Digital Intelligence and Implementation Research (DIIR)

DIIR is BIGD’s integrated unit for digital intelligence and implementation research. Its purpose is to generate rigorous and actionable evidence using the best mix of data sources and methods, combining advanced analytics with learning-oriented evaluation approaches to support evidence-informed decision-making, adaptation, and program improvement, built on BIGD’s deep field data collection expertise.

Digital intelligence applies econometric analysis, machine learning, and AI to surveys, administrative records, satellite imagery, and real-time monitoring streams to generate new insights from diverse data. At the same time, implementation research and learning-oriented evaluation examine how programs are designed, delivered, and adapted in practice.

The DNA of the unit is methodological range with rigour. DIIR pairs newer quantitative tools with evaluative approaches to deliver studies that may be shorter or longer than a conventional evaluation, but are deliberately less traditional, using the methods best suited for the decision at hand rather than a standard research template.

Core Functions

• Digital intelligence and Data Innovation

Building and maintaining data infrastructure such as DataHub Bangladesh; applying econometric analysis, machine learning, and AI to diverse data types; and developing dashboards, forecasts, and real-time analytics that make evidence accessible and usable.

• Implementation research

Embedded research on how programs and policies work in practice, diagnosing implementation bottlenecks, testing adaptations, and supporting course correction and continuous improvement during implementation rather than after it.

• Learning-oriented monitoring and systems evaluation

Developing theories of change, learning-oriented monitoring frameworks, and context-specific evaluation approaches for complex programs and systems, while applying systems-informed and complexity-aware methods to generate timely insights that support learning, adaptation, and decision-making.

• Capability building

Growing new skills within the unit and across BIGD, including data science and adaptive evaluation methods, and enabling teams to lend and borrow expertise across BIGD’s research clusters.