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Tom Mckeown

The great Irish statesman Edmund Burke was known to have said, “Those who don’t know history are doomed to repeat it.”  This adage is as true in business as it is in politics.  Failed business leaders rarely look at more than the current moment or quarter when making important decisions, while successful ones have a strategy plotted out that encompasses a much broader timetable.

Metrics are pieces of data that are merely a snapshot in time.  In the human resource world, an example of a popular and useful metric is workforce turnover.  If you were to ask a VP of HR what the rate of turnover is at their company, they could likely access their HRIS system and provide that to you in short time.  But what does that tell you, that the current rate of turnover at the company is say 15%?  How do you know if that is good or bad?

Analytics are what would give you the relative picture on metrics.  The first step is to trend metrics.  The above metric of 15% might be a positive one if the previous months were 25% and 20% respectively, or bad if the prior months were lower.  You then might be able to tie certain events to trends, such as the fact that turnover began to rise when your company implemented a new benefits policy, or decreased when a new CEO came on board.  Thus you are able learn from your history and plan for the future.

Search engine giant Google has always been on the forefront of search analytics, but they’ve also applied that expertise to their hiring process.  Through researched data and historical patterns thecompany has deep knowledge into the likelihood of retention.  For example, one of Google’s findings is that new salespeople, who do not get a promotion within four years, are much more likely to leave the company.

The second step in analytics is the drilling down on your data.  Again you might see the overall turnover trend going down month to month, but is that true in all areas of your business? Smart organizations track high performers and high potentials as groups within their employee population.  You might find that overall turnover is going down but high performer departures are on the rise.  This would certainly be a trend you would want to reverse, and learning the history and root causes would be the first step.

A good example at drilling down on analytical data can be provided at the GSA (General Services Administration).  This independent agency was set up to help manage and support the basic functioning of federal agencies.  Officers at the GSA often need to drill down across divisions and through management levels to find where employee problems are and what needs to be fixed.  Analysts and managers require this capability to track aggregate employee engagement and how divisions are performing against each other.

So, make sure you are getting the whole picture when looking at your HR data.  Trending your past metrics into actionable analytics can let you know if you are on the right course, or indicate whether you need to make to a correction.

This article originally appeared on the TrenData website.