Data and Evidence: The Foundation of Development Policy

Drivers of Success

The World Bank’s success is attributable to its technical expertise, the ability to link global needs to national needs, initiatives that were sustained for the long term, and well-aligned partnership engagements.

There were also significant successes in countries where the World Bank and its partners used a system-wide approach to statistical capacity building.

Data and evidence are the foundation of development policy and effective program implementation, and countries need data to formulate policy and evaluate progress.

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.

How Has the World Bank Supported Data Production, Sharing, and Use?

This evaluation finds that the World Bank has been highly effective in producing influential data globally and until recently in promoting global data partnerships.


  • The World Bank was mostly effective at the country level in supporting data production, promoting open data, encouraging some country clients to share data, and in building the capacity of national statistical organizations in countries where it adopted a system-wide approach.
  • The World Bank was less effective in adapting to the changed global partnership landscape where the complementarity of new partnerships is less clear. It was also less effective in fully using its leverage to encourage data sharing by client countries which have been reluctant to do so, and even less effective in promoting data use in government decision making, building subnational data capacity, strengthening country clients’ administrative data systems, and staying at the forefront in analyzing the potential and pitfalls of big data for development.

See Chapter 2, Global Development Data, and Chapter 3, Building the Data Capacity of Countries, for more information


1. Implement goals and priorities reflecting the findings of this evaluation with regard to the World Bank’s support to global data and global partnerships, country data capacity, and a user-centered data culture.

2. Mobilize and deliver additional support to countries’ statistical systems, using a more comprehensive model of statistical capacity building that also factors in needs and opportunities to strengthen administrative data systems.

3. Step up engagements with global partners and client governments on long-term funding for development data.

4. Scale up promotion of data sharing and data use.

5. Implement coordinated actions so that World Bank operations benefit from big data’s insights and clients receive appropriate support for big data use.

See Chapter 6: Conclusions and Recommendations

Body Also See

Watch In Brief: Why Data Matters in Development

To guide its inquiry, the Independent Evaluation Group (IEG) developed a list of ingredients for successful national data systems of the future, included in the infographic below.


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