Greece – Mechanism for diagnosing labour market needs

Mechanism for diagnosing labour market needs is an online tool for monitoring and anticipating skills needs in the labour market with an innovative tool for analysing skills data.

A mechanism for diagnosing labour market needs as a tool for good practice

In June 2025, the ‘labour market diagnostic mechanism’ was introduced as a best practice in all practices of the European Network of Public Employment Services (PES) of the European Commission, including those reflecting EU employment policy in the context of the Europe 2020 strategy.

Get to know the initiative

The Greek labour market is developing rapidly. Within this framework, a labour market diagnostic mechanism has been developed, an online labour market monitoring tool that combines big data analysis with data on job and skills demand and offers solutions for more effective employment services and labour market policies. The tool helps anticipate skills needs to improve labour market information and improve the services provided to PES advisers, jobseekers and employers.

It operates under the supervision of the DYPA (Public Employment Service) and the Expert Unit for Employment, Social Security, Social Security and Social Affairs (MEKY) of the Greek Ministry of Labour and Social Security and is a pioneering initiative that brings innovation in monitoring and anticipating skills needs.

The tool, updated in 2024, uses data from the Ergani job register,the Hellenic Statistical Institute (ELSTAT) and the ESCO European Skills Classification System to map the most-demanded skills by sector, demographic groups and regions. This tool was initially tested in the information technology and communications sector and in the pharmaceutical sector, and is planned to be extended to all economic sectors by the end of 2025. The initiative is supported by the European Social Fund (ESF) and is part of the Programme for Human Resources Development and Social Cohesion 2021-2027.

Why is this an example of good practice?

The mechanism is an excellent practice for both the Greek and European labour markets for the following reasons:

• Data-driven analysis: It combines data from different sources (Ergani, ELSTAT, ESCO) to provide accurate skills forecasts and overcome the challenges of traditional questionnaire-based surveys. This enables a quick and reliable mapping of labour market needs.
• Strengthening DYPA services: This tool helps employment advisers deliver more targeted services by improving the match between unemployed and vacancies.
• In 2024, 861 DYPA advisors and 53 senior officials received training on the use of the Facility, which increased the efficiency of their services.
• Adaptation of training programmes: The results of the instrument lead to a reform of the curricula in VET institutions DYPA and ensure that education offers match current and future market needs.
• Support for businesses and employees: By using ESCO's European classification and validation through Employers' Working Groups, the tool helps businesses identify the required technical skills and invest in training their employees.
• Flexibility and adaptability: The tool has a user-friendly interactive interface that allows the selection of demographic or local data and makes it accessible to different target groups, such as policy makers, employment advisers and students.
• Contribution to policy-making: the mechanism provided documentation for the update of the National Upskilling and Labour Market Connectivity Strategy, which was positively assessed by the National Labour Skills Council.

Results and benefits

The instrument has already delivered significant results:

• Better employment services: Consultants trained in DYPA use skills forecasts to better match jobs and the unemployed.
• Targeted policies: References to the instrument support evidence-based active labour market policies and reduce the imbalance between skills supply and demand.
• Strengthening vocational training: DYPA VET institutions receive regular information on skills needs, allowing their programmes to be adapted.
• Labour market resilience: The Facility helps prevent unemployment and strengthen the resilience of the labour market through preventive measures.

Lessons and Success Factors

The success of the mechanism is due to the simplified presentation of complex data, the regular training of consultants and the validation of results through employers’ working groups. A key lesson is the need for continuous training for users of the tool and its adaptation to more user-friendly formats, such as the provision of unemployment indicators by occupation and by region.

Conclusion

The mechanism for diagnosing labour market needs is an exemplary practice that brings Greece closer to a modern, evidence-based and flexible labour market. By using advanced technologies and data, the tool not only improves DYPA services, but also strengthens the link between education, employers and employees, contributing to a more resilient and competitive economy. Its extension to all sectors by the end of 2025 will further strengthen the dynamics of the Greek labour market, making the mechanism a model for other countries.