Predictive Analytics in HR: Our Crystal Ball Says …

Part IV

We are continuing to take a look into our crystal blog with our five-part predictions series. This fourth prediction is probably the most important for you to consider as you develop analytical capabilities in your organization. By the way, if you missed our previous predictions, you may read them here.

#4 Bad Analytics Leads to Bad Business

There are lots of vendors jumping on the analytics bandwagon. Some are just re-branding things they were already doing and calling it analytics. Most of these tools/approaches use very basic methods and don’t connect results directly to business results. Others are pushing new approaches based on machine learning and algorithms. These may be truly innovative, but be very careful in this area. Remember that one of HR’s primary roles is risk mitigation and some of these “new” approaches introduce very real risks. Let’s explore some of the potential risks:

  • Manager Mayhem: HR will go overboard with the data they have and lose great employees by giving managers individual turnover risk metrics. We are already seeing this happen in the market. So what do you think the likely outcome will be if you give managers an individual level turnover risk metric? A manager might fire or not promote someone because they are a “turnover risk.” Can you say lawsuit?
  • Affirmative Action Wins: Affirmative action lawsuits will be won in court based on a “predictive metric” with adverse impact or discrimination. This is where the machine learning component becomes risky. In this approach, correlations are sought for any and all data points. So, if a font style is a predictor of success in the resume screening process, is it possible the algorithms might have adverse impact? Sure it is. We can’t say for sure when this will happen, but it definitely will.
  • Buyer Beware: Many “predictive” analytic technology companies will fail and go out of business by rushing to get unproven things to market that aren’t actually predictive tools. These companies will fail because (1) clients will discover that bad analytics don’t actually drive success and/or (2) lawsuits. So, don’t just assume that something new and innovative will work. Be an educated buyer for your organization. Don’t make the mistake of buying something that will likely fail or result in significant risk for your organization.

Stay tuned next week for our last prediction.

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