About Data Analytics, Systems, and Use (DASU)

DASU is a practical and results-oriented framework designed to strengthen health systems and other public services through effective data use, digital tools, and innovation. Grounded in three foundational elements of functional data ecosystem—data analytics, data systems, and data use, DASU enables institutions to become more responsive, transparent, and performance-driven.
  • Data analytics is at the heart of DASU’s ability to convert information into impact. It involves the application of a broad range of advanced techniques (such as descriptive and inferential statistics, machine learning, artificial intelligence, geospatial modeling, and predictive analytics) to generate actionable insights from high-volume, diverse, and rapidly evolving datasets.
DASU is purposefully designed to work within complex and interconnected data ecosystems that span routine health information systems, programmatic data, financial records, population surveys, and real-time digital platforms. Leveraging scalable infrastructure and adaptable tools, DASU integrates and analyzes diverse data sources to support real-time monitoring, equity analysis, and service optimization. By coupling technical sophistication with capacity building, DASU ensures that analytics are not only powerful but practical, enabling decision-makers at all levels to act on evidence and drive sustained and system-wide improvement.
  • Data systems serve as the digital backbone of the DASU framework, providing the infrastructure, platforms, and governance needed to collect, integrate, and manage diverse and interconnected data sources. These include routine health information, programmatic data, financial records, surveys, facility assessments, population estimates, laboratory and diagnostic data, public health emergency (PHE) data, logistics and supply chain information, and community-based data. By enabling interoperability and improving data quality, DASU-supported systems ensure timely and reliable access to information that is essential for effective planning and decision-making.
In the health sector, DASU-supported data systems are instrumental in strengthening service delivery, enabling real-time monitoring, and supporting performance management by facilitating seamless data flows from facility level to subnational and national platforms. Beyond health, these systems are adaptable to other sectors (such as education, agriculture, social protection, finance, etc.) where they contribute to integrated planning, efficient resource allocation, and evidence-based program management. At the core of DASU’s approach is its emphasis to digitization and data-driven innovation. The framework embeds cutting-edge tools (such as AI-powered dashboards, real-time monitoring platforms, geospatial visualization, and automated feedback loop systems) within system design. These innovations support equity analysis, improve institutional responsiveness, and enable adaptive, cross-sector decision-making. DASU ensures that data systems are scalable, secure, and aligned with national priorities, positioning them as foundational assets for long-term health system strengthening and public sector transformation.
  • Data use ensures that insights are translated into meaningful action, shaping policies, improving services, guiding resource allocation, and strengthening accountability. It embeds evidence into institutional planning, budgeting, and performance management processes, creating a culture of routine and impactful data use.
DASU also contributes to a broader research and development (R&D) ecosystem by fostering continuous learning, testing scalable innovations, and generating context-specific evidence. Through partnerships with governments, research institutions, and implementing partners, DASU enables co-creation and adaptation of tools and methods that respond to local priorities and evolving system needs. Through this integrated and forward-looking approach, DASU enables health systems to become more agile, transparent, and results-driven, delivering equitable and sustainable impact. DASU has demonstrated proven impact in the health sector, improving data quality, strengthening service delivery, and enabling real-time performance and equity monitoring. Its modular and adaptable design also makes it effective in other sectors (such as education, agriculture, social protection, and public finance), empowering governments to make timely, evidence-based decisions that are targeted, transparent, and impactful. Designed for sustainability and scale, DASU supports capacity building, integrates with national systems, and embeds data-driven approaches into institutional processes. By aligning robust systems, emerging technologies, and actionable insights – within a strong R&D ecosystem – DASU provides a transformative platform for building agile, modern, and data-powered systems that deliver measurable and lasting results across sectors.

Objective

The objective of the Data Analytics, Systems, and Use (DASU) Initiative is to strengthen health system performance by institutionalizing the routine generation, analysis, and use of data for monitoring progress, guiding strategic decision-making, and advancing equity, quality, and efficiency at all levels of the health system. 
 
DASU addresses critical structural and system-level challenges within the data ecosystem, such as fragmented systems, limited interoperability, governance gaps, and underinvestment in infrastructure and workforce capacity. The initiative promotes the integration and triangulation of diverse data sources—such as routine health information, program data, household surveys, facility assessments, administrative records, geospatial data, and population censuses—while fostering multi-institutional collaboration and data governance. It also supports the development of enabling environments for the adoption of emerging technologies (such as artificial intelligence and machine learning) to enhance predictive analytics, real-time insight generation, and evidence-informed policy, planning, and program monitoring.