Up until recently, the strategy for hiring decisions has focused primarily on the past: what experience a job candidate has gained, what degrees they’ve earned, what places they’ve worked, etc. But with roughly a quarter of new hires leaving a job within a year of their start date, this hasn’t proven to be the most effective means of finding and keeping talent.
It’s no surprise that businesses are increasingly turning to “big data” and predictive analytics to acquire suitable talent. Already widely used in business and other industries to predict outcomes and anticipate risk, predictive analytics can help companies save millions of dollars in recruitment, rehiring, and productivity.
Rather than using a job candidate’s past performance as a means of judging their suitability, predictive analytics uses personal data mined from a candidate’s digital footprint (i.e. social media accounts, online forums, internet browsing history, etc.) to predict the potential future performance of a candidate. It can also help a company target the best locations to invest in recruitment campaigns for certain skills.
What does this mean for you? Should the use of predictive analytics be feared or welcomed?
The idea seems both Orwellian and Darwinian. It’s a little creepy to think that companies are watching what you do online. And they’re using that data to come to all sorts of conclusions about you, including your professional potential.
If an algorithm is deciding the fate of future hires, doesn’t this create a kind of survival of the fittest scenario, where only the most educated and experienced workers get the best jobs?
Not necessarily. The way we currently judge professional potential is not only ineffective; it’s also rife with all sorts of personal biases and prejudices. An algorithm is not influenced by age, sex or race. Nor does it pay much heed to things such as where you’ve gone to school, grown up or even what you’ve majored in. Sometimes it doesn’t even matter if you’ve graduated from college or have any specific experience at all. The bottom line is how well you fit the parameters that determine your compatibility for the job, not only professionally but also personally.
All in all, the ultimate result can be more, rather than less democratic hiring, with employees being selected on the basis of merit and compatibility, rather than snap judgments and personal biases.
This isn’t to say that predictive analytics is some kind of magic bullet. Because the use of predictive analytics to assess professional potential is still new, it’s still untested in terms of long-term effectiveness. No one believes it will eliminate the need for human judgment. But it does offer the possibility of someday helping people select jobs that are best suited to their unique talents and personal attributes.
Research has shown that the more effective you feel on the job, the happier you’ll be. As these tools improve, they can help employees achieve mastery in their jobs and provide guidance on how to grow professionally. Sure, it might be more difficult to convince an employer that you’re right for a job, when you’re not. But really, is that such a bad thing? It might have taken years for you to realize this on your own. But technology could give you a chance to find your true calling sooner.
Photo via Flickr / cykocurt
