Dr. Ian Malcolm’s Take on Using Big Data for Human Capital Sourcing
We recently discussed the wave of “Big Data Mania” sweeping the workforce management community on the nextSource blog. The piece sparked some interesting discussion leading to questions about the extent Big Data could be effectively used to improve sourcing or even automate the sourcing process entirely.
While industry voices from every vertical hyperventilate about the potentially transformative effects of Big Data on workforce management –and sourcing in particular –this blogger is reminded of the words of Dr. Ian Malcolm, a character in the Michael Crichton book (and Steven Spielberg movie) Jurassic Park. In a famous scene, Dr. Malcolm (portrayed in the movie by actor, Jeff Goldblum) warns of the consequences of fooling with powerful science that is not yet fully understood. Malcolm scolds Jurassic Park’s developers saying, “Your scientists were so preoccupied with if they could, they didn’t stop to consider if they should!”
That sobering line could arguably be applied to the idea that Big Data could ultimately supplant the more traditional ‘carbon-based’processes involved in sourcing talent. There are numerous reasons why Big Data will not likely ever be a complete replacement for sourcing talent. At the heart of all the reasons, it is the immutable fact that the sourcing portion of human resources requires exactly what its name implies –a human perspective.
Sourcing the best talent (not just acceptable talent) requires the judgment, creativity, analysis, common sense, and pattern recognition only a human being (and preferably a seasoned talent recruiter) can provide. While computing power is growing at an amazing pace (see Moore’s Law), even the vaunted, Jeopardy-winning AI, “Watson”cannot even approximate the synthesis of information needed to identify which identically credentialed Javascript Developer III will be the best candidate for any role. Sitting face to face with both candidates, however, will make the decision much easier for the recruiter who is a sensitive gauge of personality and humanity.
Now, before the poindexters of the data sciences get all huffy-puffy, let me qualify this by saying that there is indeed a great deal of good that a robust “Big Data”initiative can bring to a workforce management program. After all, the ATS alone shaves countless hours of mind-numbing, manual selection of resumes; time better spent by sourcing personnel in other, more strategic areas. However, the shortcomings of even this step in the overall automation of sourcing practices is ripe with challenges. For example, think about the inconsistencies in the terms used by candidates on their resumes. Small semantic distinctions are already erroneously disqualifying excellent candidates like the exceptional software engineer candidate who referred to herself as “developer”on her resume while the ATS was scanning for “Software Engineer”.
Considering that (as we discussed in our earlier post) barely 5% of organizations actually achieve true predictive analytics capabilities via big data for human capital management today, it is clear that leveraging Big Data for sourcing is difficult to achieve. It is because there are just some things about humanity that are intangible and simply cannot be derived from a clinical examination of data points.
Just because the industry could replace the humans in human resources in favor of a fully automated sourcing process, they ought to take a moment to determine if they really should.