National Data Systems

Moderator

• Timothy Lubanga, Commissioner for Monitoring and Evaluation, Office of the Prime Minister, Uganda

Panellists

• Joao Cardoso, President, National Statistical Institute, Cabo Verde
• Nemariam Yohanes Mengistu, Director, Ministry of Finance and National Development, Eritrea
• Elena Kukharevich, First Deputy Chairperson, National Statistical Committee of the Republic of Belarus
• Camille Spencer, Programme Director, Monitoring and Evaluation, Ministry of Planning and Development, Trinidad and Tobago

Evaluation needs data. How do we ensure our National Evaluation Systems, and the monitoring and evaluation of progress towards the SDGs, are supported with credible national data systems?

• Data is the key ingredient for decision-making and accountability. Absence of high‑quality data and information is one of the most significant challenges for generating evidence in an evaluation ecosystem for making informed decisions and policies.
• Strong data and statistical systems are essential for National Evaluation Systems and measuring progress towards the SDGs. There is a need to ensure alignment between regional and national development goals, indicators and targets and the SDGs. There is a need to increase the coverage of indicators as well as harmonization of internal and external data against them.
• Weak and archaic national statistical systems remain a challenge. While they are absent in some countries, they need to be modernized and made fit-for-purpose in others where they exist.
• Inadequate human resource capacity and skills, insufficient coordination within and across ministries, between government, partners and national stakeholders, and limited political buy-in for data and data systems at all levels of the government impedes progress in establishing and maintaining credible national data systems.
• Strengthening national data systems requires a multipronged and holistic approach. This can be done through:
  • Revitalization of NES by strengthening legislation on data and statistics; introducing state-of-the-art software and technology; promoting data innovation; and creating a national structure for development statistics.
  • Inclusion of data from the beginning of the national development planning and policy cycle (not as an afterthought) and making the required public and private sector investments.
  • Engaging in partnerships with universities, research institutions, development partners and international organizations to build capacity, harmonize efforts and bridge data gaps.
  • Institutionalizing a culture of results-based management in the government by strengthening government data collection and management systems, developing a national monitoring and evaluation policy and developing a national evaluation agenda that mandates data collection at all levels of government.
  • Ensuring high-level political ownership and buy-in, as it drives demand for and financing of data.

Conclusion

National Evaluation Systems support data-driven decision-making and government accountability. This requires strong data collection systems that are robust, timely and reliable. Strong data and evidence are essential for strong National Evaluation Systems and to build forward better, although challenges are not insignificant. Strengthening national data systems requires a multipronged and holistic approach. Statistical systems need: modernization and better coordination within and across national partners; better accounting for culture and context; stronger political ownership of data; and for data to become part of the policy cycle and integral to national planning and budgeting.