2017年-世界发展银行全球_Data_for_Development___An_Evaluation_of_World_Bank_Support_for_Data_and_Statistical_Capacity_112页_2mb

Data for Development: An Evaluation of World Bank Support for Data and Statistical Capacity

Core Content

This evaluation assesses the World Bank's support for development data and statistical capacity, focusing on its effectiveness in data production, sharing, and use. It highlights the World Bank's role in global data partnerships, country-level data support, and the potential of big data for development.

Main Viewpoints

• Data as a Foundation: Data and evidence are essential for development policy and program implementation, both at the national and global levels.
• World Bank's Global Leadership: The World Bank has a strong global reputation for producing influential and widely used data and cross-country indicators, which help benchmark countries and stimulate research and policy action.
• Partnerships and Innovation: The Bank has played a leading role in global data partnerships, but the evolving landscape requires careful re-evaluation of its role. New partnerships for data innovation lack coherence and may be redundant.
• National-Level Support: The World Bank has been effective in supporting data production through its lending and trust fund mechanisms, but has been less successful in promoting data sharing and use.
• User-Centered Data Culture: There is a need to shift towards a more user-centered approach, where data is used by governments and citizens to inform decisions and improve outcomes.
• Big Data Opportunities and Risks: Big data offers significant potential but also presents risks. The World Bank needs to better understand how to integrate big data with traditional data and address internal and external challenges related to its use.

Key Information

Global Data Support

• The World Bank has been a key player in the global statistical system, producing influential data and cross-country indicators.
• It has supported the establishment and funding of global data partnership programs since 1999, contributing significantly to filling data gaps.
• The World Bank's success is attributed to technical expertise, alignment of global and national needs, long-term initiatives, and successful partnerships.

Country-Level Data Support

• The Bank has supported data production in many countries through its lending and small trust fund grants.
• However, it has been less effective in promoting data sharing and use, particularly with governments and citizens.
• A systemwide approach to building national statistical capacity has yielded positive results, but there is a need to expand support to subnational systems and administrative data.

User-Centered Data Culture

• The World Bank has influenced some countries to share data publicly, but political, quality, and financial concerns often hinder this.
• Promoting data use is a challenge, especially in poorer countries where data literacy and research communities are weak.
• The evaluation recommends a more inclusive and empowering data culture, where data users are involved in the design of projects and the types of data produced.

Big Data Potential

• Big data is defined as extremely large datasets resulting from digitization and offers significant opportunities for development.
• The World Bank's big data initiatives have been ad hoc, lacking a coordinated institutional approach.
• Scaling up big data work would require a more structured approach, including clear responsibilities, data science expertise, and mechanisms to combine different data sources.

Recommendations

1. Implement Goals and Priorities: Align the World Bank's support with the evaluation's findings, including global data, partnerships, country data capacity, and user-centered data culture.
2. Enhance Statistical Capacity Building: Use a more comprehensive model to support statistical systems, with a focus on administrative data and subnational capacity.
3. Secure Long-Term Funding: Strengthen engagements with global partners and client governments to ensure long-term funding for development data.
4. Scale Data Sharing and Use: Promote universal data sharing and use, ensuring that all data financed by the World Bank is shared, and encouraging government and citizen demand for data.
5. Coordinate Big Data Initiatives: Develop a coordinated approach to leverage big data insights, including reviewing opportunities, specifying accountabilities, and ensuring management oversight.

Conclusion

The World Bank has been effective in data production and global partnerships but needs to improve its approach to data sharing, use, and the integration of big data. A more strategic, user-centered, and coordinated approach is necessary to sustain progress and meet the growing data demands of development goals.