Evaluation is about looking for improvement. But so is performance measurement. So why don’t we call them the same thing? Well, it’s because they’re different.
Even though both performance measurement and evaluation are about deciding if something is better or not, they differ in a few fundamental ways.
Evaluation focuses on an intervention. Measurement focuses on a result.
That might sound not quite right. Evaluation is about results too, isn’t it? Yes but in a different way.
Performance measures focus on specific performance results that might be the target of several interventions, several different initiatives or projects applied at different points in time. It’s about asking the question “Is this result improving or not?”
Evaluation is usually about asking the question “Did this intervention work or not?”
Evaluation is a point in time. Measurement is through time.
Evaluation is usually about a before and after comparison. You want to set a baseline with certain indicators before an intervention takes place, and then compare those same indicators after the intervention is done:
- What impact did this education program have on teenage pregnancy in our city?
- How did speed-related traffic accidents change as a result of the lates TV advertising campaign?
- How much did customer loyalty change after we implemented our new loyalty rewards program?
Performance measurement is a continual monitoring of a result through time, often for many years, to look for different signals of change that might be due to a range of different programs or campaigns or initiatives:
- How is teenage pregnancy tracking over time?
- Is the rate of speed-related traffic accidents increasing, decreasing, or staying the same?
- What signals or patterns are there in the trend of customer retention rate?
Evaluation looks for the story. Performance measurement looks for the signals.
Evaluation certainly can use quantitative measures to decide if change has happened or not. But it also very often pulls qualitative information into the pot. Sometimes, as with the Most Significant Change Technique, the data is only qualitative.
With performance measures, you really are looking for signals of change in the time series of quantitative data. It’s not to say you should use your performance measures in isolation. When linked together, a set of performance measures can tell a powerful story too.
The difference is subtle, but definitive.
You can use evaluation to see if a specific initiative has had an impact on a particular performance measure. And you can use performance measures as tools within an evaluation. The perspective that each takes is a bit different, is all.
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