Modernization of the labour force forecasting system for Ukraine’s industry

Анотація

The article examines the challenges of ensuring an adequate supply of skilled labour for Ukraine’s industrial sector during wartime and substantiates approaches to modernizing the state system for forecasting labour demand. It is established that the shortage of qualified personnel in industry is systemic and shaped by a combination of demographic, migration, and structural factors that constrain industrial modernization and limit the potential for sustainable economic recovery. A comparative analysis of international practices of labour market forecasting is conducted, focusing on approaches based on multi-level modelling, scenario analysis, the integration of statistical and administrative data, and the use of big data derived from online vacancies. The study evaluates the current Ukrainian Methodology for Forecasting Labour Demand and identifies its major shortcomings, including methodological inertia, the absence of scenario-based forecasting tools, the failure to account for technological and structural changes in skill composition, and the insufficient integration of data from diverse sources. The article substantiates the need to develop a renewed forecasting system that combines macroeconomic, sectoral, occupational, and skills-based levels of analysis, allowing for the modelling of multiple labour market development scenarios. An institutional model is proposed that envisages the establishment of a specialized state analytical centre responsible for coordinating methodological frameworks, consolidating data sources, and producing scenario-based forecasts of labour market needs. Such a system would enable the regular updating and harmonization of forecasts across sectors, regions, and education levels, improving the responsiveness of workforce planning to real industrial demand. The research findings provide a conceptual foundation for enhancing the evidence base of employment, education, and industrial policies in Ukraine and for building an integrated national system of analytical and forecasting support in the context of post-war economic recovery.

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