Response Innovations for Somalia Emergencies (RISE) Report

The Response Innovations for Somalia Emergencies (RISE) program, funded by the United States Agency for International Development’s Office of Foreign Disaster Assistance (USAID/OFDA) seeks to improve how humanitarian stakeholders prepare for and respond to disasters in Somalia. This report presents the findings from the RISE innovation ecosystem mapping study which seeks to provide a more comprehensive understanding of the key actors, factors, and relationships within Somalia’s humanitarian innovation sector. Specifically, the study identifies needs, opportunities, and gaps in the existing ecosystem as well as potential barriers to and drivers of a successful, thriving innovation ecosystem. RISE is led by the George Washington University’s Elliott School of International Affairs (GW/ESIA), in collaboration with the Somali Disaster Resilience Institute (SDRI) and the Somalia Resilience Program (SomReP). Together, these partners are testing and implementing the global Response Innovation Lab’s (RIL) approach to improve stakeholders’ understanding of humanitarian innovation in Somalia. RISE is grounded in the tenets of the United Nation’s Grand Bargain (2016) which emphasizes localization by shifting support, resources, and financing more directly to local and national actors. RISE also seeks to amplify the voices of local innovation stakeholders as well as the voices of the communities served. The study employed both quantitative and qualitative methods undertaken concurrently. A systematic review of publicly available organizational data was derived from various Internet sources and produced the underlying ecosystem map and accompanying database. Fifty key informant interviews (KIIs) were conducted among individuals in the Somali innovation sector using semi-structured interviews to complement the social network analyses (SNA). SNA was conducted on the innovation ecosystem map data using key metrics through the Kumu Inc platform. These metrics included closeness centrality, eigenvector centrality, and reach which helped in the identification of key actors and connections within the ecosystem. Given the newly emerging innovation ecosystem in Somalia, the mapping of this system involved constant learning and readjustment, similar to that of innovation programming where no known causal pathway exists (Obrecht, Warner, & Dillon, 2017). This learning was a process of structuring the unknown through theoretical sampling to develop, define, and refine theoretical categories. Relationships and entities were identified via snowball sampling and negotiated meaning-making across individual, institutional, and social understandings of innovation.

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