bad news is, that's because you now have to worry about employees going rogue and downloading the better, cheaper Amazon equivalent. Bezos!
  • Everyone's talking about the new Facebook Home for Android phones! Will it introduce new security threats* or just help decrease worker productivity? This Wired piece tells you all about it. (*Skip to the 11th paragraph and see if you don't get a little freaked out.)

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Should data-crunching "Moneyball" style analytics be applied to employees in regular businesses?

Karen Goulart, Senior Features Writer
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