Outcome Harvesting
Also known as: OH, Wilson-Grau Outcome Harvesting
Outcome Harvesting is a participatory evaluation approach, developed by Ricardo Wilson-Grau and Heather Britt, that identifies outcomes after they have occurred and then works backward to determine whether and how an intervention contributed to them. Instead of measuring progress against predefined targets, evaluators 'harvest' evidence of observable changes in the behaviour, relationships, actions or policies of social actors, then assess the program's contribution to each. It is designed for complex settings where cause-and-effect relationships are not fully understood in advance and outcomes cannot be specified ahead of time.
Key highlights
- Captures unanticipated and negative outcomes that predefined-target systems would overlook.
- Works without baseline data or a fixed results framework, fitting emergent, complex interventions.
- Grounds contribution claims in documented outcomes verified by independent sources.
- Engages primary users throughout, supporting learning and use of the findings.
Intuition
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How it works
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When to use it
Use Outcome Harvesting in complex, dynamic interventions where outcomes cannot be predicted, where the program influences rather than controls change, and where capturing emergent and unintended results matters — typical of advocacy, networks, governance reform, capacity building and systems-change work. It suits retrospective evaluation and situations lacking a clear predefined results framework. It assumes outcomes can be observed and independently substantiated and that informants are available. It is less appropriate when objectives are fixed and measurable and a target-based or experimental design is feasible, when quantified impact is required, or when no credible independent sources exist to verify claimed outcomes. It complements Outcome Mapping, which provides the forward-looking intent that harvesting later tests against reality.
Strengths & limitations
- Captures unanticipated and negative outcomes that predefined-target systems would overlook.
- Works without baseline data or a fixed results framework, fitting emergent, complex interventions.
- Grounds contribution claims in documented outcomes verified by independent sources.
- Engages primary users throughout, supporting learning and use of the findings.
- Retrospective and largely qualitative, providing contribution evidence rather than quantified impact.
- Substantiation depends on the availability and candour of independent informants.
- Harvesting and verifying outcomes is labour-intensive and demands skilled facilitation.
- Vulnerable to selection bias if harvesters gather mainly favourable outcomes and overlook failures.
Common pitfalls
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Applications
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Frequently asked
How does Outcome Harvesting differ from conventional results-based evaluation?
Conventional results-based evaluation measures progress against objectives and indicators set in advance. Outcome Harvesting works in the opposite direction: it first identifies changes that have actually occurred — planned or not, positive or negative — and then assesses the program's contribution to them. This makes it suited to complex interventions where outcomes cannot be predicted, and it deliberately surfaces emergent and unintended results that a fixed indicator framework would never have been designed to detect.
What does 'substantiation' add, and is it essential?
Substantiation is the step in which independent, knowledgeable sources review a sample of harvested outcomes to confirm their accuracy and the plausibility of the claimed contribution. It is what separates Outcome Harvesting from simple self-reporting and is central to its credibility. While the depth of substantiation can be scaled to the stakes and resources, omitting it altogether undermines the method, because contribution claims then rest only on the accounts of those who produced them.
Can Outcome Harvesting prove a program caused an outcome?
No. Like other contribution-oriented approaches, it establishes plausible contribution rather than definitive attribution. For each outcome it documents how the intervention is thought to have contributed and verifies this with independent sources, but it does not construct a counterfactual or estimate a net effect. Its strength is credibly accounting for influence in complex settings where experimental attribution is impossible; where a quantified causal impact is needed, a counterfactual design is required instead.
Sources
- 1.Wilson-Grau, R., & Britt, H. (2012). Outcome Harvesting. Cairo: Ford Foundation MENA Office (revised November 2013).
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Cite this page
ScholarGate. (2026, June 22). Outcome Harvesting. ScholarGate. https://scholargate.app/public-policy/outcome-harvesting