Have you ever noticed that there seems to be a great deal of confusion on the basic terminology involved in workforce analytics? What is a measure and how is it different from pure data? Is an indicator equivalent to a metric? And finally, how do these tie into analytics in the world of human capital?
We have all heard these terms being used interchangeably. While the differences between them can seem negligible, you have to apply the terminology appropriately if you want to confidently engage in discussions related to any organizational activity.
So how does data become an integral part of analytics? Below is a brief discussion on understanding its progress.
A measure is no more than data that is collected with no specific reason or purpose. For example, the number of terminations in January 2011 is an example of a measure. How do we know if 100 terminations a month is good or bad? We don’t – a single measure has very little value without context.
Suppose we track terminations monthly over a five-year period between 2006 and 2011. Now we have some perspective and can see, perhaps, that our terminations have been creeping up. We are looking to capture a specific quality to the data. Whenever we measure something with the goal of gauging some quantifiable component of a company’s performance, whether it is revenues or terminations, we are talking about a metric.
Let’s take this one step further. Now we are examining the five-year trend of terminations which gives us a basic understanding of the relationship between our monthly numbers. However, the fact that terminations have been trending up does not give us the complete picture of how well (or not well) the organization is doing with respect to attrition. Do we know, for example, if the increase is attributable to the growth in our employee count due to our recent expansion efforts? Or are members of our staff leaving because they are unhappy with management? Measuring terminations against a baseline such as the average number of employees or budgeted terminations gives us significantly more context. Termination rates and actual vs. budgeted terminations are both indicators. They are metrics that act as guides to help assess the performance of a certain aspect of organizational activities – in this case, attrition. Additionally, employee turnover can become a Key Performance Indicator if it reflects organizational goals and has been selected as a key metric to measure progress toward those goals.
And tying it all together – analytics. Workforce analytics transforms all the above – measures, metrics and KPIs – into a relevant storyline. It is the process by which we identify what story is developing and then explain the plot by looking at trends, patterns, outliers, and possible relationships in the data, breaking it down and turning it into insight in order to make human capital decisions that impact business results.
So…what is your story?