A Learning Agenda for Community-Driven Development: Responding to Complex Contextual, Evaluation, and Inference Challenges

Governments and nongovernmental organizations around the world utilize Community-Driven Development (CDD) approaches to address complex and overlapping development challenges. Despite consistent evidence on some impacts of CDD—especially improvements in basic services—there is significant variation in most outcomes and several unanswered questions. This paper argues that the central task to advance learning on CDD (and similar complex development interventions) is identifying the conditions under which it works and the design and implementation choices that will make it most effective within a given context. The paper provides an overview of CDD, background on the existing evidence, and identifies gaps in CDD’s impact across four broad types of outcomes—cohesion, inclusion, resilience, and process legitimacy. The paper concludes by outlining a set of priority research questions that will advance learning on CDD and provides guidance on the empirical approaches and tools required to answer these research questions. The proposed learning agenda focuses on understanding variations in project design, implementation modalities, and context, arguing that increased knowledge in these domains will help to optimize the impacts of current CDD projects, inform the design of new projects, and develop an understanding of what project designs are most scalable in different contexts.