The Strategy Testing Workbook: Politically-Smart Adaptive Programming in Complex Environments - Nixon, Nicola; O'Donnell, Carolyn; Rajalingam, Gobie; Tweedie, Pauline; Sullivan, Elizabeth (The Asia Foundation, 2024)
The guide begins with a section on what we at TAF have learned about practicing Strategy Testing, highlighting things that we didn’t know when we started out. Some of these lessons may seem obvious, but others may strike you as less so. In any case, we believe that, when taken together, they provide a useful reminder of some of the pitfalls that arise in efforts to practice Adaptive Management. Moreover, they help to remind us that there are multiple layers to doing Strategy Testing effectively as a system instead of reducing it to its component parts and applying them mechanistically. Thus these lessons are useful to read now and to revisit later. The guide then comprises three more sections: • Part 1, the Design Stage, involves constructing the system and making sure everyone is on board; • Part 2, the Inception Phase (start-up phase), helps the implementing team to make the leap from the ideal initially set out in the design stage to the grounding, support, and frameworks that the team will need to implement Strategy Testing in a meaningful and impactful way. We’ve found that the gap between design and implementation is very often the cause of an ineffective ‘all talk and no walk’ approach to Adaptive Management. And finally; • Part 3 covers Program Implementation – the practices, knowledge, and culture needed for the feedback loop that underpins Strategy Testing. The guide can be used for individual or group learning, or it can be used directly to inform Reflection Sessions (see Section 3) through the questions we raise or the activities herein.

Social Accountability 3.0: Engaging Citizens to Increase Systemic Responsiveness. Background Paper - Guerzovich, Florencia; Aston, Tom (Grupo Politeia, ESAG, UDESC and act4delivery, 2024)
Social accountability has become increasingly important to development programming since the 2004 World Development Report spearheaded its first generation of programming. In 2016, Thomas Carothers synthesized global experts’ perspectives on what became known as the second generation. With an evolving global context, new research and evaluations and tacit knowledge on how those assumptions played out in practice, the time is ripe for asking what the evidence since 2004 can tell us about what the social accountability’s next generation might look like? This meta-analysis takes stock of that knowledge through a systems lens and presents a possible “social accountability 3.0.” It draws on a database of 157 cases of initiatives implemented by different civil society organizations around the world and the lived experience of practitioners. Scholarly debates present practitioners’ options in binary terms, contrasting 1.0 minimalist and 2.0 maximalist options. The review finds that this binary is inaccurate and misleading; it masks practitioners’ diverse interpretations of 2.0 and range of feasibility considerations. Instead, work in the last decade looks more like a mosaic. By opening the analysis to the broader range of evidence, and reflecting more critically on scholars’ assumptions, a more adaptable middle path for social accountability 3.0 emerges. Its key outcomes include contributing to systemic responsiveness and an operational mechanism to rework the social contract.

A Framework for Embedding Learning in Systems Change - Bertermann, Kecia; Coffman, Julia (Center for Evaluation Innovation, 2024)
This five-step framework, developed and tested by a foundation, embeds learning in emergent systems change strategies. It prioritizes the testing of hypotheses and assumptions, uses learning questions, and calls for examining both confirming and disconfirming evidence. — A framework for embedding learning in systems change strategies and for testing strategic uncertainties. Learning and evaluation approaches that accompany systems change efforts need to fit with and support the emergent nature of this work. Systems change efforts call for examining, with evidence, the hypotheses and assumptions that undergird the work and regularly adapting in response to what is learned. They require staff to be highly engaged in testing their ideas by gathering evidence, interpreting it, and then acting on its implications. This brief presents a learning approach—referred to here as the Learning Framework—developed and tested by a foundation to support its systems change strategies. It is intended for other practitioners working on approaches for integrating learning with systems change efforts. Because a wealth of conceptual work exists about why learning is critical to systems change but practical advice about how to do it is much less available, we describe the approach we took and how the Framework’s core elements fit together in practice. The primary purpose of this approach is to interrogate our strategic uncertainties. This approach to learning is different from the dominant approach to learning and evaluation in philanthropy that primarily looks for evidence (often static metrics) that expected outcomes have been achieved (an approach that is more suitable for linear and predictable change strategies). This Learning Framework is driven by, and organized around, hypotheses and assumptions. This is especially important for systems change efforts where the path forward cannot be determined with complete certainty, but where robust evidence collection and regular sensemaking can increase our confidence in chosen directions and ultimately increase our chances of success.

Guidance Note: Evaluation Criteria - Chaplowe, Scott; Child, Keith; AF-TERG (Adaptation Fund, 2024)