Today we’ve got data on almost everything and the amount is growing with exponential speed. There is no disputing that we are well and truly into the 4th industrial revolution; an exciting digital era. With the availability of complex algorithms, artificial intelligence and machine learning, our predictive powers are rapidly growing and becoming increasingly precise.
In 2016, HR began to embrace the promise of People Analytics. This shift has been driven by the pressure on HR to use employee data to create powerful insights and add value to the business. However, at the start of 2017, those in the field have still got a lot of questions. These include; How does People Analytics work? Where should we start? What will the impact be? Will this approach turn people into numbers? What value can it add? And, is it as complex as it sounds?
Getting started doesn’t need to be overwhelming. Imagine the insights you could draw from the data you already have. For example, you could:
- Explore productivity, sickness leave, over-time hours and safety incidents
- Compare the characteristics of your high performers vs. the bottom 20%
- Look at the differences between your most critical functions and your temporary workforce
- Delve into the relationship between employee engagement and employee turnover
- Focus on the link between Customer Satisfaction and employee performance
- And much more…
A key concern for those starting out is that People Analytics might be seen as turning people into statistics. But this doesn’t need to be the case. To quote Alan Murray, Editor of Fortune Magazine, ‘We don’t need to make people better machines, we need to make people better people’. I strongly believe that when People Analytics is applied in the right way, it provides the facts and insights we need to make this happen.
If we think back on the history of predicting human behaviour in a working environment, there was a time when we relied heavily on theories. Theories about what made people effective in their roles, what made them a high potential (or not), and so on. These theories are often derived from psychological or sociological insights regarding people’s key drivers and motivators. The insights are backed up by the opinions of experts; not only academics, but also managers, HR professionals and customers.
In today’s world, we can apply data to add another layer to the equation. This doesn’t replace the theory and the expertise, but it adds deeper insight and more power to the prediction. It adds evidence that can support existing ideas, but at moments can and will also challenge and alter them.
The great promise of People Analytics is threefold
- To support us with making evidence-based people decisions
- To create new, deeper, and more varied insights
- To increase fairness, transparency and objectivity.
People Analytics is often seen as something complex; focussed on making convoluted predictions regarding what might happen in the future. In my experience, it doesn’t have to be complex and even taking small steps will add huge value. What’s essential is to use the available data in a smart way and to educate ourselves and our organisations about taking a more fact-based approach to tackling people challenges.
The bottom line is: Using data forces us to be more open minded, to look outside of our gut-feeling and beyond our current knowledge and experience. When we achieve this, we can really begin to maximise the potential of individuals as well as the organisations they work for.
This is the first part of a two-part series by Jouko van Aggelen. Part 2 will be published on March 6th.