Measuring large scale change

Many complex programs are designed to deliver large scale change. A key concept is knowing when a change is being made, and whether it is in the right direction.  Large system change is different to process change in that it seldom has a clear beginning and end, has multiple causal factors (some of which we will never know), and the result is often separated from the action in time and space.

Differentiating the types of measures from each other helps, as well as estimating and checking connecting between them.  The following categories may be useful to you in deciding how to measure what.

Inputs: a bit like a baseline measure though perhaps a bit more active. It could be the number of patients not attending their appointments or the % of staff committed to a new organisational vision.

Activities: this counts how much is done of something designed to engender change. IN the case of large scale change there may be a variety of activities underway at the same time. This could be the % increase in number of people attending a workshop, the number of patients

Outputs: the results of the specific activities. So if the number of employees attending a patient experience workshop increased, and the workshop had an aim of improving staff satisfaction, then an output would be the amount of increase in staff satisfaction (and perhaps compared to areas where employees had not attended the workshop.

The above three measures often look alike. What is key is to understand what large scale change is being measured and to think through, and perhaps map, the links between the identified measures.

Outcomes: this differs from outputs in that it moves up a higher level - more long term, bigger impact. For example, if patient satisfaction increases then an outcome may be more patients returning, more income etc.

Impacts: this is the final level of measure. Perhaps the organisation reaches a new public grading, patients in the local area experience better health as a result of the improved services etc. Reduced health inequalities is another example.

Identifying the measures is only half of the learning from measuring for large scale change.A key step is to find a way to map out the linkages between the measures. To do this at the start of a program is helpful as learning from the actual measures can be replotted. This will help identify whether movement to the large scale change is underway as a result of the current activities - or not.