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HR Analytics is not a cost but an investment!

I often have discussions about necessary budgets for doing predictive HRA. Unfortunately HR focuses mainly on the costs and not so much on the investment aspect. I’ve noticed that HR leaders do not succeed enough in positioning predictive analytics as a necessary investment in the sustainable competitiveness of their organisation. This often has to do with an unfortunate lack of awareness as to the opportunities HR analytics can offer.


Developing an investment case

If the full power and possibilities of predictive HR analytics were known to us all, we could develop a strong investment case after a while, just like a (limited) number of HR analytics advocates are already doing. A few have even gone so far that the business team puts budgets at HR’s disposal, because they firmly believe in collaborating with HR analytics experts. The nec plus ultra.


Prove the concept, not the pilot

However, you don’t just deliver such an investment case the following Monday morning. I always recommend that organisations wanting to start with HR analytics begin with a relatively straightforward pilot. In doing this, I also always advise not to make the usual mistake of only focusing on the analytical outcomes of the pilot itself, but also on the wider context of why the pilot was organised. My motto is: prove the concept, not the pilot project (part of our 2014 learnings)!


Keep the holistic perspective

Under pressure from the organisation to deliver analytical outcomes, the holistic perspective is often forgotten and stress about proving an analysis has provided new insights takes the upper hand. As important as the pilot itself are (hold on to your hats!):

  • gathering analytical experience
  • gaining an insight into the often complex ownership of the data
  • determining the (sometimes difficult) location of the data
  • understanding the quality of the data (evolving from administrative to analytical data gathering)
  • cross-functional collaboration within the business (what I call the co-creation of analysis)
  • learning to work with and steering analysts or data scientists (inside and outside the organisation)
  • asking the right business questions or proposing the correct hypotheses
  • learning to understand analytical methodologies
  • collaborating with legal, risk management and IT departments, etc.

and I could go on for a long while.


Don’t limit yourself to analytical outcomes

 So if you want to show the added value of predictive analytics, don’t limit yourself to the analytical outcomes of your pilot, as you’ll never be able to turn it into an investment into the future of your organisation.

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