In the past few years, HR has been growing increasingly excited about People Analytics. There’s no doubt that this emerging field has huge potential to revolutionize the way we support, develop and manage our talents. A few weeks ago, I stated that although it can come across as complex, People Analytics as such doesn’t have to be. In this article, I would like to focus on the next step: How can you start? How you can realize the great potential of People Analytics?
Actionable insights: The essence of People Analytics
The essence of People Analytics is to make use of the available data in a practical way, in order to access facts for better decision-making. It’s no more or less than this. It is all about combining input data (data on your people) with output data (data on your business objectives) to create actionable insights.
I want to emphasize the word ‘actionable’ here. The insights generated from People Analytics should enable you to take action; to do something that focuses on improvement. Furthermore, the feedback loop is key. By implementing a feedback loop, you can be sure that you’re tracking progress and evaluating the actions you take. Without a feedback loop, initiatives end up being one-offs and potentially you’ll miss the opportunity to learn and continuously optimize the way you’re working.
Levels of analytics maturity (and ambitions)
There’s a lot of enthusiasm about the opportunities People Analytics brings, but at the same time I see a that many working in talent management are struggling to get started and to develop the field to a more advanced level. A recent Cubiks survey found that just 2% rated their People Analytics activities as ‘advanced’. The majority of survey respondents (67%) rated their analytics programs as ‘operational’.
So, is this a bad thing? Should we all be aiming for the advanced level? No. Definitely not! As outlined in my previous article, using the available data in a smart (or smarter) way can already create a big impact. Also, I’m convinced that it isn’t always worthwhile for every organization to work towards getting to the advanced level.
Some practical advice
Many HR departments are being pushed to make a start with People Analytics. Frequently, we hear things along the lines of, ‘we’ve got a lot of data and information on our people, and we want to use it to improve our business’. In the long term, this is of course doable, but ideally the starting point is more focused and less explorative.
9 HR Analytics
In this case study collection, we have collected the best People Analytics examples we’ve come across over the past years.
To get the best ROI on your analytics activities, you need to be focused. Begin by zooming in on a burning business issue that has a strong people component. Involve a diverse group of people (not just your HR colleagues) to explore the issue and map it out in a data-driven way. Include data from the full employee lifecycle and pay attention to your existing HR metrics and business KPIs. Here are a few examples of questions People analytics can help you answer.
- How does variable pay impact engagement?
- How does team composition impact team productivity?
- How is customer satisfaction impacted by employee engagement?
- Is productivity impacted by overtime hours?
- What causes long and short term sick leave?
Last but not least, you’ll need to be ready to take the final hurdle. When you have done the analyses, combined the data in a smart way and created actionable insights you will need to get your senior team on board. The whole process often starts with them (let’s use the data we have), but experience and research show us that they don’t always find it easy to embrace and accept the insight that the data creates. In the end, they often still trust their gut and tend to rely more on their own experiences instead of the data when they need to make a decision. In a future article, I will spend some more time exploring this dilemma.
To conclude, People Analytics is a huge field, so it’s understandable that taking the initial steps can be overwhelming. In this article, I’ve offered a few tips on the do’s and the don’ts when starting out. Hopefully this practical advice will get you kick started thinking about how to apply analytics in your organization.