With the publication of our Human Capital analytics research earlier this summer, we drew a lot from the space of evidence-based practice. This approach, championed by the likes of CEBMA and Future Work Centre calls for “decision-making through the conscientious, explicit and judicious use of the best available evidence, by drawing information and data from multiple sources” (Barends et al, 2014). The theory recognizes four types of evidence, all of which should be considered when making decisions:
Figure 1: Four forms of evidence in evidence-based practice (adapted from Barends et al, 2014)
Looking at figure 1 it is clear that there is a place for human capital analytics: in the organization internal data quadrant.
Organisation internal data: HR and human capital analytics
A finding from our recent research was that the “analytics” space is full of confusing terminology. We (myself included!) have over time used many different terms to describe the process of analyzing data relating to the HR function: HR analytics, people analytics, talent analytics, talent insights…. the list goes on. This often causes confusion across the profession, and can also cause real frustration trying to work with HR people and their many types of ‘talent dashboards’.
Only recently have academics tried to pull together a synthesized view of HR analytics; whats in and whats out (see Marler and Boudreau, 2017), which describes HR analytics, and many of its pseudonyms in more detail. In my view, we should think about human capital analytics as a very specific exercise for understanding the composition of the intangible part of the workforce: knowledge, skills and abilities. Here we can talk about skills audit results, outcomes from L&D activity etc. Alongside this there is HR analytics, which is concerned with the operation aspects of people at work: time to hire, cost of recruitment, health and safety scores. These operational measures are key to a well-oiled HR function and are likely score-card measures; whilst longer-term investment measures are likely to relate to human capital, and hence be part of the human capital analytics process.
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