Data Analytics & AI
Strengthening Crisis Monitoring Through Mapping Data Gaps
Enhancing the UNDP’s risk monitoring and measurement capabilities by identifying critical data gaps in the areas of economic, social and political risk.
Client: UNDP Office in South-Eastern Europe
Sector: International Development / Crisis Monitoring
Category: Data Analytics, Data Gap Mapping, Composite Index Design
Key achievements and results
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- Delivered comprehensive data gap mapping that directly informed client’s design of a risk monitoring system for better quantifying and monitoring economic, social and political risks.
- Established an evidence-based statistical framework for the comparative analysis of data availability, quality and coverage against regional peers. The final assessment mapped data availability across 17 thousand indicators from more than 250 global data sources.
- Provided strategic recommendations for the development of the risk-monitoring system and informed wider data advocacy engagement with the government.
Problem
A UNDP office in South-East Europe faced fragmented and inconsistent data sources across critical indicators needed for crisis monitoring. Existing datasets were incomplete, lacked standardization, and created analytical gaps in the UNDP’s monitoring of economic, social and political risks. This data fragmentation made it impossible to establish reliable baselines, conduct meaningful regional comparisons, or support real-time crisis monitoring for evidence-based decision making and strategic planning.
Approach
I conducted a comprehensive gaps analysis beginning with an extensive inventory of 17 thousand indicators from more than 250 global data sources. Through systematic mapping of data coverage gaps, I compared data availability for the focus country with regional peers to identify specific deficiencies in data coverage, quality and quality. The analysis employed rigorous statistical validation methods while maintaining focus on practical policy applications. I developed targeted recommendations for key indicators that would effectively measure critical risks and vulnerabilities within existing data constraints.
Identifying critical data gaps through regional benchmarking
Results
The gaps analysis provided crucial insights that shaped development of both the risk index and visualization system. By identifying specific areas where data coverage was insufficient, I enabled targeted collection strategies and designed a monitoring system that works within existing constraints while highlighting future improvement areas. This established new possibilities for comparative regional analysis and created a clear framework for prioritizing critical indicators. The resulting composite risk index and visualization system now enable systematic monitoring and quantification of relative risks across multiple dimensions.
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