09 02 2015
door Inostix

The HR Analytics Value Pyramid (Part 3)

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GizaThis blog post has been prepared to respond to the many questions we get with regards to how to add value with HR Analytics. With the HR Analytics Value Pyramid we hope to provoke and to help how you could create value in your organization with HR Analytics. We’ve created this Pyramid based on real-life experiences of our consultants and on our ongoing research.

There are many (HR) analytics maturity models in the market but we’ve approached it from a different perspective: what should/could be the ideal focus for HR with regards to HR data and reporting in general and with (predictive) HR Analytics more particularly? We have started with Part 1 (Pyramid Levels 1/2), continued with Part 2 (Pyramid Level 3) and now this final Part 3 (Pyramid Level 4). Enjoy the reading and feel free to react!

 

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Fig. 1 – The HR Analytics Value Pyramid – Level 4

 

Level 4

What?

The fourth and last level of the pyramid is called the Business Optimisation level, bringing people and business data together to drive business outcomes (instead of people outcomes as in our Level 3). To quote Dave Ulrich again: ‘Start with the external perspective (business performance optimisation, our Level 4), not the internal (HR activities optimisation, our Level 3). This is the level where organisations add the people component to the predictive analysis of business issues, risks & opportunities.

To be able to optimise business outcomes, business processes need to be monitored end-to-end, including the people component of course, which – after all – not many companies are considering (which is strange to us). If you are analysing your manufacturing productivity risks and you don’t add the people component to your analysis, you are leaving out one of the biggest drivers of risk.

Examples

  • Improving call centre agent ‘time to productivity’ ratio, due to more effective onboarding training or coaching
  • Improving client satisfaction by predicting (and reducing) account manager churn risks
  • Reducing machine downtime by better operator safety training (based on predictive risk analysis)
  • Predictive staffing based on predicted case/business volume (law firms, retail banking, consultancies, technical support, logistics/transport, etc.)
  • Reducing road accident risk by predicting driver behaviour based on tracking data (from the truck/bus tracking system)

Characteristics

  • Predictive
  • Focused on optimisation of core business processes and activities
  • Business connected
  • Multiple Source Data (HR & business)
  • Necessity to break operational and functional silos to get access to data and to collaborate on the project(s)
  • Looking at the future: risks & opportunities (‘risk’ is the language of business!)
  • High value – can create competitive advantage in business processes and activities
  • Mirroring Marketing: optimisation thru a better understanding of behaviours (of employees instead of customers, of course)
  • Transformational

Watch out!

  • Remember Pasha Roberts saying in Part 2: “Find business pain and solve it!” Unfortunately, HR is on one side not usually very familiar with core business processes, is not involved in the analysis of it, and on the other does not have a good level of credibility in the business of adding value to such processes. In our experience, that’s a real challenge for HR. Developing HR analytics capabilities is one side of the coin, whereas getting involved in and adding value to the optimisation of core business processes, is often a huge challenge for HR.
  • In his recent blog, Prof. Baesens – iNostix’ academic advisor – strongly advocates that “the need for HR analytics should come from the business itself”. Strangely enough, we’ve met HR professionals who tell us that the business does not require this kind of support, hence why HR is not pro-actively developing this analytical capability. Dear HR pros, if you wait until someone asks you, nothing will happen! Business will not ask (because HR – in most cases – has no analytical credibility and/or poor business understanding/involvement) and it’s HR’s responsibility to develop the (analytical) capabilities to be able to add value.
  • Our awesome client Patrick Coolen from ABN-AMRO, working with the business on HR analytics projects for more than 2 years now, has started his HR analytics journey with adhering to ‘the 3Ps vision’: Pilot, Prove and Preach! Now, a few years later, always tying HR data to actual business issues, he has built the credibility of the function and this has led to real business sponsorship and funding.
  • Those companies experimenting at this level consider their efforts far too much as (a series of) projects instead of a continuous exercise. If analytics are tied to critical business processes, there’s (most likely) no end to improving these processes…and no end to the analytical effort, of course. Month-after-month, quarter-by-quarter, etc. Due to the current status of analytical technology, continuous measurement processes can be (rather) easily automated.
  • Compared to Part 1 & 2, we’ve added a new difference between levels 1/2 (mirroring finance) and levels 3/4 (mirroring marketing) on the left side of figure 1 above. We will come back on this difference in a separate blog post which we will announce as soon as possible.

Related articles

The HR Analytics Value Pyramid (Part 1)

The HR Analytics Value Pyramid (Part 2)

Interested in using predictive HR analytics as a key component in your HR strategy? Get in touch with CEO and co-founder Luk Smeyers for more information ([email protected]) or via Google+. Or follow iNostix on Twitter and/or Facebook for exciting international articles on HR analytics. And of course, don’t forget to subscribe for this blog!

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