People analytics: ‘Moneyball’ for human resources

Lord knows it’s expensive and time consuming, and even when they get it, it’s not clear how much students actually learn. But the one thing you could always say about a college degree was that it led to better jobs because it served as a reliable and invaluable signal to employers about a job applicant’s intelligence and persistence.

Or maybe not. Michael Rosenbaum knows from fancy degrees — he’s got a BA and law degree from Harvard, along with a master’s from the London School of Economics. But at the two software companies he has founded in Baltimore, 40 percent of the programmers have no college degrees, and half of the others got theirs from community colleges. The reason is simple: Statistically speaking, a degree from a fancy college has zero correlation with success in writing software.

Such are the insights from “people analytics,” a hot new area in human resource management that aims to bring “big data” to the task of corporate hiring and promotion. What “moneyball” did for baseball, people analytics promises to do for human resources, replacing intuition, old-boy networks and outmoded rules of thumb with computerized tests, database searches and quantifiable performance metrics.

Given the time and money companies sink into hiring and recruitment, the results are decidedly mediocre. According to a survey conducted by Arlington-based Corporate Executive Board, nearly a quarter of all new hires leave within a year, while Gallup reports that half of those who do stay reported being “not engaged. The resulting drag on profits and productivity represent a multibillion dollar opportunity for firms such as Rosenbaum’s Pegged Software, which helps hospitals and nursing homes reduce turnover of entry-level workers by putting the right people in the right jobs.

What’s surprising isn’t that companies are beginning to use more objective techniques to make personnel decisions, says Peter Cappelli, a professor at the University of Pennsylvania’s Wharton School of Management. “What’s surprising is that, for the last 20 years, they’ve been going with their gut.”

In the early versions of “people analytics,” companies asked managers to identify their best-performing employees and then tried to find patterns in each group based on biographical information, work history and their answers to computerized personality and intelligence tests. Job applicants were then “scored” based on how closely their background and test answers matched those high-performing employees.

Rosenbaum says the problem with the early efforts is that the results tended to correlate less with the actual strengths of the job candidates than with their cleverness in taking the tests. And by relying on the managers’ rating of current employees, the process reintroduced a high degree of bias and subjectivity into the scoring system.

See entire article at:  Moneyball

 

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