When Metrics Matter and When They Don’t…

datadrivenanalysisWe live in a data-driven world.  Volumes of information are accessible with the push of a button or the touch of a screen. Supercomputers exponentially more powerful than those used to put man on the moon sit casually in our pockets.  We are incredibly lucky to live in an era where the concept of advanced statistics isn't walled behind the ivory towers of institution but can be readily digested and interpreted by anyone who's willing to look hard enough.

With the amount of data available to digest and the abundance of user-friendly tools that can be used to quickly process that data, a business can generate metrics for nearly every potential process output.  On the surface, this is an enormous boon for managers, as they should be able to tell exactly what their teams are doing and how efficiently it's being done.

But that data doesn't always tell the whole story, or even the right story at all. What if all that data is doing us a disservice? What if the data we've come to rely on and, in some cases, take for granted, is harming our decision-making abilities. When do metrics matter?  And, more importantly, when don't they?

data metrics visual worldMetrics is an umbrella term used to define the data that measures performance. Businesses use metrics like overall sales volume, profitability, and total sales by category to give themselves an idea of where they stand relative to everyone else, or in many cases, how an individual business unit's productivity measures up within the organization. These numbers matter.  A business should always know what it's good at and what still needs work. It should know which processes are working, and which are redundant or broken. Metrics open that door.


People perform processes, those processes drive action that lead to more processes which ultimately creates a product or service that is purchased.  This is not a revolutionary concept but it's not as simple as it appears on paper.  Each process within a given business can potentially be broken down into smaller, multi-step sub-processes that all need to be done to keep the machine running efficiently.  As processes add layers and hand-offs, complications arise.  As most businesses grow, the focus shifts to include scalability (or, being able to expand and replicate today's process to work in tomorrow's bigger, more successful business).  This is where a metric's ability to measure performance (or success, in other words) can break down.


people analyzing dataIf a process used today won't scale well tomorrow because there are too many manual steps or moving parts, reporting that metric won't provide any insight.  Over time, you might see a change as that metric becomes harder to achieve. But with competitors around every corner, every second counts. Proactive process improvement and forward-thinking strategies often separate the rock-star companies from the failed start-ups. Metrics, unfortunately, fail to capture that future viewpoint in many cases.

Metrics can show pieces of this puzzle, but they often fall short of reporting the whole picture when looking long term.  It takes creative problem solving, teamwork, and most importantly strong management to see what's coming down the road without relying solely on the numbers. One of the most effective skills in a successful manager's arsenal is the ability to recognize when the metric isn't showing them the whole picture. Making decisions that improve not only the efficiency and scalability of a process, but also improve the validity of the metrics that can be reported for that process, creates positive ripple effects that will be felt for years to come.


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