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How can we transform monitoring and evaluation (M&E) into a more adaptive, emergent process to address uncertainty and complexity in todays’ world? How do we move from compliance and accountability to learning – to support better, more timely, decisions? Join GEI Program Manager, Dugan Fraser, as he discusses these questions and others with Special Guest, Søren Haldrup, from UNDP's Strategic Innovation Unit where he manages UNDP's innovation facility and leads a new initiative called the M&E Sandbox.
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This guidebook codifies the principles and methods of applying systems change and portfolio approaches to complex development challenges with practical tools and examples. It is based on the empirical learning generated from the collaborative initiatives in UNDP Country Offices in Bhutan, Pakistan, the Philippines, and Viet Nam with support from Regional Innovation Centre for Asia and the Pacific.
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This report presents six learnings from four pilot projects conducted by the Data Powered Positive Deviance (DPPD) initiative, a global collaboration between the GIZ Data Lab, the UNDP Accelerator Labs Network, the University of Manchester Center for Digital Development, and UN Global Pulse Lab Jakarta. The pilots seek out grassroots solutions to development challenges that range from the interaction between livestock farming and deforestation to gender-based violence and insecurity in dense...
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In this blog we are sharing a digest of some of the many useful and innovative monitoring, evaluation and learning resources and efforts that have come through the M&E Sandbox in 2022. A lot of these resources have been shared by our community in response to the overwhelmingly positive feedback from the launch of the Sandbox (please keep them coming!). We hope you find it useful. We have grouped these efforts and resources under six broad questions: - How do we measure systems...
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The Method Positive Deviance (PD) is based on the observation that in every community or organization, there are a few individuals who achieve significantly better outcomes than their peers, despite having similar challenges and resources. These individuals are referred to as positive deviants, and adopting their solutions is what is referred to as the PD approach¹. The method described in this Handbook follows the same logic as the PD approach but uses pre-existing, non-traditional data...
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