Between April and October 2018, Whave conducted five factor mapping workshops in Kamuli District, Uganda to learn about factors that affect the functionality of rural water services in the area. Factor mapping is a stakeholder-driven activity that seeks to create understanding of local systems and system leverage points by sharing, challenging, and making explicit stakeholders’ assumptions of how issues arise from a complex interaction of unique factors. This SWS report presents a synopsis of findings and methodology from the factor mapping and learning (IFML) process.

In Ethiopia and Uganda, the Sustainable WASH Systems Learning Partnership (SWS) developed and piloted a novel Factor Mapping approach to better understand the complex relationships between factors that influence water, sanitation, and hygiene services. The Factor Mapping process is a stakeholder-driven decision support technique that generates systems-based insights into how factors interact as a complex and dynamic system to affect WASH service delivery outcomes.

As rural water supply coverage rates rise across many countries, attention is increasingly being paid to finding and implementing cost-effective mechanisms to ensure this improved initial access is sustained over time. Conventional approaches to maintenance have largely been based on voluntary community-based management with communities taking on the burden of maintenance themselves, with limited, if any, support from external agencies or local government. Recently, there have been attempts to professionalize maintenance services and make these services affordable at the point of delivery.

The Sustainable WASH Systems Learning Partnership (SWS) is piloting factor mapping workshops to improve stakeholders’ understanding of complex WASH systems and align their perspectives on the key components and the interactions between them that lead to improved service delivery outcomes. Factor mapping is a type of focus group activity that enables participants to visually represent the interactions between different factors in a system.