1. The need for more future-ready vocational education and training systems
This chapter describes how skill needs are changing due to factors such as the green and digital transition and population ageing, and how the COVID-19 pandemic further impacted labour markets and education systems. The chapter highlights how vocational education and training (VET) can play a key role in adapting to changing skill needs and preparing individuals for the labour markets and societies of the future. Lastly, the chapter describes the key dimensions of future-ready VET systems that are the focus in the remainder of this report.
Structural changes in labour markets and societies have changed skill needs. Certain types of jobs no longer exist, new ones have emerged, and continuing roles have changed considerably. As such, some skills have become less in demand and others have seen increased demand, and the way in which certain skills are used and the combination of skills required in various jobs has changed.
One of the structural changes that has impacted labour markets and societies strongly in recent decades and is expected to continue to have an impact is the digital transition. Literature on job polarisation has shown that jobs that are intensive in routine tasks have seen a reduction in their employment share compared to less routine jobs. These jobs were mostly concentrated in the middle of the skills contribution, and as such automation has contributed to what has been referred to as a hollowing out of the occupational structure (Goos, Manning and Salomons, 2014[1]; Goos, Manning and Salomons, 2009[2]; Autor and Dorn, 2013[3]). A 2018 OECD study (Nedelkoska and Quintini, 2018[4]) estimated that 14% of jobs in OECD countries had a high risk of automation -meaning that they could disappear altogether - and an additional 32% could see significant changes in their task composition due to automation. The jobs most like to be impacted by automation were found to be at the lower-end and the middle of the skills distribution.
More recent analysis that takes into account recent advances in artificial intelligence (AI) shows that the set of skills and abilities that can be replicated by automation technologies has broadened (Lassébie and Quintini, 2022[5]). It finds that some skills and abilities previously identified as bottlenecks to automation are now more susceptible to automation, like for example the knowledge of fine arts, several psychomotor abilities (the ability to work in cramped workspace and awkward positions, finger dexterity, and manual dexterity), reading comprehension, deductive and inductive reasoning skills, fluency of ideas and scheduling skills. However, there remains significant bottlenecks to automation. In particular, skills related to complex problem-solving, high-level management and social interaction can hardly be automated given the current state of technological developments. As these bottleneck skills are most strongly concentrated in high-skill jobs (Figure 1.1), the occupations at highest risk of automation remain essentially low-skilled - even if AI increasingly allows automating certain skills and abilities required in high-skilled occupations. However, also certain occupations that are typically classified as low- or middle-skill have a large share of bottleneck skills, e.g. personal care, service, sales.
Note: Share of bottleneck and highly automatable items among important items by occupation (SOC 2 digits), where important items are skills and abilities with importance values strictly higher than three. See Lassébie and Quintini (2022[5]) for details.
Source: OECD calculations based on OECD Expert Survey on Skills and Abilities Automatability and O*NET.
At the same time, digitalisation also leads to job creation. In fact, evidence suggests that job creation has exceeded job destruction (Autor and Salomons, 2018[6]). However, the jobs that are being created have a very different profile from the jobs that disappear due to automation. Therefore, those who have lost their job are likely to need substantial reskilling to move into these new types of jobs. Across OECD countries on average 49% of jobs are in sectors with medium-high or high levels of digital intensity. This ranges from 42% in Iceland to 57% in the Netherlands (Figure 1.2).
Note: Digital intensity is defined according to the taxonomy described in Calvino et al. (2018[7]).
Source: The OECD Going Digital Toolkit, based on the OECD Structural Analysis (STAN) Database, http://oe.cd/stan and the OECD Trade in Employment Database, http://oe.cd/io-emp.
Another important trend that is contributing to changing skill needs is the green transition. As societies move to greener consumption and production patterns, this changes the sectoral and occupational composition of the labour market and the skill content within occupations and sectors. For example, jobs in carbon-intensive industries will likely decline as a consequence of those shifts, while new jobs will be created in sectors related to green energy. The skill requirements in both types of sectors are likely very different. Likewise, workers in car maintenance and repair require a different set of skills when working on electric cars than when working on combustion-engine cars. Forthcoming OECD analysis (OECD, forthcoming[8]) estimates that structural transformations needed to meet the EU Fit for 55 policy targets1 lead to an employment increase of 1.3%, with a decrease in employment for blue collar and farm workers of 3% and an increase for other categories of between 4% and 5%. Many of the skills that are projected to face the strongest increase in demand relate to inter-personal communication and the use of digital technologies, whereas skills related to the use of tools and technologies adopted in traditional manufacturing processes are found on the other end of the spectrum.
These structural changes put the importance of lifelong learning at the forefront. This is reinforced by the fact that populations are ageing and staying longer in the labour market. Indeed, the old-age dependency ratio (i.e. the number of individuals aged 65 and over per 100 people of working age - defined as those at ages 20 to 64) has increased to 33% in 2023 across OECD countries (11 percentage points higher than in 2000) and is projected to reach 53% by 2050 (OECD, 2023[9]). Retirement ages have been increased in many OECD countries. In addition to creating a strong need for lifelong learning opportunities, population ageing also changes the demand for certain goods and services (e.g. related to health and social care) - which in turn impacts skill needs in the labour market.
All of these changes have contributed to skills imbalances around the world. Many employers struggle to find workers with the right skills. For example, across EU countries 61% of firms reported in 2022 that the availability of staff with the right skills is a major obstacle for their investment activities (European Investment Bank, 2023[10]). According to the 2023 Manpower Global Talent Survey 77% of employers worldwide report difficultly in filling roles (ManpowerGroup, 2023[11]). The most in-demand technical skills reported by employers are IT and data, engineering, and sales and marketing. The soft skills reported most in demand are reliability and self-discipline, creativity and originality, and critical thinking and analysis. According to the OECD Skills for Jobs database, shortages of medical knowledge and training and education skills are substantial across the 43 countries included in the database (OECD, 2022[12]). These two areas have been facing large and increasing shortages for the past eight years, pointing towards a structural problem of under-supply.
In light of these continuing changes in skill needs and already prevailing skill shortages, it is of crucial importance that education and training systems adapt in order to ensure that young people and adults have the skills needed to be successful in today’s and tomorrow’s labour markets and societies. This will require updating initial education and training programmes so that they prepare young people for these new realities, both in terms of equipping them with a set of transversal skills that make them adaptable and resilient in light of changes and in terms of developing the technical or occupation-specific skills that are in demand. Moreover, these changes call for investment in lifelong learning – as individuals will need to continue to invest in their skills also after leaving initial education. Evidence from OECD countries shows that only about four in ten adults participate in training, and that this share is lower among those who may need training the most, like adults with low levels of educational attainment, older adults, and workers in jobs most exposed to automation (OECD, 2019[13]).
The COVID-19 pandemic disrupted societies, labour markets and education systems around the world. It brought several vulnerabilities to the forefront, and highlighted that not all population groups are equally resilient in light of unexpected changes. For example, young people were particularly badly hit by labour market disruptions, as school-to-work transitions were more difficult, they were more strongly concentrated in sectors that were impacted by job loss and less exposed to teleworking opportunities, and the prevalence of temporary work among youth provided less stability for them. In education, all countries faced school closures and resorted to distance learning opportunities, but not all learners had equal access to digital tools to make the most of these distance learning solutions. Certain parts of the education system faced particular challenges, as was the case for VET where distance solutions for practice-oriented learning were not readily available and workplace learning opportunities were reduced (OECD, 2021[14]).
The pandemic and ensuing recovery also accelerated some of the ongoing structural changes discussed above. Digitalisation took an important leap forward, for example through increased teleworking. The pandemic also gave an impulse to the green transition, with many countries highlighting that the recovery from the pandemic should be a green recovery. At the same time, the pandemic (as well as recent geopolitical instabilities) highlighted value chain vulnerabilities that have made countries reflect on their economic structures and the related skill needs.
In education systems as well, the pandemic gave an impetus for change. An increased reliance on online teaching and learning highlighted the role that digital technologies can play in the education system. While there is still a lot to learn about what works and the enabling factors, there is clearly a lot of potential. At the same time, increased use of digital technologies risks exacerbating already existing inequalities in access to (quality) education – as not all learners and schools/providers will have equal access to technology or to the same quality of digital materials. The recent experiences have also highlighted the importance of investing in the skills of teachers and trainers so that they can make effective use of digital technologies in their practice.
In light of the changes presented above, VET could play a key role in ensuring that young people and adults have the skills that societies and labour markets require today, but also in the (near) future. At the same time, VET can equip people with the transversal skills needed to adapt to changing circumstances.
VET plays an important role in education and training systems around the world. Across OECD countries, 42% of learners in upper-secondary education are enrolled in vocational programmes (Figure 1.3). This goes up to 70% in countries like Czech Republic, Finland, and Slovenia. In the majority of countries the shares are slightly lower when focusing on the age group of 15- to 19-year-olds only, as adult learners also enrol in VET. In most countries adult enrolment in upper-secondary VET programmes is limited (as described below and in Chapter 3), but in some countries these programmes mostly cater to older learners as VET is considered mostly as a post-school option (e.g. in Ireland)). Also at the post-secondary level, various countries have a large professionally-oriented sector, including short-cycle tertiary programmes and professional bachelor programmes. Countries with low VET enrolment at the upper-secondary level often have focused their provision of VET at post-secondary levels, like for example in Canada and the United States.
Note: In Italy, upper secondary vocational programmes include post-secondary non-tertiary programmes.
Source: OECD (2020[15]), Education at a Glance 2020: OECD Indicators, https://dx.doi.org/10.1787/69096873-en.
On average, young people with VET qualifications have relatively strong labour market outcomes, especially at the start of their careers (Figure 1.4). Across OECD countries, individuals aged 25 to 34 who have an upper-secondary vocational qualification as their highest qualification have employment rates that are substantially higher than those with a general qualification at the same level and those without an upper-secondary qualification. Their employment rates are fairly close to those of individuals with higher levels of educational attainment. These average employment rates mask substantial differences between countries. Even within countries there will be differences between graduates from different fields of study and different programme types (e.g. apprenticeship vs. school-based programmes).
The employment rate advantage is smaller for older age groups, but nonetheless remains (Figure 1.4). OECD (2020[16]) confirms this pattern when comparing individuals with similar skill levels and other personal characteristics: the gap in employment rates between those with vocational and general upper-secondary qualifications disappears by age 45, while individuals with VET qualifications maintain their advantage relative to those without upper-secondary education in all age groups. Individuals with tertiary education degrees have higher employment rates than all other education groups at all ages. A similar picture is found for unemployment rates, although here the gap between individuals with vocational and general upper-secondary qualifications already disappears for the 35-44 age group. Similar patterns have been found by Brunello and Rocco (2017[17]), Forster, Bol and van de Werfhorst (2016[18]), Hanushek et al. (2016[19]), and Rözer and Bol (2019[20]).
Note: The share of adults with a given educational attainment varies across age groups.
Source: OECD (2020[15]), Education at a Glance 2020: OECD Indicators, https://dx.doi.org/10.1787/69096873-en.
As discussed by Rözer and Bol (2019[20]), lower long-run returns to VET could be caused by several mechanisms: i) VET preparing students for employment in manual and craft jobs that have limited potential growth opportunities; ii) VET graduates mostly having job-specific skills rather than transferrable skills; and iii) VET graduates participating less in on-the-job training, making them less flexible in light of structural or technological changes. OECD (2020[16]) finds that the jobs held by young adults with upper-secondary vocational qualifications are relatively strongly exposed to automation, especially when compared to the jobs held by tertiary education graduates. As discussed above, even if recent advancements in AI have meant that certain tasks in high-skill jobs are now also automatable, the largest risks are still found in occupations at lower skill levels – including many occupations typically targeted by VET, such as production, construction and transportation (Figure 1.1). However, various typical VET occupations are also among the occupations that remain difficult to automate, including personal care and service occupations. As such, it is important for VET to be responsive and adapt to changes observed and expected in the labour market, including those caused by automation. Moreover, as labour markets continue to change and certain jobs may disappear or alter significantly, VET needs to prepare individuals to be adaptable.
For individuals to be able to adapt to change once they are in the labour market, they need access to opportunities for upskilling and reskilling. VET could play an essential role in this respect, as it can provide adults with labour market relevant training that leads to widely recognised formal qualifications. Nonetheless, VET systems in most countries predominantly focus on young learners in initial education. While such programmes are often open to older learners, they may not be well aligned with the needs and preferences of this age group. Figure 1.5 shows that in many countries relatively few adults participate in upper secondary VET - with an OECD average of 17%, and fewer than 5% of older students in 14 out of 34 countries. In countries like Ireland and New Zealand the very high share of older learners reflects the fact that VET is predominantly a post-school option, whereas the relatively high shares in Denmark and Finland show that VET can serve young and adult learners at the same time. At the short-cycle tertiary level, which has predominantly vocationally or professionally-oriented programmes, the share of older learners differs strongly between countries - with countries like France, Korea, Mexico and Portugal having at most 15% of learners aged 25 or older compared to at least 70% in Iceland, Poland, Sweden and Switzerland. However, these programmes are relatively small in many countries (see Chapter 2). In countries with low enrolment of adults in VET programmes, adult learning may predominantly be in non-formal training or in academically-oriented formal education and training programmes (e.g. higher education delivered by universities).
Note: Data for Belgium (French Community) in Panel B exclude participants in adult higher education.
Source: OECD (2020[15]) Education at a Glance 2020: OECD Indicators, https://dx.doi.org/10.1787/69096873-en (Panel A); OECD (2022[21]), Pathways to Professions: Understanding Higher Vocational and Professional Tertiary Education Systems, https://doi.org/10.1787/a81152f4-en (Panel B).
As such, VET has the potential to prepare young people for the labour market and to support adults in their upskilling and reskilling, but it may require re-engineering on various fronts to achieve that potential. Firstly, VET will need to stay relevant in light of changing skill needs in labour markets and societies. This will require aligning the offer and content of programmes with employer requirements, but also giving sufficient opportunities for learners to develop the transversal skills need to be adaptable. Secondly, VET needs to be a vehicle for lifelong learning, both in terms of offering programmes that are accessible and relevant for adult learners and in terms of providing effective pathways for learning after VET. Such a re-engineered VET system should be underpinned by solid career guidance efforts that help young people and adults navigate change and find their way into VET. It should also be coupled with efforts to make the VET system inclusive, so that it is an attractive and accessible option for learners from various backgrounds and with different needs and aspirations. These re-engineering efforts could be supported by increased technology use in VET, which has the potential to make VET more accessible, attractive, effective and efficient.
This report looks at different elements of future-ready VET systems, focussing on responsiveness, flexibility and inclusion, supporting transitions, and innovation. For each of these dimensions, the report presents a set of key questions that policymakers and other VET stakeholders should consider when re-engineering VET to make it more future-ready. While the report does not aim to come up with one particular answer or solution for these questions - and different VET systems will require different approaches - it provides an overview of data and evidence that highlight the importance of the questions for the future of VET and describes a large range of policies and practices put in place in OECD countries and beyond to move towards more future-ready VET systems.
The four dimensions and the corresponding key questions are presented below. Each dimension is explored in detail in the remaining chapters of this report.
Creating responsive VET systems
To ensure that VET programmes remain relevant for learners and employers in a changing world of work, they need to be aligned with labour market needs. VET programmes could be provided at various levels of education, including at the tertiary level, and in a variety of fields. The use of high-quality information on skill needs, based on a range of data sources and stakeholder inputs, is crucial in the design of responsive VET systems. Moreover, strong engagement with social partners in the different phases of VET policy can contribute to ensuring that relevant and up-to-date programmes are provided. Information on skill needs should also be used to inform skills development opportunities for VET teachers.
Making VET more inclusive through increased flexibility
VET can play an important role in providing training opportunities to a broad audience. Therefore, sufficient flexibility is needed to ensure that students with different personal characteristics, needs and aspirations can have access to VET programmes that are tailored to their needs. In light of changing skill needs, VET can foster lifelong learning by providing accessible and relevant opportunities for up-skilling and re-skilling to adults.
Key questions for designing flexible and inclusive VET systems include:
Supporting transitions
A changing world of work implies that individuals will need to be able to adapt to change throughout their working lives. Ensuring that initial VET students leave the education system with strong foundational skills will be important to ensure that they can successfully engage in further learning to keep their skills up to date. Moreover, strong transversal skills will help VET graduates be resilient and adaptable. To ensure that individuals can navigate a changing labour market and are able to find VET programmes that suit their needs, solid career guidance is essential.
Key questions for designing VET systems that support transitions into the labour market and further learning include:
Innovating in VET
The use of new teaching and learning methods can support the effective delivery of VET. This includes the use of new technologies, such as simulators and virtual reality, in classrooms and in workplaces, but also the use of innovative pedagogical approaches. Such innovation requires strong leadership in VET institutions, well-trained VET teachers, and strong coordination with the world of work.
References
[3] Autor, D. and D. Dorn (2013), “The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market”, American Economic Review, Vol. 103/5, pp. 1553-1597, https://doi.org/10.1257/aer.103.5.1553.
[6] Autor, D. and A. Salomons (2018), “Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share”, Brookings Papers on Economic Activity, Vol. 49/1, pp. 1-87.
[17] Brunello, G. and L. Rocco (2017), “The Labor Market Effects of Academic and Vocational Education over the Life Cycle: Evidence Based on a British Cohort”, Journal of Human Capital, Vol. 11/1, pp. 106-166, https://doi.org/10.1086/690234.
[7] Calvino, F. et al. (2018), “A taxonomy of digital intensive sectors”, OECD Science, Technology and Industry Working Papers, No. 2018/14, OECD Publishing, Paris, https://doi.org/10.1787/f404736a-en.
[10] European Investment Bank (2023), EIB Investment Survey: Tracking investment needs and constraints across Europe, https://data.eib.org/eibis/graph.
[18] Forster, A., T. Bol and H. van de Werfhorst (2016), “Vocational Education and Employment over the Life Cycle”, Sociological Science, Vol. 3, pp. 473-494, https://doi.org/10.15195/v3.a21.
[1] Goos, M., A. Manning and A. Salomons (2014), “Explaining Job Polarization: Routine-Biased Technological Change and Offshoring”, American Economic Review, Vol. 104/8, pp. 2509-2526, https://doi.org/10.1257/aer.104.8.2509.
[2] Goos, M., A. Manning and A. Salomons (2009), “Job Polarization in Europe”, American Economic Review, Vol. 99/2, pp. 58-63, https://doi.org/10.1257/aer.99.2.58.
[19] Hanushek, E. et al. (2016), “General Education, Vocational Education, and Labor-Market Outcomes over the Lifecycle”, Journal of Human Resources, Vol. 52/1, pp. 48-87, https://doi.org/10.3368/jhr.52.1.0415-7074r.
[5] Lassébie, J. and G. Quintini (2022), “What skills and abilities can automation technologies replicate and what does it mean for workers?: New evidence”, OECD Social, Employment and Migration Working Papers, No. 282, OECD Publishing, Paris, https://doi.org/10.1787/646aad77-en.
[11] ManpowerGroup (2023), The talent shortage, https://go.manpowergroup.com/talent-shortage.
[4] Nedelkoska, L. and G. Quintini (2018), “Automation, skills use and training”, OECD Social, Employment and Migration Working Papers, No. 202, OECD Publishing, Paris, https://doi.org/10.1787/2e2f4eea-en.
[9] OECD (2023), OECD Pensions Statistics, https://doi.org/10.1787/pension-data-en.
[21] OECD (2022), Pathways to Professions: Understanding Higher Vocational and Professional Tertiary Education Systems, OECD Reviews of Vocational Education and Training, OECD Publishing, Paris, https://doi.org/10.1787/a81152f4-en.
[12] OECD (2022), Skills for Jobs 2022: Key insights, OECD, Paris, https://www.oecdskillsforjobsdatabase.org/data/S4J2022_results.pdf.
[14] OECD (2021), Implications of the COVID-19 Pandemic for Vocational Education and Training, OECD Publishing, Paris, https://doi.org/10.1787/55afea00-en.
[15] OECD (2020), Education at a Glance 2020: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/69096873-en.
[16] OECD (2020), OECD Employment Outlook 2020: Worker Security and the COVID-19 Crisis, OECD Publishing, Paris, https://doi.org/10.1787/1686c758-en.
[13] OECD (2019), Getting Skills Right: Future-Ready Adult Learning Systems, Getting Skills Right, OECD Publishing, Paris, https://doi.org/10.1787/9789264311756-en.
[8] OECD (forthcoming), OECD Skills Outlook 2023: Skills for Recovery and Resilience, OECD Publishing, Paris.
[20] Rözer, J. and T. Bol (2019), “Labour Market Effects of General and Vocational Education over the Life-Cycle and across Time: Accounting for Age, Period, and Cohort Effects”, European Sociological Review, Vol. 35/5, pp. 701-717, https://doi.org/10.1093/esr/jcz031.
Note
← 1. Fit for 55 refers to the EU’s target of reducing net greenhouse gas emissions by at least 55% by 2030. The Fit for 55 package is a set of proposals to revise and update EU legislation and to put in place new initiatives with the aim of ensuring that EU policies are into line with the climate goals agreed by the Council and the European Parliament.