This chapter describes three opportunities for improvement and related recommendations for strengthening the governance of the Swedish skills system under Priority Area 3 “Improving the skills data infrastructure”, namely: Building a more user-orientated skills data infrastructure, Strengthening strategic co‑ordination and collaboration across the skills data infrastructure, and Improving understanding and co‑ordination of Sweden’s engagement with EU-wide skills data initiatives.
Strengthening the Governance of the Swedish Skills System
Final Report
Abstract
As skills systems advance and grow in complexity, the effective management of data and information becomes a critical policy concern. Establishing a robust framework for gathering, sharing and distributing skills data enhances the formulation of effective skills policies, which in turn promotes enhanced employability, use of skills, productivity and competitiveness. (OECD, 2019[1]).
In recent decades, huge strides have been made in the collection of data on labour demand and supply, skills needs, competency development, and mismatch in the labour market. New technology and analytical techniques offer rich insights on a range of issues relevant to the governance of skills systems, including the determinants of learning and employment trajectories, labour market transitions, and future skills needs (OECD, 2020[2]). Skills assessment and anticipation exercises have become particularly important, as global megatrends, not least the twin digital and green transitions, drive structural changes in the economy, labour market and skills requirements of many EU and OECD countries (ILO, 2017[3]; OECD, 2016[4]).
Accurate, timely and relevant labour market information (LMI) is important in supporting evidence-based policy making and in guiding the educational and occupational choices of learners. Embedding information on employment prospects, earnings, skills requirements and other features of work in different occupations within careers guidance can help steer individuals towards courses and careers that offer good employment prospects and align with their interests, aptitudes and abilities. At a macro-level, better aligning education and training decisions with labour market demand can help to reduce skills mismatches and shortages (Hofer, Zhivkovikj and Smyth, 2020[5]).
At the EU level, Action 2 of the European Skill Agenda considers that improving the skills intelligence is the basis for upskilling and reskilling, mentioning “graduate tracking surveys and administrative data matching, artificial intelligence and big data analysis” (European Commission, 2020[6]). The European Strategy for Data aims to create a single market for data that will ensure Europe’s global competitiveness and data sovereignty (European Commission, 2020[7]). The EU is currently undertaking work to develop and deploy a European Common Data Space for skills, which will provide a secure and trusted data space for the sharing of skills data.
Strengthening the skills data infrastructure will therefore be central to Sweden’s efforts to ensure an agile and responsive skills supply that supports improved job and education matching and careers guidance. Building integrated information systems is the third pillar underpinning strong skills governance arrangements, as identified by the OECD (see Chapter 1).
Sweden is taking active steps to support the development and management of an integrated skills data infrastructure. As mentioned previously, in 2021 the government tasked eight national agencies1 to work together to develop a coherent data infrastructure for skills supply and lifelong learning.
The task was structured around six sub-tasks: 1) developing common concepts; 2) developing secure methods for handling individual data; 3) developing a national database for publicly funded education; 4) making available data on all qualifications in the Swedish qualifications framework; 5) sharing data for strengthened innovation power; and 6) developing proposals for the development and management of the agencies’ cohesive data infrastructure in the future. The overarching goal of these sub-tasks was to strengthen the conditions for government agencies and other actors to create and provide digital services that strengthen the position of individuals in the labour market, while also meeting private and public sector skills needs (Government of Sweden, 2021[8]). The final report from the task was published in January 2024, setting out progress made against the sub-tasks and providing recommendations for ongoing work in a range of areas (discussed further below).
Background
Sweden continues to work to further strengthen its well-developed portfolio of high-quality, timely skills data. Details of the sub-tasks of the 2021 government task included strengthening the data infrastructure for lifelong learning through further development of the Swedish National Agency for Higher Vocational Education (Myndigheten för yrkeshögskolan, MYH) qualifications database and extending the information included in the ‑Susa Hub (see Box 5.1).
Developing the MYH qualification database
As part of the 2021 government task, the MYH was tasked with developing a qualifications database that can manage information about qualifications and components of qualifications (e.g. learning outcomes, sub-qualifications and classifications). The database has been developed and currently includes basic data on qualifications (SeQF, EQF level, content of the qualification in the form of learning outcomes, SSYK and/or SUN code, validity period, who is responsible for the qualification, etc.), as well as a user interface to search for qualifications hosted on the MYH website and an open API published on the data portal. The database currently includes information on non-formal qualifications and higher vocational education qualifications. Future work envisaged includes qualifications from primary school, secondary education and higher education. Data on qualifications is uploaded from the database to the Europass platform through the Qualifications Dataset Register, and uses the European Learning Model (ELM) as standard.
Expanding the Susa Hub
The Susa Hub aims to provide learners with a single source of information on all state-funded education, from school to university education. Susa is a collaboration between various actors, led by the Swedish National Agency for Education (Skolverket) and connected to the services of the Swedish Council for Higher Education (Universitets- och högskolerådet, UHR), MYH, folk high schools, and various providers of upper secondary education and adult training (komvux), from where data is automatically retrieved on a daily basis. Susa data is available to everyone, including public and private actors, who can build websites, apps and other services based on its content.
The 2021 government task worked to further extend the information included in the Susa Hub, including police education and labour market training, and to extend communication and marketing of the Susa Hub. Future work envisaged includes continuing to strive to include all publicly funded professional programmes and continuing education, more comprehensive information on study paths in upper secondary education, and ensuring comprehensive data on the focus of upper secondary education. There is also a need for ongoing active participation in the Swedish learning standard (EMIL) and to consider alignment with the EU’s ELM.
Note: Susa stands for “Samverkan Utbildningsinformation Skolverket – Arbetsförmedlingen” (Collaboration on Education Information Skolverket - Arbetsförmedlingen).
Source: Skolverket (2023[9]), Om Susa-navet [About the Susa Hub], www.skolverket.se/om-oss/oppna-data/utbildningar-som-oppen-data/om-susa-navet; Arbetsförmedlingen (2024[10]), Uppdrag att utveckla en sammanhållen datainfrastruktur för kompetensförsörjning och livslångt lärande: Slutredovisning [Mission to develop a cohesive data infrastructure for skills supply and lifelong learning], https://arbetsformedlingen.se/download/18.70846b5318d40100840663/uppdrag-att-utveckla-en-sammanhallen-datainfrastruktur-for-kompetensf%C3%B6rs%C3%B6rjning-och-livslangt-larande-slutredovisning.pdf; Europass (2024[11]), What is the Qualifications Dataset Register (QDR)?, https://europass.europa.eu/en/what-qualifications-dataset-register-qdr.
Improving data sharing2 between government agencies and with wider actors in the skills data infrastructure has also been a key area of focus and an important part of Sweden’s National Data Strategy (Government of Sweden, 2021[12]). Sweden benefits from strong conditions for data sharing. Co‑operation between government agencies is regulated by the Administrative Law (2017:900), and there are laws that require the public sector to make data available for reuse, especially in the form of open data (2022:818). Sweden’s common digital infrastructure, Ena, includes a range of building blocks in areas such as digital services, information exchange, information management, and trust and security. Sweden also has a range of taxonomies that promote common concepts and semantics, enabling data matching and promoting interoperability3 between systems, and supporting the customisation of digital services.
Sweden's Dataportal platform, managed by the Agency for Digital Government (Myndigheten för digital förvaltning, Digg), makes data visible from various agencies and organisations in Sweden (see Box 5.2). While the management and distribution of datasets are decentralised to their respective agencies, the Dataportal provides a central location for metadata describing the respective authority's datasets, APIs, conceptual structures and specifications.
Developed by the Digg in response to Sweden’s National Data Strategy, Sweden’s Dataportal aims to provide a unified platform for accessing public data. Its primary objective is to enhance transparency, stimulate innovation and promote efficient data use across sectors. The portal facilitates access to a vast array of datasets, fostering a data-driven culture that supports decision making in public administration, business and research.
The Dataportal offers a comprehensive suite of features to ensure data accessibility and usability. It includes a user-friendly interface with advanced search functionalities, allowing users to easily find relevant datasets. The portal supports various data formats, ensuring compatibility with different analytical tools. Metadata descriptions provide essential information about each dataset, including its source, format and update frequency. Additionally, the portal offers APIs for developers, enabling the seamless integration of data into applications and services. A collaboration space encourages data sharing and collaboration among different stakeholders, enhancing the portal’s value.
Digg works continually to review and enhance the Dataportal. In March 2024, significant improvements were made to the digital interface and new pages were added to improve understanding of the roles and responsibilities of different agencies. Links were also added to support, tools and training, good practice examples, and case studies illustrating the benefits and approaches to data sharing.
While the Dataportal currently focuses on open data, Digg intends to expand its focus to include promoting controlled data sharing and strengthen its role as National Single Point of Information, following implementation of the European Data Governance Act (2022).
Source: Digg (2024[13]), Sveriges dataportal för ökad innovationskraft (homepage) [Sweden's data portal for increased innovation], www.dataportal.se/.
The 2021 government task included work to ensure that all data sources relevant to skills provision and lifelong learning, and their various concepts, codes and specifications, are searchable via the Dataportal. It also included wider efforts to strengthen the conditions for data sharing. The Semantics project has started work on developing common concepts or translation keys between existing conceptual structures to enable the development of services for validation, matching and guidance. The Swedish Public Employment Service (Arbetsförmedlingen) has also led an exploration of secure methods for handling individual data, building on an earlier government task led by Digg exploring secure and efficient electronic information exchange in the public sector. While the solution initially considered was ruled out during the exploration process, the sub-task identified a range of important learnings to guide future work in this area, including the need to choose established technology that could complement Sweden’s existing digital infrastructure (Ena), and to monitor ongoing initiatives at the EU level (discussed further in Opportunity 8 below).
Issue
Despite recent efforts, there is scope to further strengthen the collection, exchange and dissemination of skills data in Sweden, and to sharpen focus on increasing the value of skills data for users. Figure 5.1 illustrates the benefits of such an approach.
The availability and accessibility of Sweden’s skills data is not always well-aligned to user needs
Building a more user-orientated skills data infrastructure is seen as a key priority for Sweden, and there is a range of areas where skills data is not fully meeting the needs of users. For example, where data is provided on a voluntary rather than mandatory basis, resultant datasets are only partial in their coverage and/or are not comprehensive. Consulted stakeholders highlighted a need for more granular data on the tasks and skills needs within occupations to better inform jobseekers of the skills needed by employers and the transferability of their skills to new professions. Ongoing work on the MYH qualifications database and Susa hub is also important to establish comprehensive national databases of all state-funded education and qualifications in the formal education system. Similarly, the inclusion of certificate and diploma supplements within Europass will strengthen information and improve international transparency on the knowledge and skills acquired through vocational training qualifications, better connecting learning outcomes with skills. However, there remain differences between the conceptual structures used to organise information and classify data on education (SeQF, SUN) and the labour market (SSYK, SNI), as well as with European Classification of Skills, Qualifications and Occupations (ESCO). This creates a divide between information on education and the labour market, and inhibits data matching, analysis and forecasting, as well as the quality of digital guidance.
There is scope to enhance the accessibility and navigability of skills information for users in Sweden. There are several alternative sources of labour market projections, underpinned by different forecasting methodologies, which can prove challenging for stakeholders in the skills data infrastructure who depend on this insight to inform service delivery, such as transition organisations. With the regions playing a more central role in aligning skills supply to regional labour market needs, there is a need to examine the adequacy and accessibility of more granular, regional skills data. There is also a range of different data portals that aim to provide information to support the learning or career choices of individuals, including Skolverket’s Training Guide (https://utbildningsguiden.skolverket.se/), the folk high schools searchable database (http://folkhogskola.nu/), MYH’s Higher Vocational Training platform (www.yrkeshogskolan.se/), UHR’s Study Now platform (www.studera.nu/) or various resources available from Arbetsförmedlingen.
In the OECD Digital Government Index 2023, Sweden ranks below the OECD average in the “user-driven” domain (29 out of 33 countries) and “proactiveness” domain (22 out of 33). There are many different users of skills data in Sweden – students, guidance professionals, education and training institutions, jobseekers, workers, employers, social partners, transition organisations,4 policymakers – who all require different types of information, at different levels of aggregation, presented in different ways. Some users will be technical experts able to process and analyse data and develop digital platforms and applications, while others will require data to be interpretated, contextualised and presented in a concise and accessible manner so that it can inform decision making and policy formation. Given these differences, countries need well-developed mechanisms for engaging with users so that they can better understand and anticipate their needs.
Awareness, membership and engagement with Sweden’s existing user forums can be limited
While there are some mechanisms to support engagement in Sweden, particularly with the analytical community (see Box 5.3), awareness of these forums is currently limited, and there is scope to consider how to expand engagement or membership. Sweden also needs stronger mechanisms for engaging with other users of skills data, particularly those who are not data analysts or enthusiasts, but who are dependent on evidence-based insights to deliver services or make decisions (e.g. career guidance professionals, transition organisations, employment support advisors, social partners, education and training providers, and the private sector). There is also a need to more effectively use policy forums (e.g. the MSV or the Network for Regional Skills Supply Work) as key vehicles for understanding the extent to which skills data is sufficient to inform evidence-backed policy making.
Sweden’s Data Portal Community Forum
Sweden’s Data Portal Community Forum aims to foster collaboration and knowledge sharing among users of the Swedish Dataportal and the wider data community. Managed by Digg, it promotes open data usage and digital innovation.
Key features include discussion threads on general topics, technical support and data requests. The forum also offers tutorials, guides, case studies and best practices for data management. It provides information on workshops, webinars, news and updates. Users can create profiles, network and collaborate on projects. The forum helps members stay informed, access expertise, solve problems and find partners for projects, enhancing their skills and contributing to Sweden's data-driven solutions.
SCB User Councils
Statistics Sweden’s (Statistiska Centralbyrån, SCB) User Councils aim to create a system of organised user contacts to continually provide SCB with knowledge about new and changing needs for official statistics, and to obtain the views of key users regarding changes in the statistics. There are currently 11 user councils, including those focused on labour market and education statistics.
The User Council for Labour Market Statistics is chaired by Riksbanken, the central bank of Sweden, and includes representatives from the Ministry of Labour and Employment, Ministry of Finance, Mediation Institute (Medlingsinstitutet), Swedish Trade Union Confederation (Landsorganisationen i Sverige, LO), Unionen, Swedish Confederation of Professional Employers (Tjänstemännens Centralorganisation, TCO), Swedish Industry (Svenskt Näringsliv), Work Environment Agency (Arbetsmiljöverket), Riksdag’s investigation service (Riksdagens utredningstjänst), Arbetsförmedlingen, Swedish Institute for Social Research (Institutet för social forskning, SOFI), Region Skåne, Swedish Confederation of Professional Associations (Sveriges akademikers centralorganisation, SACO), Swedish Agency for Government Employers (Arbetsgivarverket), Institute for Labor Market and Education Policy Evaluation (Institutet för arbetsmarknads- och utbildningspolitisk utvärdering, IFAU), Financial Management Agency (Ekonomistyrningsverket), and the National Institute of Economic Research (Konjunkturinstitutet).
The User Council for Education Statistics is jointly chaired by SCB, Skolverket, the Swedish Higher Education Authority (Universitetskanslersämbetet, UKÄ) and the Swedish Board of Student Finance (Centrala studiestödsnämnden, CSN). Wider members include the MYH, IFAU, Ministry of Education and Research, Swedish National Council of Adult Education (Folkbildningsrådet), Swedish Association of Universities and Colleges (Sveriges universitets- och högskoleförbund, SUHF), Swedish Association of Local Authorities and Regions (Sveriges kommuner och regioner, SKR), Tillväxtverket, UHR, and the Swedish Association of Independent Schools (Friskolornas riksförbund).
The Education Statistics User Council meets twice a year, with a rolling agenda that addresses data and statistics on particular subjects or themes. Materials are circulated ahead of meetings, enabling agencies to prepare and influence the agenda. Bilateral discussions also take place outside of council meetings, meaning that there is frequent dialogue between SCB and key users of official statistics. SCB also seeks feedback on the usefulness of council meetings, with members very positive about the functioning of the council and its value in providing input to shape official statistics, keeping abreast of developments and promoting engagement with other users of skills data.
Source: Digg (2024[14]), Community on Sweden's data portal, https://community.dataportal.se/; Statistics Sweden (2024[15]), User councils at Statistics Sweden, www.scb.se/en/About-us/main-activity/councils-and-boards/user-councils/#:~:text=Statistics%20Sweden%20(SCB)%20currently%20has%20eleven%20user%20councils; Bilateral interviews with stakeholders and analysis of User Council Meeting Minutes.
There is a need to improve data competence and strengthen the culture of data sharing in Sweden
Reorientating the skills data infrastructure around the needs of users will require increased information exchange between data owners to improve data comparability, promote data linking and matching, and enable data users to access information from multiple sources in one place. Sweden already has a legislative framework that promotes data sharing, and ongoing work to address technical obstacles to data sharing (e.g. to develop common concepts, translation keys and secure methods for transferring personal data) remains important. However, it is necessary to complement activities that seek to address technical obstacles with measures that strengthen the culture of data sharing between national agencies and other actors in the skills data infrastructure, including the private sector. While the exploratory work undertaken as part of the 2021 government task on building a coherent skill data infrastructure was reported to have improved knowledge of the technical issues and experience of the techniques needed to overcome them amongst those involved, consulted stakeholders emphasised the need to widen and deepen understanding and confidence in sharing data more widely across government. This includes building a stronger appreciation amongst staff of the value of data as an asset, the different categories of data, and the allowances and limits to sharing this information in a safe and legally compliant manner. As countries work to implement the European Governance Act (2022) there will be increased need for the Swedish government to take a more active approach to sharing data, including both restricted access to personal or sensitive data, and open data.
Summary
Building a more user-orientated skills data infrastructure is a key priority for Sweden, which already benefits from high-quality data on labour demand and supply. Despite recent efforts to strengthen data collection and sharing, there remains a need to improve the comprehensiveness and accessibility of skills data to meet the diverse needs of users. Enhancing engagement with stakeholders such as careers guidance professionals and the private sector is crucial for understanding and anticipating their data needs. By fostering better data comparability, linking and matching, Sweden can ensure that its skills data infrastructure supports informed decision making and policy development across the labour market.
Recommendations
Sweden should strengthen mechanisms for engaging with different user groups on an ongoing basis to improve the relevance, navigability and value of skills data for users. More specifically, it should develop and implement a plan to improve awareness and strengthen engagement with the Data Portal Community Forum as a key vehicle for open dialogue,5 particularly with the analytical community. This could include nominating a staff member within each national agency to act as lead contributor to the forum and take responsibility for posting relevant information such as recent data releases, development plans and events. Efforts to extend the portal’s content should be accompanied by communications activities to raise awareness of the forum amongst agency staff and wider stakeholders in the skills data infrastructure, aligned with Digg’s plans for promoting the Dataportal.
It will also be important for Sweden to use and expand forums for more active dialogue6 with different users of skills data, including the analytical community and wider users of skills data who may not be technical specialists or data enthusiasts, but who rely on data-based insights to inform service delivery or decision making. Sweden should undertake a review of the membership, mandate and promotion of existing forums for engaging with different user groups. The SCB’s User Councils for Education Statistics and Labour Market Statistics are particularly important in supporting ongoing dialogue with a range of stakeholders from across the skills data infrastructure. The review should weigh the merits of widening the membership of the councils and adapting the members invited to each meeting, depending on the themes or statistics being discussed. The councils should also consider expanding their terms of reference to include official statistics7 and other data of relevance to data users. In addition to the SCB user councils, Sweden should effectively engage with the Regional Network of Analysts (Reglab) to explore regional data issues. It should also use the MSV, National Arena for Skills Supply and the Network for Regional Skills Supply Work as key mechanisms for discussing the adequacy of skills data and priorities for strengthening data infrastructure with policymakers, stakeholders and the regions (respectively), as part of MSV’s annual priority-setting process (see Chapter 3).
Sweden should complement the ongoing dialogue facilitated by these forums with a rolling programme of surveys of users of specific data products and platforms, alongside targeted research to explore the needs of different user groups and the extent to which these are being met through existing skills data. Such a programme would offer the potential for deeper engagement with specific user groups, helping to understand specific use cases and the user experience in accessing and using the skills data they need. It would also enable a more detailed examination of specific data products or platforms, which could inform more detailed plans for their development. Such a combined approach has been adopted by Canada’s Labour Market Information Council (LMIC) to help it understand shared data challenges and inform a collaborative five-year strategy for the ongoing development of the LMI ecosystem (see Box 5.4).
Canada’s Labour Market Information Council (LMIC) plays a central role in improving the timeliness, reliability and accessibility of skills data across the country. LMIC is a non-profit organisation established in 2017 on the recommendation of Canada’s Forum of Labour Market Ministers – an intergovernmental forum that promotes collaboration and co‑ordination between government ministries and federal, provincial and territorial governments on national and regional skills issues.
In a complex LMI ecosystem with diverse stakeholders, LMIC acts a broker between various users and creators of skills data in Canada. The LMIC’s Board of Directors comprises 15 senior government officials representing each province and territory, plus Employment and Social Development Canada (a department of government) and Statistics Canada. To inform the direction, priorities and activities of the organisation, LMIC follows an extensive and ongoing process of engagement with wider stakeholders in the LMI system, including institutes, universities and colleges, research centres, charities and social enterprises, social partners, sector councils and associations, private sector businesses, and citizens.
Its work is guided by two forums: 1) the National Stakeholder Advisory Panel, which provides strategic recommendations on organisational priorities and projects; and 2) the Labour Market Information Expert Panel, which acts as a key resource for feedback, advice and guidance on research practices and methods.
To further understand the needs of LMI users, identify data gaps and shape priorities, LMIC and Statistics Canada have administered an online user survey to gather input from organisations and professionals with an interest in LMI. They have also undertaken targeted research to explore the challenges faced by particular user groups, such as career development professionals, in accessing, understanding and using skills data.
In addition to identifying improvements to datasets or digital platforms, this strong process of stakeholder engagement enables LMIC to articulate shared data challenges, for example a lack of local and granular LMI data, the use of traditional rather than innovative methods, a lack of consistency in the methodology for projecting future skills, data that is inaccessible or misaligned to stakeholder needs, LMI tools that do not meet the needs of end users, a lack of impact metrics for the LMI system, a lack of data on diverse population groups, and difficulties accessing and validating private sector proprietary data. These challenges then inform LMIC’s long-term strategic goals, as set out in its Strategic Plan 2021-2025, which are monitored on an ongoing basis through annual reports.
Source: LMIC (2023[16]) Perceptions of LMI: Feedback from the Canadian ecosystem, https://lmic-cimt.ca/perceptions-of-lmi-feedback-from-the-canadian-ecosystem/#toc2; LMIC (2024[17]) Navigating labour market information: Challenges faced by career development professionals, https://lmic-cimt.ca/navigating-labour-market-information-challenges-faced-by-career-development-professionals/.
Sweden should launch a multi-faceted upskilling programme to strengthen the capability and culture of data sharing across the Swedish government. This would have particular benefits for the skills policy field, where roles and responsibilities are distributed across a large number of national agencies, overseen by different ministries (see Chapter 3).
As part of the forthcoming Digitalisation Strategy, the Swedish government should task national agencies, working in partnership and with representatives of Swedish regions, with designing and implementing a major, multi-faceted upskilling programme to strengthen the data capabilities of all staff within ministries and agencies, regions and municipalities.
Resources and training provided by Digg should sit at the centre of this programme, particularly as the agency expands its focus to include promoting controlled data sharing (alongside open data) and strengthens its role as National Single Point of Information, following the implementation of the European Data Governance Act (2022). A central part of the programme would see national agencies with a mandate for skills supply working actively with Digg to deliver communications activities that raise awareness of the tools and support available, including “how-to” guides, webinars, online training and Digg’s frontline services that can offer customised advice on data sharing issues. Ministries, agencies, regions and municipalities should also nominate staff to join Digg’s Ambassadors programme,8 and ensure that they are sufficiently resourced to support knowledge sharing across their organisations, engage with wider stakeholders on data issues and become active contributors to Digg’s Dataportal.
Lessons from other countries, such as Australia’s Public Services’ Data Professional Stream Strategy (see Box 5.5), highlight the importance of defining the data capabilities required in roles across organisations – from basic data literacy to advanced digital skills – and offering development opportunities customised to these needs. As part of the upskilling programme, Sweden should embed data competencies within the job descriptions of public sector staff and require staff to complete the training needed to achieve these competencies as part of their learning and development plans.
Sweden should give particular attention to improving the skills of managers at varying levels within ministries and national agencies, actively engaging with Digg’s new “Data Lighthouse” concept9 for leaders (once launched) to strengthen understanding of the benefits of data sharing.
In addition to promoting engagement with Digg’s resources and training, the upskilling programme could feature peer-to-peer learning opportunities. Sweden could also explore the potential for challenge-based learning such as data sandboxes10 and hackathons, as well as pan-government awards and other initiatives that recognise and incentivise data sharing to support service improvements and positive societal outcomes. Such approaches are used successfully in other countries, including Australia (see Box 5.5) and the United Kingdom (see Box 5.6).
In summary, to enhance the relevance and usability of skills data, Sweden should strengthen mechanisms for ongoing engagement with different user groups. This includes improving awareness and participation in the Data Portal Community Forum and expanding forums for active dialogue with various users of skills data, including non-technical specialists. Complementing these efforts with surveys and targeted research will provide deeper insights into user needs and inform data infrastructure improvements. Additionally, launching a multi-faceted upskilling programme will strengthen data sharing capabilities across government, promoting a culture of data literacy and collaboration, and ensuring that the skills data infrastructure meets the evolving needs of its users.
The Australian Data Professional Stream Strategy was launched in 2020 following an independent review that found a need for the Australian Public Service (APS) to make better use of data in delivering public services.
The strategy recognises data as a strategic national resource and has advanced a series of measures to strengthen data capability across the APS to generate deeper insights, inform evidence-based decisions and enable more effective service delivery. A series of APS-led workshops were held with public agencies to understand priorities and objectives for the data professional stream. A Senior Reference Group and Senior Working Group were established, with members drawn from different agencies and across the data value chain tasked with developing and agreeing an initial two-year work programme.
The programme included initiatives to uplift data capability for existing APS employees, as well as professionalising the recruitment, development opportunities and career pathways for data professionals. Measures were targeted at all APS employees, managers and agencies, from foundation to advanced levels, in recognition of the critical role of data capability in the APS. Measures included the development of the following:
Data Capability Framework: Defines the data skills, knowledge and behaviour required to perform effectively in the APS. It offers clear and consistent language for use when discussing data capability needs, strengths and development opportunities, providing an important foundation for wider initiatives, including the development of a data capability assessment tool, job descriptions, learning and career pathways.
Data literacy: Development of a toolkit and suite of data literacy development options tied to data literacy learning pathways to uplift data capability across the entire APS workforce and develop a culture of data excellence.
Immersive learning: Including short-term and long-term mobility of data professionals across the APS to encourage the sharing of expertise and to grow data capability across agencies. Complemented the existing APS data fellowship programme to develop advanced data skills amongst data specialists.
Data professional network: Open to all APS staff in data roles to build professional capability through peer-to-peer learning. The network provides shared access to resources, promotes learning opportunities, identifies best practice and hosts events, including “hackathons” to tackle problems where sophisticated and innovative data use is key.
Co-design has been a key principle in the delivery of the strategy, with cross-agency collaboration and engagement taking place with different user groups, including senior managers, human resource professionals, data and non-data managers, and employees.
Source: Australian Government (2020[18]), APS Data Professional Stream Strategy, www.apsc.gov.au/publication/aps-data-professional-stream-strategy; Australian Government (2021[19]), APS Data Professional Stream Strategy Mid-point program report, www.apsc.gov.au/sites/default/files/2021-12/APS_Data_Professional_Stream_Mid_point_program_report_Septermber_2021.pdf.
Every year, as part of its Research Excellence Awards, the UK Office for National Statistics (ONS) selects around 250 projects that will be granted access to ONS secure data to support statistical research that delivers positive economic or societal outcomes. The awards recognise excellent, innovative analyses and best practice research methodologies deployed during these projects. They are designed to promote greater awareness and understanding of the data available, as well as of the public good that can be delivered from statistical research.
Categories and criteria vary from year to year. In 2022, there were five award categories: Research Excellence Award, Cross-government Analysis Award, Linked Administrative Data Award, Early Career Research Award, and the People’s Choice Award.
Award winners attend an official ceremony in London and are presented their awards by the National Statistician. Successful projects typically feature collaborative research and data linking to support a range of outcomes. For example, past projects have included informing control measures to mitigate the transmission of Covid-19, shaping targeted educational support for those with chronic health conditions, and determining departmental priorities to reduce reoffending.
Source: ONS (2024[20]), ONS Research Excellence Awards 2024, www.ons.gov.uk/aboutus/whatwedo/statistics/requestingstatistics/onsresearchexcellenceaward.
Strengthen mechanisms for engaging with different user groups on an ongoing basis to improve the relevance, navigability and value of skills data for users. Sweden should implement a plan to improve awareness and strengthen engagement with the Digg Data Portal Community Forum as a key vehicle for open dialogue. It should also undertake a review of the membership, mandate and promotion of existing forums for active dialogue with users of skills data, particularly the SCB User Councils and Regional Network of Analysts, and use the MSV, National Arena and Network for Regional Skills Supply Work as forums for engaging with policymakers, stakeholders and regions on data issues. Ongoing dialogue through these forums should be complemented with a rolling programme of user surveys and targeted research to examine the effectiveness of specific data products or platforms, and to explore the needs of different user groups.
Launch a multi-faceted upskilling programme to strengthen the capability and culture of data sharing across government. The Swedish government should task national agencies, working with representatives of Swedish regions, to design and implement this programme. Digg resources and training should sit at the centre of the programme, and national agencies with a mandate for skills supply should work with Digg to deliver communications activities that improve awareness and expand take-up. Ministries, agencies, regions and municipalities should nominate staff to join Digg’s Ambassadors programme, and actively engage with Digg’s new concept for leaders (Data Lighthouse) to strengthen understanding of the benefits of data sharing amongst managers. Sweden should also maximise opportunities for peer-to-peer learning and explore the potential for challenge-based learning (e.g. hackathons, awards) to strengthen incentives for data sharing.
Background
The governance of the skills data infrastructure in Sweden (as set out in the Mapping section) is complex, with responsibilities spread across multiple government agencies, levels of government and stakeholders. While this is the case in many EU and OECD countries, this complexity places emphasis on the strong management and organisation of constituent parts of the system that support the collection, sharing and dissemination of skills data.
Countries with well-developed labour market intelligence systems demonstrate a number of common features, including strong legal frameworks; clear designation of roles and responsibilities; explicit focus on the needs of stakeholders and end users; shared visions, strategies and work plans for the development of information systems, supported by long-term funding; and mechanisms that support collaboration and co‑operation between institutions at a strategic and operational level. This delivers a range of benefits, including improving the quality, coherence and value of skills data; promoting greater efficiency in its production; driving innovation through the pooling and sharing of data; and strengthening the translation of information into intelligence that can inform policy making (Barnes et al., 2023[21]).
In Sweden, national agencies have considerable organisational independence, and this extends to skills data. Despite being highly decentralised, the national statistical system in Sweden has been acknowledged for its high levels of trust and widespread culture of dialogue (European Commission, 2021[22]).
There are a range of mechanisms for promoting co‑ordination and collaboration between different actors in Sweden’s skills data infrastructure (Table 5.1). SCB co‑ordinates the system for official statistics, providing advice and support and promoting co‑operation between the agencies responsible for national statistics. It also operates wider co‑ordinating mechanisms, including the Council for Official Statistics, the Scientific Council and a range of User Councils, including those for education statistics and labour market statistics. Mechanisms for promoting collaboration on issues relating to skills data also include working groups on the analysis of skills data and forecasting, and integrating EU skills tools and initiatives into the Swedish skills system, which have been established under the MSV (discussed further below).
The Swedish government provides an additional steer to promote co‑operation between agencies in a range of areas relating to skills data. For example, The MYH has been tasked through their ordinance with directives to co‑operate with Skolverket, the Swedish Schools Inspectorate (Skolinspektionen) and the UHR in applying various EU tools to support the development of vocational training and mobility.
Source: Compilation by the OECD based on publicly available information and information shared by Sweden.
The 2021 government task sought to support the development and management of an integrated data infrastructure for skills supply and lifelong learning in Sweden. It required eight national agencies11 to work collaboratively in delivering its six sub-tasks.12 The government mandate also stated that the agencies must jointly submit a proposal for how the long-term development and management of a cohesive data infrastructure for skills supply and lifelong learning should be organised, including identifying which agency or agencies are best suited to co‑ordinate the management and development of the skills data infrastructure (Government of Sweden, 2021[8]).
In the final report from the government task, the agencies concluded that appointing a single agency responsible for promoting the management and sharing of data on competency development and lifelong learning would not promote the conditions for a coherent data infrastructure. Instead, they made a series of proposals for individual agencies and for a collaboration between agencies:
Individual agencies should prioritise data sharing to a greater extent than at present. This should include being able to demonstrate the prioritisation and resource allocation for the development of data in their business planning; promoting the use, processing and reuse of data (including as open data); working to make data searchable, accessible, compatible and useable via Sweden’s data portal, and communicate digital resources via the Data Portal’s community forum; and participating in the joint administration digital infrastructure for information (Ena).
Agency collaboration for competence supply and lifelong learning should be operationalised through a forum for co‑ordination around common needs and activities concerning data. This forum would be “instruction-driven”, thus enabling long-term agreements and commitments, and would enable wider collaborations with other agencies, businesses and organisations. The report identifies several MSV working groups where work on the data infrastructure could be appropriate, including Analysis, EU initiatives, and Validation and Guidance. It also suggests that alternatively a new group responsible for data infrastructure could be established.
Issue
Sweden benefits from a range of mechanisms to promote co‑ordination between different actors in the skills data infrastructure, such as the MSV Analysis Working Group or SCB’s Council for Official Statistics. The 2021 government task to develop a coherent skills data infrastructure has further strengthened collaboration between the national agencies involved and has clarified the benefits of collaboration where experiences are exchanged and common issues are addressed. Nevertheless, there remains scope to strengthen strategic co‑ordination and collaboration across the skills data infrastructure in a range of areas.
There is a lack transparency in the plans of national agencies regarding skills data and a lack of incentives for joined-up working
First, the system of governance in Sweden leads national agencies to prioritise resources towards delivering on appropriation directives (regleringsbrev) and tasks (regeringsuppdrag) from the government. National agencies responsible for the production and dissemination of skills data report to several different ministries (as detailed in the Mapping section), which could promote silo-based working and a focus on skills data and digital resources needed by individual agencies in delivering their day-to-day operations. In addition to the need for stronger prioritisation and resource allocation for the management, sharing, use and reuse of skills data (as envisaged in the final report of the 2021 government task), there needs to be greater transparency in the plans of national agencies regarding skills data and digital services, and stronger incentives for national agencies to find, understand and use the data of other agencies, or to consider how other actors may wish to use their data.
Sweden needs governance structures that promote ongoing development and management of skills data infrastructure over the long-term
Second, with the 2021 government task now complete, there are concerns that the momentum gained in recent years might be lost, slowing progress in a range of important areas, such as improvements to the quality and comprehensiveness of skills data and the technical foundations that support data sharing. A defining challenge relates to the governance structures that will promote ongoing co‑ordination and collaboration between different actors to develop and manage a coherent skills data infrastructure. There are benefits to positioning this function within the existing structure of the MSV with the establishment of the new MSV Data Infrastructure Working Group. For example, this could create a stronger link between the data needs of policymakers and other agencies working to promote a well-functioning supply of skills and the work programme of the group aiming to strengthen Sweden’s skills data infrastructure. During 2024, the WG appointed Arbetsförmedlingen and Skolverket as joint process owners, agreed its membership, set out its work plan for 2024, and is developing plans for initial engagement activities with key user groups. As this group becomes more established, and (as proposed in Chapter 3) potentially expands its remit to include the synthesis and analysis of skills data to inform MSV priority setting, there is a need to review its initial membership13 and formalise the process through which its annual work plan is set.
For the Data Infrastructure WG to provide the central function for the ongoing management and development of the skills data infrastructure, stakeholder engagement will be key. This is particularly important in the context of MYH’s 2024 appropriation directive directed at the MSV (as mentioned above), which states that the agencies must work to ensure that other relevant actors at national and regional levels are given the opportunity to contribute to collaboration for a well-functioning skills supply. While the WG seeks open dialogue with stakeholders through Digg’s Community Forum, and publishes all documentation on Arbetsförmedlingen’s GitLab, it will also be important to promote active dialogue with other actors in the skills data infrastructure. This builds on the initial events planned by the WG to develop a regular programme of engagement activities with a wide range of stakeholders in the skills data infrastructure, including research councils, universities, regions, wider members of the research community, and sector councils and other arenas (where they exist, such as the National Arena for Skills Supply). The private sector is also an important actor in the skills data infrastructure, with the 2021 government task emphasising the benefits of strong collaboration between public and private sector actors. Promoting greater dialogue and collaboration with actors outside of the data infrastructure for skills supply and lifelong learning is also seen as important for the further development of digital guidance and matching services, as wider information important for individual and region-based decision making (e.g. transport, childcare, housing) can be included.
Improvements to the skills data infrastructure will require technical expertise and a collaborative approach
Fourth, there are outstanding questions concerning the delivery of the priorities identified by the potential governance structure in charge of skills data. Lessons from the execution of the 2021 government task highlight the importance of openness, transparency and collaboration, as well as bringing together subject matter experts from across the skills data infrastructure, particularly when addressing technical issues. Those involved in the recent task emphasised the importance of clearly specifying, planning and adequately resourcing these activities.
Summary
The collection, analysis and dissemination of skills data in Sweden involve multiple actors, requiring strong governance, clear responsibilities and robust collaboration mechanisms. While existing structures such as the MSV’s working groups and SCB’s User Councils promote co‑ordination, there is a need for enhanced strategic oversight and transparency across agencies. The new MSV Working Group on Data Infrastructure has the potential to address these co‑ordination challenges, provided it reviews its membership and engages actively with wider stakeholders to inform its priorities and work plan. Fostering a collaborative environment based on the principles of openness and transparency will be crucial for effectively managing and developing Sweden’s skills data infrastructure.
Recommendations
First, Sweden should publish three-year data strategies to improve transparency and strengthen conditions for greater collaboration between agencies working to improve skills data. As part of the forthcoming Digitalisation Strategy, the Swedish government should task national agencies with producing three-year data strategies, setting out their aims, priorities, activities and implementation plans regarding skills data. These strategies should align with the planning processes of national agencies and reference the priorities set out in the European Strategy for Data (European Commission, 2020[7]).
Examples from other countries, such as Australia’s Department for Education (see Box 5.7), suggest that such strategies can be wide-ranging, spanning issues such as culture and leadership, governance, data infrastructure, analytics and visualisation, data sharing and use, and staff capability, often encompassing upskilling programmes similar to those discussed previously.
For Sweden, these data strategies provide an opportunity to respond to the recommendations of the 2021 government task, which called for national agencies to do the following: demonstrate the prioritisation and allocation of resources to support data sharing, including efforts to strengthen the knowledge and skills of staff (see Opportunity 6 above); promote the accessibility and value of their data for wider actors; and make effective use of the data of other national agencies and other stakeholders in the skills data infrastructure. The data strategies could also identify opportunities for engaging with EU-wide initiatives relevant to their mandate (see Opportunity 8 below).
Data strategies should be published on the website of individual agencies and communicated through relevant forums (e.g. the MSV Data Working Group, SCB User Councils, Reglab) and digital platforms (e.g. Digg’s Data Portal Community Forum). The MSV Data Working Group could review the data strategies published by national agencies, examining potential gaps and overlaps and identifying opportunities for collaboration and joined-up working (discussed further below).
The Department for Education’s Data Strategy 2023–25 sets the strategic direction for the department’s data capabilities, analysis, release and development, and is aligned with the Australian Data Strategy and reform agenda for the Australian Public Service.
The department’s data priorities focus on uplifting its data capabilities to support policy development and programme management. The strategy is structured around six focus areas: 1) culture and leadership; 2) governance; 3) data infrastructure; 4) analytics and visualisation; 5) data release, sharing and use; and 6) staff capability. For each theme, the department sets out the aims, vision (the “future state”) and implementation priorities for delivery in years one to three, and on an ongoing basis.
The department employs a “hub and spoke” model for data activities, where the Analysis, Data and Measurement Branch (the “hub”) acts as a centre for excellence for data management, data integration, data sharing, data analysis, data visualisation and education measurement, providing advice and support and connecting department staff with relevant experts in the department and across the public service. Individual data teams (the “spokes”) hold specialist data knowledge and skills, and collect, manage and analyse data.
A Data Working Group provides a collaborative forum to agree approaches to better use data to address policy and programme delivery issues, test ideas, take a whole-of-department and whole-of-government approach to data management and analysis, share information, and foster collaboration on key initiatives. It also guides the desired future state for data capability in the department, shaped by strategic policy issues and challenges. The Data Working Group reports biannually to the department’s Executive Board.
Source: Australian Government (2023[23]), Data Strategy 2023-25, www.education.gov.au/about-department/resources/data-strategy-2023-2025.
Sweden should position the reformed MSV Data WG (as discussed in Chapter 3) as a key forum for promoting the management, sharing and use of skills data. In the context of the complex skills data infrastructure in Sweden, and in the absence of a dedicated council or network charged with co‑ordinating its constituent parts, the MSV’s Data WG has a vital role to play in promoting the management, sharing and use of skills data. To enable the WG to fulfil this function, Sweden should widen its remit. As set out in Chapter 3, the WG could serve a dual purpose in aggregating and synthesising skills data, presenting a shared view of the most pressing skills supply issues to inform MSV decision making, while also identifying opportunities to improve skills data itself, identifying data gaps and strategic, collaborative projects that would strengthen the skills data infrastructure.
With this broader, more strategic remit, Sweden should review the membership of the MSV Data WG. In particular, SCB, Digg, Swedish Board of Student Finance (Centrala studiestödsnämnden, CSN) and Vinnova should be added as members. Although working across wider policy domains, these national agencies were involved in the 2021 government task to build a coherent data infrastructure, and their involvement would promote alignment between the priorities and activities of the national agencies responsible for skills supply and those charged with co‑ordinating the system of national statistics, promoting digitalisation and driving innovation (respectively). The MSV should also consider inviting the Swedish Board of Student Finance CSN to join the Data WG, given its responsibility for official statistics describing student financing and its role as co-chair of the SCB User Council for Education Statistics. Tillväxtverket will help to ensure that regional skills supply issues and data needs are sufficiently represented at the national level, particularly given its role in convening the Network for Regional Skills Supply Work. In addition to reviewing the organisational membership of the Data WG, Sweden should ensure that individual representatives offer the necessary expertise to deliver the Data WG’s stronger strategic role in providing insight for policymakers, identifying data gaps and strategic priorities, as well as projects to improve the skills data infrastructure.
The Data WG must retain its principles of openness and transparency, while also seeking out active dialogue with governmental actors and stakeholders from across the skills data infrastructure. It should build on initial workshops planned for its first year to develop a regular programme of engagement with different user groups and forums (see Opportunity 6 above). This would mirror the “network-orientated” approach seen in other countries when determining shared priorities and co‑ordinating activities to improve labour market information systems (see Box 5.8), without introducing additional structures to the already complex skills data infrastructure in Sweden.
The Jobs and Skills Network (Réseau Emplois Compétences, REC) is a joint initiative between the French government and social partners. It aims to strengthen collective capacity to understand and anticipate employment and skills needs in France.
Established as part of France Stratégie – an agency tasked with improving the co‑ordination of skills anticipation in France – REC aims to be:
A space for knowledge exchange, dialogue, and the sharing of analyses and experiences between those involved in analysing and forecasting jobs and skills at national, regional and sectoral levels.
A place for strengthening collective expertise in identifying the employment and skills needs of tomorrow, and supporting businesses, workers and those who represent them to adapt to these developments.
As a collaborative network, REC brings together a wide range of stakeholders, including government ministries, other public agencies (e.g. the National Employment Agency; the Directorate for Research, Studies and Statistics; the Centre for Studies and Research on Qualifications), employer associations, trade unions, universities and research institutes, regional councils, sectoral bodies, education providers, and civil society.
It also organises numerous webinars, workshops and conferences on relevant topics, conducts joint research, develops policy recommendations based on collective insight and analyses, and publishes a range of briefings and reports to disseminate findings to a broader audience. REC relies on the commitment of its members, and favours cross-disciplinary and exploratory approaches to create shared knowledge between a diversity of actors. It encourages innovative and partnership-based approaches.
Source: France Stratégie (2024[24]), Feuille de route 2024 du Réseau Emplois Compétences [Jobs and Skills Network 2024 roadmap], www.strategie.gouv.fr/actualites/feuille-de-route-2024-reseau-emplois-competences
The shared priorities and collaborative projects related to strengthening Sweden’s skills data infrastructure identified by the reformed Data WG should be presented to the MSV StG for approval. These would subsequently be discussed with the National Arena for Skills Supply and the Network for Regional Skills Supply Work, as part of the MSV’s priority-setting process, set out above (see Chapter 3).
Sweden should establish task forces in the MSV to deliver collaborative, strategic projects, selected through MSV’s annual priority-setting process (see Chapter 3), that strengthen Sweden’s skills data infrastructure. These time-bound task forces would support a more outcome-orientated approach. The establishment and workings of the task forces should follow the model described in Chapter 3.
It will be important to curate the membership of each task force to draw together required technical expertise from across the skills data ecosystem, including governmental actors and stakeholders and, where relevant, regions and the private sector. Convening outcome-orientated task forces comprised of specially selected teams of experts is an approach effectively used in other countries, particularly to support innovation, with one notable example being Germany’s Innovation lab for strategic forecasting and analysis (see Box 5.9).
In summary, Sweden should publish three-year data strategies to improve transparency and collaboration among agencies working on skills data, aligning these strategies with national planning processes and the European Strategy for Data. Expanding the remit of the MSV Data WG, and reviewing its membership to include key national agencies such as SCB, Digg, Vinnova, CSN and Tillväxtverket, will strengthen its role as a key forum for promoting the management, sharing and use of skills data. The WG should retain its principles of openness and transparency, while also extending active engagement with wider governmental actors and stakeholders when determining its priorities and work plan. Additionally, establishing task forces within the MSV to deliver strategic projects will support a more outcome-orientated approach, drawing on technical expertise from across the skills data ecosystem to drive innovation and improvements.
As part of its National Continuing Education Strategy (NWS), the German government established topic-orientated innovation laboratories and a working group, comprising a selection of government ministries, strategy partners and wider experts that offered the necessary blend of knowledge and expertise to develop concrete solutions and recommendations. These thematic laboratories covered four areas: 1) strategic foresight and analysis tools; 2) literacy and improving basic skills; 3) advisory structures in continuing education; and 4) quality assurance in continuing vocational training.
The Strategic Foresight and Analysis Innovation Lab sought to address action goal 10 of the strategy paper of the NWS: “to further develop the instruments for strategic foresight and to improve the information channels, particularly towards SMEs”. Under the leadership of the Federal Ministry of Labour and Social Affairs, a participatory process was set up with an alliance of NWS partners and other institutions, including national forums for ministers and senators, federal ministries, business associations, and trade unions. Membership was based on synergies and expertise. Participants agreed a detailed, outcome-orientated work plan comprised of four steps. Following these stages, the Innovation Lab drew conclusions and presented recommendations for ongoing work. Participants also made specific commitments to further progressing specific initiatives, often with other partners, nurturing a culture of ongoing collaboration.
Source: German Federal Ministry of Labour and Social Affairs (2021[25]), Themenlabore: Begleitpublikation zum Umsetzungsbericht der Nationalen Weiterbildungsstrategie [Thematic laboratories: Accompanying publication to the implementation report of the National Continuing Education Strategy], www.bmas.de/SharedDocs/Downloads/DE/Publikationen/a805be-final-report-innovation-labs.pdf?__blob=publicationFile&v=3.
Publish three-year data strategies to improve transparency and strengthen conditions for greater collaboration between agencies working to improve skills data. The Swedish government should task national agencies with producing these strategies, aligned with their planning processes and the (forthcoming) Digitalisation Strategy, and with reference to the EU Strategy for Data. The strategies should clearly demonstrate the prioritisation and allocation of resources to support data sharing between national agencies and with wider stakeholders. They should be widely disseminated, including through Sweden’s Data Portal Community Forum.
Position the reformed MSV Data Working Group as a key forum for promoting the management, sharing and use of skills data. As set out in Chapter 3, the reformed Data WG should have a dual mandate: compiling data analysis to inform the StG’s priority setting; and identifying data gaps, shared priorities and collaborative projects that would strengthen the skills data infrastructure. To enable the reformed Data WG to fulfil this broader, more strategic function, its membership should be reviewed and expanded, in particular to include SCB, Digg, Vinnova, CSN and Tillväxtverket, and to ensure individual representatives offer the necessary expertise. The WG should retain its principles of openness and transparency, while also developing a regular programme of active engagement with different user groups and policy forums to inform shared long-term goals and short-term priorities and collaborative projects.
Establish task forces in the MSV to deliver collaborative, strategic projects that strengthen Sweden’s skills data infrastructure. These time-bound task forces should be outcome-orientated, and the membership of the Task forces should be curated to offer the required breadth and technical competency, including governmental actors and stakeholders and, where relevant, regions and the private sector.
Background
Sweden’s efforts to promote a coherent skills data infrastructure coexist within wider EU initiatives in the areas of skills and digital transformation. In 2020, the European Commission launched the European Skills Agenda, which includes 12 flagship actions to enable individuals and businesses to develop more and better skills and drive the twin green and digital transitions. Action 2 concerns strengthening skills intelligence, where embedding robust skills data into national skills strategies and training and education systems supports skills supply that is relevant to the needs of the labour market. The action includes a range of measures, such as developing an online platform of real-time information on skills intelligence (Cedefop’s Skills-OVATE), and presenting skills information tailored to the needs of individuals in Europass, an EU-wide platform that enables individuals across Europe to develop CVs and search for courses and jobs across Europe (see Box 5.10).
Cedefop Skills-OVATE
Skills-OVATE offers detailed information on the jobs and skills that employers demand based on online job advertisements (OJAs) in 28 European countries. Users can access information based on millions of OJAs collected from thousands of sources, including private job portals, public employment service portals, recruitment agencies, online newspapers and corporate websites. Data is presented for the last four available quarters and is updated four times a year. Yearly averages are provided for key variables, supporting both up-to-date information and trend analysis. Skills-OVATE provides information on occupations (based on ISCO-08), skills (ESCO or O*Net) and regions (NUTS-2).
European Skills, Competences, Qualifications and Occupations (ESCO)
The ESCO classification identifies and categorises skills, competences, qualifications and occupations relevant for the EU labour market and education and training. It systematically shows the relationships between the different concepts.
Europass
Europass is an EU-wide platform that provides a range of skills information and resources for individuals. This includes tools to develop CVs and build a digital profile capturing skills, qualifications and experience. Users can also search for courses and jobs across the EU. Europass digital credentials provide a trusted, secure framework for recognising foreign qualifications across the EU. A key aim of Europass is to improve the transparency and comparability of the qualifications of European citizens, enabling their mobility in accessing opportunities across Europe.
European Learning Model
The European Learning Model (ELM) was developed by the European Commission to provide a framework for describing formal and non-formal learning opportunities, qualifications, accreditation and credentials, and to facilitate faster credential recognition and greater mobility of citizens in the European labour market. The ELM is multilingual and fully aligned with existing open frameworks and standards, including the European Qualifications Framework for Lifelong Learning (EQF) and ESCO. The ELM aims to address disparities in how nations describe learning, creating a single vocabulary that supports the recognition of qualifications and digital credentials across Europe and opens up new possibilities for skills data exchange and interoperability.
Source: Cedefop (2024[26]), Skills-OVATE, www.cedefop.europa.eu/en/tools/skills-online-vacancies; European Commission (2024[27]), About ESCO, https://esco.ec.europa.eu/en/about-esco; European Union (2024[28]), About Europass, https://europa.eu/europass/en/about-europass; European Union (2023[29]), Launch of the European Learning Model, https://europa.eu/europass/en/news/launch-european-learning-model.
There are also EU-wide initiatives to promote common concepts and a shared language around skills across Europe. For example, the European Skills, Competences, Qualifications and Occupations (ESCO) classification identifies and categorises skills, competences, qualifications and occupations relevant for the EU labour market and education and training, while the European Learning Model (ELM) aims to create a single language describing formal and non-formal learning (see Box 5.10).
Sweden is actively involved in many of these initiatives. For example, there is alignment between Sweden’s classification systems and those at a European level. SUSA hub and MYH qualifications database also supply data to the Europass platform, following EU-standards, and the Europass portal is searchable in Swedish.
Work underway as part of the European Strategy for Data and the Digital Europe Programme (DIGITAL) is also relevant to Sweden’s efforts to promote data sharing and the interoperability of systems. There have been a number of legislative reforms, such as the Data Act (2024), the Interoperable Europe Act (2024) and the Data Governance Act (2022), which provide the necessary legal provisions to facilitate data sharing, promote trust, and develop connected public services for businesses and citizens. SCB and Digg have been appointed as responsible agencies in Sweden under the European Data Governance Act (DGA).
There have been developments in the EU around common data spaces in strategic economic sectors and domains of public interest. Data spaces differ from open data portals in that they provide the secure infrastructure for a multitude of stakeholders to share their data under conditions that they themselves stipulate. As such, data spaces aim to promote the sharing and access of skills data for innovation purposes, supporting the development of new data-driven services, for example for validation, matching and guidance. Regarding skills, the European Commission has funded the EDGE Skills Project and Data Space for Skills project under the Digital Europe Programme (see Box 5.11).
To harness the value of data for the benefit of the European economy and society, the European Data Strategy set out plans to establish Common European Data Spaces in a number of strategic fields, including health, agriculture, manufacturing, energy, mobility, financial, public administration and skills. The intent is that these data spaces will be interconnected to form a single market for data.
The Common European Data Spaces will enable data from across the EU to be made available and exchanged in a trustworthy and secure manner. The data spaces will have a number of features, including: being open for participation by all organisations and individuals; having a secure infrastructure to pool, access, share, process and use data; and well-defined and trustworthy data governance mechanisms. A distinct feature of the data spaces is that data holders will determine the conditions through which their data is shared, including granting access to data and defining how it may be used. The data spaces are expected to provide a safe and reliable framework for the sharing of data for innovation purposes, supporting the development of new data-driven products and services in the EU.
While all European data spaces will share a common data infrastructure and governance framework, and the European Commission will provide a range of wider support, stakeholders in each sector will drive the evolution of the data spaces.
Two initiatives connected to the Common European Data Spaces are particularly relevant for skills:
The EDGE Skills Project was initiated to develop and deploy a cloud-to-edge infrastructure for education and skills capable of connecting services and data, enabling decentralised data sharing and making the data space infrastructure widely accessible. This project aims to create innovative building blocks to enable this decentralised infrastructure, and helps to finance sectoral use cases, demonstrating their value in solving real issues that organisations and people face.
Data Space for Skills with the completion of a 1-year preparatory phase (2022–23) which sought to prepare the ground for the development of an open and trusted European Data Space for Skills. This initial phase, DS4Skills, featured a number of work packages to define relevant data sources and map existing platforms and projects. It also developed a blueprint for the deployment of this data space in the future, with various conceptual approaches and options, as well as specific use cases. The European Commission subsequently issued an open call for the deployment of the European Data Space for Skills, which will develop a secure infrastructure and governance framework to enable skills data from across the EU to be shared in a secure and trustworthy manner, promoting innovation and the development of new data-driven products and services.
Source: European Commission (2024[30]), Common European Data Spaces, https://digital-strategy.ec.europa.eu/en/policies/data-spaces.
Issue
Sweden collaborates on a range of EU initiatives. Its National Data Strategy prioritises the country’s engagement with European common data areas as important mechanisms for improving data access, data sharing and co‑operation. The EU perspective was also explicitly integrated into the implementation of the 2021 government task to develop a coherent data infrastructure, for example in work to develop common concepts and standards for data exchange. Despite this, there remains scope in a range of areas to improve understanding and co‑ordination of Sweden’s engagement with EU-wide skills data initiatives as part of its wider commitment and activity within the framework of the EU’s Skills Agenda and the European Strategy for Data.
Stakeholders can lack detailed knowledge of EU skills data initiatives and their benefits
First, there is a need to strengthen understanding of different EU-wide initiatives. While stakeholders at the virtual workshop considered Sweden’s participation in EU initiatives to be important, and rated this highly during the interactive polling, further discussions revealed that many stakeholders lack understanding of the various initiatives at the European level, what they aim to achieve, how they relate to one another and why they are relevant to work being progressed to strengthen the skills data infrastructure in Sweden. Where this knowledge exists within agencies, it can sit in silos, for instance held by particular individuals or departments rather than widely understood by staff across the organisation. While some agencies benefit from international affairs co‑ordinators, who can build understanding and capacity to work in an international environment, these roles do not exist in all national agencies. Collaboration between individuals and agencies engaged in EU initiatives tends to happen on an ad hoc basis, with stakeholders also reporting a need for greater clarity in the extent to which other agencies and wider actors are engaging with EU projects.
Sweden lacks a consistent approach to prioritising and resourcing EU projects
Second, there is a need to strengthen the case for Sweden’s engagement in EU-wide initiatives. EU initiatives address many of the same challenges that Sweden faces in promoting a coherent data infrastructure for skills supply. For instance, the European Learning Model (referenced in Box 5.10 above) seeks to address disparities in how learning, qualifications and credentials are described to support data sharing and the interoperability of systems, which is also identified as a priority in Sweden. Ongoing work on the Common European Data Space for skills is developing use cases, governance frameworks and infrastructure to promote data sharing for innovation, which is another objective of Sweden’s 2021 government task. Sweden’s own efforts to develop common concepts and translation keys, and to examine methods for the secure transfer of sensitive data also provide valuable learning for other European nations with similar endeavours. More active participation could, therefore, promote shared problem solving and foster innovation in addressing the obstacles to the effective and impactful sharing of skills data. However, consulted stakeholders suggested that such initiatives were often deemed as largely technical exercises, with the potential benefits to Sweden of deep and sustained engagement not always clear. Ongoing work being led by Arbetsförmedlingen and Vinnova in developing use cases and drawing learning from data spaces in other sectors (e.g. health) will be important in promoting stronger engagement amongst Swedish stakeholders. However, Sweden lacks a consistent approach to building understanding of different EU initiatives and of the value of participation within and across national agencies. While there are several examples where engagement with EU initiatives has been determined a priority by ministries, stakeholders reported a need for greater clarity on the government’s position and ambition with regards to EU projects. There is also a need for greater transparency, structure and consistency in the processes through which different agencies prioritise and assign resources towards EU skills data initiatives.
Third, despite engagement with EU initiatives being identified as a key priority by the Swedish government, some national agencies report a lack of dedicated resources as a barrier to more active participation in EU skills data initiatives, with different budgets and capacities of government agencies seen as a key factor. Without clear mention in agencies’ appropriation directives and/or tasks from the government, resources are often allocated to the day-to-day activities of an organisation, and engagement with wider activities, such as EU initiatives, is often enabled through the allocation of short-term funding and/or the discretionary efforts of staff, which undermines the potential for Sweden to engage on a significant and sustained basis.
Summary
Sweden’s efforts to promote a coherent skills data infrastructure are aligned with the wider European Skills Agenda, the European Strategy for Data and the Digital Europe Programme. While Sweden collaborates on various EU initiatives, there is still room to improve understanding and co‑ordination of these efforts. Stakeholders often lack detailed knowledge of EU initiatives and their benefits, and engagement tends to be ad hoc. Additionally, a lack of dedicated resources and clear government direction hampers more active participation. Strengthening awareness, co‑ordination and resource allocation will enhance Sweden’s engagement with EU-wide skills data initiatives.
Recommendations
First, to ensure that Sweden can make a significant contribution to, and benefits from, the European Skills Agenda, there is a need to strengthen and promote greater consistency in the approach taken by national agencies to building understanding and prioritising engagement with EU skills data initiatives.
Sweden should establish a consistent structure for the management of EU data initiatives within national agencies. A relevant example from Spain is described in Box 5.12 below. In Sweden, all national agencies should have, as a minimum, an appointed international affairs co‑ordinator, promoting consistency in their roles and responsibilities and building their visibility within and beyond the agency.
International affairs co‑ordinators should serve a number of functions that would enable agencies to be more proactive in engaging with EU skills data initiatives, including:
Mapping EU-wide skills data initiatives, examining their relevance to the day-to-day operations of the agency, following the progress of these projects, identifying key milestones or decision points, and reviewing how peer countries are engaging with these initiatives.
Convening internal networks of agency staff working on international affairs to share experiences and approaches to engaging with EU initiatives, and developing a shared mission and aligned work plans that would support a co‑ordinated, agency-wide approach.
Working with governmental actors and stakeholders externally, including other government agencies, Vinnova, universities and private sector businesses, to further explore the strategic value of different initiatives, develop use cases, and shape partnerships and proposals.
Building a shared understanding across the agency of the purpose and value of different EU skills data initiatives, and Sweden’s strategic position in their regard. This should include developing resources and training for agency staff, aligned with wider efforts to strengthen data capability across the government (see Opportunity 6 above).
International affairs co‑ordinators should report on progress regularly and provide annual recommendations to the agency’s management boards on opportunities to strengthen engagement in EU-wide skills data initiatives, informing the agency’s annual planning process. Where EU-wide skills data initiatives are deemed a priority, agencies should appoint or nominate dedicated members of staff to co‑ordinate the agency’s response, including additional financial resources required to support initiatives within its annual budget demands to the government.
The Spanish Ministry of Education and Vocational Training has a dedicated unit responsible for analysing EU skills initiatives: the General Sub-Directorate of Territorial Co‑operation and Co‑ordination of High Inspection (Subdirección General de Cooperación Territorial y Coordinación de Alta Inspección). The unit has various responsibilities, including:
Monitoring EU education policies: Keeping track of developments in EU education policies and initiatives and assessing their implications for the Spanish skills system.
Co‑ordination of EU-funded programmes: Managing Spain's participation in EU education programmes such as Erasmus+ and ensuring effective implementation and co‑ordination of these programmes within Spain.
Analysis and compliance: Analysing the impact of EU directives and initiatives on the Spanish education system, and ensuring compliance with EU regulations.
Policy development: Shaping Spain's positions on EU education policies and advocating for Spanish interests within the EU framework.
Collaboration: Working with other EU member states and institutions to foster collaboration and alignment with broader European education goals.
The unit collaborates with other directorates within the Ministry of Education and Vocational Training, as well as with the Ministry of Science, Innovation and Universities; the Ministry of Foreign Affairs, European Union and Cooperation; and the Spanish Service for the Internationalization of Education, to co‑ordinate Spain’s participation in EU skills initiatives and ensure that their country’s skills system aligns with European standards. It also ensures that Spain benefits from EU initiatives and funding opportunities.
Source: State Agency Official Gazette, (2024[31]) , Real Decreto 274/2024, de 19 de marzo, por el que se desarrolla la estructura orgánica básica del Ministerio de Educación, Formación Profesional y Deportes [Royal Decree 274/2024, of March 19, developing the basic organizational structure of the Ministry of Education, Vocational Training and Sports], www.boe.es/buscar/act.php?id=BOE-A-2024-5482&p=20240320&tn=1#a2.
Finally, Sweden should position the MSV Data WG as a key forum for prioritising and co‑ordinating Sweden’s engagement in EU-wide skills data initiatives, where relevant to more than one agency. The benefits of engagement with EU skills data initiatives will often accrue to a wide range of beneficiaries, meaning that there will be a frequent need for national agencies to work collaboratively and to engage with wider stakeholders when assessing strategic value, prioritising and co‑ordinating engagement with different EU-wide skills data initiatives.
Sweden should position the MSV Data WG as a key forum to promote this co‑ordination and a place where members can discuss the mapping and recommendations presented by agencies’ international affairs co‑ordinators, determine shared priorities, and co‑ordinate Sweden’s engagement in EU-wide skills data initiatives.
An important first step will be for the agencies involved in the MSV Data WG to work together to establish a systematic process for reviewing and prioritising EU-wide data initiatives so that there is a consistent and transparent approach to determining the scale and extent of Sweden’s collective engagement. This could build on the approach used by the eight agencies involved in the 2021 government task when prioritising projects as sub-tasks. It should set out specific criteria (and associated weight) aligned to the strategic priorities of ministries and agencies, and determine the process through which EU skills data initiatives are evaluated.
While the MSV Data WG can provide an important mechanism for promoting consistency in the approach to assessing EU-wide skills data initiatives, it will be vital for this group to consult with wider governmental actors and stakeholders in the skills data infrastructure, particularly higher education institutions and businesses, to determine the collective value and potential use cases of these initiatives. This process should also support open discussion on which stakeholders are best placed to lead Sweden’s engagement, and the potential (high-level approach) and associated resource requirements. The MSV Data WG should provide a summary briefing on EU-wide developments to the MSV StG, including recommendations for priority initiatives that warrant significant and sustained engagement.
These recommendations could subsequently be discussed with wider stakeholders through the National Arena for Skills Supply and the Network for Regional Skills Supply Work (as per the MSV’s annual priority-setting process set out in Chapter 3), and could be taken forward either by task forces within the MSV or through partnerships that sit outside of the MSV, or even outside of government, led by higher education institutions, private sector organisations or public–private partnerships.
In summary, to enhance Sweden's engagement with EU skills data initiatives, national agencies should adopt a consistent approach by appointing international affairs co‑ordinators to build understanding and determine priority projects. The MSV Data WG should serve as a central forum for co‑ordinating and prioritising Sweden's involvement in EU-wide initiatives, where relevant to more than one agency, ensuring alignment with strategic priorities and promoting collaboration among agencies and stakeholders. This process should involve mapping relevant initiatives, sharing insights and establishing transparent criteria for evaluating and prioritising engagements. Regular briefings and consultations with the MSV StG, National Arena for Skills Supply and the Network for Regional Skills Supply Work will ensure that Sweden's engagement is strategic, well-co‑ordinated and effectively resourced.
Strengthen and promote greater consistency in building understanding and prioritising engagement with EU-wide skills data initiatives. Sweden should establish a consistent structure for the management of EU-wide skills data initiatives within national agencies. This should include ensuring all national agencies have appointed international affairs co‑ordinators with responsibility for mapping EU-wide skills data initiatives; building understanding of EU initiatives across the agency; making recommendations to the management board on priority projects; and engaging with external stakeholders to examine strategic value, develop use cases, and nurture partnerships and proposals.
Position the MSV Data WG as a key forum for prioritising and co‑ordinating Sweden’s engagement in EU-wide skills data initiatives, where they are relevant to more than one agency. The MSV Data WG should establish a systematic, shared process for reviewing and prioritising EU-wide skills data initiatives, including the criteria, weighting and process for evaluating initiatives of joint relevance. It should consult widely, including with stakeholders such as higher education institutions and private sector businesses, and present recommendations for priority initiatives that warrant shared action and significant and sustained engagement. Such initiatives could be taken forward by task forces within the MSV, or by partnerships outside of the MSV or government, including those led by higher education institutions, private sector businesses or public–private partnerships.
References
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[1] OECD (2019), OECD Skills Strategy 2019: Skills to Shape a Better Future, OECD Publishing, Paris, https://doi.org/10.1787/9789264313835-en.
[4] OECD (2016), Getting Skills Right: Assessing and Anticipating Changing Skill Needs, OECD Publishing, Paris, https://doi.org/10.1787/9789264252073-en.
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[9] Skolverket (2023), Om Susa-navet [About the Susa Hub], Swedish National Agency for Education (Skolverket), https://www.skolverket.se/om-oss/oppna-data/utbildningar-som-oppen-data/om-susa-navet.
[31] State Agency Official Gazette (2024), Real Decreto 274/2024, de 19 de marzo, por el que se desarrolla la estructura orgánica básica del Ministerio de Educación, Formación Profesional y Deportes, [Royal Decree 274/2024, of March 19, developing the basic organizational structure of the Ministry of Education, Vocational Training and Sports], https://www.boe.es/buscar/act.php?id=BOE-A-2024-5482&p=20240320&tn=1#a2.
[15] Statistics Sweden (2024), User councils at Statistics Sweden, https://www.scb.se/en/About-us/main-activity/councils-and-boards/user-councils/#:~:text=Statistics%20Sweden%20(SCB)%20currently%20has%20eleven%20user%20councils.
← 1. Swedish Public Employment Service (Arbetsförmedlingen); Swedish National Agency for Education (Skolverket); Swedish National Agency for Higher Vocational Education (Myndigheten för Yrkeshögskolan, MYH); Swedish Research Council (Vetenskapsrådet); Swedish Council for Higher Education (Universitets- och högskolerådet, UHR); Statistics Sweden (Statistiska Centralbyrån, SCB); Agency for Digital Government (Myndigheten för digital förvaltning, Digg); and the Swedish Agency for Innovation Systems (Verket för Innovationssystem, Vinnova).
← 2. “Data sharing” refers to the provision of data by the data holder, on a voluntary basis. It includes the re-use of data based on commercial and non-commercial conditional data-sharing agreements, as well as open data.
← 3. Interoperability refers to the ability of different digital services to work together and communicate with one another. The European Interoperability Framework identifies four layers to interoperability: 1) legal interoperability (e.g. the extent to which laws or regulations enable effective information exchange); 2) organisational interoperability (e.g. co‑operation between different authorities or agencies to support effective co‑ordination of activities and sharing of data); 3) semantic interoperability (common concepts or standardised categorisation of data elements); and 4) technical interoperability (the specifications, services and protocols that enable systems and services to communicate and connect with one another).
← 4. Sweden’s job transition organisations help those who have been dismissed or who have terminated a limited-term employment to find new work. They work on behalf of employers and unions, supporting workers through the transition process. They also offer those in employment an opportunity to strengthen their future position in the labour market through career and study guidance, and financial support during education.
← 5. Open dialogue refers to communication with all potential stakeholders, supporting transparency and inclusivity and fostering a collaborative environment where all voices are heard.
← 6. Active dialogue involves dynamic and engaging conversations with active participation, listening and responsiveness from all parties involved in the discussion, promoting mutual understanding and problem solving.
← 7. Official statistics are a special category of data regulated by law (Official Statistics Act 2001:99 and Official Statistics Ordinance 2001:100). These laws place specific requirements on the data with regards to its quality and accessibility.
← 8. Digg’s Ambassador programme is a digital education programme that includes recorded films, short texts, reading and knowledge tests to raise data sharing competencies. Digg Data Ambassadors are expected to spread knowledge further within their organisations.
← 9. Digg is introducing a new concept for leaders that aims to increase knowledge about data sharing and demonstrate the benefits of data sharing through various examples. This will include films featuring several leading representatives of the public sector talking about data as a strategic resource from different perspectives. The project was initiated as part of the 2021 government task to develop a coherent data infrastructure for skills provision.
← 10. Data sandboxes are secure, isolated environments where data can be safely analysed and tested without impacting wider systems. They facilitate experimentation, development and testing with controlled access and compliance.
← 11. Swedish Public Employment Service (Arbetsförmedlingen); Swedish National Agency for Education (Skolverket); Swedish National Agency for Higher Vocational Education (Myndigheten för Yrkeshögskolan, MYH); Swedish Research Council (Vetenskapsrådet); Swedish Council for Higher Education (Universitets- och högskolerådet, UHR); Statistics Sweden (Statistiska Centralbyrån, SCB); Agency for Gigital Government (Myndigheten för digital förvaltning, Digg); and the Swedish Agency for Innovation Systems (Verket för Innovationssystem, Vinnova).
← 12. Further information on the 2021 government task can be found in the final report (Arbetsförmedlingen, 2024[10]) and associated webinar (www.youtube.com/watch?v=5P5VoVRCGeY).
← 13. Initial membership of the MSV Working Group on Data Infrastructure includes Arbetsförmedlingen, Skolverket, MYH, UHR, the Swedish Research Council (Vetenskapsrådet) and the Swedish National Council of Adult Education (Folkbildningsrådet).