How Can We Make Use of Big Data in HR?

July 12, 2017 Richard Justenhoven
big talent data

The Challenge of Accessing HR Data

So-called ‘Big Data’ continues to prompt discussion and investigation within businesses. The initial focus on consumer applications remains but now there is interest in how to apply this approach to internal business functions such as HR.

Peter Cappelli suggests in his article for Harvard Business Review that HR’s interest in Big Data may be because it’s seen as the ‘next big thing’ and that, as a function, it’s under pressure to be more analytical, less ‘soft’ and, in many cases, more strategic.

Cappelli questions whether HR actually possesses the ‘Big Data’ it thinks it has citing that typically HR data is held on possibly thousands of employees and applicants – and not the millions that is usually associated with Big Data projects in, for example, consumer research. He also points out that much of HR’s data is from annual events such as performance reviews rather than the perhaps daily interactions and data points gathered in commercial projects. But Cappelli sees the greatest challenge to Big Data projects within HR is HR data is typically stored in separate databases (such as assessment systems, Application Tracking systems and other HR information systems) making data access difficult.

He is of course correct on all these points – and there is greater integration by vendors between such systems – but he misses out a key area.

In our work with clients we see that one of the most fundamental challenges to such projects is that most organisations just don’t have standardised ways of assessing performance, let alone storing it and matching it up with assessment data.

And yet, despite these challenges, we see a growth in the level of interest in this area and a thirst for wanting to dig deeper, understand the data that they have and change their processes to make the information they have more valuable. They want to make greater use of the data that they store and to try to understand what the combinations and correlations mean.

Talent Analytics is an area of our work which helps organisations to look at what makes people successful in different positions in their company and this then forms the basis for defining potential for these positions. We believe that, for HR, Big Data needs to be transformed into more meaningful, ‘smart data’ – and this is done through Talent Analytics.

We help clients to forward plan, and guide them as they look to cleanse their data and concentrate only on that which is valid and reliable. We help them to identify the relevant performance metrics and therefore what high performance means across different jobs and levels, and on a practical level we help them set up their systems so that the data can be matched.

We offer statistical and number crunching nous – and, with a Research team focused on helping clients get the very most from their assessment data, we help them to then tweak their assessment processes.

We see that our clients want to apply their new found knowledge and to make the tweaks and changes needed to refine their HR processes and approaches to bring about, for example, better prediction.

So what have predictive talent analytics given businesses?

One client we have helped to make sense of its talent data is Dell. By drilling down into the understanding of the characteristics of great sales people and adjusting selection assessment accordingly, it was able to show an increase of 36% more revenue and 42% more profit for a specific area of its business. And this is just one example.

So, how big is Big data in HR? It’s going to get bigger.


Cappelli, P. (2017, June 2). There’s no such thing a Big Data in HR. Harvard Business Review.

About the Author

Richard Justenhoven

Richard Justenhoven is the product development director within Aon's Assessment Solutions. A leading organizational psychologist, Richard is an acknowledged expert in the design, implementation and evaluation of online assessments and a sought after speaker about such topics.

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