Senior managers have become so interested in using HR data to improve their decision making that at the HR Tech World Congress in Paris last year the biggest queues by far were for the sessions on “HR analytics”, as the discipline is called.
The excitement is not surprising, as leaders increasingly expect their HR functions to create business value – help a company make more money or spend less money – from HR data, and this will only increase as HR teams find new ways to find value in unstructured and qualitative workforce data.
In fact, 80% of CEOs want to base important company decisions (for example in managing staff productivity or labor costs) on insights from workforce data, but only a fifth say they get sufficient information from HR (see chart 1).
This is surprising because investing in better HR analytics has a proven, positive effect on talent management: compared to the average organization, those companies that range in the top quartile for the quality of their HR analytics achieve 12% better performance in terms of succession management, their employee performance review system, the quality of the people they hire, and how engaged their employees are (see chart 2).
But HR data can also help companies more directly. For example, healthcare firm, Roche, was facing high attrition rates in Asia that were jeopardizing revenue growth targets. Roche’s HR Analytics team developed and tested 16 hypotheses to explain the attrition and was able to statistically prove the relevance of six factors determining the high fluctuation.
As well as working on the root causes, Roche is now also developing an early warning system for similar situations based on analysis of unstructured (or “big”) data. This has contributed considerably to the success of the business.
Chart 1: Importance and sufficiency of workforce data Source: CEB analysis
Chart 2: Effects on talent outcomes of better HR analytics performance Source: CEB analysis
Three Steps to Improve Your HR Analytics
HR teams are keen to improve their analytics ability and to become more “mature” in the discipline. CEB data show that, on average, teams want to increase their analytics maturity by 2.5 levels within the next three years, moving from being at an average of level 2 in 2015 to 4+ by 2018 (see chart 3).
Chart 3: Five stages of HR analytics maturity Source: CEB analysis
Click chart to expand
However, project leads often find it difficult to start on this improvement project. They should start by addressing three main questions.
Where should I focus HR analytics? (“Criticality”): Successful managers prioritize projects that are the most scalable ways to help managers hit strategic goals, rather than simply fulfilling on-demand data requests.
Focusing on well-defined, small, and easy analytics “showcases” in the first step to create awareness and appetite for analytics support with senior business stakeholders is a good start to show how critical good analytics can be.
How do I develop my analytics team? (“Capability”): On one hand, companies require skills of four role types in their HR Analytics teams, which can come from different people or, if they’re lucky, all be provided by one person.
A “business challenger” who is able to influence and work with stakeholders inside and outside of HR.
An HR domain expert with the skills to analyze HR-related business needs.
A programmer able to design databases and integrate different sources.
A data scientist with classic analytics abilities plus advanced big data analytics skills.
On the other hand, companies also need to think about the adequate HR analytics tools and technology they might require from external vendors so that they don’t have to build-up all advanced analytics capabilities internally.
How can I increase the influence of HR Analytics (“Credibility”): The best teams ensure they collaborate with stakeholders throughout the process of identifying which topics or projects the HR analytics team will work on, all the way through to interpreting the results.
Not only does this give analytics teams the best chance of their work helping achieve strategic goals, it means stakeholders will trust the results and so are more likely to act on them.