Background of the Problem Statement
India's skilling ecosystem trains lakhs of candidates annually across sectors, but training capacity is frequently misaligned with actual industry demand at the district and sector level.Some trades see chronic oversupply of certified candidates relative to available jobs, while emerging and high-growth trades remain under-served by training infrastructure. This mismatch stems from the absence of a real-time, granular view of labour demand that planners can use when allocating training targets, sanctioning new centres, or revising course curricula. Existing labour market data (PLFS, NCO-based job postings, industry hiring signals, e-Shram registrations) is fragmented across sources and rarely synthesized into a decision-ready format for scheme planners. MSDE, as the apex department for skilling,requires a forecasting capability that can flag demand-supply gaps early enough to influence annual training targets, NSQF course revisions, and centre-level capacity planning, rather than discovering mismatches only after placement outcomes are reported.
Description of the Problem Statement
The challenge is to build a Labour Market Intelligence System (LMIS) that can:
Aggregate and normalise labour demand signals from job portals, industry hiring data,NCO/NSQF-coded postings, and government employment databases (e-Shram, NCS). Cross-reference demand signals against current training capacity and annual seat allocation by sector, trade, and district. Generate forward-looking demand-supply gap forecasts at sector and district granularity, updated periodically rather than annually. Rank trades/geographies by severity of oversupply or undersupply to inform target-setting for the next training cycle. Provide an interactive dashboard for MSDE/NCVET/Sector Skill Council planners, with drill-down from national to district level.
Expected Solutions / Outcomes
A functioning forecasting dashboard covering at least a few pilot sectors and States. A documented methodology for combining heterogeneous labour market data sources into a single demand index. Early-warning flags for trades approaching saturation or acute shortage. An API/export layer so forecasts can feed into scheme target-setting workflows. Multilingual, accessible interface for state-level planning units.