Outcome harvesting is about collecting and explaining a (hopefully long and substantial) list of intended and unintended outcomes after the fact, and identifying how the programme contributed to the outcomes. But it's just like a list of cause-effect relationships. It can be a challenge to understand how those causes and effects overlap with one another or influence one another.
Causal mapping is quite similar. It is not an evaluation method in its own right, but more of a tool which can assist with either. it's about visualizing and interrogating the whole web of causes and effects. It explicitly addresses the challenge of overlap and influence between causes and effects. It doesn't rely on a fixed theory of change but on the factors and links between them which are actually mentioned in documents and interviews.
How causal mapping can help with Outcome Harvesting:
- causal mapping can input a pile of Outcome Harvesting data and link them all together into the form of a larger web. (Britt et al., 2025).