SFW: Analytics Are Improving the Way We Hire and Fire People
Moneyball transformed baseball. Now the same data-driven analytics and statistical models are coming to a human resources department near you. And they might just effect whether you get hired, fired or promoted. The big boys -- Google, Intel, etc. -- have already adopted this approach, and now smaller companies are finding their interest piqued as well.
Coming to your HR department
What is the problem companies are trying to solve? Well, we are not very good at hiring people. The typical interview process is not a good way to determine whether a person will be a good employee.The Atlantic's Don Peck writes:
Examples of bias abound. Tall men get hired and promoted more frequently than short men, and make more money. Beautiful women get preferential treatment, too--unless their breasts are too large. According to a national survey by the Employment Law Alliance a few years ago, most American workers don't believe attractive people in their firms are hired or promoted more frequently than unattractive people, but the evidence shows that they are, overwhelmingly so. Older workers, for their part, are thought to be more resistant to change and generally less competent than younger workers, even though plenty of research indicates that's just not so. Workers who are too young or, more specifically, are part of the Millennial generation are tarred as entitled and unable to think outside the box.
But it doesn't stop there: make sure your parents named you correctly:
For a 2004 study called "Are Emily and Greg More Employable Than Lakisha and Jamal?," the economists Sendhil Mullainathan and Marianne Bertrand put white-sounding names (Emily Walsh, Greg Baker) or black-sounding names (Lakisha Washington, Jamal Jones) on similar fictitious résumés, which they then sent out to a variety of companies in Boston and Chicago. To get the same number of callbacks, they learned, they needed to either send out half again as many résumés with black names as those with white names, or add eight extra years of relevant work experience to the résumés with black names.
So, if you're a short man, a good-looking female cursed with breasts too large, old or very young, or have a Black-sounding name, the new "Moneyball" approach to hiring, firing and promoting might be good for you.
I say this partially tongue-in-cheek. More seriously: the relevant psychological research shows -- as distilled above -- that we routinely rely on cognitive biases rather than sensible reasons for hiring or promoting people. Thus, "big data" is helping to improve this process. Let me give one small example: a person's GPA is not considered by data-friendly companies more than two years after graduation. Why? Because it does not correlate with being a productive employee.
While there may be some discomfiting aspects of all this -- indeed, novelist Dave Eggers recently wrote a book about the dystopian possibilities where a company ranks employees based solely on data -- it is probably, overall, a good thing.
Look at this way, in the face of a recent Brookings Institution report which shows that those born rich are likely to stay rich no matter if they are of "modest skill" (the "Glass Floor" the authors call it), and the implications of Chris Hayes' thoughtful book, Twilight of the Elites: America After Meritocracy (the elites have essentially pulled the ladder up after them so few else can climb it), the new analytics might be a boon for the smart go-getter who didn't have the luck to be an Ivy League legacy or born into wealth. Indeed, this might be the start of placing some substantive heft back into the idea of the American Dream. We can at least hope.