Article

Four myths of performance management

– that may prevent managers from even getting started

This article was originally co-authored by

Published

14 September 2020

A performance management system is a set of metrics that tells us if we have a winning strategy and whether we are doing a good job or not. Knowing the answer to these fundamental questions should be relevant to all companies trying to pursue success in the market.

Few management systems are more effective yet as fast and easy to implement as a performance management system. In spite of this, we can only find a few great performance management systems, and some companies do not even have a first prototype.

Saying that implementing a performance management system is quick and easy is not the same as saying that it does not take some effort. However, if we compare it with implementing other management systems such as an ERP system, GDPR or launching a trainee programme, the effort and investment needed are relatively small.

Looking at performance management a bit simplified, all you need to do is to agree on the targets, gather some performance data and then learn from it. As with any good system, it may of course fail due to bad implementation and execution. There are several articles describing bad performance management practices, e.g. this article on Twelve common pitfalls to avoid – when designing your performance management system.

If you are experiencing any of the pitfalls or mistakes on your journey towards implementing a performance management system, this means that you are at least facing a learning opportunity, and eventually you will get it right. But still, there are a lot of companies out there that will find excuses to not even get started.

This article focuses on the misbeliefs or myths that are holding back some companies from even starting to prototype and eventually succeeding with a performance management system.

Myth #1 Employees will be more stressed by performance measures

Several managers use this myth as a reason not to introduce performance metrics. In their defence, they usually mean well and have the best intentions. These managers do not micromanage and usually have high trust in their employees. However, while believing they are protecting their employees from stress, they often achieve the opposite.

One of the main causes of stress at work is not knowing what is expected of you. At the end of the day, we all want to be able to leave work knowing that we have done a good job. And this is what a well-designed performance management system can provide.

When you clearly define expectations through targets, it is easy for your employees to plan their work accordingly and know when they have met expectations. It goes without saying that targets must be fair, accepted and achievable. Involving your employees in defining target levels is an easy way to gain acceptance and make goals motivating.

Myth #2 We need advanced statistical software and digital screens before we can start

In the modern digital society, many managers think that everything needs to be digital to be taken seriously. This mindset usually delays or stalls improvement initiatives.

Many of the best measures and dialogues we have seen in relation to performance have been around a whiteboard where we have collected data and written it down manually with nothing more expensive than a 40-cent pen. Add Excel, and you are done.

Let’s take a typical call centre manager as an example. They want to know how many of the customer calls that could have been avoided by providing the customer with the right information from the start. The fastest and easiest way to get started is to have each employee draw a line every time one of these calls comes in. The implementation time is close to 0, and in a day or week, you will have a first sample. If the same manager insisted on first building a digital platform where employees would need training to know how to enter and extract data, they would probably still be waiting for the numbers.

Performance management is not about the tools; it is about the conversations and insights you gain from the analysis.

Myth #3 We need real-time data before we can start

Real-time data is typically good for making ongoing decisions while we work. For instance, if you are running a customer service centre, it is always good to know how many customers are waiting on the line so you can switch on more team members when needed.

But in most industries, few performance measures need 100% real-time data. We usually do not need to know how many customers that are currently in all our stores globally. The reason is that we cannot constantly change the way we work in real time anyway. Often, it is enough to know how we performed in the last hour, day or month. So, if your system can only deliver weekly reports, it is no excuse for not getting started. And as with any prototype, you can develop it over time.

If your system can only deliver weekly reports, it is no excuse for not getting started.

Measurements affecting the short-term plan are a bit more time-critical than measurements that tell us if we need to develop new ways of working. However, either scenario rarely has to be done in real time.

That said, performance measures are great for reflection and crucial to our ability to continuously adapt our plans and improve our work. And this is something we should do frequently. However, if we spend all day monitoring real-time data, we probably will not get anything done.

Myth #4 We need perfect data before we can start

How often do you need to know something on the fourth decimal? I am sure you can think of an example if you spend a couple of minutes. But then ask yourself, in how many cases do you think it is the fourth decimal that tells you if you are winning with your strategy or if you are doing a good job?

Don’t get me wrong, accuracy of data is important. But we also need to know when to be pragmatic and see the big picture. In most cases, we want to know if we are going in the right or wrong direction.

It might be that we cannot cut our data in a way so that we know if our customers prefer blue screwdrivers with long handles to red screwdrivers with short handles, but we do know that the sale of screwdrivers is going really well. Or, if five customers called us yesterday to complain about not finding the right information on the website, we should probably review our website instead of waiting for a large enough sample size to prove statistically that the information is not good enough.

Data that is far from perfect still tells us something. Do not be afraid to start using the data you have, and then continue to gather and improve the data just as you would be improving anything else. Analysis paralysis is a state where managers do not dare to act until they have the perfect data, and hence, some are still waiting.

In how many cases do you think it is the fourth decimal that tells you if you are winning with your strategy or if you are doing a good job?

Tips to get started

Start by asking yourself and your team what you need to know to tell whether you are winning and whether you are doing a good job, and define the minimum information you need to answer those questions.

If you cannot get daily reports yet then start with weekly reports, and if you cannot get weekly reports then start with monthly reports. And if you cannot tell if blue screwdrivers sell better than red screwdrivers, but you are making a profit on screwdrivers, you at least know that you should continue to sell screwdrivers.

The accuracy, frequency and level of detail in your performance metrics can be improved over time. But as with everything else, good enough and used is better than perfect but never launched.