Over my career, I’ve learned to become a raving fan of good data. Through trial and error attempts, going as deep as into the databases themselves, I’ve seen how having good data can support making better informed business decisions. Despite all of this, I’ve also seen instances where the metrics that came from this good data were not as effective and meaningful as they could have been.
Based on this, here are some guidelines I’ve learned along the way that can help to ensure your metrics are more effective and meaningful to your stakeholders:
Metric selection and development should occur only after understanding the problem.
Start with the problem you want to address and then find the right way to measure it. This seems self-evident, but we have all seen a dashboard or report and wondered what information or insight the report provided. If no one knows how it is helpful or used, it probably isn’t needed and could lead to confusion.
Metrics need to align with critical business functions.
Failing to align your metrics with critical business functions can lead to measuring things that don’t matter or measuring things for the wrong reasons. Every metric needs to have a purpose and should ultimately reflect the mission and goals of your organization.
What gets measured gets managed.
Metrics should reflect the work the organization wants to monitor and manage. Managing by data allows for better understanding and can often lead to changes in behavior.
Metrics drive both good and bad behavior.
People are inherently competitive in the workplace. This can lead to people doing whatever they need to do in order to ensure their metrics are good, even if it means throwing common sense out the window. This is particularly true if metrics drive scores on annual reviews, promotions, or some other performance criteria. I have seen cases in a call center where average talk time was monitored very carefully and when the call was starting to exceed the desired average, the team member would tell the customer they would need to call them back and end the call. This type of behavior kept their average talk time down, but it did not provide the best level of service to the customer. Metrics provide a benchmark, but they do not replace good management.
Metrics should drive action.
Metrics are ultimately intended to help make informed decisions. A good metric is intended to function as a gauge or indicator of a historical snapshot or trend. Looking at metrics over a period of time allows organizations to identify patterns that will influence future decisions.
Metrics need to be revised or they will become irrelevant.
As processes, personnel, and goals mature and grow, so should the metrics used to monitor key business initiatives. This can be challenging; however, metrics are only effective if they reflect the right underlining definition and processes.
When appropriate, there should be a baseline or time component.
Some metrics must have context in order to be relevant. Reporting that you’re operating at 87% efficiency or have had a 19% increase in sales means nothing without knowing what your normal efficiency level is or how long it took to increase your sales.
Metrics need to be based on legitimate data and calculated accurately.
Stephen Wright said, “42.7% of statistics are made up on the spot”, and while the saying is funny, there is about as much of a foundation for the number 42.7% as there are for the calculations that are sometimes used for metrics. There is the temptation to base metrics on data that makes your team look good. We all know this is ineffective, yet I have seen managers do it without even noticing that they have. It is important to agree on where your data is coming from, how it is gathered, and how aggregate metrics will be calculated.
While this is not an exhaustive list of best practices, hopefully this list will help you refine and keep your metrics on track.