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Hiring With Science: Big Data Brings Better Recruits

NetApp

Analytics fans say big data is the key to hiring great talent and reducing attrition.

It can also help you pay real market salaries, and increase your diversity.

So what should you know before you turn recruitment over to the robots?

As the U.S. economy improves, private-sector employee-quit rates are rising: They're now at an monthly average of 2.1%. But retaining an employee costs less than hiring a replacement: That classic rule of thumb is as true today as it’s always been.

The real costs of hiring and training replacements make a significant dent in any organization’s bottom line—so wouldn’t it be great to predict who’s likely to be a successful, long-term employee before you hire them?

Enter Big Data

According to Prof. Peter Cappelli, director of Wharton's Center for HR, big data can predict successful hires far better than your HR department. He cites recruitments specialists Evolv, which found that candidates’ histories of job-hopping don’t predict whether or not they leave a company.

Common sense—and even established research—have been leading human recruiters astray for too long, as he told me:

The industrial psychologists who’ve been working on this for a hundred years have their own sets of models. The great possibility of big data is in finding things that are outside these paradigms.

Can Bots Have Biases?

As with all big-data analytics, there are elements of HR that are beyond the reach of human understanding.

So is there a danger that your organization could find itself missing out on talent because the model has a blind spot? Yes, according to Cappelli:

The people who complete college in four years might be better on average than someone who took five years, but maybe they took a year off to help a sick parent or to prop up a family business that was struggling. That changes the picture quite a bit and the data wouldn’t necessarily reflect that.

You should be aware of the danger of lawsuits, if these sorts of models are more likely to discriminate against people from less prosperous backgrounds for example. But Linn Foster Freedman, a legal expert in data-privacy and -protection, told me it’s business as usual:

If you’re hiring someone based on publicly available data then that’s no different than using paper résumés. Organizations are going to need to comply with the same state and federal laws that apply to discrimination, regardless of what format the information is in.

WLTM: Finding Your Dream Employee

In fact, data mining can help your organization open up a much larger pool of talent.

According to Dr. Vivienne Ming, for every candidate pursued by recruiters through traditional routes, there are 100 equally talented developers available:

There are about 100 times as many qualified but un-credentialed candidates out there, at every level of ability. Organizations are creating their own blind spots, which leads to companies paying too much for their hires and to talent being squandered.

Ming’s employer, Gild—a specialist tech recruiter—mines open-source code to find the best software engineers. Its algorithms have allowed its clients to hire talented individuals who are self-taught self-starters, who are just looking for their first big break.

Ming says that her research shows that it’s possible—at least in the field of software development—to hire based entirely on merit. Data-mining lets her find the largest and best possible talent pool.

The Bottom Line

Big data can help you to...

1. find talent your competitors miss,

2. stop you over-paying for great talent, and

3. keep that talent.

What's your take? Weigh in with a comment below, and follow Emma Byrne (Google+) @SciWriBy (Twitter).

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[Editor's note: This is an updated version of an article we published last year.]

Image credit: James Montgomery Flagg (public domain)