There are two terms in Performance reporting that are used interchangeably, but they shouldn’t be. Evaluation and Measurement are very similar processes, but they have important differences. Which process you use is dependent on the information you require about performance.
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 key is in deciding what information you require to make a decision, and then choosing the correct process to provide that information, in other words the right kind of reporting. Until you can articulate what you need to know, you’ll get ALL of the data, not just what you need in any report. It’s a common mistake, but one I see all too often – just because you have the data, doesn’t mean you should include it in your reporting!
Evaluation and Measurement can be used together to assist in the development and improvement of people or systems, but it is important to understand what they are each used for in order to create meaningful reports about your performance.
According to PuMP Creator Stacey Barr, there are some simple ways to think about the differences:
|Focuses on Intervention||Focuses on a Result|
|A Point in Time||Through Time|
|A Before and After Comparison||Continual Monitoring of a Result Through Time|
|Looks for the Story||Looks for the Signals|
|Usually Qualitative but can use Quantitative Data||Generally Quantitative data|
If we put this in some context, measurements 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?”, while evaluation is usually about asking the question “Did this intervention work or not?” – in other words, “did we getting the result that we expected from this intervention?”
With evaluation you need to set a baseline with certain indicators before an intervention takes place, and then compare those same indicators after the intervention is complete. Measurements require continual monitoring of a result through time to look for different signals of change that might be due to a range of different initiatives.
Evaluation uses quantitative measures to decide if change has happened or not, but it also requires qualitative information. As Stacy says in her ‘Measure Up’ blog, with 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.”
So remember, first articulate what you need to know, and then you’ll get meaningful measures and be able to create interventions to improve performance.