Measuring the impact of integrated systems research: promising approaches and why CGIAR needs to care

cg.contributor.crpForests, Trees and Agroforestryen
cg.contributor.crpPolicies, Institutions, and Marketsen
cg.contributor.crpWater, Land and Ecosystemsen
cg.identifier.doihttps://doi.org/10.5337/2022.203en
cg.identifier.iwmilibraryH050911en
cg.isbn978-92-9090-936-1en
cg.placeColombo, Sri Lankaen
cg.subject.systemEvaluationen
dc.contributor.authorJohnson, Nancyen
dc.date.accessioned2022-02-17T20:01:31Zen
dc.date.available2022-02-17T20:01:31Zen
dc.identifier.urihttps://hdl.handle.net/10568/118156
dc.titleMeasuring the impact of integrated systems research: promising approaches and why CGIAR needs to careen
dcterms.abstractMeasuring the impact of integrated systems research has been a challenge to CGIAR since it expanded into natural resource management research in the early 1990s. Despite repeated efforts, it has yet to be adequately addressed. Meanwhile, the demand for evidence of impact on development outcomes has only increased, as have calls for greater methodological rigor. At the same time, there is greater recognition of the complex, systemic nature of many problems facing society today and the need for new approaches to designing, implementing and evaluating research. In an attempt to provide pragmatic guidance to One CGIAR and others on how to address these issues in the design of research for development programs that involve integrated systems research (ISR), CGIAR held a virtual workshop on Measuring the Impact of Integrated Systems Research on September 27–30, 2021. Participants took stock of recent experiences and reviewed existing and new tools and approaches with the potential to overcome conceptual, empirical and institutional challenges that obstruct ISR. In terms of methods for assessing the impact of ISR, the workshop highlighted recent advances in the use of geospatial data and called for more significant investment in both the quantity and quality of qualitative methods. Integrating monitoring, evaluation, learning and impact assessment (MELIA) into the research programs will require greater capacity on the part of managers, researchers and MELIA specialists to use theory of change effectively and efficiently for multiple purposes. It is also becoming increasingly clear that some of the challenges in conducting ISR in CGIAR are not technical but have to do with structures, processes and internal tensions within CGIAR itself about the kind of outcomes it seeks and the way it organizes and implements research. While calling for research that contributes to sustainability and systems transformation, CGIAR has in different ways failed to adequately support, and to learn from, the kinds of integrated systems approaches that will likely underpin success. Workshop participants proposed tackling this head-on through changing CGIAR systems, processes and incentive structures, and engaging directly with funders on how impact is understood and measured.en
dcterms.accessRightsOpen Accessen
dcterms.audienceCGIARen
dcterms.audienceDonorsen
dcterms.available2021en
dcterms.bibliographicCitationJohnson, N. 2021. Measuring the impact of integrated systems research: promising approaches and why CGIAR needs to care. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Research Program on Water, Land and Ecosystems (WLE). 21p. [doi: https://doi.org/10.5337/2022.203]en
dcterms.extent21p.en
dcterms.issued2021-12-31en
dcterms.languageenen
dcterms.licenseCC-BY-4.0en
dcterms.publisherInternational Water Management Instituteen
dcterms.subjectagricultural research for developmenten
dcterms.subjectintegrated systemsen
dcterms.subjectsystems researchen
dcterms.subjectimpact assessmenten
dcterms.subjectcgiaren
dcterms.subjectresearch programmesen
dcterms.subjectmonitoring and evaluationen
dcterms.subjectnatural resources managementen
dcterms.subjectinvestmenten
dcterms.subjectfundingen
dcterms.subjectorganizational learningen
dcterms.subjectfood systemsen
dcterms.subjectland useen
dcterms.subjectwater systemsen
dcterms.subjectremote sensingen
dcterms.typeReporten

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