How are Successful HR Analytics Functions Built?

Andy Charlwood University of Leeds

By Andy Charlwood - Professor Human Capital Management, Univerity of Leeds

Co-host of the upcoming webinar - How to Build an Optimal People Analytics Function

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Professor Andy Charlwood previews the first findings of a University of Leeds/3n Strategy research project that seeks to answer this question.

There is a lot of (good) thought leadership on what effective HR analytics functions look like. However, a lot of the case studies and examples come from leading edge firms. What books and articles in this genre seem to leave out is an account of how HR analytics functions develop over time – what makes some organisations able to make rapid progress while others struggle to break out of basic operational reporting?

My research with 3n Strategy aims to provide better answers to the question of how firms can best develop HR analytics capabilities. To date, over 100 HR analytics leads have contributed to our benchmarking survey, with some participants participating for three years in a row. We are now following up survey respondents, asking them to participate in in depth interviews so we can understand more about the stories behind their survey responses. This blog provides a brief overview of some of the initial findings from our first fifteen interviews (we are aiming to complete another 25 over the next couple of months).

  • HR analytics is not a linear journey from basic reporting to predictive analytics. Analytics maturity models have conditioned a lot of people (me included) to see the development of HR analytics as a journey from basic reporting to advanced reporting through technology upgrades to more strategic use of statistical modelling and machine learning to full predictive analytics. This thinking is holding a lot of analytics teams back. In practice, teams who have made the most rapid and impressive advances in developing advanced analytics have appreciated that statistical modelling is an entirely different capability to advanced reporting and have focused on developing that capability without taking on a reporting role. This is important because success in reporting breeds demand for more and better reporting capabilities and satisfying these demands prevents resources being devoted to developing the statistical modelling capabilities needed for advanced and predictive analytics.


  • A major factor holding a significant number of HR analytics teams back is that their key customers – corporate HR leaders and HR business partners in different business units – don’t place much value on the reporting tools and dashboards that the analytics team produce within a traditional reporting environment (Excel and HRIS based reporting tools) so use of HR dashboards is minimal. Teams that reported higher levels of engagement with data-driven decision making and advanced reporting typically make use of BI software to offer a much more immersive and interactive data experience for their HR BP customers. However BI software alone isn’t enough to drive engagement from more than an active minority – extensive training opportunities and changes to hiring and promotion criteria so that new HR BPs have some aptitude and orientation towards data are necessary too.


  • It is well known that ‘storytelling’ skills are necessary to communicate the results of HR analytics projects back to the business in a way that promotes action, but some of the most advanced HR analytics teams are realising it is only the start of the journey of turning analytical insight from advanced analytics projects into management action. They are focusing attention on developing change management methodologies that mean that insight from their analytics project is ‘industrialised’ – impacting on all areas of the business through training programmes that raise awareness and new BI dashboards that promote managerial engagement and action.

The research is also generating fascinating new insights that challenge some of the received wisdom on issues like data quality, skills shortages as an impediment to analytics progress and the role of leadership in developing analytics functions. Time and space prevent me from going into more detail on this now, but I aim to do another Tucana blog covering these issues in the next couple of weeks.

If you’re a HR analytics professional, and you want take part in the research, you can complete the initial survey online here: – Everyone who participates will get a copy of the report we are going to produce on the full findings. I hope to talk to you and hear your story soon.

If you want to hear more about our initial thoughts and findings on what makes for a successful HR analytics journey, you can also register for the webinar


Nigel Dias (3n Strategy) and I will also be at Tucana’s People Analytics Forum conference in London at the end of November. If you are going to be there too, come over and say hello!