Bleecker L, Sauveplane-Stirling V, Di Ruggiero E, Sellen D. Evaluating the integration of strategic priorities within a complex
research-for-development funding program.
Eval Program Plann 2021;
89:102009. [PMID:
34562669 DOI:
10.1016/j.evalprogplan.2021.102009]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 06/26/2021] [Accepted: 08/27/2021] [Indexed: 06/13/2023]
Abstract
This paper examines the application of Complexity Theory constructs to a research-for-development program evaluation and presents an overview of the implications and promising approaches for evaluating complex programs. We discuss lessons learned from an evaluation completed for the International Development Research Centre's Food, Environment and Health (FEH) program, which investigated the integration and outcomes of five strategic program priorities: partnerships, southern leadership, gender and equity, scale, and environmental sustainability. We present interpretations from a secondary, thematic content analysis that categorized evaluation findings across four complexity constructs: emergence, unpredictability, contradiction and self-organization. Viewing the evaluation through these constructs surfaced some important features of the FEH program to date, specifically its evolving approach, adaptiveness to emergent issues, non-linear outcomes, and self-organizing agents, which had several implications for the evaluative process. We conclude that the most appropriate evaluation designs for complex funding programs are participatory (to explore all stakeholders' influence), adaptive (to capture the unexpected) and assess external contexts. The application of complexity constructs may be useful for evaluators to gain a deeper understanding of how program contexts change in the face of complexity and why some evaluation methods work more effectively than others.
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