Evidence-led adaptive programming: Lessons from MUVA - Sharp, Samuel; Riemenschneider, Nils; Selvester, Kerry (ODI, 2022)
Calls for more ‘adaptive programming’ have been prominent in international development practice for over a decade. Learning-by-doing is a crucial element of this, but programmes have often found it challenging to become more learning oriented. Establishing some form of reflective practice, against countervailing incentives, is difficult. Incorporating data collection processes that generate useful, timely and practical information to inform these reflections is even more so.This paper explores MUVA - an adaptive female economic empowerment programme in Mozambique. MUVA, we suggest, is atypically evidence-led. It combines systematic, inclusive reflective practice with extensive real-time data collection. We describe the fundamental features of MUVA’s monitoring, evaluation and learning (MEL) approach that supported this. One, how data collection and analysis are synchronised with set cycles for learning and adapting projects. Two, how MEL systems are designed to prioritise actionable learning, with data collection oriented more to the needs of implementing staff than to the reporting requirements of funders.This approach was enabled by building collective ownership over the programme’s objectives and the purpose of MEL from the outset. Implementers are asked about their motivations, and these are related to the programme’s Theory of Change. The evidence culture is supported by the proximity of MEL staff to implementing staff; and through structuring upwards accountability to funders around justifying evidence-based adaptations instead of reporting on more narrow indicators. We conclude by considering the relevance, or not, of MUVA’s approach to programmes in other contexts or issue areas trying to replicate a similarly evidence-informed approach to adaptive management. Key messages Learning-by-doing is essential to adaptive programming, but it can be challenging to establish data collection processes that generate useful, timely and practical information. MUVA – a female economic empowerment programme in Mozambique – has an atypically evidence-led adaptive management approach. This has two fundamental features. One, data collection and analysis are synchronised with set cycles for learning and adapting projects. Two, data collection is oriented more to the needs of implementing staff than to the reporting requirements of funders. Monitoring, evaluation and learning (MEL) systems are designed to prioritise actionable learning. This approach was enabled by building collective ownership over the programme’s objectives and the purpose of MEL from the outset. Implementers are asked about their motivations, and these are related to the programme’s Theory of Change. The evidence culture is supported by the proximity of MEL staff to implementing staff; and through structuring upwards accountability to funders around justifying evidence-based adaptations instead of reporting on more narrow indicators.

Nimble adaptation: Tailoring monitoring, evaluation, and learning methods to provide actionable data in complex environments - Serpe, Lauren; Ingram, Mason; Byom, Kate (New Directions for Evaluation, 2022)
This chapter examines good practices in implementing effective Monitoring, Evaluation, and Learning (MEL) systems within complex international development Democracy, Human Rights, and Governance (DRG) programs, which are characterized by challenges of non-linearity, limited evidence of theories of change, and contextual and politically contingent nature of outcomes. The chapter presents three cases of MEL systems in complex projects implemented by Pact across distinct and diverse operating contexts – Zimbabwe, Cambodia, and Somalia – to illustrate those projects’ MEL approaches that enabled continuous adaptation. The authors analyze the cases to respond to two questions: (1) What are the key elements of effective adaptive management-focused MEL systems in complex environments? (2) What is practical guidance for designing and enabling complexity-responsive and effective adaptive management-focused MEL systems? The case studies illustrate three key elements: (1) Information gathering that closely links context, research, and performance data; (2) Systems for reflection that offer scheduled learning moments of varying frequency and intensity, as well as multiple feedback mechanisms; and (3) Enabling structures that promote adaptive mindsets and attitudes within project teams.

Measuring and Monitoring Adaptive Learning: A Landscape Review - LaFond, Anne; Adrian, Haley (USAID MOMENTUM Knowledge Accelerator, 2022)
This landscape review on measuring and monitoring adaptive learning highlights the learning from five adaptive programming guidelines and toolkits and one implementation science framework to inform the monitoring and evaluation of adaptive learning. The introduction of adaptive learning processes and skillsets in global health programming is part of an emerging strategy to advance a learning culture within projects and teams to improve health program performance. The monitoring and evaluation of adaptive learning is an emergent field aiming to monitor how adaptive learning processes have been introduced, how they are used, and whether they are having the intended results. Although there is a growing body of literature on adaptive programming more generally, there is a limited knowledge base on the monitoring and evaluation of adaptive learning interventions and their impacts. Unlike other implementation strategies or program management approaches, there are no standard metrics or a monitoring and evaluation framework to track the integration, implementation, and effectiveness of adaptive learning in health programming.

Transforming M&E for Uncertain and Complex Contexts: The UNDP’s Innovation Sandbox Approach - Fraser, Dugan; Haldrup, Søren (Powered by Evidence Podcast, 2022)
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.

Monitoring and evaluation for thinking and working politically - Aston, Thomas; Roche, Chris; Schaaf, Marta; Cant, Sue (Evaluation, 2022)
This article explores the challenges of monitoring and evaluating politically informed and adaptive programmes in the international development field. We assess the strengths and weaknesses of some specific evaluation methodologies which have been suggested as particularly appropriate for these kinds of programmes based on scholarly literature and the practical experience of the authors in using them. We suggest that those methods which assume generative causality are particularly well suited to the task. We also conclude that factoring in the politics of uncertainty and evidence generation and use is particularly important in order to recognize and value diverse experiential knowledge, integrate understandings of the local context, accommodate adaptation and realistically grapple with the power relations which are inherent in evaluation processes.

The Art and Craft of Bricolage in Evaluation - Aston, Thomas; Apgar, Marina (CDI Practice Paper, 2022)
This CDI Practice Paper by Tom Aston and Marina Apgar makes the case for ‘bricolage’ in complexity-aware and qualitative evaluation methods. It provides a framework based on a review of 33 methods to support evaluators to be more intentional about bricolage and to combine the component parts of relevant methods more effectively. It discusses two cases from practice to illustrate the value added of taking a more intentional approach. It further argues that navigating different forms of power is a critical skill for bricolage, and that doing so can help to ensure rigour.

Evaluating complex interventions: What are appropriate methods? - Masset, Eduardo (CEDIL, 2022)
In the CEDIL Methods brief, ‘Evaluating complex interventions: What are appropriate methods?’ we identify four types of complex development interventions: long causal chain interventions, multicomponent interventions, portfolio interventions, and system-level interventions. These interventions are characterised by multiple activities, multiple outcomes, multiple components, a high level of interconnectedness, and non-linear outcomes.