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Organizations have access to more performance data than ever. Reports are generated, dashboards are reviewed, and KPIs are tracked across departments and teams.
But more data doesn’t always create more clarity.
A measure may show that performance changed, but is the change meaningful? A dashboard may display dozens of metrics, but which ones actually tell you something important about the health of the work? And when a gap appears, how do you know where to focus?
Work Measurement helps connect the work being done, the measures used to evaluate it, and the data behind those measures so leaders can better understand performance and focus improvement.
Work Measurement is a structured way to define what successful performance looks like, determine what needs to be measured, and use those measures to identify meaningful performance gaps and opportunities for improvement.
It starts with the work itself.
What does successful performance look like? What should we measure to know whether we are achieving it? Where are the gaps? Which gaps actually require attention?
Without those answers, it is easy to keep adding KPIs, reports, and dashboards without improving how performance is managed.
The goal is not to measure more. It is to measure what helps people understand the work and make better decisions.
Suppose an operation completed 1,200 units this week.
Is that good performance?
If the expectation was 1,000 units, the result may indicate strong performance. If the expectation was 1,500, there is a gap to investigate. And if output increased while quality declined, there is more to consider.
The number alone isn’t enough. It needs context.
Leaders need to define what successful performance looks like so actual results can be compared against expectations. When a meaningful gap appears, they can determine whether it requires attention and begin looking at what is driving it.
That is much more useful than simply knowing whether a number went up or down.
Once you know what needs to be measured, the next question is whether you have the right data to support it.
Where does the data come from? How is it developed? Is it reliable? Is it structured in a useful way? Can the right people access it when they need it?
This is where performance measurement and data strategy need to connect.
Work Excellence focuses on what matters to measure, what successful performance looks like, what the measures are telling you, and where improvement should be focused.
EPM Strategy focuses on the data needed to support those measures: how it is developed, where it resides, how it is structured, and how Microsoft tools can help people access and use it.
If an organization identifies an important measure but cannot reliably access the data behind it, that measure becomes difficult to use consistently.
At the same time, well-organized data has limited value if it is not connected to what leaders need to know about the work.
Technology can make performance information easier to access, organize, visualize, and use. But technology works best when the organization first understands what it needs to know.
Before building another report or dashboard, ask:
What do we need to know about performance? Which measures will help us understand it? What data supports those measures? Where will that data come from? What decisions should this information help people make?
With those questions answered, Microsoft tools such as Power BI can make the information more accessible and useful.
A dashboard is a tool. The decisions about what belongs on it come first.
Performance reporting tells you what happened. Performance management helps you determine what deserves attention and what to do next.
That distinction matters.
Managing performance requires knowing what was expected, comparing expectations to actual results, identifying meaningful gaps, and determining whether action is needed.
It also requires consistency across the organization.
Leaders need measures that reflect what is happening in the work. Teams need to know what is expected. The people responsible for data need to understand what information is needed and how it will be used.
When those pieces are not connected, different parts of the organization can end up working from different views of performance. One department tracks one set of measures while leadership reviews another. More reports get created to answer questions the existing reports do not address.
The organization ends up with plenty of information but no consistent way to determine what deserves attention.
As organizations grow, seeing what is happening across the business becomes harder.
There are more people, processes, systems, customers, and sources of data. Leaders cannot observe everything directly, so measures become an important way to understand how the work is performing.
But everything that can be measured does not need to be measured.
Useful measures help leaders narrow their attention to the areas that say something meaningful about performance. When there is a gap, they can look deeper. When performance is where it should be, they can focus elsewhere.
That ability to focus is one of the practical benefits of Work Measurement.
Instead of asking, “What does all this data tell us?” leaders can ask, “Where are the meaningful gaps, and what deserves our attention?”
A practical performance measurement process starts with the work, not the dashboard.
First, define what successful performance looks like. From there, determine what needs to be measured and what data is required to support those measures.
Then make that information available to the people who need it and use what the measures reveal to determine where improvement is needed.
Understand the work. Define the measures. Connect the data. Focus improvement.
This gives leaders a practical way to move from collecting information to using it.
Organizations often have plenty of measures but still struggle to understand performance. Some common signs include dashboards that continue to grow, teams tracking different versions of the same metric, meetings spent debating the numbers instead of acting on them, or leaders repeatedly asking for additional reports to understand what is happening.
Another sign is having measures that report activity without showing whether the work is performing as expected.
When that happens, the problem may not be a lack of data. The organization may need a clearer connection between the work, the expected outcome, the measure, and the data supporting it.
Work Measurement is not about creating more measures. It is about making sure the measures being used help people understand performance and know where to focus.
That means looking beyond the measure itself.
Organizations need to understand the work being measured, define what successful performance looks like, identify the measures that provide meaningful visibility, and make sure reliable data is available to support them.
Technology can then help organize and deliver that information in a way that makes it easier to use.
The result is not simply a better dashboard. It is a better way to understand performance and focus improvement.
This is the focus of the upcoming Work Measurement Executive Working Session on October 29 in Bentonville, Arkansas, presented by Work Excellence and EPM Strategy.
The working session will bring together two sides of performance management that are often addressed separately: determining what you need to measure and understanding the data and technology needed to support it.
Participants will explore how to define meaningful measures, understand performance gaps, evaluate the data behind those measures, and use tools such as Power BI to make performance information more accessible and useful.
The goal is practical: leave with a clearer way to think about what your organization measures, what the data is telling you, and where to focus next.
For leadership teams, there is a simple question worth asking:
Do the measures and data we have today actually help us know where to focus?
If the answer is not clear, there may be an opportunity to rethink what is being measured, how success is defined, and whether the right data is available to support it.
Know what you need to measure. Understand the data behind it. Know how to put it to use.
