Relief and development coherence (RDC) aims to ensure complementarity between humanitarian and development assistance efforts. Humanitarian assistance focuses on serving the basic needs of populations in crisis, whereas international development assistance targets longer term needs. Coordination of these programs, particularly in refugee crises, can simultaneously improve the conditions of refugees while continuing to make progress on a host-country’s economic and social development agenda.
Given the complexity of both humanitarian and development assistance programs, how can policy makers and planners know when coordination efforts have occurred? More importantly, how can they know if they have been successful?
This project identifies metrics for both strategic and operational coherence efforts through comparative case studies of Uganda and Ecuador. Both countries host large number of refugees from South Sudan and Venezuela, respectively. Developed through models generated with national data sets and machine learning methods, strategic metrics will enable policy makers to anticipate where coordinating refugee and host country aid will have the greatest chance of success. At the same time, qualitative analyses of data flows in ongoing operations will identify operational metrics. These complementary metrics provide a ‘bottom up’ counterpart, reflecting current efforts and enabling future measurement of grass roots coordination efforts.
In addition to its practical impact, the research will inform theories of humanitarian information management, data governance and policy making. The collaborative project, including NetHope, a Georgetown University data scientist, and a gender specialist. For more information, see https://www.state.gov/an-information-centric-perspective-on-coherence-collaboration-analyses-of-uganda-and-ecuador-penn-state/