Other times, it is public officials that may lack the skills or time to summarize the data to a shape from which value can be generated. In Brazil, for instance, evidence from 2,150 municipalities found that informing municipal mayors of research findings on the effectiveness of a simple policy change increased the probability that their municipality implemented the policy by 10 percentage points (Hjort et al. 2021).

Another example, where making the data more understandable helped guide policy choices, comes from Pakistan. Prior to 2008, Pakistan’s Punjab province suffered from poor government service delivery due to inefficiencies, rent seeking and more. Lack of digitized service delivery processes made it impossible to track service delivery and monitor performance and satisfaction with services. In an attempt to take on these challenges, in 2008, officials in one district of Punjab put in place a pilot Citizen Feedback Monitoring Program (CFMP), in which data on service provision from citizens was crowd-sourced using simple text messaging and other information and communications technology (ICT) applications. Analytical reports were sent to government officials enabling them to identify patterns and take evidence-based corrective measures. In 2012, the initiative was scaled up to 36 districts of the province and across 25 different public services. To maximize feedback collection and minimize cost and data literacy issues, in 2016 the CFMP introduced a robocall method to gather the data. As of 2019, CFMP had contacted 29 million citizens to solicit their feedback, and the government of Punjab had taken 41,600 corrective measures in response to CFMP data, including warnings, penalties and suspension. One of many results of this is that the availability of medicine increased from 46 percent to 77 percent (Global Delivery Initiative 2019). In a 2015 evaluation of the program, 90 percent of respondents said it had helped build trust between citizens and authorities (Masud 2015).

# **Interoperability**

When data sources are interoperable the potential use and value of data expand. As one example, interoperability can help governments prioritize scarce resources by cutting costs such as by eliminating duplicate or ghost recipients of social transfers—beneficiaries, often of pension funds, who are no longer alive. This was the case in Argentina where the government identified noneligible beneficiaries across various social programs using the country’s system of unique taxpayer ID numbers to link data sets, generating an estimated savings of $143 million over eight years (World Bank 2020a and World Bank 2018b).

Interoperability can also help improve targeting. In Jordan, the Profile Global Registration System (ProGres), the main database used by the UNHCR to register refugees, has traditionally been used to target cash assistance to refugees outside camps. This database contains key socioeconomic characteristics on almost all refugees since most register with UNCHR at some point in time. ProGres does not contain information on expenditure of households, though, preventing transfers to be targeted explicitly to poor households. Combining ProGres with the Jordanian Home Visits database, which contains only a subset of the population of interest, but 19