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The Four Levels of Data Analytics and Why They Matter for Recruiting

As recruiting moves away from "gut feeling" hiring to data-driven decision making, leading players are beginning to offer analytics solutions, but how should hiring managers best make use of them?

iCIMS, Lever, Bullhorn, Hyrell, and many others offer analytics capabilities in addition to basic candidate management. In fact, an entire candidate assessment field exists to make this process faster and more accurate.

There are four levels of analytics that hiring managers need to be aware of:

  • Descriptive: What is happening? E.g. are we hiring more men than women?
  • Diagnostic: Why is it happening? E.g. what qualifications are common among the employees hired in the past year that have done well vs. ones that have not?
  • Predictive: What is likely to happen in the future? E.g. how likely is a particular candidate to accept the job offer?
  • Prescriptive: What should we do about it? E.g. what is the best way to entice a candidate to accept an offer?

When used purposefully, data analytics in recruiting is a win-win for both the employer and the candidate. A streamlined search and hiring process, as well as a better fit between candidate and organization, means better-performing, happier employees.

Source: SoftwareReviews, Report Published July 2019

Our Take

  • The use of analytics in talent recruitment is on the rise.
  • Different levels of analytics provide varying degrees of insight.
  • Analytics should be used purposefully to be worth the investment.
  • Proper use of analytics benefits both organization and candidate.
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