The findings of any experiment are only as good as its ingredients. As in, if any are missing, or contaminated, the results will be unreliable. In our case, measuring program impact requires that all relevant variables be added to our client implementation and performance data.
Identify Participant Variables
First, we need to account for participant variables. This means whoever we were working directly with to implement the program (which is often delegated by the client to the appropriate member of their management team). Education level, business experience, tenure, ownership status, etc all have the potential to affect outcomes. This of course requires participant consent and participation.
Identify Business Variables
Second, we need to account for situational business factors. This includes business age, size, previous managers, etc.
Identify Market Variables
Third, consider situational market factors. Seasonality, weather disasters, pandemics (like Covid-19), politics (like tariffs), recessions, etc.
Lastly, we compile all variable data, within the determined timeframe, and format it for interactions with our implementation and performance data sets.
Worth noting: All data gathering is done with client approval and participation.
At this point, assuming that we have a critical mass of data, we now have all the necessary raw ingredients for an econometric study. Next up, enter objective researchers…