Bridging Learning and Action: How Did CLARISSA’s Participatory Adaptive Management Approach Foster Innovation, Effectiveness, and Stakeholder Empowerment? - Prieto Martin, Pedro; Apgar, Marina; Afroze, Jiniya; Arulanantham, Amit; Hicks, Jacqueline; Karki, Shanta; Mareschal, Sophie; Paul, Sukanta; Snijder, Mieke; Uddin, Forhad; Veitch, Helen (CLARISSA Research and Evidence Paper, 2024)
Child Labour: Action-Research-Innovation in South and South-Eastern Asia (CLARISSA) is an evidence and innovation-generation programme funded by the United Kingdom’s Foreign, Commonwealth & Development Office (FCDO), responding to the challenge of the worst forms of child labour (WFCL) in Bangladesh and Nepal. It is a challenge characterised by a poor understanding of its drivers and a lack of evidence on what works to combat it. To handle such fundamental uncertainty, the programme adopts a child-centric and participatory action research approach, which is supported by an adaptive management model to respond better to challenges and opportunities. From its inception, the programme needed to navigate shocks and challenges, such as Covid-19 lockdowns, political upheaval, and sustained budget cuts, which put its capacity to learn and evolve to the test. This paper shares insights emerging from evaluating CLARISSA’s participatory adaptive management (PAM) practices, connecting them with current discussions on adaptive management. It provides an in-depth evaluation of CLARISSA’s PAM approach, exploring how adaptive strategies were implemented and evolved throughout the programme’s life cycle. Multiple cases of adaptation and misadaptation were selected and analysed through a series of in-depth interviews and review of programme documentation, allowing us to assess whether and how the adaptive management practices have been operationalised, the degree to which they led to enhanced decision-making and effectiveness, and their empowering effect on children and other programme stakeholders. Through conceptual analysis and real-world examples, the paper examines the key stages and critical dimensions of PAM, conveying the complexities and dynamism of adaptive management in development work, while highlighting both the successes and challenges encountered in operationalising PAM within CLARISSA.

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.

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.

Developing, representing, and using theories of change for interventions in complex systems - Rogers, Patricia (Theories of Change in Reality, 2024)
Theories of change for interventions in complex systems present a challenge for usual approaches to developing, representing, and using theories of change. Interventions in complex systems operate under conditions of ongoing uncertainty, not because of a lack of information but because of three features that contribute to this uncertainty: (1) numerous, diverse, and interacting components; (2) nonlinear relationships; and (3) changes brought about through self-organisation, agency, adaptation, and learning. In such situations, a different approach is needed to theories of change. Their primary intended use needs to be supporting ongoing single-loop and double-loop learning and adaptation by the various actors involved, rather than monitoring compliance with an initial plan. The underlying change theories need to be appropriate for managing complex systems—for example, focusing on developing an effective network of actors, creating an enabling environment, and supporting iterations of learning and adaptation rather than planning tightly prescribed implementation of ‘what works’.

The law of the instrument: Would you rather be a theory or a nail? - Freer, Gordon (Theories of Change in Reality, 2024)
Using the hammer-and-nail analogy of the law of the instrument, often attributed to Abraham Maslow, this essay explores the minimal utilisation of theories of change within programmes despite their almost mandatory inclusion in programme proposals, designs, and evaluations. The essay then considers reasons for this lack of use and explores potential solutions to the same. The essay contends that theories of change can be used for a variety of purposes—in programme design; as complementary programme management tools; adding value to reporting, adaptation, and learning; as well as contributing more broadly to refining social science theories.

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