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Better skills data for smarter financing of education and training
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Link Type
Skills Intelligence publication url
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Target audience
Digital skills for allDigital technology / specialisation
Big DataDigital skill level
BasicGeographic Scope - Country
European UnionIndustry - Field of Education and Training
Generic programmes and qualifications not further definedTarget language
Type of initiative
International initiative
Event setting
Publication type
General guidelinesSkip to content
Effective education and training policy depends on reliable skills data, yet many governments face significant gaps that limit their ability to evaluate programmes, prioritise investment and improve the use of public resources. This paper from the OECD identifies key challenges, including fragmented data systems, weak links between education and labour market records, incomplete coverage of skills development areas, and problems with data quality, accessibility, consistency and timeliness. These limitations prevent policymakers from gaining a complete understanding of how investments in skills translate into outcomes.
The paper reviews ten major data sources used in education, employment and skills policy, explaining their applications, strengths and limitations. It highlights how better use of data can strengthen financial decision making by supporting cost-benefit analysis, identifying inefficiencies and directing funding towards programmes with stronger returns. However, it also emphasises that governments are only one part of the skills ecosystem, alongside employers, private providers and individuals who contribute substantially to training and development.
To improve the use of skills data, the paper outlines four major barriers: institutional and governance challenges, limited analytical capacity, legal and regulatory constraints, and technical issues such as incompatible systems and cybersecurity risks. It concludes that progress depends less on collecting new data and more on integrating and effectively using existing information through stronger co-ordination, improved governance and greater analytical capability. Modern technologies, including artificial intelligence, can enhance these efforts, but only when supported by high-quality data and effective data governance.
