# **3. Case studies**

When the 12 attributes of the data are present, data can yield vast value for development outcomes. This section relies on case studies illustrating how each attribute can bring about positive change. Most examples involve several features either directly or indirectly, and as outlined above, having a single feature in isolation is seldom enough to bring about value.

## **Completeness**

When data cover the entire population of interest it is possible to make inferences that one otherwise would not be able to. One of the most fundamental ways in which countries can make sure their data cover their entire population of interest is through foundational identification (ID) and population registration systems, and particularly by assuring that all individuals are covered in government databases.<sup>3</sup> In Thailand, at the turn of the century, only 71 percent of the population was covered by a public health insurance scheme that was intended to be universal. Yet the country had a near-universal population register in which citizens were issued a personal identification number when they were born or when their household was registered for the first time. Leveraging this register and the personal identification information from the existing public insurance scheme, the government was able to identify the population not covered and increased health insurance from 71 percent to 95 percent (World Bank 2020a and World Bank 2018a).

In the absence of nation-wide administrative data, representative survey data fulfill a similar role. A recent example in Nigeria illustrates the power of data that are representative of the entire population of interest. The Government of Nigeria commissioned the 2015 National Water Supply and Sanitation Survey to understand access to water and sanitation of all households in Nigeria. As part of the survey, 201,842 households, 89,721 improved water points, 5,100 water schemes, and 51,551 public facilities including schools and health care facilities were enumerated. Coupling these data with advanced mapping techniques to better understand geographic variation in access to water and sanitation services revealed that 130 million Nigerians did not meet the standard for sanitation as expressed in the United Nation’s Millennium Development Goals. More specifically, the data revealed that inadequate access to water is particularly an issue for poor households, and that public expenditure in water and sanitation is limited and of poor quality (Map 1) (World Bank 2017). In response to these findings, President Muhammadu Buhari declared a state of emergency in the sector and launched the National Action Plan for the Revitalization of Nigeria's Water, Sanitation and Hygiene (WASH) Sector (Nigeria Federal Ministry of Water Resources 2018). President Buhari pledged that his administration would prioritize WASH infrastructure development, long-term planning, and stakeholder coordination. In recognition of the sector-wide crisis, the government requested from the World Bank a 700 million USD lending operation to support the sector. The overall goal of

> 3 Identification systems that use common identifiers across data sets also promote interoperability which can be a powerful tool for improving granularity through the overlay of multiple data layers.

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