Working towards National-Level WASH Data Management in Malawi

3 min readMar 6, 2019

Snippets from a workshop held at the Colorado WASH Symposium in March 2019.

Progress of mapping rural water points in Southern Malawi:

“Going from data collection to better decision making” is a phrase often heard at WASH conferences. But how often is that more than an aspiration? And how often is this decision-making limited to a pilot, project or an individual NGOs operations?

At Colorado WASH we ran a workshop focussed on direct interaction with fresh, comprehensive WASH data collected in Malawi. Data, moreover, that national and local level government officials need, have access to, and are able to use to make operational decisions on where to focus their resources. In this post we open up an interactive console fed by that data for you to explore, and to get a closer handle on, the complexities of data-driven decision making in rural WASH in Malawi.

The Climate Justice Fund: Water Futures Programme has been working in Malawi since 2011 aiming to support the government of Malawi to achieve SDG 6. This work, led by the University of Strathclyde, is part of Scotland’s long-standing strategic partnership with the government of Malawi. In 2017, powered by mWater, the CJF began assessing every rural water point across Malawi, as well as potential risks to water quality (e.g. sanitation and waste sites). This data collection is coupled with capacity building initiatives, including setting up a national-level regulating body modeled on Scotland’s own regulator with the intent of having the skills and structures in place in-country to keep relevant data coming through on a permanent basis.

Strathclyde is establishing a decision support tool in close conjunction with Malawi’s national and local governments to advise on water supply interventions.

More granular data allows for more informed decisions

In our workshop, having SDG Service Levels mapped at the household level gave us an initial picture of where interventions might be targeted. However, this picture immediately gets more nuanced whenever we overlay water point functionality information as well as the locations of institutions, substantially changing our analysis of the situation. Ultimately, this data is coupled with local knowledge and interpretations. Equipped with these analyses, local decision-makers can better think through and justify their interventions, and then hope to assess the impact of their efforts through further SDG-linked Service Level monitoring.