ACDI/VOCA
The Complexity-Aware Monitoring and Evaluation Project (C-AME) was implemented by Democracy International (DI) to contribute to USAID's Program of Alliances for Reconciliation (PAR) by providing additional data to inform decision-making and adaptive management.
2020 · 9 pages

Abstract
C-AME's strategy is complementary to PAR's M&E activities, as it uncovers blind spots that naturally exist in traditional M&E approaches, enabling improvement of the Activity's programming. C-AME's developmental evaluation supports implementers to generate more sustainable and higher impact social change with a strong basis in research and development approaches. A monitoring system and periodic deliverables, such as communication tools, newsletters, and quarterly reports, accompany the developmental evaluation. These deliverables offer PAR and the Mission a better understanding of context dynamics in the operating environment. The C-AME project focuses on three components of CLA: Collaboration, Learning, and Adapting. Collaboration between the implementer and evaluator is crucial, as C-AME's conceptual framework builds upon notions of internal and external collaboration between PAR and the external evaluator. Lessons from this setup emerge at two levels: first, related to the understanding of C-AME as a learning tool for PAR and USAID, and second, as a coordination mechanism for data collection and results sharing. One key lesson learned from C-AME's implementation is the importance of ensuring understanding of C-AME as a learning tool among interested parties. Early in its implementation, C-AME faced challenges trying to convey to PAR its role and potential as a learning tool for existing and future programming. To overcome this challenge, technical teams from the implementer and evaluator, as well as USAID, should work collaboratively in the early stages of implementation to ensure all parties understand complexity-aware methods and how they supplement traditional monitoring to enrich implementation. Another key lesson learned from C-AME's implementation is the importance of collaboration for data collection. As an external evaluator, C-AME has had limited ability to access timely and complete program implementation data to ensure that monitoring and evaluation conclusions are accurate and unbiased. To address this challenge, C-AME and PAR held regular planning meetings to discuss M&E activities and schedules, and C-AME coordinated with PAR's field facilitators, beneficiaries, and stakeholders and gained access to implementing partners and project information. The C-AME methodology focuses on two key analyses to identify blind spots within implementation and between implementation and context. The first is project-level analysis, which gathers primary and secondary programmatic data from PAR staff, implementing partners, and project participants to analyze implementations and their roles in realizing PAR's Theory of Change goals. The second is a localized context analysis, gathering data from a broader group of stakeholders and secondary data that can illuminate the complex dynamics that exist in the context of implementation. Using the case study approach, C-AME collects data on-site in the local contexts of interventions to characterize the dynamics of reconciliation, key actors, relationships, conflicts of interest, and other elements that facilitate understanding of the environment in which PAR operates. This approach allows C-AME to conduct a deep analysis of the narratives of actors engaged in implementation, as well as the interactions between them, to understand, on the level of a single intervention, the complex processes driving behavioral and attitudinal changes towards reconciliation. The C-AME project has made significant contributions to PAR's programming, including a deep understanding of project-level interventions and the complex dynamics of local contexts. By emphasizing a "learning" rather than an "accountability" M&E approach, C-AME has ensured that its results are used to inform and improve PAR's programming, rather than to evaluate its success or failure.
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Classification
USAID DEC