Service Management Leadership - Sticky Metrics

Speaker A: M. Foreign. Welcome to the Service Management Leadership Podcast with Jeffrey Tefertiller. Welcome to the Service Management Leadership Podcast. My name is Jeffrey Tfertiler and I have a great topic for you. I have been a, uh, part of the sports analytics world for a lot of years. Coming up on year 20 this fall. And in the sports analytics world there is a something called sticky metrics and there's this big desire to identify sticky metrics and what Sticky metrics seems like an odd name, but it's ones with historically strong correlation as leading indicators. We have these in our own lives that we just gloss over. If it thunders outside, it's probably going to rain, right? Think about that. In every part of our business world, our service management world, our transformation world, there are sticky metrics that have strong correlation as leading indicators, meaning we can predict that if something happens, something else will happen. In the stickiness just refers to the strong correlation and predictability. So this means that we are able to make educated decisions based upon the predictability of these metrics. Some sports are easier to identify metrics than others. I think of um, watching the World cup, maybe time of possession, shots on goal. There are metrics that predict outcomes much better than others. But a lot of times sports struggle with analytics because maybe there's not a big enough data sample size, maybe the predictability is difficult for one reason or another. But the stickiness metrics has made me think about our IT metrics. Right. Of course, I always think about it in our work terms. Which of our metrics have large enough sample sizes that are still very highly correlated leading predictable indicators. There are some, if we stop and think about it. Let me start by saying that this observation that most organizations don't think like this, so they really don't think what's sticky and what's not, what's predictable and what's not. But let me give you one. If we have a failed change to a big system, we're probably going to have an outage. Right? That makes sense. But let's start with some really deep ones. Positive user experience is the outcome we get oftentimes very predictable. When there is great self service, you have great self service. It's predictable that you will have great user experience. Another one, you have, uh, higher rates of incidents when unaddressed defects are allowed to go live. That's very sticky. Right? You have defects that go live. M. We're probably going to have incidents that we don't know how to resolve quickly. Here's another one. Service desk volume metrics. After A failed change. Yep. The service desk phones are going to get lit up Tom, because there's an outage and people are just struggling to be able to do their work. And here's the last one. You're going to have higher rates of uh, failed changes if you have an unpredictable, unreliable cmdb. If we know that these sticky metrics are true and you can think of the ones in security. Right. If you don't patch frequently and often you're, you're pretty likely to have a security, uh, incident or situation. You can adapt these to whichever ever, whichever part of an organization you reside. But if you grant me this thought process that these are true, how do you respond? How will you now say it? I, uh, know that if this happens, then that happens. How are you going to respond? How are you going to change the ways that you do work? Because many times we try to resolve the symptom when really the sticky metric is showing us the down deep rooted problem. This is Jeffrey Tiefertiller. Thank you for being a part of what we're doing. Thank you for supporting service management leadership. Let me know how either I or service management leadership can help your organization. We, uh, put out a lot of content just to try to be of value to those that are trying to increase how they think about these topics. So thank you for your support. Hope you have an awesome rest of your day and bye.