Tyler Cowen points to yet another story today about how HR departments are using big data to hire and manage employees, and it's fairly interesting throughout. However, my appreciation for the power of this approach was certainly enhanced when I read the following:
For Xerox this means putting prospective candidates for the company’s 55,000 call-centre positions through a screening test that covers a wide range of questions....The results are surprising. Some are quirky: employees who are members of one or two social networks were found to stay in their job for longer than those who belonged to four or more social networks (Xerox recruitment drives at gaming conventions were subsequently cancelled). Some findings, however, were much more fundamental: prior work experience in a similar role was not found to be a predictor of success.
This was something I always scratched my head about back when I was a hiring manager. Obviously you want someone with work experience that's related to the job you're trying to fill, but an awful lot of my fellow managers seemed pretty obsessed with finding candidates with almost identical experience. I understood the attraction of hiring someone who seemed like they could be slotted in immediately and hit the ground running, but it still seemed misplaced. Which would you rather hire? Someone fairly good with exactly the right experience, or someone really good who might take a month or two to learn some new things? I'd choose the latter in a heartbeat.
On the other hand, I suppose valuing experience highly might be a good idea if you really had no faith in your ability to distinguish good from really good. And the truth is that most of us probably don't. So maybe finding perfect fits makes more sense than I gave it credit for. After all, back in the Middle Ages we didn't have access to Xerox's whiz-bang big data.