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How big data is changing hiring and recruiting

Richard Jones Archive

Technology in recent years has markedly improved the way businesses recruit and hire talented professionals. In a previous era, companies were reliant upon old-fashioned methods - collecting resumes and cover letters in the mail, filing them and sifting through candidates one by one with an arduous interview process.

Times have changed. Recruiters now follow an expedited process - they can use social media sites and other online tools to find attractive applicants, and they can quickly make connections with the best candidates using technologies like video interviewing software. Companies can hire new workers quickly, reliably and cost-effectively.

Now, there's yet another high-tech innovation coming to the hiring game - big data. Recruiters may have their preconceptions about what makes a good job candidate, but by performing data analysis, they can back up their opinions with facts. What educational backgrounds should employees have? What experiences and skills do they need? Business leaders no longer need to rely on guesswork to answer these questions.

A simple test
According to Inc. magazine, even the simplest big data initiatives could have a profound effect on a company's hiring practices. Nathan West, director of analytic products for Evolv, an HR data software company, says that businesses can expect to see immediate results. Small observations can lead to big revelations about who makes the best employees.

"A simple test could help identify better candidates for jobs," West told Inc. "Someone who has downloaded and installed a browser other than the one shipping with his or her computer or device shows a willingness to adopt new technologies. Using the browser factor as an indicator, the company found that employees who scored higher on tests of 'willingness to adopt new technology as well as technical proficiency ... actually stayed 17 days longer, missed 15 percent less work, and adhered to schedule much better when they were at work.'"

Having said that, recruiters should proceed with caution when relying on data-driven hiring processes. They should ask themselves a few key questions before they proceed. Where is their data coming from? Is there any inherent bias in how it's been collected? Are there any problems with data quality?

Data analysis isn't always a seamless process, but if businesses know what they're doing, they can position themselves to capitalize.

Dispelling myths
Recruiters tend to have many biases about the hiring process, based on their experience and personal knowledge. Thanks to the advent of big data in hiring, they can use analytical processes to verify them. They might be surprised by the results.

According to Quartz, big data has disproven many preconceived notions about who makes a good employee and who doesn't. For example:

  • Former convicts aren't necessarily bad employees. They actually work just as hard and achieve just as much as anyone else in the workplace.
  • If employees spend a lot of time on social media, it doesn't mean they're slacking off. People with active social media accounts are actually very energetic, plugged-in people who accomplish a lot for their employers.
  • If a worker has a long commute, that doesn't mean that he or she is likely to quit. On the contrary - it means the person is highly committed to the job and likely to stick with it.

Using data in hiring can help uncover many more truths like this. Companies today can't afford to ignore this possibility - there's too much to lose. Every bad hire leads to a snowball effect of lost productivity and bad workplace habits, so recruiters must do everything in their power to avoid making hiring mistakes. Luckily, big data makes this process much easier.

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