I haven’t done the detailed research, but imagine if I look back at all of my post-HR Technology Conference blogs over the last six years, the word ‘analytics’ would come up each and every time. Analytics are important – 54% of respondents to Brandon Hall Group’s 2014 Workforce Management Study said that their top priority was improving their workforce analytics capability. We’ve been talking about HR analytics for long time, and now more of us are starting to talk predictive analytics. But a lot of people – both HR professionals and solution providers – are talking about analytics without really understanding what it means.
When people say analytics, what they are really thinking about is data dressed up and presented in full living color. But just because your data is displayed in color, doesn’t mean you have analytics. Because data is just that – points of information. It doesn’t have context or relative meaning. It just is – the depiction of reality for one facet of information. Data are things like the number of new hires that leave the organization within 90 days, or the number of people who are absent in a given month. This information can be useful. Certainly having more visually appealing ways and dashboards to examine it can be helpful. But it’s not analytics.
Analytics requires you to combine information to start to understand why things are happening. If you can combine information on new hire turnover with data on training completion rates, new hire engagement scores, or assessment of critical skills and capabilities, you start to have insight. While you may not always be able to draw direct causation, you can begin to understand correlation. You can notice a trend that, when new hires don’t complete their training, they tend to leave the organization. You can see that when you have more than three people absent in a given week, productivity drops by 6%. This is the type of insight that allows organizations to start diagnosing critical issues, and putting in place strategies to address them.
Predictive analytics takes things to a whole new level, requiring a depth of data analysis that truly allows you to understand causation, and use that information to model what is likely to happen under given circumstances in the future. The analytical horsepower required for this level of detail takes real work, and is something that many organizations and solutions still struggle to deliver. It doesn’t mean it’s not possible or real, but it is a different way of thinking about your HCM data, and not something every provider can do out-of-the-box.
Data, analytics, and predictive analytics are exceptionally important for the modern HR organization, but leaders need to be aware that data in color is not analytics. If you really want to get a return on your analytics investment, you need to find solutions and build processes that allow you to truly get at combining data to allow for insight, and using that data to get at root causes and correlations that will ultimately let them be predictive.