This chapter traces the emergence and evolution of skills-first practices. It documents the global trends accelerating the transition towards skills-first approaches, and outlines the economic rationale underpinning the shift, with particular attention to efficiency and equity. Building on this analysis, the chapter proposes a novel and comprehensive definition of the skills-first paradigm that extends beyond recruitment to encompass learning systems, skills recognition and enabling institutional conditions. Finally, it presents the Skills-First Readiness and Adoption Index, a new composite measure designed to assess the extent to which countries are prepared for, and actively implementing, skills-first approaches.
A Skills‑First Labour Market
Abstract
Labour markets are shifting from credentials to skills
Labour markets have traditionally been organised around formal qualifications, which are increasingly ill-suited to fast-changing economic conditions. Over the past decade, skills-first approaches have emerged, initially in firm-level hiring and later extending to broader human resource practices and lifelong learning. Firms are restructuring internal labour markets around skills, while education and training providers are expanding modular and flexible learning pathways.
Skills-first approaches are gaining importance as employers face persistent hiring difficulties alongside widespread skills underutilisation. In 2025, more than eight in ten employers in several countries, including Japan and Germany, reported problems finding suitably skilled candidates, while more than one in three workers on average across participating countries indicated that their skills are not fully aligned with their jobs, with even higher shares in countries such as the United States and Canada. These challenges are expected to intensify as skill requirements evolve more rapidly.
The shift towards skills-first approaches is also justified by economic theory. Educational attainment is an imperfect proxy for skills, weakening labour market signalling and contributing to mismatches. A focus on demonstrated skills provides more precise information on capabilities, improving allocative efficiency. They also have distributional benefits, by expanding access to opportunities for groups historically disadvantaged by credential-based systems.
This chapter proposes a holistic definition of skills-first approaches that extends beyond recruitment. Skills-first systems prioritise demonstrated skills in hiring, training and career progression, with qualifications serving as complementary rather than gatekeeping signals. Skills-first systems rest on two core pillars – skills development and skills recognition – supported by a broader enabling environment including policies, infrastructure, and data systems.
To assess progress, the chapter introduces the Skills-First Readiness and Adoption Index, aggregating 25 indicators across learning ecosystems, talent recognition and enabling conditions. While no country leads across all dimensions, several emerge as frontrunners overall, notably Australia, Sweden, France and the United Kingdom, which combine relatively strong skills-focussed learning systems with more advanced mechanisms for recognising skills and supportive institutional environments.
The global labour market is undergoing a structural realignment shaped by technological change, demographic trends, evolving employment relations, and the transition to low-carbon economies. These transformations are reconfiguring the demand for labour, increasing the value placed on adaptability, and requiring workers to redeploy and update their skill sets more frequently. Existing workforce development systems, however, remain predominantly oriented around formal qualifications and credential hierarchies (Gog, Sung and Sigelman, 2025[1]). This institutional legacy – designed for times of structural stability – constrains labour market responsiveness and limits the capacity to address emerging skill shortages in a timely manner.
Since the early 2010s, reform efforts have sought to integrate skills more explicitly into labour market and lifelong learning policy and practice, yet implementation has been uneven. Many economies have adopted hybrid systems that embed competency frameworks and recognition of prior learning mechanisms within qualification structures. While these initiatives have improved transparency in some sectors, their impact has been somewhat limited. Persistent skill mismatches on the one hand and talent shortages on the other continue to weaken labour productivity and job quality. According to recent international assessments, these inefficiencies affect a substantial share of the global workforce (OECD, 2024[2]), reinforcing the need to place skills – rather than credentials – at the centre of employment and adult learning policy design.
The emerging “skills-first” paradigm proposes a reorientation of how human capital is developed, validated, and utilised in the labour market. It positions demonstrated skills as the primary indicators of capability, with formal qualifications functioning as complementary rather than gatekeeping signals. Realising such an approach requires the development of robust methods for skill identification and assessment, interoperable systems for recognition and transfer, and sustained collaboration between employers, education and training providers, and public authorities to ensure the credibility and consistency of skill signals. It also entails examining employers’ readiness to adopt skills-first workforce practices and the distributional implications for workers across socio‑economic groups.
As there is no universally accepted definition of the “skills-first” paradigm, it is useful to define its contours by situating it within existing frameworks for identifying workers’ abilities. Gog, Sung and Sigelman (2025[1]) distinguish two established models that pre‑date the emergence of skills-first approaches. The first, qualification-centric systems – dominant until the early 21st century – treat (formal) educational attainment as the primary indicator of employability. The second, skills-based hybrid systems – which gained prominence in the 2000s – incorporate competency frameworks and recognition of prior learning but continue to rely on formal credentials as the main signal of capability. Both models have proven increasingly inadequate in responding to the rapidly changing nature of work. Over the past decade, and particularly in the aftermath of the COVID‑19 pandemic, employers have reported persistent challenges in filling vacancies (OECD, 2025[3]). These shortages have been amplified by structural changes in labour demand associated with advances in AI (Acemoglu et al., 2022[4]) and the acceleration of the green transition (Popp et al., 2024[5]). The rapid emergence of entirely new occupations – such as those linked to generative AI – and changing skill needs within occupations have expanded the range of skills required in the economy. As education systems are slow to adjust and degrees take several years to complete, governments have invested in non-formal training to provide adults with emerging skills.
In response, a number of firms have begun to adjust their recruitment strategies by removing degree requirements in job vacancies or by matching workers to roles based on their skills rather than credentials. This trend has been most visible among large multinational enterprises with mature human resource functions. By relaxing or removing qualification requirements in a large number of positions, these firms have widened their potential talent pools and accessed previously under-utilised groups. For instance, the United States branch of IBM began adopting a skills-first approach to hiring more than a decade ago to address shortages of technology professionals. Whereas most positions once required a college degree, more than half of IBM’s current postings in the United States no longer do, and approximately one‑fifth of its American hires now do not hold a college qualification (OECD, 2024[6]). This shift has increased applications from under-represented groups by around 63%.
The emphasis on skills has gradually extended beyond recruitment into wider human resource and organisational practices. Companies are redesigning internal labour markets to support career progression and lifelong learning based on skills visibility. A notable example is Unilever’s U-Work internal talent marketplace, which enables employees to move flexibly between projects and tasks (Unilever and Wired Consulting, n.d.[7]). The company increasingly organises work around projects, deliverables, and required skills, rather than fixed job titles. To further support skills development, each employee develops a personalised “Future Fit Plan”, a skills development framework linking individual learning pathways to organisational priorities and future skill needs.
In parallel with developments in the private sector, public administrations have also begun re‑evaluating the link between hiring practices and formal educational credentials. In the United States, a growing number of states have moved to reform degree requirements in public employment. Since Maryland’s announcement in early 2022, 25 states have introduced measures – through executive action or legislation – to eliminate unnecessary degree prerequisites from state government job postings (Heck et al., 2024[8]). Initial results indicate measurable improvements in recruitment outcomes. The Delaware Department of Human Resources, for example, reviewed qualification criteria in hundreds of public service positions. In the case of Family Service Specialist roles, bachelor’s degree requirements were replaced with relevant work experience. Following this change, the number of applicants increased by 575% (National Governors Association and Lightcast, 2025[9]). Some states have extended these reforms beyond the removal of degree requirements to develop comprehensive, skills-based hiring frameworks (Peterson, Douglas and Noy, 2024[10]). Arizona, for instance, established a cross-functional team tasked with streamlining job analysis processes, creating standardised job templates and descriptions, and providing training on the principles of skills-first approaches for hiring managers and human resource staff (National Governors Association, 2025[11]).
Reflecting the fact that most applications of skills-first approaches have emerged organically among private or public sector employers, academic research has until recently focused exclusively on hiring practices. Drawing on 34 interviews with senior human resource leaders in multinational enterprises, Jooss et al. (2023[12]) show that adopting a skills-matching approach can enhance strategic agility. Moving from rigid job hierarchies towards more flexible, skill-oriented structures allows firms to deploy talent more effectively, particularly when emphasis is placed on skills with high strategic relevance and strong transferability across functions. Collings and McMackin (2025[13]) similarly argue that, although skills-first human resource management remains at an early stage, it constitutes a promising alternative for organisations facing volatile business conditions and heightened uncertainty.
Beyond the analysis of the (theoretical) links between skills-first hiring and agile talent management, a small body of academic research has sought to quantify the extent of this shift. Brown and Souto-Otero (2020[14]) analyse data from 21 million online job postings in the United Kingdom between 2012 and 2014 and find that employers prioritise “job readiness” over formal qualifications, with fewer than one in five vacancies specifying a minimum educational requirement. More recent evidence points to similar patterns in emerging occupational domains. Bone, González Ehlinger and Stephany (2025[15]) also exploit online job vacancy data in the United Kingdom to examine whether employers requiring novel skills (such as those linked to AI) adopt skills-first recruitment strategies to broaden their potential talent pool. They find that, between 2018 and 2023, demand for AI-related roles grew by 21% as a share of total postings, while mentions of university degree requirements for these roles declined by 15%.
In 2022, LinkedIn reported that 40% of recruiters used skills data to fill open roles on their platform, representing a 20% increase compared to the previous year (LinkedIn, 2022[16]). The platform also found that recruiters leveraging skills data were 60% more likely to achieve a successful hire than those relying primarily on traditional credentials. By 2023, LinkedIn estimated that approximately 19% of online job postings in the United States no longer required a university degree, up from 15% in 2021 (LinkedIn, 2023[17]). Comparable evidence is provided by the Burning Glass Institute, which examined 51 million job postings in the United States between 2017 and 2020 and documented a significant “degree reset” (Fuller et al., 2022[18]). During periods of constrained labour supply, employers reduced degree requirements for 46% of middle‑skill roles and 31% of high-skill roles, with the most notable changes observed in IT and managerial occupations. This trend expanded during the COVID‑19 pandemic, when the share of job postings for intensive‑care and critical-care nurses requiring a degree declined from 35% in 2019 to 23% in 2020. Drawing on more recent online job vacancies data, the Institute reports an almost fourfold increase in the number of roles from which employers removed degree requirements in the United States between 2014 and 2023 (Sigelman, Fuller and Martin, 2024[19]).
From the education and training perspective, there has also been a marked evolution towards a more skills-oriented paradigm. This transformation is taking place along several interrelated dimensions. First, governments are reforming qualification and certification frameworks to place skills at the centre of education systems. Many countries are strengthening mechanisms for the recognition of prior learning (RPL) to make informal and non-formal learning more visible and portable across sectors (Meghnagi and Tuccio, 2022[20]; OECD, 2023[21]). National qualification frameworks and registries are increasingly being aligned with explicit skill descriptors, codifying qualifications in terms of the competencies and proficiency levels they certify (Voorhees, 2001[22]; OECD, 2024[23]). This shift improves the transparency and comparability of qualifications, facilitates international recognition, and allows employers to interpret the skill content of educational credentials more accurately.
Education and training providers are also diversifying learning pathways by introducing more flexible and modular forms of provision (Siddiqi, 2024[24]). Universities, vocational institutions, and private training providers are expanding their offer of short courses and micro-credentials that target specific, well-defined skills (Kato, Galán-Muros and Weko, 2020[25]). These programmes are designed to respond quickly to changing labour market needs and to allow learners to build skills incrementally over time. The growing interoperability of micro-credentials within national qualification systems also enables individuals to combine multiple short learning experiences into recognised qualifications, supporting lifelong learning and employability across the life course.
In addition, pedagogical models are increasingly integrating experiential and applied learning (Deming et al., 2023[26]). Curricula are shifting from theory-centred teaching towards learning approaches that emphasise practice, problem-solving, and real-world application. Apprenticeships, work-based learning, project-based assignments, and simulation-based training are becoming more prevalent across both vocational and higher education, and in adult learning. These approaches strengthen the connection between learning and work, helping learners develop both technical and transversal skills such as teamwork, adaptability, and critical thinking. Finally, the digital transformation is amplifying the reach and personalisation of skills-based learning (Holmes et al., 2018[27]; Laak and Aru, 2025[28]). The use of online learning platforms, open educational resources, and AI – supported learning analytics allows providers to tailor instruction to individual skill gaps and learning preferences. Digital badges and blockchain-enabled credentialing are also emerging as tools to document and share verified skills in real time, creating closer alignment between educational outcomes and labour market demand (Pritchard and Maury, 2025[29]).
Overall, these developments in the lifelong learning sphere mark a gradual but significant reorientation of education and training systems. The emphasis is shifting from the acquisition of formal credentials towards the development, validation, and continued updating of skills that are measurable, portable, and relevant to evolving economic and technological contexts.
Why are skills-first approaches becoming increasingly important in today’s economies? Across OECD labour markets, employers are finding it harder to recruit workers with the right skills, while at the same time, many individuals are employed in roles that do not fully utilise their capabilities. This dual imbalance – simultaneous talent shortages and skills underutilisation – lies at the heart of the growing momentum behind skills-first strategies. As shown in Figure 1.1, the share of employers reporting difficulties in filling vacancies due to a lack of skilled talent has risen markedly over the last decade in all OECD countries (except Japan where it remained relatively stable). In 2025, more than 8 employers out of 10 in the Slovak Republic, Greece, Japan, Germany and Ireland indicated problems finding suitably skilled candidates, up from already high levels in 2015. These widespread recruitment challenges suggest that traditional qualification-based hiring practices may no longer provide an accurate or timely measure of workers’ actual capabilities. As job profiles evolve faster than curricula and credentialing frameworks, firms increasingly face a misalignment between what qualifications signal and what jobs require.
Percentage of employers reporting difficulty filling jobs due to a lack of skilled talent, 2015 and 2025
Note: For OECD countries, only those with values for both 2015 and 2025 are shown.
Source: ManpowerGroup (2015[30]; 2026[31]).
At the same time, large shares of workers report being either over-skilled or under-skilled relative to the requirements of their jobs (Figure 1.2). According to the 2023 Survey of Adult Skills, over 40% of workers in several countries – including the United States, Canada, and Germany – experience some form of skills mismatch.1 On average across participating countries, more than one in three workers (36%) report that their skills are not fully aligned with their roles. This persistent mismatch reflects inefficiencies in how skills are developed, identified and deployed. It implies that while employers face shortages in specific skill domains, significant untapped potential exists among workers whose abilities are underused or misallocated. A skills-first approach aims to bridge this disconnect by shifting the focus from formal credentials to demonstrable competencies, thereby improving both job matching and productivity outcomes.
Percentage of workers reporting their skills to be either higher or lower than what is required by their job, 2023
Note: The figure covers employed adults aged 25‑65 who are not self-employed. Data are shown for economies that participated in Cycle 2 of PIAAC. Caution is required in interpreting results for Poland due to the high share of respondents with unusual response patterns – see note for Poland in the Reader’s Companion (OECD, 2024[32]). For consistency, the country name is reported for Belgium and the United Kingdom, even if PIAAC is conducted only at the subnational level – namely in the Flemish region and in England, respectively.
Source: 2023 OECD Survey of Adult Skills (PIAAC).
While skills mismatches and hiring difficulties already pose serious challenges, the evidence suggests that the pace of change in skill requirements is set to accelerate further. As shown in Figure 1.3, employers across OECD countries anticipate substantial disruption to the skill composition of their workforces in the coming years. On average, they expect that around 30‑40% of core skills required today will change by 2030. This implies that a majority of workers will need to acquire new or updated skills within a relatively short timeframe to remain productive and employable. While the scale of anticipated disruption varies across countries, the expectation of change is universal. In economies such as Colombia, Portugal, and Türkiye, more than 40% of current core skills are projected to evolve by 2030, reflecting both the speed of technological innovation and the transformation of work processes. Even in countries where the rate of change is slightly lower, such as Denmark, the Netherlands or the Czech Republic (Czechia), employers still expect nearly a third of core skills to shift. These figures underline the systemic nature of the challenge: the expected change in the relative importance of skills is not confined to a few advanced sectors but spans most occupations and industries.
Average share of core skills required for workforce that employers expect to change in the next five years, 2025
Note: OECD countries with available data and Singapore are shown.
Source: World Economic Forum (2025[33]), The Future of Jobs Report 2025, https://www.weforum.org/publications/the-future-of-jobs-report-2025/.
To identify which countries face the greatest pressures to transition towards a skills-first economy, the OECD/SUSS-IAL (2025[34]) have developed the Labour Market Pressure for Skills-First Approaches Index. This composite, multi-dimensional index measures structural characteristics of national labour markets that intensify the need to adopt skills-first approaches. Factors such as persistent talent shortages, biased hiring practices, limited workforce diversity, skills mismatches, and the rapid evolution of skill requirements all contribute to greater pressure for reform – see Box 1.1 for a description of the data and methodology of the Index.
Urgency to adopt skills-first approaches varies substantially across countries (Figure 1.4). Türkiye, Portugal, and New Zealand face the highest levels of labour market pressure, indicating significant room for skills-first policies to address talent shortages and structural mismatches. Conversely, countries such as Poland, Lithuania, and the Slovak Republic show lower composite scores, suggesting comparatively less acute short-term pressure – though these economies may still benefit from adopting skills-first practices to strengthen resilience and inclusiveness over time. Overall, the index underscores that while all economies face some degree of pressure to shift towards a skills-first orientation, the nature of that pressure differs. In some contexts, it stems primarily from tight labour markets and unmet skill demand; in others, from the need to enhance mobility, diversity, or adaptability within the workforce. These findings point to the importance of tailoring national strategies to local labour market conditions, ensuring that skills-first reforms are targeted, feasible, and aligned with broader economic transformation goals.
Labour Market Pressure for Skills-First Approaches Index (scale 0‑1), 2025
Note: Refer to OECD/SUSS-IAL (2025[34]) for a detailed description of the methodology to construct the composite index. OECD countries with available data and Singapore are shown.
Source: OECD/SUSS-IAL Skills-First Readiness and Adoption Index, available at: https://www.oecd.org/en/data/dashboards/skills-first-readiness-and-adoption-index.html.
The Labour Market Pressure for Skills-First Approaches Index developed by OECD/SUSS-IAL (2025[34]) aggregates nine variables across four dimensions (Table 1.1). After normalising and aggregating these indicators using equal weights, the resulting index highlights where the pressures – and potential benefits – of adopting skills-first strategies are greatest. A higher index score reflects stronger structural incentives to transition, whereas lower scores suggest less immediate pressure, though not necessarily less relevance for long-term competitiveness. See OECD/SUSS-IAL (2025[34]) for a precise description of how the composite index is constructed.
Source: OECD/SUSS-IAL (2025[34]), “Skills-First Readiness and Adoption Index: Methodological Note”, https://www.oecd.org/content/dam/oecd/en/data/dashboards/skills-first-readiness-and-adoption-index/OECD%20SUSS-IAL%20(2025)%20Skills-First%20Readiness%20and%20Adoption%20Index%20Methodological%20Note.pdf.
The shift towards skills-first approaches is not only a response to visible labour market pressures, but it is also grounded in its potential returns. Yet, the economic rationale of skills-first approaches remains underexplored. This section offers an initial examination of the links of skills-first approaches to established strands of the economic literature, including human capital and matching models. However, further analytical and empirical work is needed to assess more rigorously the magnitude of the efficiency and distributional effects associated with a transition towards skills-first systems.
The economic rationale for prioritising skills rests on a refinement of how human capital is conceptualised and measured. Classical human capital theory (Mincer, 1958[35]; Becker, 1962[36]) establishes a link between individuals’ accumulated knowledge and abilities and their productivity, which in turn determines earnings and economic growth. In empirical applications, however, human capital has traditionally been proxied by educational attainment or years of schooling, due to the limited availability of direct skill measures. While these proxies are correlated with skill proficiency, they are imperfect and increasingly insufficient in explaining productivity differences across workers, firms, and countries. From a theoretical point of view, skills represent the true operational currency of the labour market. They capture the cognitive, technical, and interpersonal competencies that enable individuals to perform tasks effectively.2 Formal education remains a key channel for skill acquisition, but it is not the only one. Skills are also developed and updated through informal learning, work and life experience, on-the‑job training, and individual capacity for adaptation. Because traditional credentials do not fully reflect these broader processes of human capital formation, they risk both underestimating and misrepresenting the productive potential of individuals.
Growing empirical evidence reinforces this point. Cross-country assessments such as the Survey of Adult Skills (PIAAC) reveal large differences in skills proficiency among people with the same level of education. Figure 1.5, for example, illustrates this pattern for numeracy. Although years of schooling are positively associated with numeracy proficiency, the dispersion around the trend line is substantial: individuals with the same number of school years often differ markedly in their actual skills. Indeed, only about a fifth of the differences in numeracy scores can be attributed to differences in years of schooling (R² = 0.20). This does not imply that numeracy scores alone determine productivity at the country level, nor that higher measured proficiency automatically translates into higher output. Aggregate productivity depends not only on the stock of skills, but also on their utilisation and institutional settings (OECD, 2026[37]). Rather, the evidence indicates that education-based indicators capture only a limited share of the heterogeneity in underlying competencies, supporting the case for complementing them with more granular information on skills and knowledge.
The distinction between qualifications and skills affects how well labour markets function. A skills-first labour market can reduce information frictions and improve matching efficiency, raising productivity at both the firm and economy-wide level. In fact, traditional hiring systems rely heavily on credentials as a proxy for capability, but degrees provide only a coarse signal of what workers can actually do. This coarse signalling weakens job matching and contributes to structural unemployment, even when significant numbers of vacancies remain unfilled. A skills-first approach offers a more precise mechanism for aligning labour supply and demand, thereby creating measurable economic gains.
Search frictions are a defining feature of modern labour markets. In standard search-and-matching frameworks – such as the Mortensen-Pissarides model (Mortensen and Pissarides, 1994[38]) – employment outcomes depend on the efficiency with which unemployed workers and vacancies are paired. Matching efficiency reflects how effectively the labour market brings together suitable workers and available jobs, given the information available to both sides. High matching efficiency implies rapid and accurate pairings. Low efficiency reflects delays, misallocations and costly hiring processes.
Note: The figure covers all adults aged 16 to 65 currently not studying for formal qualifications. It aggregates the 31 economies participating in Cycle 2 of PIAAC, namely Austria, Belgium (Flemish region), Canada, Chile, Croatia, Czechia, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, the Netherlands, New Zealand, Norway, Poland, Portugal, Singapore, the Slovak Republic, Spain, Sweden, Switzerland, the United Kingdom (England), the United States.
Source: 2023 OECD Survey of Adult Skills (PIAAC).
Under traditional, credential-based systems, employers observe educational attainment but have only limited information about a candidate’s actual skills, proficiency level, or potential fit. Workers, in turn, often lack full visibility into the skill requirements of available jobs. These asymmetries create skills mismatches, persistent vacancies, and inefficient job mobility. As a result, matching efficiency is reduced, and overall labour market performance is weakened. Indeed, Figure 1.6 shows that qualifications often do not map neatly onto actual skill requirements in jobs. Many adults classified as under-qualified based on their credentials are in fact well-matched or even over-skilled for the tasks they perform, suggesting that their formal qualifications underestimate their real capabilities.3 Among those whose qualifications formally match their job level, a sizeable share – around one‑third – still exhibit a skill mismatch. Even among the over-qualified, a non-trivial minority lack the skills needed for their roles. These patterns reveal that credentials alone cannot reliably signal productive capacity.4
The economic costs of skill mismatch are substantial. When workers possess more skills than their job requires (over-skilling) or fewer (under-skilling), productivity losses occur through misallocation of talent, lower engagement, and weaker firm performance. Empirical studies consistently show that mismatched workers earn lower wages and contribute less to firm productivity (Badillo-Amador and Vila, 2013[39]; Fanti, Guarascio and Tubiana, 2021[40]). At the macro level, high mismatch rates are associated with weaker aggregate productivity growth and slower diffusion of new technologies (McGowan and Andrews, 2017[41]; Sekmokas et al., 2020[42]).
A skills-first system has the potential to strengthen the matching function by enabling employers to observe a richer and more granular set of information – such as demonstrated skills, validated assessments, and detailed skill profiles – rather than relying solely on degrees. When matching decisions are made on the basis of the overlap between a job’s skill requirements and a candidate’s observed skill bundle, quality of matches can improve. From an efficiency standpoint, this enables better matching between people and jobs, more accurate identification of skill gaps, and more effective workforce planning as technologies and organisational needs evolve. Workers can more easily transition between occupations that share similar skill needs, and employers can identify non-traditional but productive candidates who might be excluded under credential-based screening.5
Note: The figure covers all adults aged 16 to 65 currently not studying for formal qualifications. It aggregates the 31 economies participating in Cycle 2 of PIAAC, namely Austria, Belgium (Flemish region), Canada, Chile, Croatia, Czechia, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, the Netherlands, New Zealand, Norway, Poland, Portugal, Singapore, the Slovak Republic, Spain, Sweden, Switzerland, the United Kingdom (England), the United States.
Source: 2023 OECD Survey of Adult Skills (PIAAC).
Evidence from employers supports this theoretical rationale. Novel surveys and large‑scale analytics demonstrate that organisations adopting skills-first practices outperform those relying primarily on credential-based screening. A Deloitte survey of more than 1 000 workers and over 200 business and HR executives across 10 countries found that organisations embracing skills-based practices6 are 63% more likely to achieve stronger performance outcomes – including meeting financial targets, innovating, and delivering high customer satisfaction – than those relying primarily on traditional credentials (Jones et al., 2022[43]). Similarly, a 2025 TestGorilla survey of over 1 000 employers in the United Kingdom and the United States reports that hiring holistically – i.e. considering the “whole candidate”, including their skills, personality, and cultural alignment in recruitment decisions – improves the performance of the organisation, with 50% saying that it also increases retention (TestGorilla, 2025[44]). Big-data evidence from the United States further confirms this pattern: when employers drop degree requirements, non-degreed candidates hired into those roles exhibit substantially higher two‑year retention rates – around 10 percentage points (p.p.) higher – than their degree‑holding peers (Sigelman, Fuller and Martin, 2024[19]).
Beyond productivity gains and gains from lower turnover, skills-first approaches also contribute to better job quality and worker well-being by ensuring a closer alignment between individuals’ skills and the roles they perform. When workers fully deploy their skills, they tend to experience greater autonomy, stronger intrinsic motivation, and higher levels of job satisfaction (OECD, 2026[37]). Evidence from the Survey of Adult Skills illustrates this pattern across OECD countries: as shown in Figure 1.7, the predicted probability of being satisfied at work is systematically higher for workers whose skills are well matched to their jobs. In many countries, the gap exceeds 10 p.p., and in some – such as Italy, Spain and Portugal – the difference is considerably larger. These patterns remain robust even after controlling for demographic characteristics, education, occupation, industry, and wages, underscoring the central role that skills alignment plays in shaping job satisfaction.
Note: The figure covers working adults aged 16 to 65 who are not self-employed and are not currently studying for a formal qualification. It displays the predicted probability of being satisfied at work (job satisfaction equal to 4 and 5 in a 1‑5 scale), based on a weighted regression model. Coefficients are adjusted for gender, age, age squared, immigration background, whether one lives with a partner or has children, educational attainment, literacy proficiency, occupation, industry, firm size, permanent contract, and hourly wages. All coefficients are statistically significant (at the 1% significance level). Data are shown for economies that participated in Cycle 2 of PIAAC. For consistency, the country name is reported for Belgium and the United Kingdom, even if the Survey of Adult Skills is conducted only at the subnational level – namely in the Flemish region and in England, respectively.
Source: 2023 OECD Survey of Adult Skills (PIAAC).
Skills-first approaches also carry significant distributional implications. Credential-based systems tend to disadvantage groups with historically limited access to formal education, including individuals from low-income backgrounds. These groups frequently develop skills through work experience, informal learning, or community and family roles, and some migrants may hold qualifications that are not recognised in the host country but have relevant skills. Yet such skills often remain undervalued because they are not captured by traditional qualifications.
Figure 1.8 illustrates this structural disadvantage by showing the share of adults without tertiary degrees across different levels of numeracy proficiency and parental educational attainment. A well-established pattern emerges. Adults whose parents lack tertiary education are themselves substantially more likely to have no tertiary qualification. However, the figure also highlights a more novel and policy-relevant insight: even among individuals with high numeracy proficiency (Level 4 and above), those from non-graduate families remain disproportionately likely to have no tertiary degree compared with their peers from graduate families. In relative terms, the parental education gap is widest at the top of the skills distribution. This suggests that formal credentials are not consistently aligned with individuals’ actual skill levels and that socio‑economic background continues to shape labour market trajectories – even for the highly skilled.
These findings underscore the extent to which reliance on degrees alone can obscure talent and perpetuate inequalities. Skills-first systems help mitigate these barriers by recognising skills irrespective of where or how they were acquired. By valuing practical learning, micro-credentials, and task-specific proficiency assessments, they expand labour market opportunities for individuals who may be highly capable but under-represented in traditional qualification pathways. Evidence from LinkedIn (2023[17]) illustrates the scale of this effect: broadening hiring criteria to include workers with relevant skills rather than formal degrees increased the potential talent pool nearly tenfold. The gains are particularly pronounced for groups facing structural barriers. In occupations where women are under-represented, adopting a skills-first approach expands the share of women in the potential talent pool by 24% more than men. Similarly, the pool of candidates without bachelor’s degrees grows, on average, 9% more than for those holding degrees.
Note: The figure covers all adults aged 25 to 65 currently not studying for formal qualifications. It aggregates the 31 economies participating in Cycle 2 of PIAAC, namely Austria, Belgium (Flemish region), Canada, Chile, Croatia, Czechia, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, the Netherlands, New Zealand, Norway, Poland, Portugal, Singapore, the Slovak Republic, Spain, Sweden, Switzerland, the United Kingdom (England), the United States. Proficiency levels refer to numeracy.
Source: 2023 OECD Survey of Adult Skills (PIAAC).
The implications for social mobility are substantial. Hiring practices centred primarily on formal degrees reinforce a strong link between socio‑economic background and access to high-productivity, high-wage occupations. Because parental educational attainment remains a powerful predictor of an individual’s likelihood of obtaining a degree, credential-based systems risk entrenching intergenerational inequalities. Skills-first approaches weaken this transmission mechanism by creating alternative, skills-validated pathways into well-paid roles. In doing so, they not only reduce structural barriers but also contribute to more inclusive, merit-based labour markets that better recognise and utilise the full spectrum of available talent.
Much of the existing literature and media commentary continues to portray the skills-first paradigm primarily as a matter of recruitment and internal firm practices. Yet, as the previous sections demonstrate, even where the term “skills-first” is not explicitly used, education and training systems are also evolving towards a more skills-centred orientation. A comprehensive and conceptually robust definition of skills-first approaches must extend beyond the traditional employer-centric perspective that focuses on skills solely at the point of hiring. It should situate skills-first approaches within a broader context that links firm-level demand signals with the systemic processes through which skills are developed, validated, and recognised in education, training, and labour market institutions. Within this expanded framework, skills are understood not as static attributes to be measured once, but as dynamic capabilities that are continuously shaped, refined, and rewarded through interdependent systems of learning and work.
Drawing on OECD/SUSS-IAL (2025[34]), this report proposes a novel, holistic definition of skills-first approaches. Namely, skills-first approaches prioritise demonstrated skills over formal qualifications and experience in hiring, talent management, and training, positioning skills as the core currency for articulating, developing, and recognising capabilities across the labour market. In these approaches, qualifications serve not as gatekeepers but as supplementary signals, supporting rather than substituting for recognisable skills and proficiency. At the core of skills‑first approaches are, therefore, two interlinked components: developing skills (“learning ecosystem”) and valuing skills (“talent recognition”) (Figure 1.9). The interaction of these two components establishes a feedback loop in which skills are both developed and rewarded through coherent, mutually reinforcing systems, thereby advancing a more inclusive, efficient, and innovation-ready workforce.
Source: OECD/SUSS-IAL (2025[34]), “Skills-First Readiness and Adoption Index: Methodological Note”, https://www.oecd.org/content/dam/oecd/en/data/dashboards/skills-first-readiness-and-adoption-index/OECD%20SUSS-IAL%20(2025)%20Skills-First%20Readiness%20and%20Adoption%20Index%20Methodological%20Note.pdf.
Skills development takes place within the broader learning ecosystem. Governments and training providers are increasingly investing in flexible, modular, and targeted learning opportunities that equip individuals with specific, in-demand skills. As the concept of skills-first has emerged in response to widening skill gaps, these programmes are often designed in close alignment with labour market needs. Individuals are actively pursuing upskilling and reskilling opportunities, while employers are supporting employee participation in skills-focused learning and embedding skills development into broader talent strategies. Career guidance professionals are also shifting their focus, helping individuals identify relevant skills and connect with appropriate learning pathways. Together, these efforts contribute to a more agile and responsive learning system that places importance on the acquisition and use of skills over the completion of traditional credentials.
Talent recognition focuses on how skills are signalled, recognised, and valued in the labour market. This means shifting from recruitment and progression systems that rely heavily on formal qualifications and experiences to ones that acknowledge and reward demonstrated skills, regardless of how or where they were acquired. Skills signalling is a critical component, ensuring that individuals can clearly communicate their capabilities and that employers can articulate their skill needs. Recognition of prior learning plays a complementary role, enabling individuals to have their non-formal and informal learning validated. This is particularly helpful in contexts transitioning from qualification-based to skills-first systems, where such mechanisms help bridge the gap and ensure that skills are both visible and valued. When skills are clearly identified and fairly rewarded, labour market matching improves, delivering benefits not only for individuals and employers but also for the wider economy.
However, to fully develop a skills-first economy, the right learning and talent recognition systems are not enough: a much broader enabling environment – encompassing infrastructure, policies, data systems, and cultural mindset – is also needed to support and sustain skills-first approaches. In particular, a common skills language is essential, as fragmented skills frameworks can hinder communication and co‑ordination among key stakeholders. When existing tools such as national qualification registers and occupational standards are aligned with a shared skills framework, it becomes easier to develop, signal, and recognise skills throughout the system. Reliable labour market information, particularly on current and emerging skills demand, helps all actors make informed decisions and supports efforts to close skills gaps. Public policies that remove barriers to adult learning, such as financial constraints and lack of time, can increase participation and engagement, especially among underrepresented groups. Organisational resistance to change remains a challenge in many contexts, so fostering a business mindset that embraces innovation and lifelong learning is crucial for the success of skills-first reforms.
Together, the three domains of learning skills, recognising skills, and building an enabling environment form a coherent skills‑first readiness and adoption framework that unites key stakeholders and aligns fragmented initiatives. By responding to immediate labour market pressures while building long-term system capacity, skills-first approaches can help address existing labour market challenges and foster a workforce that is not only better matched to today’s needs, but also resilient and adaptable for the future.
As highlighted in the previous section, skills-first approaches encompass a broad and interconnected set of practices spanning education and training systems, labour market institutions, and firm-level talent management. Given this multidimensionality, no single indicator can adequately capture the extent to which countries are moving towards a skills-first paradigm. To address this challenge, OECD/SUSS-IAL (2025[34]) developed the Skills-First Readiness and Adoption Index. This composite measure synthesises a wide range of indicators into a single, interpretable metric. By aggregating information across multiple domains, the index makes it possible to identify broad trends and structural patterns that may be difficult to detect using disaggregated data alone. In doing so, it provides a structured foundation for policy analysis, stakeholder engagement, and international benchmarking.
Mirroring the conceptual framework laid out in the previous section, the Skills-First Readiness and Adoption Index is organised around three complementary sub-indices (Figure 1.10). The Skills-First Learning Ecosystem sub-index assesses the extent to which skills-first principles are embedded in the design and delivery of education and training. The Skills-First Talent Recognition sub-index examines whether skills are formally recognised, signalled, and rewarded in labour markets and organisational practices. Finally, the Enabling Environment for Skills-First Approaches sub-index evaluates whether countries have the institutional, regulatory, and data infrastructures necessary to support and sustain a shift towards skills-first systems.
Each sub-index is further structured into four dimensions, yielding a total of 12 dimensions and 25 indicators. Together, these indicators are designed to capture the full lifecycle of skills: from development and continuous learning to recognition and utilisation, and finally to the systemic conditions that enable both. They reflect not only policy choices, but also the roles played by key stakeholders in the skills ecosystem – including governments, employers, education and training providers, and individuals themselves. In all components of the index, higher scores are associated with stronger readiness for, and more advanced adoption of, skills-first approaches (see Box 1.2 for details on the statistical methodology used to construct the composite index).
Source: OECD/SUSS-IAL (2025[34]), “Skills-First Readiness and Adoption Index: Methodological Note”, https://www.oecd.org/content/dam/oecd/en/data/dashboards/skills-first-readiness-and-adoption-index/OECD%20SUSS-IAL%20(2025)%20Skills-First%20Readiness%20and%20Adoption%20Index%20Methodological%20Note.pdf.
As detailed in OECD/SUSS-IAL (2025[34]), the Skills-First Readiness and Adoption Index is constructed by aggregating 25 indicators into 12 dimensions, which are then combined into three sub-indices and, ultimately, into a single composite measure. The full list of indicators and their corresponding dimensions is presented in Table 1.2. At each stage of aggregation, equal weights are applied. Indicators are first aggregated into dimensions using equal weights; dimensions are then aggregated into sub-indices using equal weights; and, finally, the three sub-indices are combined into the overall index, again assigning equal weights. This weighting scheme reflects the absence of strong empirical or theoretical grounds for privileging any single indicator, dimension, or sub-index over others, and ensures transparency and replicability. Because the indicators are measured in different units, all values are normalised prior to aggregation. For each indicator, country values are rescaled to a 0‑1 interval using a min – max normalisation based on the observed distribution across countries. A value of 0 corresponds to the lowest observed score among countries with available data, while a value of 1 corresponds to the highest.
For a limited number of countries, data are missing for some indicators. Imputing missing values in such cases would require strong assumptions and introduce statistical noise, particularly where correlated proxy variables are either unavailable or conceptually distinct. Rather than applying imputation techniques that may artificially inflate inter-indicator correlations, the index adopts a “complete case analysis” approach at the dimension level. When data for one or more indicators within a given dimension are unavailable, the dimension score is calculated using only the indicators for which data exist. This approach preserves the empirical integrity of the index and avoids potential bias arising from model-driven estimations that lack sufficient theoretical or empirical justification. Further discussion and methodological guidance on the treatment of missing data in composite indicators can be found in OECD/European Union/EC-JRC (2008[45]).
Note: Information on public policies draws primarily from the OECD Trends in Adult Learning Policy (TALP) questionnaire, distributed to representatives from OECD Member countries and Singapore by the OECD Secretariat in early 2025, and supplemented by desk research conducted over the same period.
Source: OECD/SUSS-IAL (2025[34]), “Skills-First Readiness and Adoption Index: Methodological Note”, https://www.oecd.org/content/dam/oecd/en/data/dashboards/skills-first-readiness-and-adoption-index/OECD%20SUSS-IAL%20(2025)%20Skills-First%20Readiness%20and%20Adoption%20Index%20Methodological%20Note.pdf.
Figure 1.11 presents the results of the Skills-First Readiness and Adoption Index, highlighting cross-country variation in the extent to which skills-first practices are embedded in education systems, labour markets and institutional frameworks. Several countries emerge as frontrunners, notably Australia, Sweden and France, which record the highest overall index scores. These countries combine relatively strong skills-focused learning ecosystems with more advanced mechanisms for recognising skills and supportive enabling environments. At the other end of the distribution, countries such as Hungary, Greece and Korea score lower on the index, indicating that skills-first approaches are still at an earlier stage of development and adoption.
Skills-First Readiness and Adoption Index (scale 0‑1), 2025
Note: Refer to OECD/SUSS-IAL (2025[34]) for a detailed description of the methodology to construct the composite index. OECD countries with available data and Singapore are shown.
Source: OECD/SUSS-IAL Skills-First Readiness and Adoption Index, available at: https://www.oecd.org/en/data/dashboards/skills-first-readiness-and-adoption-index.html.
Despite these differences, the overall picture is encouraging. By construction, the index ranges from 0 to 1, yet the average score across countries is 0.58, suggesting that most OECD countries have already put in place a meaningful set of foundations for skills-first approaches. Moreover, the gap between the highest- and lowest-scoring countries is relatively narrow – just 0.26 – indicating that no country is starting from scratch. Rather, all countries reviewed display areas of relative strength, even if these strengths are distributed differently across the three sub-indices and their underlying dimensions. At the same time, results also underscore that there is considerable scope for further progress. No country attains the maximum score of 1, signalling that even the most advanced systems have yet to fully operationalise skills-first principles across learning, recognition and enabling environments. This reflects the inherently systemic and ongoing nature of the transition towards skills-first approaches: advancing further will require sustained policy attention, continued co‑ordination among stakeholders, and ongoing adaptation as skill needs evolve.
While the overall index provides a useful summary of progress, it inevitably masks important differences in countries’ underlying strengths and weaknesses. Countries may achieve similar aggregate scores through very different combinations of policy settings, institutional arrangements and stakeholder practices. For this reason, it is essential to complement the composite results with a more granular examination of the individual components that constitute skills-first approaches. The remainder of the report therefore explores the core features of skills-first approaches in greater depth, bringing examples from numerous good practices around the OECD. Chapter 2 focuses on the Enabling Environment, with particular attention paid to the development of a common skills language as a foundational instrument for advancing skills-first approaches. Chapters 3 and 4 examine, respectively, the Skills-First Learning Ecosystem and Skills-First Talent Recognition. Finally, Chapter 5 discusses cross-cutting elements that connect learning and recognition – such as career guidance, skills signalling, and the recognition of prior learning – and reflects on the inherently multi-stakeholder nature of skills-first approaches.
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← 1. A skills mismatch occurs when a worker has either higher or lower skills than required for their job. The variable is constructed exploiting the question “Overall, which of the following statements best describes your skills in relation to what is required to do your job?” included in the 2023 Survey of Adult Skills (PIAAC) – see OECD (2024[2]) for a more detailed description on how to measure skills mismatches in PIAAC.
← 2. At the same time, available measures of skills are themselves partial and subject to measurement constraints. No single assessment captures the full range of cognitive, technical and interpersonal competencies, nor the domain-specific knowledge that underpins effective performance in many occupations. In this report, the term skills is used in a broad sense to encompass knowledge, cognitive abilities, technical competencies and transversal attributes. This conceptual breadth exceeds what is typically observed in large scale assessments. For example, the Survey of Adult Skills measures selected information-processing skills, but does not capture occupation-specific technical knowledge or the full spectrum of applied competencies that contribute to productivity.
← 3. A qualification mismatch occurs when a worker has either higher or lower educational level than that required for their job. The variable is constructed exploiting the question “Talking about your current job: if applying today, what would be the usual level of education, if any, that someone would need to get this type of job?” included in the 2023 Survey of Adult Skills (PIAAC) – see OECD (2024[2]) for a more detailed description on how to measure mismatches in PIAAC.
← 4. These findings could also partly reflect credential inflation. In several countries, occupations that previously did not require a degree have introduced formal qualification thresholds, even where the underlying task content has changed only marginally. In such cases, workers may be labelled under-qualified despite possessing the relevant skills, while others hired under earlier, less restrictive requirements may appear over-qualified relative to current norms. A skills-focussed perspective can help disentangle genuine skill gaps from credential-based screening practices.
← 5. However, these gains are not automatic. For skills to function as more precise signals in practice, substantial investment is required in reliable assessment methods, common skills taxonomies and trusted validation mechanisms. Without credible and scalable ways to measure and communicate competencies, a shift away from credential-based screening risks replacing one imperfect proxy with another.
← 6. According to Cantrell et al. (2022[43]), the skills-based organisations ratio reflects the combined weighted ratios of the HR executive survey item “Our organization’s business and HR executives are aligned on the importance of skills in making decisions about work” and the worker survey items “My employer treats workers as whole, unique individuals who can each offer unique contributions and a portfolio of skills to the organization”, “My organization supports me in pursuing opportunities to create value through activities that are outside of the direct scope of my job” and “My organization makes it easy to apply my skills where they are most needed”.