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  • Julia Boulenouar

Data in Water and Sanitation: Bridging the Gap Between ‘Technically Brilliant’ and Real-World Decision-Making

We have access to greater and greater volumes of data as never before, and new tools, devices and platforms are being developed all the time. The WASH sector is no different, with data initiatives being launched across many countries at different scales. In part as response to the proliferation of such data initiatives, the Osprey Foundation and the Conrad N. Hilton Foundation funded a study to assess how such tools – and the data generated by them – have impacted on decision-making in the sector.

The study was led by Aguaconsult working together with IRC of the Netherlands and looked at the application of several different data tools and platforms in four countries, including Colombia, Ghana, Sierra Leone and Uganda. Although the choice of data initiatives was not exhaustive and involved only a limited set of experiences, a number of interesting insights were gained, including the following:

  • Use of data in decision making in the WASH sector is a complex, non-linear, process, which is influenced by a set of factors that can be grouped in three categories related to data characteristics, capacities, and motivations to engage and use data for decision making.

  • This research highlighted the importance of all factors needing to be at least at a base-level, for data to be effectively used in decision making.

  • It identified several factors playing a particularly influential role on others, notably the existence of an “evidence based decision-making culture” being critical to the creation of other influential conditions such as incentives, motivations, and personal interest.

  • It has also identified factors playing a “leveraging role” (highly influential and with limited dependency on other factors), such as organisational and institutional capacities.

The findings point to the need for data initiatives to not only present smart offerings – the supply side – but to make more effort to understand the ‘demand-side’ of data use: who will ultimately use the data in decision-making? what capacities and resources do they have at their disposal? When do they need the data and in what formats?

Beyond highlighting the need to better understand the data-to-decision-making pathway, the findings stress the importance of addressing the entire data eco-system. This cannot be done in isolation, rather it should consider long-term systemic support and commitment to capacity building.


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