Are You Overlooking the HR Research That’s Already Out There?

Most of the useful data crunching in HR occurred long before the term analytics graced the booths of every darned vendor in the trade shows. That work was done by trained scientists in universities and subject to peer review. It was, compared to most of the analytics we can realistically do within companies, good quality work. The results of this research can be found in journals on industrial organizational psychology (now sometimes re-branded as behavioral economics) and related disciplines.

By all means we should embrace the analytics movement, but part of that should be paying more attention to the excellent data crunching that’s already been done for us.

There are three reasons why scientific evidence has been underutilized in HR:

1. No one cared — Prior to the analytics movement managers didn’t worry too much whether or not HR decisions were based on data.

2. Scientific data was inaccessible — It was, and still often is, too hard to access and make sense of scientific data. That’s changing thanks to the work of the Center for Evidence Based Management, ScienceForWork and to some extent Google’s Re:Work.

3. Everyone felt they were special — Managers always feel their organization is unique and hence findings based on research elsewhere are irrelevant. It is a good idea to ask the question whether a given set of research findings is relevant to your situation; it’s a bad idea to ignore everything that is known in a field because you think you’re special.

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As you can see from my commentary in those bullets, I think all the barriers that stood in the way of better use of scientific evidence are weakening. Add to that the enablers of a better educated HR workforce (i.e. professionals with post-grad education are now commonplace) and easy internet access to research and I think we’ll find much more frequent use of scientific findings in HR decision-making.

The main step for HR is to get into the habit of taking a quick look at the available scientific evidence as part of any analytics project. The analytics team, in addition to the number crunchers, should have people who are comfortable looking at the scientific literature and assessing what parts are valuable.

There are still lots of shortcomings that inhibit the usefulness of scientific findings in HR, but usually some evidence is better than no evidence, and when evidence can be accessed for a low cost — since a university has already done the work — it’s foolish not to take a look.

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Special thanks to our community of practice for these insights. The community is a group of leading organizations that meets monthly to discuss analytics and evidence-based decision making in the real world. If you’re interested in moving down the path towards a more effective approach to people analytics, then email me at

David Creelman is CEO of Creelman Research. Based mainly in Toronto and partly in Kuala Lumpur, he’s best known for his research on the latest issues in human resources.

He works with think tanks such as Talent Tech Labs (New York), Works Institute (Tokyo), Workforce Institute (Boston) and CRF (London). He’s collaborated with leading academics such as Henry Mintzberg (leadership development), Ed Lawler (“Built to Change”) and John Boudreau (future of work).

His books include The CMO of People: Manage employees like customers with an immersive predictable experience that drives productivity and performance with GrandRound’s CHRO Peter Navin; and Lead the Work: Navigating a world beyond employment with John Boudreau (USC) and Ravin Jesuthasan (Willis Towers Watson).

You can connect to Mr. Creelman on LinkedIn