How Big Data Will Mean the End to Job Interviews

Companies will rely more and more on analyzing mountains of data to determine who’s the best fit for a job

Who makes a good call center worker? Big Data knows.
Who makes a good call center worker? Big Data knows. Photo courtesy of Flickr user State Farm

I have good news and bad news for anyone who will be looking for a job in the coming years. The good news is that some time in the future, job interviews may go away. Okay, maybe some companies will still do them for the sake of tradition, but they won’t matter all that much.

Which leads me to the bad news–Big Data is more likely to determine if you get a job. Your dazzling smile, charming personality and awesome resume may count for something, but it’s algorithms and predictive analysis that will probably seal your fate.

Here’s why. Enormously powerful computers are beginning to make sense of the massive amounts of data the world now produces, and that allows almost any kind of behavior to be quantified and correlated with other data. Statistics might show, for instance, that people who live 15 miles from work are more likely to quit their jobs within five years. Or that employees with musical skills are particularly well-suited for jobs requiring them to be multilingual. I’m making those up, but they’re not so far-fetched.

Some human resources departments have already started using companies that mine deep reserves of information to shape their hiring decisions. And they’re discovering that when computers mix and match data, conventional wisdom about what kind of person is good in a job doesn’t always hold true.

Run the numbers

Consider the findings of Evolv, a San Francisco company that’s making a name for itself through its data-driven insights. It contends, for instance, that people who fill out online job applications using a browser that they installed themselves on their PCs, such as Chrome or Firefox, perform their jobs better and change jobs less often. You might speculate that this is because the kind of person who downloads a browser other than the one that came with his or her computer, is more proactive, more resourceful.

But Evolv doesn’t speculate. It simply points out that this is what data from more than 30,000 employees strongly suggests. There’s nothing anecdotal about it; it’s based on info gleaned from ten of thousands of workers. And that’s what gives it weight.

“The heart of science is measurement,” Erik Brynjolfsson, of the Sloan School of Management at M.I.T., pointed out in a recent New York Times article on what’s become known as work-force science. “We’re seeing a revolution in measurement, and it will revolutionize organizational economics and personnel economics.”

Evolv, which largely has focused its research on hourly employees, has spun from data other strands of of H.R. gold, such as:

  • People who have been unemployed for a long time are, once they’re hired again, just as capable and stay on their jobs just as long as people who haven’t been out of work.
  • A criminal record has long been a thick black mark for someone in the job market, but Evolv says their statistics show that a criminal background has no bearing on how an employee performs or how long they stick with a job. In fact, it has found that ex-criminals actually make better employees in call centers.
  • Based on employee surveys, call center workers who are creative stay around. Those who are inquisitive don’t.
  • The most reliable call center employees live near the job, have reliable transportation and use one or more social networks, but not more than four.
  • Honesty matters. Data shows that people who prove to be honest on personality tests tend to stay on the job 20 to 30 percent longer than those who don’t.

And how do they gauge honesty? One technique is to ask people if they know simple keyboard shortcuts, such as control-V, which allows you to paste text. Later they’ll be asked to cut and paste text using only the keyboard to see if they were telling the truth.

It’s getting creepy

Data-driven hiring has its flaws, of course. One is that it could result in unintended discrimination against minority or older employees. Minority workers, for example, tend to travel farther to their jobs. And that could create legal problems for a company that steers clear of long-distance employees because statistics show they don’t stay in jobs as long.

Then there’s the matter of what lengths a company will go to gather data on its workers. Where will it draw the line when it comes to tracking employees’ behavior in the name of accumulating data?

“The data-gathering technology, to be sure, raises questions about the limits of worker surveillance,” Marc Rotenberg, executive director of the Electronic Privacy Information Center, told The New York Times. “The larger problem here is that all these workplace metrics are being collected when you as a worker are essentially behind a one-way mirror.”

That’s a serious issue, but it’s not likely to slow the trend of replacing a boss’ gut reaction with the perceived wisdom of algorithms.

Case in point: Earlier this year eHarmony, the company that’s made its mark in online matchmaking, announced plans to tweak its algorithms and get into the business of hooking up employees and companies.

Big Data is watching

Here are other ways Big Data is having an impact:

  • The roads less traveled: Delivery companies like Fedex and UPS are starting to see significant savings by using data analysis to guide drivers to less congested roads to avoid idling in traffic.
  • Have phone, will travel: Scientists in Africa are using data gathered from cell phone usage to track the spread of diseases like malaria by seeing where people travel.
  • Big C, meet Big D: The American Society of Clinical Oncology has launched a project to create a massive database of electronic records of cancer cases so doctors can apply analytics to determine how to best treat patients.

Video bonus: Still don’t get the whole Big Data thing. Photographer Rick Smolan shares his epiphany about it.

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