More and more, development organizations are under pressure to demonstrate that their programs result in significant and lasting changes in the well-being of their intended beneficiaries. However, such "impacts" are often the product of a confluence of events for which no single agency or group of agencies can realistically claim full credit. As a result, assessing development impacts is problematic, yet many organizations continue to struggle to measure results far beyond the reach of their programs

Participatory Impact Pathways Analysis (PIPA) is a practical approach to planning, monitoring and evaluation, developed for use with complex research-for-development projects. PIPA begins with a participatory workshop where stakeholders make explicit their assumptions about how their project will make an impact, and produce an ‘Outcomes logic model’ and an ‘Impact logic model’. These two logic models provide an ex-ante framework of predictions of impact that can also be used in priority setting and ex-post impact assessment.

This chapter examines empirical results of evaluation reports from the AfrED database in order to unpack the relationship between the demand for evaluations and the capacities needed to meet that demand. The analysis further explores ways in which current M&E training and education provision can be enhanced to respond to capacity development needs. In achieving its objectives, the chapter also draws evidence from a secondary analysis of the results of a survey of evaluation practitioners’ perceptions of ECD challenges in the sector.

Agricultural innovation is an essential component in achieving the SDG and accelerating the transition to more sustainable and resilient farming systems across the world. Innovations generally emerge from collective intelligence and action, which requires effective agricultural innovation systems (AIS). An AIS perspective has been widely adopted, but the analysis of AIS, especially at country level, remains a challenge. The need for and potential of a diagnostic tool for AIS analysis is currently receiving attention in the global agricultural policy debate.