As the name signifies, outcome harvesting is used to harvest outcomes to help find, describe, verify, and analyze results. Outcome harvesting specifically looks at the change in behavior, relationships, actions, activities, policies, or practices of an individual, group, community, organization, or institution as an outcome in (Wilson-Grau and Britt, 2013).
Outcome harvesting works by gathering evidence of change, “outcomes,” to ascertain whether and how an initiative, program, or organization has contributed to the change. Outcome Harvesting does not track advancement toward specified objectives or outcomes, unlike other evaluation techniques. Instead, it collects proof of changes and goes backwards to assess whether an intervention was at the root of these instances. The action and outcome(s) can be great or awful, deliberate or accidental, direct or indirect, but the connection must make sense.
Evaluators and/or program managers confirm, rate, and explain “outcomes” through outcome harvesting in programming circumstances where cause and effect relationships are ambiguous.
Using outcome harvesting #
The optimal uses of outcome harvesting are for efforts with uncertain outcomes or dynamic actions and circumstances. It first asks people about the intervention to determine if and to what extent caused the changes. It assists in keeping track of unanticipated effects in hectic contexts.
Outcome harvesting is usually prescribed and can be done through a sequence of steps: #
Design #
In the first step, it is necessary to “design the harvest”. Results harvesting carefully consider the stakeholders’ objectives, expectations, and viewpoints. It starts by exploring what does the evaluation goal for the team. The effects and ramifications of the strategy might be called into question. Data gathering should be based on these queries. Many of these concerns will be influenced by knowing what data the project collects and how it does so.
Data Collection #
At the next stage, evaluators will collect the data. For design and data collecting, evaluators will explore changes. And outcome and would also explore the contribution, i.e., what led to the outcome? Describe the connection between the change agent and the outcome.
Interaction #
The third step is essential since the evaluator will test hypotheses with the change agents and other project participants after collecting and writing about the results. Iterative polling and interviews with important individuals. Your outcomes statement and links are made obvious and credible throughout this step. Plans ought to show this.
Substantiation of the outcomes #
In this step, the evaluator will substantiate the outcome. The evaluation’s primary users consult with impartial individuals familiar with the area or results from a sample.
Analytics and interpretation #
All outcome data are examined at this step. Data grouping could highlight significant trends. Depending on the project, analytic software may be used. Further, depending on your data and plan values, data analysis can be customized, and evaluators then apply findings at the next stage.
Utilization of findings #
This stage involves presenting your results to the evaluation’s users and suggesting interpretations. However, Outcomes Harvesting is only a perspective on what happened and what caused the change.
It is important to mention that these steps are not sequential; depending on the outcomes and analysis, they may overlap and result in several iterations. Therefore, the process discusses the outcome, whether planned or unintended, and enables us to link this change to our intervention.
References
Blundo-Canto, Genowefa, Andrieu, Nadine, Soule Adam, Nawalyath, and Ndiaye Ousmane, and Chiputwa, Brian. 2021. « Scaling Weather and Climate Services for Agriculture in Senegal: Evaluating Systemic but Overlooked Effects ». Climate Services 22 (April): 100216. https://doi.org/10.1016/j.cliser.2021.100216.
Douthwaite, Boru, and Kuby, Thomas, and van de Fliert, Elske, and Schulz Steffen. 2003. « Impact pathway evaluation: an approach for achieving and attributing impact in complex systems ». Agricultural Systems, Learning for the future: Innovative approaches to evaluating agricultural research, 78 (2): 24365.
Douthwaite, Boru, Ashby, Jacqueline. 2005. « Innovation Histories: A Method for Learning from Experience ». The Institutional Learning and Change (ILAC) Initiative, 4
Wilson-Grau, Ricardo. 2018. Outcome Harvesting: Principles, Steps, and Evaluation Applications. IAP.