When I talk with HR managers and professionals I often get asked the question: “What are the best tools for HR analytics?” I think this question represents one of the biggest problems with HR analytics today. Let me explain why.
HR analytics is about the statistical analysis of people data. Here’s what Sjoerd van den Heuvel and Patrick Coolen write about HR analytics:
“the systematic identification and quantification of the people drivers of business outcomes” – Heuvel & Bondarouk, 2016
“People analytics is using statistics or some data mining technique on combined data sets of HR and the business to find relationships in the data that improve decision making” – Patrick Coolen, 2016
Unfortunately, there are hardly any tools that actually do HR analytics. However, if you google for HR analytics tools you will find lots of companies that claim to have great HR analytics solution. Unfortunately, hardly any of the tools they provide enable you to do actual analytics.
Most HR analytics pretenders (for lack of a better word) are great at combining different data sources. These tools aggregate data from different systems and enable HR to slice and dice their data in a way they’ve never done before. These tools can for example show the HR professionals how many people work in different segments of the company, where in the organization high potentials are located, in which part of the organization turnover and absenteeism is highest and what percentage of attrition is unwanted.
These slice and dice tools link different data sources with each other to provide an overview of (all) available data within a company. This information is very helpful for HR, as it can, for example, combine the absenteeism system with the talent management system. This combination helps HR to see whether absence rates are lower for high performers compared to low performers. In addition, these tools can provide insight in different HR metrics and help HR in their monthly reporting. They are also helpful in identifying potential problem areas.
Because these tools provide a level of insight that HR professionals were not used to previously, they can be very helpful – and often do a good job in impressing a first-time user.
The insight in the data that these tools enable, is important. However, we should not pretend that these tools do analytics.
Slice and dice tools provide insight into where in the company turnover rates are highest and they show what the engagement levels are between high performers and low performers. However, they cannot tell you if these levels differ by chance, or whether they are statistically significant.
Proper HR analytics tools
This is where HR analytics comes in. Analytics is all about finding relationships. For example, if you’d want to know how engagement leads to higher customer service ratings you need to statistically analyze the relationship between both constructs.
Or say you want to know how turnover rates impact sales performance. This is a question with a direct impact on the business and is also about relationships in the data.
To properly analyze data and make predictions you require statistical tests like correlation analysis, regression analysis and more advanced analytics, like decision trees. These statistical functionalities are most of the time not included in existing slice and dice tools.
Contrary to these tools, the tools used for HR analytics are not hard to implement. They are also quite cheap (if not for free). Tools like SPSS, R, Weka and Excel offer all the analytical functionalities you need. These tools enable you to do true HR analytics.
I would encourage everyone to call a spade a spade. Slice and dice tools help you slice and dice your data – and in doing so offer amazing new insights. However, they do not do HR analytics – so let’s not call them analytics tools.
Only when a tool enables you to find (causal) relations in your data, you can call it HR analytics. HR analytics tools are way cheaper (indeed, they are often for free) and help you get more insights from your data than any slice and dice tool every can.