Data-Driven HR

Greg Beato digests the news that “work force analytics consultants can now determine what attributes and propensities are associated with success in a given position”:

Employees who live within 10 minutes of the office may be 20 percent likelier to stay at the company at least six months than ones who live 45 minutes away or further. Employees who have a college degree may be less inclined to stick with a call-center job than those who do not. According to The Wall Street Journal, Evolv, the company assisting Xerox in its recruitment efforts, determined that the ideal candidate to staff the company’s call centers “uses one or more social networks, but not more than four.”

Beato finds “liberating, empowering aspects to this kind of data analysis”:

For example, by analyzing thousands of work histories, Evolv determined that there is “very little relationship between the number of jobs an employee has held and their current tenure,” and that “companies that screen out job hoppers and the unemployed have been needlessly limiting their candidate pool.” Even more strikingly, Evolv suggests that while many companies refuse to hire applicants who have criminal records, including some who have only been arrested, its analysis shows that “crimes committed before a person entered the workforce had no predictive value for any counterproductive workplace behaviors,” and that “people with records who stay arrest-free for four to five years are only as likely as the average person to be arrested again.”