A couple of posts ago I reported on a study on rates of return to research. One of the main challenges identified by the author was the attribution problem -which could be re-interpreted as the contribution problem.
This brief note by John Mayne for ILAC provides an approach to address this challenge. In his words:
Contribution analysis explores attribution through assessing the contribution a programme is making to observed results. It sets out to verify the theory of change behind a programme and, at the same time, takes into consideration other influencing factors. Causality is inferred from the following evidence:
- The programme is based on a reasoned theory of change: the assumptions behind why the program is expected to work are sound, are plausible, and are agreed upon by at least some of the key players.
- The activities of the programme were implemented.
- The theory of change is verified by evidence: the chain of expected results occurred.
- Other factors influencing the programme were assessed and were either shown not to have made a significant contribution or, if they did, the relative contribution was recognised.
This type of analysis is consistent with theory based approaches like Outcome Mapping, the RAPID Outcome Mapping Approach (ROMA), and the RAPID Outcome Assessment (ROA). It is particularly relevant for interventions where various actors are involved and partially responsible for influencing change.