It’s telling that Wall Street Journal ran an article about Moneyball and HR at around the same time the movie hit dollar theaters, because most of the folks that read it felt that it was fairly close to worthless. In the hopes of catching the big data tidal wave, many HR practitioners are using the buzz word without really grasping the meaning of the trend or what it means for our industry. Data and analytics have always been part of the HR technology arsenal. Big Data is a completely new trend and one that the industry needs to be trained for and through:

The big data revolution is just beginning to penetrate the HR industry, said Josh Bersin, chief executive and president of Bersin Associates. Some companies have a progressive view of how data analytics can help their HR departments. Most don’t. “Of the companies we talk to, five to 15% are very sophisticated at analyzing people data,” he said.

Part of the reason for the belated hype is Billy Beane’s appearance at the TLNT Transform conference, where, by all accounts he dazzled and thrilled the audience. However, it was Dwane Lay, who finally pinpointed why Moneyball (and the allusion to big data behind it) is important to HR. As Lay points out, the key is not running the numbers or running around screaming about “big data!”, it’s learning how to use that to attract and retain the best talent. “It’s about finding hidden value that no one else is going after and capturing it for yourself,” writes Lay:

If HR were to truly adapt the Moneyball approach, here are the kinds of things you would see…New ways to source talent, new ways to use talent, new ways to get the most from your resources. The statistics make it go, but they are enablers, not the focus of the approach.

Jason Averbook of Knowledge Infusion feels differently. His take on the Moneyball article in WSJ and the book and movie (is it too soon to start calling it a business philosophy?) was radically different, while Lay pointed out using statistics as the engine to discovering previously unheeded value within the organization (or while scouting to stick with the sports metaphor), Averbook paid close attention to the short quote in the WSJ article that mentioned financial risk modeling and asks (as Capital One has), why can’t HR use this data the same way?

Here is the real lesson of Moneyball thinking.  It isn’t the decision that we make, it is the decision we DIDN’T make that we need to reexamine.  Take internal mobility, for example.  We might pass on a dozen or so equally qualified employees for an advancement opportunity, in favor of an individual we feel has the “stuff” of leadership.  Our pick has demonstrated the characteristics we value, like willingness to make decisions, or openness, or risk taking, whatever.  But we have no real way of knowing if any of these attributes actually make better leaders, we just believe they do.

So what’s the answer? Understanding big data is not a requirement for being a competent HR professional. Understanding there may be value in the implications for your organization, that IS a requirement. If you are locked in a battle for excellent talent, and you don’t have a serious budget, “crunching the numbers” of your employees isn’t the worst idea. Assuming that because you have the data you know what to do with it? That’s a bit of a farce.

Perhaps Tim Sackett got it right in his (one of the first) posts about Moneyball where he (and I am paraphrasing here) writes that production wins over pedigree, change is very often necessary and you have to give it to employees straight. Now that’s an HR lesson!



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