There are three mistakes that are common to managers when it comes to metrics. It happens with new managers, but even those who feel that management is old hat sometimes forget about the pitfalls of metrics. At Mystech, we do business analytics and metrics with statistical relevance are very important, but it helps to take them with a grain of salt.
The biggest three mistakes that we see managers make with metrics are: I.) Not using metrics at all. II.) Trying to manage by metrics alone. III.) Not allowing the metrics to evolve.
Not using metrics at all means that the manager is relying on their gut feeling or periodic notes they’ve taken to determine if their employees are performing well. This works well until the employees aren’t performing well and it’s too late to do anything about it. If you’re in the service industry, you find out when customers are complaining. If you’re in the widget industry, you find out when production drops. Metrics are important because they abstract the manager from the personal feelings they have about employees. A good manager compartmentalizes, but a point of reference is necessary to judge how well that compartmentalization is happening and also to recalibrate from time to time. Metrics are that point of reference. If John Q. Employee goes from 45 widgets per hour to 10 widgets per hour, it’s time to start looking into why. How do you measure John’s widget productivity without looking at it? You can’t.
Managers will tell me that they know their employees well enough to know when their production is going to flag or they’re going to start doing poorly on the job. However, that requires the manager to watch their employee all the time and be completely in tune with their employees every day. Let’s face it, even the best managers have off days. Much like blip on a submarine’s sonar, metrics tell you “take a look at this” and once you’re managing with metrics, you’ll never want to go back.
And once you’re managing by the metrics, the pendulum often swings the other direction. It’s easy to see that John’s productivity went from 45 widgets per hour to 10 widgets per hour now. Does that mean John’s a poor employee? What about Jake T. Worker who never produced more than 30 widgets per hour? He was always below John’s 45 widgets. This is where the grain of salt comes in. There is no magic bullet metric or even complex algorithmic combination of metrics that will replace a manager. Metrics give managers insight into what’s going on, but it’s up to the manager to interpret the data and understand why the metric is where it is. The go-to in this scenario is the pep-talk: “Hey guys, production is down and we need to get production back up. Let’s go out there and produce!” But if production is down because the equipment isn’t working (widget machines are on the fritz, we can’t take new orders because the phones are layered with static, our service is slow because we have that one new customer taking up all of our time) then it’s unlikely that the pep talk is going to work.
Managing by metrics is great because they tell you that something needs to be looked at, but they don’t tell you WHAT needs to be looked at. Sure, sometimes that thing that needs to be looked at is that John went off the deep end and isn’t coming back to the productivity cycle, but an effective manager reviews the metrics and then finds out why the metrics change. Of course, there’s always the pitfall of explaining all of your metrics away, but striking the balance is where a good manager falls.
This brings us to evolving metrics. A good manager can also explain every reason that metrics change; especially a good manager in middle management who has to report in a weekly meeting. There are always reasons and they’re all good reasons, but metrics are never stagnant targets. If you find yourself explaining away your metrics every week, it means that either those metrics don’t fit your business or the metrics have evolved such that they need to be modified. Good organizations are constantly changing — direction, focus, equipment, people, processes. These are all variables that change the metrics. We get faster, more efficient, or even more automated. It’s important to realize when your metrics need to evolve, and that requires understanding what your metrics are telling you.
The best example I’ve seen of this is when a new efficiency process is added to automate some of the work. All of a sudden production metrics go down because now the automation is taking care of all of the “quick stuff.” John is producing 10 widgets because he’s working on the line for the new machine and the 10 widgets he’s producing sit on top of the 100 widgets the machine is producing. Now we’re at 110 widgets per hour, but the machine is doing the majority of production. John’s productivity is too low based on our previous metrics, and the machine’s is extremely high, so the metrics need to evolve to take this into account. Maybe John’s new goal is 1 widget for every 10 that his automated machine produces. This goes for service tickets, phone calls, whatever your organization is measuring. It’s important to understand your metrics.
Good managers understand their metrics. The best managers effectively use their metrics to drive efficiency and affect change in the organization. It’s how you get upper management to buy that new software, get employees to work faster, or just continue with a great level of output showing how much better you are than your competition. The key is an intimate understanding of your metrics and how to use them. What are some metrics that you’re measuring right now that may not fit just right?