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The keys to reduce resistance to performance measurement lie within the objections our leaders and colleagues hold up against it.

You’ve done your research, you’ve prepared your case, and your next step is to try and convince leaders and colleagues to endorse your proposal to introduce KPIs or improve the performance measurement framework for the team or organisation. And you brace yourself because you know what’s coming…

It will be a torrent of ‘yeah-buts’: objections to giving time, money or effort to performance measurement.

But don’t give in to that initial resistance. The resistance is there for a reason, and it’s the perfect starting point to make a rock-solid case for more meaningful measurement.

Objections are the key to reducing KPI resistance.

Sure, there may come a time when you realise your organisation’s culture is simply not ready for performance measurement. But that should never be your first reaction. Rather, when people object to performance measurement, we can take their objection, without judgement, and redirect its energy to open up a wider point of view. We can more clearly see and test assumptions that aren’t true, and create more choices to reach the outcomes we all want, through better measurement.

But we need to raise and test people’s assumptions about performance measurement delicately, because beneath the surface can be some touchy nerves. They may be fearful of the transparency, of losing their jobs or losing status or resources. But be prepared to test these assumptions too, if they do bubble to the surface, because often they’re not always truth, either.

Let’s explore how this can work for the most common excuses, rebuttals and truisms that keep our leaders and colleagues resisting performance measurement:

1. Performance measurement hasn’t worked in the past.
2. We don’t have time for performance measurement.
3. We already know what matters; performance measures won’t tell us anything new.
4. We only need to measure the bottom line (or budget).
5. It’s too boring and tedious.
6. We don’t have enough data (or the right data).

Let’s dive in…

Objection 1: Performance measurement hasn’t worked in the past.

What’s happening with this objection is that the person is assuming that because there has so far been no successful approach to performance measurement, that means there can’t be a successful approach in the future. Your focus can be on highlighting and testing the assumption that past measurement experiences will repeat themselves. Then, offer an approach to performance measurement that acknowledges the causes of those failures in the past and show how that approach solves those causes.

Time and again we find that it’s actually a lack of a proper performance measurement approach that is the cause of measurement not working. Brainstorming, writing OKRs, and populating a Balanced Scorecard Strategy Map are not proper measurement approaches, and generally will lead to poor measures that fail to inspire anyone.

You might say something like this to test the assumption that past measurement experiences can only repeat themselves:

“You’re absolutely right that performance measurement has had problems – we’ve got too many measures, people don’t find the measures useful, they don’t align to our strategy and staff are spending too much time collecting data for these useless measures. So if we want performance measurement to succeed, we obviously need to modify our approach, to more deliberately solve and prevent these kinds of problems. Here’s how I think we can do that…”

It will work wonders if you do a quick before-and-after demonstration for them, focusing on one of their goals or measures, and show a little of how your approach makes a difference.

Objection 2: We don’t have time for performance measurement.

At the foundation of this objection is the assumption that everything people are currently doing is of a higher priority than performance measurement. This objection sounds like this: “I’ve got real work to do!” The assumption is that getting that work done is more important than knowing if that work is having the intended impact.

Interesting. Why are we busier than we know we should be? Doing things less than optimally or doing things that don’t need to be done at all are often the culprits. That’s what measuring helps us diagnose and test. We already know that people spend a lot of time on urgent things that aren’t in alignment with strategy. We know that time is wasted on rework that results from ineffective or inefficient processes. This is what we need to highlight: how good performance measures can reduce the time wasted by ineffective or inefficient work, and therefore is of a higher priority than getting more of this work done.

Try saying something like this to test the assumption that getting things done is more important than knowing if the right things are getting done the right way:

“I agree – it seems like we’re all getting busier and busier and the last thing we need is something ELSE to try and squeeze into our days. And yet I can’t help noticing how a good proportion of the things we do can be done so much easier and quicker. I truly believe that it’s better to risk taking time out from some of these urgent-but-not-important activities, in order to prevent them from continuing to waste more of our time in the future.”

Make sure to arm yourself with examples from your organisation that reveal hidden rework and inefficiencies in how some work is currently being done, and the consequences this has on business performance.

Objection 3: We already know what matters; performance measures won’t tell us anything new.

This is a belief that merely by looking around or relying on experience, everything that matters is obvious. The assumption is that looking around gives an unbiased, complete and detailed understanding of current performance, and enough detail to detect small but real shifts in performance. Unbiased, complete and sufficiently detailed. But how exactly do they know? How can they put so much credence to their opinion over facts?

The truth is, we all have biases caused by our values and moods and what we notice and what we don’t notice. And these biases prevent us from seeing objectively the patterns and trends that data can show us more quickly and easily. It’s not hard to demonstrate this with a few examples of how data has led people to surprising and valuable insights they otherwise would have missed.

You could try this angle to test the assumption that looking around tells us all we need to know about performance:

“Our people have a fantastic knowledge of the work they do and a very strong commitment to doing their best. Our job is to empower them, so they can more easily focus on what will produce the best results. We can’t expect them to simultaneously watch the big picture as well as what’s right in front of them. Performance measures are great for showing them what’s happening in the big picture, quickly and easily, so they can make the best choices about what’s currently in front of them. “

Follow up with some examples of how performance measures have produced insights that no-one noticed from just looking around, or where their experience led them to conclude something very different to what the data revealed.

Objection 4: We only need to measure the bottom line (or budget).

This is a deeply ingrained belief in many leaders and managers, as a consequence of what is taught in management school. Notice how organisations are structured with a formal Finance team, but so few have formal Performance teams. The assumption is that we only need to measure the movement of money to conclude how an organisation is performing.

The financial bottom line is information that’s too little, too late. We need a broader scope of performance measures about non-money related results that matter, like employee safety and customer value and innovation speed. We also need measures about what drives the results, so we don’t waste money (and time and both physical and psychic energy) pursuing them in the wrong ways. Profit is not the end-game.

Saying something like this could help to test the assumption that business success is evidenced solely by financial measures:

“Financial results will always matter. But any business that wants to survive and thrive has to balance dollars with improving the experiences of people who the business depends on. Customers give us their money, so we cannot ignore the value they expect in return. And employees spend that money, both through the salaries we pay them and their actions at work, so we cannot ignore the performance of the business processes that guide them in doing that. We need a balanced set of measures that make sure our financial results are focused on organisational success.”

You could then sketch out a small Results Map, to demonstrate the systemic relationships among financial and non-financial results and measures, to show the power of a more complete story of business success.

Objection 5: It’s too boring and tedious.

Relating to the first objection above, that measurement hasn’t worked in the past, many people have had only soul destroying experiences with performance measurement. The assumption is that measuring is about monotonously collecting volumes of data and compiling spreadsheets swimming with numbers, then reporting all that to someone else, who doesn’t even use it. Completely understandable!

It highlights one of the biggest failures of measurement approaches: failing to engage people in the value they get from measuring performance. Measurement works when teams are the focal point of the approach. This means each team sets a few measures of goals that matter to them, creates some simple and clear time series graphs for those measures, and collaborates to make the lines on the graphs move closer to a motivating target. This way, they experience purpose, motivation and satisfaction in an important job well done. Measuring performance has been reframed as improving what matters.

You could say this to test the assumption that measuring performance is about data collection and reporting for someone else’s purposes:

“Collecting and reporting data for others is not rewarding, especially when it’s not even clear that they’re using it for anything important, or at all. But that’s now what performance measurement should be. Teams know what matters most in their work, and they can feel so inspired and motivated when they can make a meaningful difference in their work. Measurement is only meaningful when teams choose and use their own measures.”

It will also help to include a story of a team choosing and using their own measures, to illustrate the difference in how the team felt about measurement.

Objection 6: We don’t have enough data (or the right data).

Even if people are open to the idea of measuring performance more meaningfully, they often don’t feel ready for it. And that readiness is often a lack of useful data. The assumption is that the data you have is the only data you should ever need, or can ever have.

Rest assured, no organisation gets the data right, first go. You get the right data when you ask the right questions. And well chosen measures are an expression of the right questions. So having no data is really not an excuse for resisting measurement; it’s actually the only way to get better data.

You could try this opening to test the assumption that data is a prerequisite to starting to measure better:

“How did we decide on the need to collect the data we already have? Was it a deliberate decision or was a bit more random or ad hoc than we might have expected? It’s true that new performance measures often can’t be constructed on existing data. But it’s also true that we won’t ever have the data we need until we start choosing the measures (or information) that is important for our organisation’s success. We can be less ad hoc in our future decisions about the data worth collecting simply by starting with defining the measures we need for our strategy and operations.”

Talk them through identifying one thing they wish they knew about their business performance, but cannot get from existing data. And then guide them to design a measure that would give them that information, and the data it would need. How hard would it be to get at least some sample data for this measure?

The key is to not push back, but instead redirect.

Handling objections to performance measurement requires that we dig a little deeper to understand the assumptions people are making that lead to their objections, raising those assumptions so everyone realises they are there, and then stimulating some dialogue to move beyond the objection.

It’s not about winning a debate with the person who voices the objection. It’s about elevating the dialogue to a constructive level, redirecting the energy toward a better understanding, toward better options and outcomes.