In mid-July, Professor Andy Charlwood from the University of Leeds and Nigel Dias from 3n Strategy will host a free webinar on the findings of their recently published HR analytics strategy report.
The development of HR analytics is often portrayed as a journey to ‘maturity’, from simple reporting, metrics, and dashboards for operational purposes to the use of statistics and machine learning for strategy execution and to optimise people management decision making. However, as US academics John Boudreau and Wayne Cascio have observed, many organisations hit a wall that prevents them moving from metrics and dashboards to more advanced and strategic HR analytics. Recent evidence from Josh Bersin also suggests that few of the organisations that Bersin has surveyed made significant progress in developing HR analytics capabilities over a three year period. Simply put, some organisations start their HR analytics activities on the far side of the wall and most others can’t break through the wall to develop advanced capabilities.
Why is this? There is no shortage of ‘best practice’ guidance on how organisations should go about developing advanced capabilities, so why aren’t more organisations following the advice and breaking through the ‘wall’? To try to start answering this question, I recently interviewed 18 HR analytics leaders in a wide variety of different industries and countries as part of the HR Analytics Think Tank’s ongoing programme of research. The first thing I noticed is that the organisations that feature in best practice case studies are different to other organisations in ways that best practice guidance does not always bring to life. Typically, ‘best practice’ organisations have a wider business strategy of creating value from data. Consequently they have the skills to do HR analytics and an expectation from senior general managers that HR should be data driven. They may also enjoy dominant positions in their industries, meaning that they have the resources to invest in developing HR analytics capabilities.
In many cases, it may not even be obvious to the HR analytics leader what specifically made them successful ~HR Analytics ThinkTank Report
The key point here is that HR analytics capabilities depend on wider business, HR, data and analytics strategies, which feed through to investments in technology and people. Drawing on evidence from HR Analytics Think Tank research, we have devised a typology of HR analytics capabilities which captures this relationship between strategy, technology and capability. The typology has five capabilities: labour intensive basic reporting; automated advanced reporting; advanced BI (business intelligence); basic people insight and advanced people insight. The most sophisticated organisations typically have capabilities in advanced reporting, advanced BI and advanced people insight, but such organisations are relatively rare.
Our evidence suggests that many organisations developing people analytics capabilities are typically focused on cost based strategies. This means improving the efficiency of HR operations through the adoption of new HR information systems (HRIS). These HRIS may have some analytics capabilities, but analytics is not the key reason for their adoption. Using data generated by HRIS in analytics requires a lot of effort, because data have to be entered consistently across large diverse organisations before it can be used in meaningful analysis. To get to this stage requires big efforts to define the metrics that matter and to set in place data governance process that ensure that the data are accurate. Getting metrics right and getting managers to use them appropriately in decision making is often a second order consideration so organisations adopt an ad hoc approach instead.
Organisations in more regulated industries (e.g. financial services, pharmaceuticals) need to report a lot of data to demonstrate regulatory compliance. In more regulated industries, automating reporting through the latest HRIS can result in significant cost savings. Change processes linked HRIS adoption often result in the development of better metrics and KPIs. However, many of our interviewees found the self-service reporting was not much used because of poor user experience, so it was hard to get managers to make use of them as tools for evidence based people management. This has led some organisations to look to develop advanced BI capabilities with a much better user experience. Organisations that have done this have also found that making data visible through BI leads to more accurate data, because managers become accountable for the quality of HR data that they generate. However, even those organisations with advanced BI capabilities tend to be quite conservative in the way these capabilities are used, reporting metrics like turnover and absenteeism to diagnose problems and control costs rather than to address strategic issues.
Many of the organisations we spoke to found that advanced reporting and BI capabilities resulted in increasing interest in and demand for analytics. Despite this extra interest they still found it difficult to break through the wall. They struggled to get the (often quite limited) resources they needed to access to non-HR data and the expertise of data scientists. In the absence of the necessary resources they did what they could with the resources available (basic people insight). This typically means focusing on trying to maximise the value of HR related data by modelling the determinants of sickness absence and staff turnover. Such analysis can help to improve operational efficiency by saving costs, but it is rarely of strategic value.
The wall seems to be built on two related problems. Many managers, including those at quite a senior level have a strong belief in their professional judgement as a basis for making people management decisions. Data driven decision making is seen as nice to have but not essential. Consequently, the strategic business problems that HR analytics could add value to are not easily defined and analysis does not always result in actionable insights. HR analytics leaders who had managed to break through the wall were very focused on building relationships and personal credibility with a wide variety of stakeholders in order to identify business problems and to get managers to act on their insights. However, even those who had successfully developed these advanced people insight capabilities recognised they had more to do to promote the use of their insights in decision making.
The broad takeaways from this research are that outside the small number of organisations have strategies focused on extracting value from data, few organisations yet do HR analytics well. There is scepticism about whether HR analytics is necessary or valuable. If HR analytics is to break through the wall, HR analytics leaders need to get better at identifying and explaining the value that data driven people management based on advanced people insight can bring to their organisations. Understanding more about the value that HR analytics can create is a key part of our future research plans. How do you measure and explain the value of your HR analytics programme? We’d love to hear more about it.
Please see other posts from the HR Analytics ThinkTank: How to Accelerate Your HR Analytics Journey
Note: The ThinkTank has just published a paper, entitled 'How do organisations successfully build HR analytics functions?'. If you would like to receive a copy (and join the ThinkTank - it's free), please complete this form. If you would like to attend a free webinar with Professor Andy Charlwood and myself, please register here.