When Complex is as Simple as it Gets: Guide for Recasting Policy and Management in the Anthropocene - Roe, Emery (Institute for Development Studies, 2023)
Many readers recognise and understand that complex is about as simple as it gets for major policy and management. This guide is for those unwilling in the Anthropocene to shrink back into the older platitudes about ‘keep it simple’ and ‘not to worry, we’ll scale up the analysis later on’. This guide offers key concepts, methods, counternarratives, and analogies that recast major policy and management issues in ways that do not deny their complexity but help render them more tractable for action.
Accepted: 2023-06-06T09:51:20Z

Adaptive Evaluation: A Complexity-based approach to Systematic Learning for Innovation and Scaling in Development - Gokhale, Siddhant; Walton, Michael (Center for International Development, Harvard University, 2023)
Nearly all challenges in international development tend to be complex because they depend on constantly evolving human behaviour, systems, and contexts, involving multiple actors, entities, and processes. As a result, both the discovery and scaling of innovations to address challenges in development often involve changes in system behaviour or even system-level transformation. This is rarely a linear process over time and can result in unexpected outcomes. Existing evaluation techniques commonly used in international development, including Randomized Control Trials (RCT) and quasi-experimental methods, are good at assessing specific effects of interventions but are not designed for the change processes inherent to innovation and scaling within a system. There is a need to reconstruct how we use existing measurement tools, techniques, and methodologies so that they capture the complexity of the environment in which an intervention or change occurs. We introduce Adaptive Evaluation, designed to learn at various levels of complexity while supporting the transformation needed to foster sustainable change. An Adaptive Evaluation uses three main approaches to work with complex questions—systems diagnosis, theorybased assessment of change processes, and iterative designs. An Adaptive Evaluation typically builds hypotheses from field-based interactions, emphasizes learning over testing, advocates open-mindedness with techniques, and appreciates the value of dialogue and participation in navigating complex processes. It can use RCT or similar techniques to analyse specific processes within a system or a development cycle, but these are embedded in a broader approach to assessment and interpretation. It is designed to be flexible and adjust to shifting contexts. Finally, an Adaptive Evaluation can be applied at any stage in a complex intervention's lifecycle, from the interpretation of the system and change processes to rapid experimentation, prototyping, and testing of select interventions, and then adaptation to different settings for impact at scale. This paper provides the theoretical basis for an Adaptive Evaluation—the main approaches, core ideology, process, and applications.