Monitoring and evaluation to strengthen the performance of agricultural R&D

Howard Elliott, John Lynam

This chapter begins with a discussion of the performance monitoring challenge in African agricultural research with respect to monitoring change in smallholder agricultural systems, the time lag in agricultural research, the context for technology adoption, and causality in agricultural research impact pathways. Next, four M&E cases illustrate the need to balance the objectives of accountability and learning made possible by M&E: (1) monitoring inputs versus outputs, (2) monitoring research process versus outputs, (3) monitoring research outputs versus broader innovative processes, and (4) monitoring the research process versus the development process. Thereafter follow discussions of the evolution of evaluation tools, the most-used logic models and their perceived strengths in dealing with the impact pathways from research outputs to development outcomes, and evaluation methodology and the efficacy of pilot studies versus formal evaluation designs. The chapter concludes with the search for accountability in investment in agricultural research and development (R&D).