Big Data Doesn’t Make Sense for Headhunters
That’s the view of Nick Corcodilos, writing at PBS.org. Corcodilos, author of the website AsktheHeadunter.com, penned special advice for the Making Sense section of PBS’ Newshour’s website.
He wrote, ” America’s employment system is getting even more automated and algorithm-ized by applying ‘big data’ to process you. According to [an article] in The Atlantic (“They’re Watching You At Work” by Don Peck), the vice president of recruiting at Xerox Services warns that, ‘We’re getting to the point where some of our hiring managers don’t even want to interview anymore.’ According to the article, ‘they just want to hire the people with the highest scores.’”
Peck’s article proclaims, “Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed. You can now find dedicated analytics teams in the human-resources departments of not only huge corporations such as Google, HP, Intel, General Motors, and Procter & Gamble, to name just a few, but also companies like McKee Foods, the Tennessee-based maker of Little Debbie snack cakes.”
Corcodilos says, “… more data about irrelevant behaviors don’t make better predictions. In fact, it makes things worse if the data are not valid predictors of success. It’s worse because indirect assessment leads to false negatives (employers reject potentially good candidates) and to false positives (they hire the wrong people for the wrong reasons).”
In his article, Peck argues that big data may not be entirely a bad thing because it eliminates discrimination based on gender or race. “Perhaps the most widespread bias in hiring today cannot even be detected with the eye. In a recent survey of some 500 hiring managers, undertaken by the Corporate Executive Board, a research firm, 74 percent reported that their most recent hire had a personality ‘similar to mine,'” he wrote in his article.
He adds, in slamming those hiring practices, “Given this sort of clubby, insular thinking, it should come as no surprise that the prevailing system of hiring and management in this country involves a level of dysfunction that should be inconceivable in an economy as sophisticated as ours. Recent survey data collected by the Corporate Executive Board, for example, indicate that nearly a quarter of all new hires leave their company within a year of their start date, and that hiring managers wish they’d never extended an offer to one out of every five members on their team.”
Corcodilio isn’t necessarily buying all that Peck has to say, “I don’t think Peck wrote this article to promote ‘people analytics’ as the solution to the challenges that American companies face when hiring, but he does seem to think the Kool-Aid tastes pretty good. I think Peck over-reaches when he confuses useful data that employers collect about employee behavior to improve that behavior, with predictions based on silly big data assumptions.”
To further bolster his argument against big data as an effective hiring tool, Corcodilo quotes Arnold Glass, a leading researcher in cognitive psychology at Rutgers University. Glass said, “It has been known since Alfred Binet and Victor Henri constructed the original IQ Test in 1905 that the best predictor of job (or academic) performance is a test composed of the tasks that will be performed on the job. Therefore, the idea that collecting tons of extraneous facts about a person (big data!) and including them in some monster regression equation will improve its predictive value is laughable.”
He concludes his piece by saying, “One could easily make the case that employers today are afraid of making judgments and hiring mistakes, and too easily seduced by big data in the service of plausible deniability.”