Are you ready to use predictive analytics as part of an inclusive hiring process?

‘Predictive Analytics’ is still a buzz phrase in recruitment, years after it was first coined. It is a way for recruiters to make more informed hiring decisions. At their most rudimental level, predictive analytics can predict peaks and troughs in hiring demand before they occur- particularly useful for seasonal recruiters or rapidly growing companies. At a more advanced level however, predictive analytics could be used to tell you which kind of candidate is going to be good at a job.

And this is where it gets tricky.

Let’s say you record information on candidate height. Cross reference with some employee productivity stats, you could make inferences like ‘short people are typically good at {insert job title here}’. Now unless your remit is to hire an Olympic level weightlifter (unlikely), you’ve probably been led astray by your predictive analytics. Short accountants may be more productive than tall accountants, but they are not more productive because they are short.

Could you imagine an application form for an accountant that specifies a maximum height? It sounds ridiculous.  While this might seem like a trivial example- of course a candidate’s height has no bearing on their ability to be an accountant- this kind of conclusion could made with more serious implications.