Boosting the positive effects of performance management

Welcome to this 9th talk on performance management. My name is Pietro Micheli. I'm a professor of business performance and innovation at Warwick Business School in the UK. The topic is boosting the positive effects of performance management.

The first thing to do is to really analyze some of the myths that we tend to have in relation to performance management. Let me go through this slide line-by-line. The first one is that the holy grail or the end result, is often what we see as so-called objective data, something that has no subjective interference, that is rational, that is true. Now, from what we've covered so far, you've probably seen that this is a bit of a myth. Objective data doesn't necessarily exist. It doesn't mean that anything goes, but it doesn't mean either that we can find the truth. Perhaps we can land on something that is a bit clumsy when we talk about it, but probably we can relate to. In academic language, you will call this inter-subjective information, which means something that different people make sense of in the same way. So, maybe it's not the truth, but is something that we regard and understand in a similar way. It's not the truth that the ratio between sales from new product divided by total sales is the perfect measure of innovation. But actually we can probably understand it together in the same way and understand the fact that this gives us an indication. It's an indication of innovativeness as much as new ideas, or customer reactions to new products or services, and so on. That inter-subjective component is probably more interesting than aiming for something that is a bit of a myth. The second one is about the criteria that we use. Now, of course, we want our systems to be accurate and precise in the information that they give us. At the same time, perfect accuracy and precision will never be there. Perfect accuracy means that we measure something and get the data, again that are true, and precision that every time we do something, we'll get the same result. Now, we can aim for some of that. We can probably aim for something that is less demanding, but still very useful, that you could call adequacy and usefulness - so something that is good enough and that we can use. That's the most important thing, is not the data "per se", but actually what can we do with them that matters the most. Therefore, what creates value? It's not the process of gathering and analyzing data and communicating them, but it's actually what we can do with it. The user performance information becomes the priority. It's a bit of a myth that the fact that we can gather and analyze data in the perfect way is going to give us value. The value comes from the fact that we can do something about it. Information about individual performance, or group performance, and what we can do with, it's more important than trying to find the best system that we can ever come up with. Now, we've spoken about alignment in various talks as part of this series. Alignment is often thought as something that is achieved from the top-down to different levels, so functions or business units, teams, individuals and so on. Now, it's important to do so, and we certainly need to have clarity of direction, but we also need to have involvement and a sufficient degree of discretion, particularly now that organizations have to navigate environments that are much more dynamic, complex, ambiguous than we used have in the past. Relying only on a top-down implementation with lots of performance measurement systems, that essentially become disaggregated as we go down, is probably not the best way to think about. The most important thing is that we try to get engagement and involvement and have a certain level of discretion of authority lower down the system, particularly in large organizations. The focus in performance management is often on the tools that are typically measures, or KPIs, and targets. Now that's important, of course, we want to try to understand and guide performance and give targets to individuals or teams in a way that incentivizes them, or motivates them towards what we want. But ultimately, the most important thing remains our objectives. We want to aim for something that it's important to us as an organization, so we can try to improve customer loyalty, for example, or advocacy or reputation - those will be objectives. Then we can measure this in different ways. We can run surveys, we can use Net Promoter scores, we can look at waiting times, re-purchase intentions, compliments and complains, sentiment online. There's plenty of ways we can do so. But the most important thing is that, eventually, we see that the loyalty and advocacy of customers is something that increases in the various ways that we measure it. It's the objective that matters, not the mechanisms that allow us to gather data and analyze them in some way. It's important that we think about change over time that comes not only from the fact that our measurement system, at whatever level we look at it, is very comprehensive, but actually that is concise or it is not too big and it's sufficiently flexible. If we have measurement systems that are set in stone and remain the same for a long period of time, they tend to drag us back into what we were doing in the past and unnecessarily pushing us forward to where we want to be. Measurement is mainly not so much for reporting and monitoring, but it has to be there for learning and improvement. It needs to have more of an attitude of trying to give us a push towards the future, again, something that we can make better over time, not just something that we want to understand and essentially doing what is called managing by looking at the rear-view mirror. If you look at all these seven myths, the point is not that the column in the middle is entirely wrong, but the column on the right probably gives us a better sense of what we should be trying to do. Achieving a situation where the information is understood in similar ways, even though it's not perhaps perfect, that is good enough, and it's useful, and the usage of performance information is there to improve performance. There is an element of top-down implementation where we can also involve people throughout the cascading of the process, but also the design of it, where what's most important are the objectives and the main aims of the organization. Not only the tools that help us measure performance and the fact that the measurement system is sufficiently small, so it doesn't mushroom into dozens of performance indicators everywhere, and it's sufficiently flexible and eventually get us to learn and improve, not just monitor and report.