Results of Social Network Analysis in WASH in Uganda and Kenya

This blog is adapted from a version that originally appeared on Learning Lab’s website. It is the second of three blogs in a series on Social Network Analysis in WASH. The other blogs in the series explore practices to help water maintenance service providers make strategic decisions to improve WASH systems and ways to apply SNA best practices in WASH work.

As part of the USAID–funded Sustainable WASH Systems Learning Partnership (SWS), LINC, University of Oxford, and Whave Solutions conducted baseline and endline Social Network Analyses (SNA) for partners in Kenya and Uganda. 

These network analyses yield quantified visual “maps” and metrics to identify how network actors collaborate, share information, and coordinate, taking into account local actors and the complex contexts in which they exist. 

Below Cliff Nyaga and Joel Mukanga, SWS implementers who spoke on this subject during a recent online training workshop, highlight key learning from SNA and how their respective organizations applied this learning. Nyaga is a WASH systems researcher with SWS partner, University of Oxford, and the director of FundiFix, a Kenya-based organization that provides rural communities with sustainable water supply infrastructure and repairs. Mukanga is the district manager for SWS partner Whave’s Kamuli office and is responsible for partnership development with the local government.

Endline SNA helped Kitui WASH stakeholders realize its network was broader and deeper than originally imagined. 

Cliff Nyaga says the SNA helped his team “understand who's in the network, stakeholder priorities, interaction levels, their alignments, and misalignments... essentially understand the impact and effectiveness of our work...We actually found that the network is much bigger than we thought.”

He added, “Most aren’t necessarily participating in the Kitui WASH Forum, but provide important bridges to the forum and include NGO and government actors...This was a key insight because it allowed us to strengthen [bonds] and put in structures that reinforce the government’s role in the forum, which now includes members from the education and health sectors and more NGOs.”

Learn more about SWS work in Kitui County, Kenya.

Ongoing analysis improved professional water pump maintenance across 550 rural Ugandan communities. 

Joel Mukanga says the SNA helped his team “to reorganize, plan, and evaluate successes.” He and his team used the in-depth analysis to understand the “different players’ ideas and skill levels, as well as relationship strengths and resource flows.” Mukanga adds it is useful to conduct these analyses periodically to understand how stakeholders and networks “change and shift over time depending on projects and goals.” 

For example, information from a 2020 SNA alerted Whave that a once-central stakeholder was no longer serving Kamuli District because they shifted resources elsewhere. Importantly, the SNA helped Mukanga and his team get an up-to-date understanding of who their relevant and reliable working partners are. 

“If we didn't have that analysis, we probably would keep them in our records, but without them adding value to our progress,” says Mukanga. He adds that the SNA also helped his team realize “there were also a few government staff members and civil servants who were central figures in 2018, but now aren’t.” This is the type of vital information that SNAs produce, enabling organizations to pivot and adapt to their evolving network connections. 

Consider the advantages and disadvantages of network analysis. 

Network analyses are used to more effectively design, monitor, and evaluate locally-led initiatives while improving collaboration, knowledge sharing, and WASH systems at the local level. These analyses also have drawbacks, including sometimes costly and time-consuming data collection and results that can be prone to bias. Additionally, collaborative networks might not necessarily mean that the main initiative of the project is on track. Other monitoring methods still need to be used to evaluate overall project outcomes. 

However, as Nyaga and Mukanga mention, SNAs can contribute rich, valuable, and practical information to WASH programs, helping teams make data-driven decisions to fortify WASH networks and, overall, create more strategic and comprehensive programs that enable sustained water and sanitation systems.

Learn More

• Listen to online training on how SWS partners used SNA during key program stages in Ethiopia, Kenya, Uganda, and Cambodia.
• Read about a case in Debre Birhan, Ethiopia, where repeated analyses prompted the creation of a learning alliance to improve the town’s sanitation services that demonstrated significant influence on both town dialogue and budgeting decisions. 
• Explore practices to help water maintenance service providers make strategic decisions to improve WASH systems and ways to apply SNA best practices in WASH work. 

By Erin Fiorini, Communications Associate for Sustainable WASH Systems Learning Partnership (SWS)