Data for Development : An Evaluation of World Bank Support for Data and Statistical Capacity - Independent Evaluation Group (World Bank, Washington, DC, 2017)
This evaluation’s objective was to assess how effectively the World Bank has supported development data production, sharing, and use, and to suggest ways to improve its approach. This evaluation defines development data as data produced by country systems, the World Bank, or third parties on countries’ social, economic, and environmental issues. At the global level, the World Bank has a strong reputation in development data and has been highly effective in data production. It produces influential, widely used data and cross-country indicators that fill important niches, benchmark countries, and stimulate research and policy action. The World Bank has also taken a prominent leadership role in global data partnerships so far. However, the World Bank needs to determine its future role carefully because the global partnership landscape is becoming more uncertain—as old partnerships phase out, the complementarity of new partnerships is unclear. This makes the World Bank’s future role especially pivotal because the sustainability of funding from global data partnerships at both the national level and for some global data efforts is at risk. Without sustained funding, past progress will be in jeopardy, as observed in some countries where data quality worsened when trust fund support ended. At the national level, the World Bank has been mostly effective at fostering its client countries’ data production through its own financing and through financing from small trust fund grants. It has been less effective in promoting data sharing; while the World Bank has used its leverage in some of its client countries, it needs to do a better job at encouraging other countries to share data. The World Bank has been even less effective in promoting data use by governments and citizens. The World Bank’s systemwide approach to building the capacity of national statistical organizations yielded significant successes in countries where it was deployed, and it should now add a focus on building subnational capacity and strengthening client countries’ administrative data systems. The World Bank needs to make sure it clearly understands when and how big data can complement traditional data in answering key development questions related to its mission, and use big data analytics appropriately to underpin its own decisions and to ensure that it supports its country clients effectively in big data use. The World Bank still needs to address the implications for organizing big data work internally, entering into corporate agreements with private providers (typically the producers of big data), and seriously considering and addressing privacy and ethical concerns related to big data use.