Data Science versus People Science?

Do you see a benefit in having folks with an I/O Psychology background taking a lead in the people analytics space over those with a Data Science background? In our team, we frequently discuss concerns over atheoretical models without apriori hypotheses yielding spurious correlations and false positives. Or, even worse, good models that explain a valid relationship, but no clear actionability.

Hi, Kev. Great question. Of course, the answer depends. It depends on goal of the people analytics function, the needs of internal customers, the nature of the workforce, etc. I believe I/O Psychologists can be great People Analytics Leaders. I also believe Data Scientists can also be great in the role, as can Finance, IT, and other professionals. Wherever they come from, the individual must know his/her strengths and limitations and know when they need help and where to source that help. For example, most I/O’s are not going to design and build product. Similarly, most Data Scientists are not going to effectively design research projects and, in turn, develop a confidence inspiring narrative. Going further still, who’s going to manage and aggregate data, build dashboards, scenario plan, deal with privacy, ethics, etc. You get where I’m going, no doubt. Understanding the risks of spurious correlations and false positives is critical, yet so is all this other stuff. As such, no matter where we enter the field from, we must all be conscious of our background, experiences, our “structure of interpretation” and, in turn, know how this both enables and limits us. In the end, we all must remain continuously learners. People Analytics roles, and the discipline in general, demand it. Hope this helps; and thanks again for your question!

Thank you so much Al, this is really insightful!