An Administrative Data Maturity Model - Building national administrative data capacity to produce results for children.

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Karen Carter
Published online: Nov 25, 2019


Administrative data is widely recognized as essential for improving service provision, identifying and monitoring development outcomes. However, despite significant investments, many countries remain unable to report against key development indicators and data quality significantly limits the utility of much of the data that are available. At the same time, the data landscape is changing rapidly with new technologies and the expansion of national identity systems.


Many of the requirements for effective national administrative data systems are not sectoral, but rather the “foundational” elements of government data policy, use and supporting infrastructure. UNICEF is working closely with partners to develop a maturity model for administrative data systems to prioritize investments and needs across sectors, help donors assess the capacity to absorb proposed investments, and ensure impact for children. The model provides a framework for best-practice examples, and to highlight areas where additional guidance is needed.


The concept draws on the wealth of existing assessment tools and quality indicators for administrative data systems across sectors and organisations and is built on three main elements:


  • It is child focused: putting the best interests of children at the centre of system design and operation.

  • It is built from the community up: recognizing the importance of local engagement in supporting development outcomes for children and the collection of high quality data.

  • It recognizes the need for strong cross

  • sectoral foundations at the national level to support the effective and sustainable functioning of administrative data systems.

Under each element, the outcomes that a mature administrative data landscape should deliver are defined, along with the system and landscape characteristics required to achieve these. The approach also places administrative data as part of a broader national data landscape – recognizing the importance of integrating multiple data sources to validate data quality, address data gaps, and meet national data requirements.


Administrative data is widely recognized as essential for improving service provision, identifying and monitoring development outcomes. However, despite significant investments, many countries remain unable to report against key development indicators and data quality significantly limits the utility of much of the data that are available. At the same time, the data landscape is changing rapidly with new technologies and the expansion of national identity systems.

Many of the requirements for effective national administrative data systems are not sectoral, but rather the “foundational” elements of government data policy, use and supporting infrastructure. UNICEF is working closely with partners to develop a maturity model for administrative data systems to prioritize investments and needs across sectors, help donors assess the capacity to absorb proposed investments, and ensure impact for children. The model provides a framework for best-practice examples, and to highlight areas where additional guidance is needed.

The concept draws on the wealth of existing assessment tools and quality indicators for administrative data systems across sectors and organisations and is built on three main elements:

  • It is child focused: putting the best interests of children at the centre of system design and operation.

  • It is built from the community up: recognizing the importance of local engagement in supporting development outcomes for children and the collection of high quality data.

  • It recognizes the need for strong cross-sectoral foundations at the national level to support the effective and sustainable functioning of administrative data systems.

Under each element, the outcomes that a mature administrative data landscape should deliver are defined, along with the system and landscape characteristics required to achieve these. The approach also places administrative data as part of a broader national data landscape – recognizing the importance of integrating multiple data sources to validate data quality, address data gaps, and meet national data requirements.

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