Can India create an effective framework to bridge the skill gap in its workforce?
Skill gap, where individuals, even if formally qualified, lack actual competencies needed to perform effectively on the job.
The study also broadens the definition of 'skills' to include not only technical and vocational proficiency, but also cognitive and socio-emotional capabilities - all of which are critical for productivity and long-term employability.
To test and validate the proposed framework, the study took a stepwise approach.
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Selected 7 high-growth sectors based on such indicators as their contribution to GVA, employment share, growth trajectory and strategic relevance. Additional parameters such as input-output multipliers and sunrise potential were used to identify sectors most likely to drive employment in the short-to-medium term.
Roles, as defined by Sector Skill Councils (SSCs), were aligned with National Classification of Occupations (NCO) 2015 to ensure consistency across data and analytical frameworks. This harmonisation enables more accurate forecasting and helps align skill development efforts with actual labour market needs.
Macro-level workforce analysis included examining the profile of workers - educational qualifications (general, technical and vocational), gender and occupation types - using available national datasets like PLFS and Annual Survey of Industries. Simultaneously, the study identified geographical clusters across states and districts to understand where economic and employment activity is concentrated.
Input-output modelling techniques used to forecast shifts in job demand over a 3-year horizon. Drawing on data from NAS, PLFS and international growth forecasts, these simulations offered insights into the scale and nature of workforce requirements likely to emerge across sectors.
Identification of top occupations or potentially facing skill shortages and/or gaps, stakeholders across the value chain were systematically mapped and interviewed.
India needs a dynamic framework to track skill demand and supply. While national and state-level studies have been conducted since 2011, lack of a common methodology has made it difficult to reconcile a national picture.In 2024-25, skill development and entrepreneurship ministry and NCAER launched a study to build a unified, scalable framework for skill gap assessment . This aimed to create a regularly updated system for tracking skill needs across states and sectors. It proposes a dynamic framework that enables continuous monitoring and periodic forecasting.Globally, countries with mature skill ecosystems rely on a combination of quantitative and qualitative tools to assess skill needs. India, too, has seen fragmented efforts by multiple institutions, each applying its own lens.MSDE-NCEAR framework creates a baseline from which governments, training providers and employers can work together to better target resources, update training curricula, revise qualification packs, and identify underserved regions or occupations requiring focused intervention.But it requires additional steps needed to make the system fully operational and responsive to real-time changes:A more robust and granular survey instrument can capture data on employment levels, wage structures, qualifications and skill requirements across non-agricultural enterprises, with district-level representation to ensure that local workforce trends are adequately reflected in national planning.Persistent vacancies could serve as a practical proxy for identifying hard-to-fill roles. A common national definition of such vacancies would allow for consistent tracking across regions and sectors.Real-time labour market insights drawn from enterprise records, online job portals and digital employment platforms could help identify emerging occupations, spatial mismatches and shifting industry needs. This would allow for quicker course corrections and timely updates to training curricula and qualification packs.The task ahead is to institutionalise the MSDE-NCAER framework and align it with evolving labour market trends through regular data flows and support state-level adoption. For this to happen, skill-gap studies must become central to how we plan, fund and implement investments.
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