In just about every industry imaginable, companies are exploring more data-backed ways of doing things. But there’s one field that remains stubbornly unscientific: recruitment and hiring. That’s not to say there aren’t procedures in place when it comes to résumé screening. For all but the newest startups, which have basically no precedents to abide at all, there’s usually some sort of protocol in place. The problem, though, is that the typical rules for screening candidates are driven by buzzwords that seldom identify real potential and too often play to our biases. Here’s what has to change and how to change it.
The reality that hidden biases abound in the screening process is well documented, but few companies realize just how pervasive the problem can be. A growing body of research shows we make a bunch of snap judgements starting just with people’s names–and continue from there. One widely cited study found that candidates with white-sounding names but otherwise identical résumés were 50% more likely to be called in for an interview. Similar studies of résumés have uncovered significant gender bias favoring men, in such disparate fields as science and music.
It isn’t that holding certain prejudices is inherently wrong. Our brains rely on a whole host of implicit associations as cognitive shortcuts for everyday life. Without them, we’d be terrible at making decisions. But that can really scramble the résumé screening process, and there’s now even a growing industry around helping companies detect unconscious bias and weed it out from the get-go.
Some level of screening is vital in most companies, but even low-tech solutions can make a big difference. Simply having administrators black out candidates’ names and addresses before they’re reviewed by hiring managers is one surprisingly effective, easy place to start.
Keyword-driven résumé screening is especially fraught when it’s delegated to those who don’t understand the technical skills they’re screening for. That’s especially true in growing fields like data science, for instance. A human resources screener could be screening for “Hadoop” yet miss a great candidate who lists with experience tuning “Mesos” and “YARN.”
But sometimes the reverse problem is even more common. At Foursquare, we found it relatively easy to interview people with résumés full of all the right buzzwords who didn’t really understand what they meant. In other words, those candidates were anticipating a buzzword-driven screening process and loaded their applications up with them in order to get a foot in the door.
Spending hours interviewing candidates just because they triggered the right buzzwords is emotionally draining, not just for candidates but for hiring managers, too. And can really bring down morale during a tough hiring process.
Even if our snap judgements don’t typically fall along race or gender lines, we can make other assumptions about them that can be just as damaging–for instance, based on where someone went to school, the companies they’ve worked for, or even the places they’re from. Strong performers come in all stripes and don’t share common backgrounds.
Think of it this way: If all your software engineers are Stanford computer science majors, they’ve all taken classes from the same professors, completed the same problem sets, and been trained to think in much the same ways. If all your product managers come from Google, they’re accustomed to a certain set of business models and a certain set of tools. Neither of these backgrounds is bad (in fact, they’re both coveted pedigrees), but uniform experiences in any organization are limiting.
Just as you would diversify your stock portfolio, you should diversify your talent portfolio to give your company the broadest set of tools to solve problems.
It’s tempting to hire candidates who can solve your immediate needs. After all, we want employees to be productive right out of the gates. Want to build a project around product name recognition and customer loyalty? Hire that all-star marketing PhD who wrote a dissertation on brand recognition. Need to start marketing to small and midsize companies in the Midwest? Hire an advertising professional who’s worked with those sorts of accounts for a decade.
But the trouble comes when the business needs to change. What happens when we realize that customer service, not branding, drives customer loyalty? What happens when the target customer base moves from the Midwest to the Northeast–or overseas? Don’t be myopic in your hiring process. The smartest and most nimble managers look for smart, well-rounded thinkers who can adapt to rapidly evolving business needs. That way, when the problems change–and they will–the company won’t be weighed down by highly specialized experts in the wrong fields.
Résumés can provide a quick summary of a candidate’s qualifications. As a result, they’re a useful shorthand for HR professionals–who in most cases don’t have the same domain expertise as hiring managers–to quickly filter candidates. In many cases, that works just fine. But the shortcomings are getting more apparent the more quickly companies change and come to terms with the reality of unconscious bias. Ultimately, there’s no substitute for experience and judgement, and digging deeper means first getting over our reliance on buzzwords.
Michael Li is the founder of The Data Incubator, an elite fellowship program that trains and places data scientists and quants with advanced degrees into industry roles. He formerly served as a data science lead with Foursquare and with Andreessen Horowitz.