Start with the discovery: Improving capacity factors analysis with the appreciative inquiry approach

Abstract

Several decision-aid frameworks attempt to provide an optimal solution to the complex, challenging problem of delivering water supply and sanitation services to communities in need. However, a failure in proper needs assessment or handoff causes systemic failure of an installed system. Capacity factors analysis (CFA) is one such framework that focuses on personalized technology-specific alternative recommendations; and it faces similar challenges. While helpful in many ways, designers using CFA still make critical assumptions with regards to community's expressed needs and only passively include the community members in the design process. Appreciative inquiry (AI) is introduced as a means to bridge this gap and increase community empowerment. The AI approach is a four-phase process: discovery, dream, design, and destiny. The process starts with asking community members about their strengths and capabilities, follows with their vision of the community, creates a space for collaborative design, and ends with implementation. A service-learning experience in Tshapasha is provided to demonstrate AI's benefits. The results are compared to a CFA-focused study of Tshapasha from 2011.