Real-time Analytics · Risk Management
UNDP needed more granular, forward-looking analytics to help governments and development partners decide where clean-energy investments would produce the greatest equity, development, and climate-resilience impact.
Reported impact
UNDP strengthened its ability to support equitable energy planning, gave governments scenario-based visibility into underserved populations and investment trade-offs, and expanded the geographic reach of its analytics across Africa and the broader Global South.
UNDP and IBM co-developed two public analytical tools to improve energy-planning decisions: the Clean Energy Equity Index and the Electricity Access Forecasting model. The first combines clean-energy potential, socioeconomic need, infrastructure readiness, and climate-risk indicators into a geospatial index that users can adjust through a dashboard to evaluate trade-offs across Africa. The second uses IBM watsonx.ai, IBM Cloud, IBM Environmental Intelligence data, and open-source machine-learning models to forecast electricity access through 2030 at one-kilometer resolution. Geospatial, demographic, infrastructure, land-use, and climate data are fused so policymakers can move beyond historical access maps and model future access gaps under different scenarios. UNDP teams use the dashboards to compare underserved populations, explore investment options, and align clean-energy strategies with broader development outcomes rather than relying on coarse national-level statistics.
Geospatial, demographic, infrastructure, land-use, energy-potential, and climate-risk data are combined into the Clean Energy Equity Index and Electricity Access Forecasting model, where watsonx.ai and open-source ML generate country-level forecasts and scorecards that are surfaced through dashboards for policymakers and financing partners.
102 countries covered by the Electricity Access Forecasting Model
It produces projections for electricity access through 2030 at a 1 km resolution, using geospatial, demographic, infrastructure, and land-use data provided by IBM Environmental Intelligence
The Clean Energy Equity Index provides localized insights across 53 countries in Africa
The Electricity Access Forecasting model was created with IBM watsonx.ai, IBM Cloud, and open-source machine learning models.
more than 1 billion people still live in energy poverty
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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