Increasing Data and Analytics Capacity

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The purpose of this RFI is to solicit input from organizations involved in managing, analyzing and visualizing data, particularly for the purposes of informing policy and decision-making in international development. In this RFI, we seek to gather information about the scope of a draft Statement of Work (SOW) and the community’s capabilities to fulfill these requests. In particular, we want to understand the available expertise, the feasibility, and challenges faced in responding to the services outlined in our draft SOW.II. BackgroundData and their many applications are critical to development infrastructure in the 21st century, both for the United States Agency for International Development’s (USAID) programs and activities, and for the developing countries with whom we partner. The core goal of the Data and Analytics Team is to facilitate increased use of data and evidence to improve development outcomes. By strengthening USAID’s evidence base and building its capacity to apply cutting-edge analytical tools in measuring and improving impact of our work, we aim to turn data into actionable information for development. To deliver on this vision, we seek to develop partnerships, apply innovative technologies and approaches, and build analytical capacity within USAID and host-country counterparts.The ability to manage, conduct, and visualize analyses of relevant information is integral to long-term strategic planning, program and activity design, the evaluation of programs, and the dissemination of lessons learned. However, operating units within USAID are sometimes constrained by existing capacity to transform data into insights that could inform development programming. To address this need, the Data and Analytics team is seeking to partner with external organizations to provide support for data management, analysis, and visualization. Initial consultations have suggested services needed in the following five areas, described in detail in the attached draft SOW: Data analysis and visualization; Research to contextualize development efforts and challenges; Data infrastructure and information sharing; Futures analysis and scenario planning

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