Enabling data analytics for actions tackling skills shortages & mismatch

Projektinformationen

TRAILS

ID Finanzhilfevereinbarung: 101132673

DOI

10.3030/101132673

EK-Unterschriftsdatum 26 Oktober 2023

Startdatum 1 Januar 2024

Enddatum 31 März 2027

Finanziert unter

• Culture, creativity and inclusive society

Gesamtkosten

€ 2 994 403,75

EU-Beitrag

€ 2 994 403,75

Koordiniert durch

DIMOKRITIO PANEPISTIMIO THRAKIS
Greece

Periodic Reporting for period 1 - TRAILS (Enabling data analytics for actions tackling skills shortages & mismatch)

Berichtszeitraum: 2024-01-01 bis 2025-03-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The TRAILS project aims to deliver new insights and tools to bridge the gap between labour supply and demand by promoting shared awareness and co-development of skills tailored to the future needs of European labour markets:

TRAILS uniquely leverages novel, country-specific and employee-level datasets to generate new indicators and insights on key policy issues around skills mismatch, where current evidence is limited.

It creates new datasets on skill gaps, shortages, mismatch, and development to better evaluate solutions to persistent labour market challenges.

The project introduces advanced tools to estimate skills mismatch using Machine Learning (ML) applied to state-of-the-art matched employer–employee data.

It enhances skill profiling with Artificial Intelligence (AI), enabling real-time matching of workers to training and education opportunities, raising awareness of upskilling and career pathways.

TRAILS bridges theory, applied research, and skills policy through the active engagement of VET and adult learning (AL) authorities across Europe.

It offers evidence-based solutions to inform EU-level labour market policies and supports the implementation of the European Skills Agenda.

Despite growing attention to skills mismatch, several critical challenges remain:

Developing innovative metrics and classifications to measure mismatch and understand its origins and costs across diverse skill dimensions.

Combining diverse cross-country datasets in a harmonised way to better capture the scope and effects of skills mismatch.

Unpacking the links between different forms of mismatch, as addressing one may have spillover effects on others.

Using digital tools to enable real-time skill profiling and improve awareness of VET, AL, and informal learning opportunities.

Applying behavioural insights to understand how personal attitudes, gender stereotypes, and social or cultural factors influence VET and AL participation.

Creating a unified conceptual framework and analytical model to support the design of effective policy measures.

TRAILS contributes directly to 6 of the 12 actions outlined in the European Skills Agenda, including: the Pact for Skills, better skills intelligence, EU support for national upskilling initiatives, and advancing skills for the green and digital transitions.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

During the first reporting period (01/01/2024 – 31/03/2025), the TRAILS project made strong progress across key technical and scientific areas.

1. Three major survey instruments were designed: the General Population Survey, a Stated-Preference Survey, and a Platform Worker Survey. These aim to gather representative data on skills, training, and employment across the EU and nearby countries. Simultaneously, access to matched employer–employee datasets was secured in Sweden, the Netherlands, Italy, France, Portugal, Denmark, and Germany. Using Swedish data, a machine-learning indicator—Job Assignment Quality (JAQ)—was developed to assess the quality of job-worker matches at individual and firm levels.

2. Analysis of the European Skills and Jobs Survey (ESJS) assessed shifts in educational mismatch pre- and post-COVID-19. Vacancy data from 2019–2023 (Lightcast) was also examined to identify evolving skill demands, underscoring the growing importance of workforce adaptability.

3. A large-scale field experiment was launched in Tuscany, Catalonia, Borås, and Baden-Württemberg to test behavioural interventions encouraging unemployed individuals to pursue training. This included the use of behavioural "nudges" and AI-driven skill profiling, in cooperation with regional employment services and training providers.

4. The design and initial implementation of the TRAILS portal were completed. An early version was released, featuring interactive dashboards and data visualisations. Built for scalability and interoperability, the platform will integrate future analytical outputs and serve as a central hub for skills intelligence.

5. Using ESJS data (2014, 2021), the project explored how technology influences skill needs. Results showed targeted training can mitigate under-skilling and improve outcomes like wages and job satisfaction, reinforcing the importance of tailored learning paths.

6. Initial work began on a classification of basic and transferrable skills relevant to green and digital transitions. Using ESCO, early mappings of occupational skill profiles were developed. This also informed the analysis of how diversified skill sets contribute to mobility and resilience across labour markets.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Potential Contributions of the Project

1.TRAILS delivers high-resolution, real-time data on skills gaps and mismatches, enabling evidence-based decisions at EU, national, and regional levels.

2. Results from the field experiment and conjoint survey will guide the design of training offers tailored to individual motivations and market needs.

3. Findings on platform workers, gender, and regional disparities inform more inclusive policies, supporting social cohesion and the European Pillar of Social Rights.

4. AI-driven profiling and personalised skill-matching tools tested in field settings can help shape future digital services for job seekers.

Key Needs for Further Uptake and Success

1. Expanding experiments and data collection across more countries and groups is key to confirming and refining TRAILS' behavioural and ML-based tools.

2. Real-world trials with national employment agencies, VET bodies, and regional skills authorities are needed to operationalise TRAILS outputs.

3. Tools like the JAQ indicator have market potential. Clear IPR, licensing, and business models must be developed to enable exploitation.

4. TRAILS methods can extend beyond the EU. Cooperation with global partners (e.g. OECD, ILO) will support broader uptake and policy impact.

5. Ongoing training, dialogue, and capacity-building with VET providers, PES, and employers are essential for long-term tool adoption and use.