Learning, Analytics, and Knowledge Management Support in Kenya

archived

Purpose The purpose of this NOFO is to support ongoing applied research and analysis of U.S. government (USG) food security and economic growth programming in Kenya and East Africa. The proposed approach for conducting this applied analytical research should utilize a range of learning, analytics and knowledge management methodologies. The analytical research conducted should offer timely, relevant, and high-quality evidence for adaptive management, informed decision making and improved development outcomes in the agricultural sciences. Program Overview The Global Food Security Strategy (GFSS) is the primary initiative under which the United States works with host governments, civil society and private sector partners to address the needs of smallholder farmers and agribusinesses related to global hunger and food security. The initiative emphasizes the empowerment of women and youth, environments for strong agricultural markets, the promotion of research and innovation for agricultural development and investments in nutrition. Specifically, the food security and economic growth programs in Kenya and the East Africa region focus on a range of programming to include: (1) supporting agricultural market systems by addressing economic growth, malnutrition and food insecurity, (2) expanding access to economic opportunities, including for women and youth, (3) addressing policy constraints and leveraging private sector resources for inclusive and resilient growth, (4) leveraging regional and international trade opportunities, and (5) supporting partnerships and learning around water security, systems and services. For these programs to be effective, the activities must be able to adapt in response to environmental, political, and market changes. Responsive and timely analytics are needed to support decision making and adaptation at program, private sector, community, county and multi-country levels. Objective Strengthen knowledge management, adaptive learning, and data-driven decision making to inform and adapt USG food security and economic growth programs in Kenya and East Africa using mixed methodologies to collect and analyze data, develop findings and present recommendations to decision makers.

High