Capacity Development Indicators for the second phase of CGIAR Research Programs
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Permanent link to cite or share this item: https://hdl.handle.net/10947/4080
This document is a complement to the Second Call for Full Proposal Guidelines2 provided by the CGIAR Consortium. It has been developed by members of the CGIAR Capacity Development Community of Practice (CapDev CoP) and builds on the Capacity Development Framework of CGIAR3. It is a living document that will be refined further before and during the implementation of the second round of CGIAR Research Programs (CRPs), also known as the CRPII portfolio. The intended users of this document are capacity development professionals and members of the CRPII Full Proposal writing teams. The objective of this document is to enable the writing teams to develop indicators for monitoring and evaluation of the elements(10) of the CGIAR Capacity Development Framework that they decide to implement in their respective CRPs. The document suggests indicators for each of the elements in a way that is aligned with the Strategic Results Framework5 (SRF) and can be monitored and measured along the impact pathways. Hence, this document provides a guiding framework to capture and monitor capacity development outputs and outcomes of CRPs, and collectively the CRPII portfolio, with an aim to increase the impact of their work. There are many potential indicators to measure different aspects of the Capacity Development framework, beyond the mere head-counting of trainees. This document provides a framework to capture the multi-dimensionality of the concept of capacity development.Under each of the 10 elements of the framework, the document identifies a minimum set of composite indicators that we consider a ‘good enough’ proxy for overall progress, and a medium provide numbers that could be monitored over time. Making sense of the numbers and verifying that they are indeed tracking overall progress will require collecting and analyzing qualitative data regularly, and using other complementary methods such as Most Significant Change or storytelling. However, designing such corroborative qualitative data analysis is outside the scope of this exercise.