Will big data and predictive analytics take the “human” out of human resources?
If you’re a recruiter, I’m guessing that you probably hear terms like “big data” and “predictive analytics” on a near daily basis. I’m also willing to bet that while you may be familiar with these ideas and technologies in a broad sense, you may be less aware of how they actually apply in an HR and hiring context.
As LaunchPad’s resident data scientist, it’s my job to ensure our algorithms are designed to increase your team’s hiring efficiency and decision-making abilities. But it’s also my job to to help recruiters understand the importance and massive potential of data-led assessment. Obviously, this stuff can get pretty technical, so I’m going to do my best to break this down into into practical terms. So without further ado, here are five things that every recruiter should know about big data in HR.
Big data is something of a catch-all term, but in general, it refers to the collection and analysis of data sets that are too big to enter and compute manually, say, in a spreadsheet. Areas that fall under the “big data” umbrella include structured data such as personal data, scores, to unstructured data such as text, video, audio data. In other words, “some forms of big data are bigger than others.”
Companies are already beginning to collect data around job performance and using it to predict things like who the most productive employees will be, who should be promoted, who’s most likely to leave, etc. As far as recruitment is concerned, there’s no way to use data from previous jobs to determine an applicant’s fitness for an open position. Still, the use of software that analyses data to make predictions about the future, called predictive analytics, could be used to guess how well candidates will fit into a role based on their responses to interview questions, for example.
For those worried we’re heading down a slippery, Orwellian slope, you can relax for now: personal data from candidates’ social media and email accounts isn’t going to be automatically pulled and judged in by recruiter robots any time soon. Instead, interviewers will develop questions meant to measure qualities or aptitudes that have been shown to predict future job performance, rating their answers on a quantitative scale.
As the big data trend continues to ramp up, executives, hiring managers and other business leaders should implement top-down training initiatives to increase their team’s data literacy and capabilities. For example, recruiters should develop their questions and review criteria in a highly structured, consistent manner, enabling them to evaluate each candidate objectively and fairly, thereby improving the candidate experiences and hiring outcomes.
Even if you have troves and troves of data, it’s not going to do you a whole lot of good if you don’t know how to interpret and leverage it correctly. At LaunchPad, I’ve collaborated extensively with Mark Abrahams, our in-house Chartered Psychologist, to develop meaningful scales of the behaviours and qualities that employers want to see represented in their workforce. Without a solid scale of measurement in place, companies risk basing decisions on unscientific processes or on factors they don’t consider important or relevant to their hiring goals.
The key takeaway here is that big data and analytics are meant to enhance human decision-making, not to replace it altogether. With the right technology and the proper implementation, data-led assessment can help to increase efficiency and improve outcomes for your campaigns — no PhD required!