Using big data for evaluating development outcomes: a systematic map

Programme of work

Evaluating complex interventions

Principal investigator(s)

Francis Rathinam

Host institution

International Initiative for Impact Evaluation (3ie)

Project type

Evidence synthesis

Country/ies

Multi-country

Research question

Technological advances have created opportunities to use data from unconventional sources, such as satellite imagery, which are largely unexploited in evaluations. The research team will review new and advanced methods of data collection and identify: a) best strategies for data collection of primary data in difficult contexts; and b) best uses of existing non-traditional secondary data in difficult contexts. The key output will be a map that provides a visual overview of existing and ongoing studies and discusses the risks, biases and ethical challenges in using big data for measuring and evaluating development outcomes.

Research design

The research team will produce a systematic map to highlight how big data is being innovatively used in measuring and evaluating development outcomes. They will map different sources of big data available for various development outcomes to identify the current evidence base, use and gaps.

Data source

Different sources of big data

Policy relevance

For evaluators, evaluation commissioners and policymakers, the map will highlight what data collection methods are available in difficult contexts, their relative benefits and costs, and the reliability of the data collected.