This chapter considers the performance of scalers after scaling up. It provides an overview of the growth trajectories that different types of scalers follow in the years after scaling up and presents SME and entrepreneurship policies that support the long-term transformation of SMEs through strengthening access to skills, digitalisation and integration in innovation networks.
Unleashing SME Potential to Scale Up
Helping SMEs Scale Up
Abstract
For most scalers, the changes they undertake while scaling up are persistent and even lead to further (high) growth.
Most scalers maintain their new size or even continue to grow but a larger scale also brings new challenges. Between 54% and 73% of scalers remain at their newly-achieved scale or continue to grow in the three years after scaling up, with about one in five scalers even scaling up for two consecutive three-year periods. Scaling up is not primarily driven by short-term demand spikes or volatile business cycles but a transformative process that can include changes in the managerial structure or ownership, or engagement in new activities (e.g. research or export). Scalers are more likely to continue to scale up in turnover than in employment. Those that grew initially in employment are especially likely to follow up with gains in productivity and further investments to scale up turnover. Between 22% and 40% of employment scalers become turnover scalers in the following three-year period.
Rapid growth brings new challenges, with some scalers failing to adapt. As they scale up, scalers increase assets and debt at similar rates, maintaining a debt-to-assets ratio 10% higher than non-scalers. Despite higher debt-to-asset ratios before and after scaling up, scalers only incur, on average, higher interest expenses per unit of debt afterwards, as their financial risk increases with rising debt levels. About 1 in 10 scalers revert to their initial size or become smaller in the three years following their initial growth, and about 1 in 10 cease to operate. Following scale-up, firms may need to comply with stricter regulations, improve their managerial practices, or adopt a different financial model. They might also experiment with new ideas or products and choose to exit and restart if unsuccessful, leading to “up-or-out” dynamics, evident in a higher share of young scalers that exit compared to older ones. Sectoral specificities can also play a role. Around 34% of scalers in the construction sector shrink after scaling up, which is more than 6 percentage points higher than in other sectors. The sector's dependence on business cycles contributes to this, as well as temporary expansions of firms to fulfil large contracts that are not planned to be maintained.
Access to skills is essential for all scalers, especially those in knowledge‑intensive sectors. Scalers have higher labour costs per employee after scaling up than other SMEs, reflecting the need to attract and retain skilled employees. At 5-9% the gap with other SMEs is largest for scalers in advanced tradable service sectors and high or medium-high tech manufacturing. More than 46% of employment scalers in these knowledge‑intensive sectors continue to add jobs after their initial growth period, highlighting the critical role of talent in these sectors. About 80% of skills-related policies focus on skill development through upskilling or reskilling either directly to employees or to firms. Several countries have introduced financial incentives to help SMEs cover the cost of training, such as loans, grants or vouchers. Countries are also implementing various policy measures to support the development of managerial skills in areas like strategic planning, change management, human resources, accounting, marketing, logistics, certification, and quality control, as well as entrepreneurial skills such as teamwork, resilience, self‑learning, and problem‑solving. Most of the policies aimed at enhancing transversal skills do not adopt a sector-specific approach.
Participating in innovation networks increases the capacity of scalers to transform and innovate. Innovation networks connect SMEs and start‑ups with other actors in global, national, and regional innovation systems through collaborative R&D, open innovation, and technology transfer. All but 2 of the 38 OECD countries have implemented policies to help SMEs access innovation and knowledge networks. Approaches include innovation hubs, exporting networks, incubators and accelerators and one‑stop‑shop digital portals, training, and connections to universities. Close to half (45%) of those policies have at least a partially international scope. SMEs often make use of knowledge-intensive business services (e.g., ICT, design, engineering, or legal services inputs) to support innovation and help increase internal capacity. However, policies that support access to market-based solutions account for less than 2% of policies.
Digital platforms can simplify access to information and networks. Digital platforms can lower technology barriers, ease administrative processes in dealing with intellectual property rights and access to experts, facilitate co-operation with other firms and connect potential scalers with investors who could finance research and innovation adoption projects. Despite these advantages, three in four OECD countries do not incorporate digital platforms into their innovation network policies. This gap highlights an untapped opportunity to leverage digital tools as a pathway for supporting long-term transformation of scalers.
More than 50% of scalers retain their newly achieved scale or continue to grow further in the three years after scaling up (Figure 3.1). For most SMEs, scaling up is not driven by short-term demand spikes or volatile business cycles but reflects transformations that set them up for long-term success. At least 50% of scalers either continue to grow, in some cases through a second high-growth phase, or maintain their larger size in the years following scaling up. There are sizeable differences across countries. For employment scalers, the share of scalers that continue to grow or consolidate at the new scale is as high as 70% in Slovenia (71%), Portugal (70%), and Belgium (70%). Even at the lower end, in Estonia (58%), Latvia (56%), and Romania (54%), most scalers at least consolidate their new scale. For turnover scalers, the shares fall into a similar range, with some countries having high shares among both employment and turnover scalers, which is unsurprising given the overlap of SMEs scaling up in both employment and turnover (Chapter 1). For some scalers, growth is, however, temporary. About 1 in 10 scalers reduce employment or turnover in the three years after scaling up to fully reverse their initial growth. And about 1 in 10 scalers are no longer present in the data, which indicates that they are no longer operating due to the closure of the firm, or, in a small number of cases, it reflects a merger or acquisition by another company (see below).1
Share of scalers by their growth performance after scaling up, 2011-20
Note: Scalers are SMEs with at least 10 employees that grew in employment or turnover by at least 10% per year, on average, over three consecutive years. Growth patterns three years after scaling up for three cohorts of scalers that ended scaling up in 2014, 2015 or 2016 are considered, i.e. growth of scalers post-scaling during 2015-18, 2016-19, and 2017-20. Growing scalers continue to increase in employment or turnover, HG again do so by at least 10% on average per year over the three years after initially scaling up (i.e. they scale up again), partial reversal means a reduction in employment or turnover after scaling up but higher employment or turnover than before scaling up and full reversal means that the SME has lower employment or turnover three years after scaling up than it had before scaling up.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
A high share of scalers within an economy does not ensure a high share of scalers that continue to grow or consolidate at a larger scale (Figure .2). For example, Romania, Finland, and Denmark have a higher share of scalers in all SMEs compared to most other countries but they have a lower share of scalers with persistent growth after their scaling-up period. In contrast, Austria and Portugal have a lower share of scalers among all SMEs than most other countries, but a higher share of scalers with persistent growth.
Share of scalers in employment and share of scalers that continued to grow or maintained their higher employment level, 2011-20
Note: Three cohorts of scalers are analysed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. Growth patterns are observed for each cohort over the three years following their respective scaling-up periods (i.e. 2015-2018, 2016-2019, and 2017-2020). Scalers with persistent growth are all scalers that at least maintained the level of employment they achieved after scaling up in the subsequent three years. Scalers are SMEs with at least 10 employees that grew in employment by at least 10% per year, on average, during three consecutive years.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
About one in five scalers scales up twice in a row
Between 15% and 31% of scalers continue to grow in employment or turnover at a rate of at least 10% per year over a second three-year period, thereby scaling up twice in a row. SMEs that scale up twice are particularly important for employment growth. For example, around 1 200 SMEs that scaled up twice in employment over the 2013-19 period in Italy created more than 58 000 jobs, with a mean growth rate of 250% over the same period. Overall, SMEs that scale up twice in a row grow their employment by 164%-327% and their turnover by 189%-455% over a six-year period (from 2013 to 2019) across 15 countries.
Scalers are more likely to continue to scale up in turnover than in employment. The share of turnover scalers that continue to scale up in turnover ranges from about 20% to 31% (Figure .3). The share of employment scalers that follow the growth in employment by scaling up in turnover is between 22% and 40% (Figure .4). Hiring to grow the workforce is a forward-looking decision driven by expectations of future revenues requiring new hires. This investment pays off in subsequent years. Hiring and dismissing workers, which is often subject to labour regulations, entail costs requiring firms to have strong confidence in future business prospects to decide to expand their workforce. The share of employment scalers that continue to scale up for a second three-year period is accordingly lower, ranging from 15% to 25% for the 15 countries with available data (Figure .3). Turnover increases, in contrast, are already realised increases in sales using available resources. The longer-term commitment and potential adjustment costs associated with employment decisions result in lower shares of scalers in employment that continue to scale up for a second 3-year period compared to scalers in turnover.
Share of scalers that scale up again following their initial scaling-up period, 2017-19
Note: Three cohorts of scalers are observed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. The charts show the share of scalers that scaled up again in the three years following their initial scaling-up period. Shares are calculated by using unweighted averages of the three cohorts for each country. Scalers are SMEs with at least 10 employees that grew in employment or turnover by at least 10% per year, on average, during three consecutive years.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
Share of scalers in employment that scale up in turnover in three years after the initial scale-up period, 2017-19
Note: Three cohorts of scalers are observed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. The charts show the share of scalers in employment that scaled up in turnover in the three years following their initial scaling-up in employment. Shares are calculated by using unweighted averages of the three cohorts for each country. Scalers are SMEs with at least 10 employees that grew in employment by at least 10% per year, on average, during three consecutive years.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
Scalers providing advanced tradable services are more likely to continue to scale up in employment than scalers in other sectors. Between 23% (Hungary) and 36% (Estonia) of employment scalers in the advanced tradable services sector continue scaling up in the three years following the first expansion, across the fifteen countries analysed (Annex Figure .A.2). Unlike other sectors where physical capital investment plays a more prominent role, SMEs in advanced tradable services intensively rely on their, typically highly skilled, workforce. Continued growth, therefore, requires continued expansion in employment. In contrast, goods producers in medium-low tech manufacturing show the lowest rates of continued scaling, ranging from 9% to 28%. This may be due to capital investment that can substitute for employment growth in these sectors and might even help maintain output levels while reducing employment.
Young scalers follow “up-or-out” growth patterns. The share of scalers that scale up twice in a row is higher among young scalers than among mature scalers in all 15 countries with available data for turnover scalers and 13 out of 15 countries for employment scalers (Figure .5). Young scalers are also significantly more likely to exit the market than mature firms, with gaps of 2 to 12 percentage points between the two groups (Annex Figure .A.2). These exits can take different forms, including firm closures or mergers and acquisitions. The high share of young scalers that exits the market is known as the “liability of newness” in the economic literature: Young firms face significantly higher risks of failure compared to their older counterparts.2 Young businesses start small as they need to experiment with their business model in real market conditions. Those who are viable need to grow quickly to reach a minimum scale and compete with older firms; those that are not successful instead tend to shrink and exit quickly (Jovanovic, 1982[1]).
The share of scalers that scale up again after their initial scaling-up period, 2017-19
Note: Three cohorts of scalers are observed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. The charts show the share of scalers that scaled up again in the three years following their initial scaling-up period. The shares are calculated for each cohort individually, and the chart shows the average of these shares across the three cohorts. Scalers are SMEs with at least 10 employees that grew in employment by at least 10% per year, on average, during three consecutive years
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
Acquisition after scaling up is a rare event in the two countries with available data
For around 10% of scalers, no information is available three years after scaling up. In most cases, the company likely ceased operations (Figure 3.1. ). The lack of information is due to the firm not being present in the firm-level databases used for the analysis or being present with missing information on employment (or turnover, in the case of turnover scalers). The lack of information can have different reasons. First, the firm may be closed or about to close, which is typically associated with the business not being successful. Second, another entity may have acquired the company, which typically indicates success rather than failure. Third, the lack of information may be “noise” in the data, e.g. due to reporting errors. In this case, it is reasonable to assume that the issue affects successful and unsuccessful businesses similarly. For most countries, knowing the exact incidence of each of the three alternatives is not possible with the main type of microdata used in this analysis, due to the way that changes in ownership or restructuring in business groups are recorded.3
In Denmark and Latvia, fewer than 2% of scalers are acquired in the three years after scaling up. Data on acquisitions are available for Denmark and Latvia. In Denmark, only 1.3% to 1.8% of scalers were acquired by other firms within three years of scaling up between 2014 and 2019, out of 7%-8% of scalers not found in the database. In Latvia, 0.9% to 1.8% of scalers were acquired in the same period, while the share of scalers that exited the database equals 6%-9%. In previous studies, acquisitions are found to be a rare event even for the most growth-oriented businesses (Breschi, Lassebie and Menon, 2018[2]). Former scalers with missing information are therefore likely to have ceased operations.
Scaling up brings additional challenges for SMEs. Firms may need to comply with stricter regulations, improve their managerial practices and business organisation, adapt to macroeconomic fluctuations, or expand financing channels. Some scalers may struggle with these adjustments and experience stagnation or contraction after growing. On average, across 15 countries with available data, 27% of SMEs that scale up in employment and continue operating subsequently reduce their workforce over the following three years. Similarly, 25% of scalers in turnover had a lower turnover three years after scaling up, underscoring the challenges inherent in maintaining an expanded scale.
Tightening borrowing conditions might constrain the continued growth of scalers. Before scalers start to grow, they seek external financing more proactively than similar SMEs, leading to an approximately 10% higher debt-to-assets ratio (Figure .6). As they scale up, scalers increase assets and debt, maintaining a debt-to-assets ratio 10% higher than non-scalers. Their borrowing conditions, however, worsen with higher borrowing costs. Prior to scaling up, scalers spend less on interest relative to their total liabilities than non-scaler SMEs. However, after scaling up, scalers, on average, incur higher interest expenses per unit of debt, as their financial risk increases with rising debt levels. This financial burden could impede scalers from securing additional funding needed to sustain high growth.
Debt-to-assets and interest-to-liabilities of scalers before and after scaling up, non-scalers=100, 2011-20
Note: Financial ratios “Before scaling up” are measured in the year preceding the start of the three-year scaling-up period. Financial ratios “After scaling up” are measured in the final year of the scaling-up period. Scalers are firms with 10 employees or more that grow in turnover or employment by at least 10% per year over three years. The debt/debt-to-total is total liabilities divided by total assets. Interest costs/interest-to-liabilities are total amount of interest costs divided by total liabilities.
Source: Calculations based on microdata sources from 9 countries for debt-to-assets and 7 countries for interest-to liabilities. See Annex of Chapter 1 for more information.
Scalers in the construction sector are more likely to shrink after scaling up than those in other sectors. Around 34% of scalers in the construction sector shrink after the scaling-up period, which is more than 6 percentage points higher than in other sectors (Figure .7). The dynamics of the sector differ from those of other sectors, as there is greater dependence on business cycles for the sector as a whole and large contracts for individual firms. Sharp contractions often follow rapid growth and expansion periods in the industry. These business cycles can lead to abrupt changes in demand, making it challenging for construction firms to maintain steady growth. For individual firms, a large contract (or subcontract by a larger company) can mean they hire additional workers for the job but even from the outset, without the intention to maintain their new scale.
Share of scalers by growth pattern after the scaling-up period, 2015-2020
Note: Three cohorts of scalers are analysed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. Growth patterns are observed for each cohort over the three years following their respective scaling-up periods (i.e. 2015-2018, 2016-2019, and 2017-2020). Scalers are defined as SMEs with at least 10 employees that grew in employment or turnover by at least 10%, on average, per year over 3 consecutive years. “Growing” firms grew by at least 10% in the subsequent three years. “Reversal” firms lost 10% or more of their employment or turnover and “Stable” firms had their employment or turnover change by less than 10% in the three years following scaling up.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
Supporting access to skills helps maintain growth momentum
Scalers require skilled workers to grow, especially in knowledge‑intensive sectors. More than 46% of employment scalers that provide advanced tradable services or high or medium-high tech manufacturing goods keep expanding the size of the workforce after the scaling-up period (Figure 3.7).4 These knowledge-intensive firms prioritise hiring and investing in skills before and after scaling up. Average labour costs per worker are 2-4% higher in scalers than in other SMEs before scaling up and 5-9% afterwards (Figure .8). The premium that scalers pay reflects the need to attract and retain skilled employees in a competitive labour market and is also evident in less knowledge-intensive sectors, albeit with smaller gaps between scalers and other SMEs. Developing and maintaining a skilled workforce is essential in sectors where growth is driven by innovation, adaptability, and expertise to maintain a competitive edge in their fields. Research shows that skill upgrading represents an important strategy small businesses adopt to scale up innovative efforts and increase competitiveness, adjust to new internal business structures and processes, or engage in new activities, whether by developing new product niches or entering new geographical destinations (OECD, 2023[3]).
Scalers’ average labour cost per worker by industry compared to non-scalers before and after scaling up, 2014-20
Note: Labour costs before/after scaling up are measured in the year preceding/the final year of the three-year scaling-up period. Scalers are firms with 10 employees or more that grow in either turnover or employment by at least 10% per year over three years.
Source: Calculations based on microdata sources from 13 countries. See Annex of Chapter 1 for more information.
A skilled workforce helps maintain growth momentum but often proves a bottleneck for SMEs. Skill gaps and shortages are prevalent among SMEs, which, compared to larger firms, typically have a more limited ability to leverage other sources of capital and productivity (OECD, 2023[3]). In Europe, 82% of SMEs consider workers with the right skills as very important for their business model but nearly 3 in 4 SMEs face skills shortages for at least one type of job (European Union, 2023[4]). Access to skills can be direct through hiring and training workers or indirect via the SME’s ecosystems, e.g. by collaborating with different organisations. The small workforce of SMEs limits the time staff can spend in training, and employees often combine multiple responsibilities as part of their role, which, compared to large firms, makes the development and use of targeted training offers more difficult. In this context, digitalisation offers unprecedented opportunities to access a wider range of resources through the ecosystem, especially for digital-savvy SMEs (OECD, 2021[5]).
Most SME and entrepreneurship skills policies focus on upskilling and reskilling. 80% of skills policies are upskilling or reskilling policies targeting employees or firms (Figure .9). To help SMEs cover the cost of training, several countries have introduced financial incentives, such as loans, grants or vouchers, primarily targeting green and transversal upskilling policies. For instance, Slovenia's government-backed SME agency, SPIRIT, provides expert guidance for developing circular business plans and substantial support for their implementation (Slovenia Business, 2024[6]). Participating companies can receive grants of between EUR 10 000 and EUR 90 000, helping them effectively adopt and execute sustainable business models. Few policies focus on recruitment or mobility programmes, barring some recently introduced measures. One such measure is the Critical Skills Employment Permit in Ireland, which is designed to attract highly-skilled workers and encourage them to take up permanent residency in the country.
Share of skills policies (%) by objective
Note: Based on a mapping of a total of 2 578 policy elements and 517 institutions in support of SME scale-up across 38 OECD countries. Shares are calculated as the number of policies by objective divided by the total number of SME and entrepreneurship skills policies in place across the OECD. Policies can have several delivery channels and shares therefore do not add to 100%.
Source: OECD SME and entrepreneurship policy dashboard
Policies that help SMEs access skills within their broader ecosystem represent 27% of the policies mapped. Higher education institutions (HEIs), as knowledge hubs, can play a crucial role in helping SMEs and entrepreneurs acquire skills (Pissareva et al., 2025[7]). These knowledge hubs are increasingly engaging with local actors and adapting curricula to support SMEs through training programmes. For instance, the Nova School of Business Economics, part of the Lisbon (Portugal) based Nova University, launched the Voice Leadership Initiative in 2023, offering mentoring and training to SMEs in critical areas like finance, technology, and sustainability (Nova University, 2024[8]).
Countries are implementing various policy measures to boost businesses’ transversal skills (Annex Figure .A.4). These policies primarily support the development of managerial skills in areas like strategic planning, change management, human resources, accounting, marketing, logistics, certification, and quality control, as well as entrepreneurial skills such as teamwork, resilience, self-learning, and problem-solving. As transversal policies, most do not adopt a sector-specific approach. For example, France's public development bank, BPI France, has launched the Acceleration PME programme, which offers training in leadership strategy and digital technologies, and fosters connections between SMEs and start-ups. In Lithuania, the Entrepreneurship Skills Programme provides intensive training on practical skills and knowledge for business creation and development.
Network policies encourage access to knowledge and innovation
Participating in innovation networks increases the capacity of scalers to transform and innovate. All but 2 of the 38 OECD countries have implemented knowledge and innovation network policies (Figure .10). In knowledge-based economies, regional, national and global innovation networks play an important role in firms’ growth strategies. The shift towards incremental, non-technological and open innovation models has brought new opportunities for firms that do not perform research and development (R&D) and for smaller firms to innovate, through access to knowledge and innovation networks (OECD, 2019[9]). These networks include i). Knowledge and innovation networks that connect SMEs and start‑ups with other global, national, and regional innovation system actors through collaborative R&D, open innovation, and technology transfer; ii) Strategic partnerships that link SMEs with business partners through contractual agreements, joint ventures, consortia, and other types of partnerships, often with an innovation or commercialisation purpose; iii) Clusters, which operate as networks of networks, with strong specialisation and spatial concentration features (OECD, 2022[10]).
Count of network policies by network type
Note: Based on a mapping of a total of 2 578 policy elements and 517 institutions in support of SME scale-up across OECD countries.
Source: OECD SME and entrepreneurship policy dashboard.
Most network policies aim to help SMEs access knowledge and innovation. The objective of over 60% of network policies is to integrate SMEs into knowledge and innovation networks, for 26% the objective is integration in strategic partnerships, and for 9% it is integration into clusters (Figure 3.10). The United Kingdom and Japan stand out for strong knowledge and innovation network policies. In the United Kingdom, the Catapult Network comprises technology and innovation centres connected to universities, research organisations, and firms. SMEs can use the Catapult Network to access expertise and facilities to test and improve their ideas and translate research into commercial products. The Japanese Yorozu Support Centres provide management advisory services to SMEs and micro firms. SMEs gain access to experts in fields such as management consultancy, ICT, design, and intellectual property, and receive free advice on various management issues.
About 45% of policies related to SME integration into knowledge and innovation networks have at least a partially international scope. Prioritisation of domestic or international networks varies across countries. For instance, network policies in Greece and the United States have a domestic focus, whereas those in Czechia, Finland and Slovenia tend to focus more on international networks. Almost all countries have created at least one programme to integrate SMEs with international innovation networks. For instance, Canada’s International Innovation Program supports Canadian companies in pursuing R&D collaborations with foreign partners on projects with commercialisation potential. Support is provided for R&D partnerships with Brazil, the People’s Republic of China, India, Israel and Korea. Another example is France’s International Technological Partnership Diagnostic, which encourages French SMEs to participate in international collaborative research, development and innovation programmes. It provides financial support for expenses related to setting up partnerships, including the search for partners, negotiation of the consortium agreement, use of specialised advice or service providers, preparation of responses to calls for projects and legal assistance.
Share of network policies (%) by focus area (domestic, international or both)
Note: Based on a mapping of a total of 2 578 policy elements and 517 institutions in support of SME scale-up across OECD countries.
Source: OECD SME and entrepreneurship policy dashboard
Countries use a wide range of policy approaches to integrate SMEs into innovation networks. Approaches include innovation hubs, exporting networks, incubators and accelerators, and one-stop‑shop digital portals, training, and connections to universities. Collaborative or contractual R&D policies are relatively frequent, accounting for 11% of all policies in the innovation network policy area (Annex Figure .A.5). For example, the Spanish programme “Cervera Transfer R+D Projects” supports SMEs in directly collaborating on R&D projects with research centres or contracting their R&D activities to research centres. The policy includes a partially reimbursable fixed interest rate loan, repayable over 10 to 15 years, and financial aid worth up to 90% of the total approved budget.
SMEs often make use of knowledge-intensive business services to support their innovation. SMEs frequently purchase knowledge-intensive business services (e.g., ICT, design, engineering, legal services), which complement their internal innovation activities. However, fewer than 2% of network policies support SMEs to access external (knowledge‑intensive) business services (Annex Figure .A.5). An exception is Ireland’s IP Plus programme, which offers a grant to companies to access external expert intellectual property (IP) advisory support services and to build the in‑company IP capability necessary to implement a detailed IP strategy. Incubators and accelerators often offer advisory and mentoring support to SMEs but are typically only accessible to start-ups.
Digital platforms can simplify access to information and networks. They can lower technology barriers, ease administrative processes in dealing with IP rights and access to experts, facilitate co-operation with other firms and connect potential scalers with investors who could finance research and innovation adoption projects. Three in four OECD countries include digital platforms as tools in their innovation network policies (Annex Figure .A.6). An example of using digital platforms is the Japanese Trade Tie-Up Promotion Programme that promotes business collaboration between SMEs and industry groups in Japan and abroad, facilitating business linkages, and developing markets. The programme uses an international business matchmaking website to inform SMEs about the support available to take their business abroad. Another example is Japan’s J‑GoodTech policy, which consists of an online business‑matching platform where Japanese SMEs can create partnerships with foreign companies.
Digitalisation policies are also important for scalers
Data is a strategic asset in the digital transition. Exploiting data can enable SMEs to raise their productivity (Müller, Fay and vom Brocke, 2018[11]) and drive growth in employment and revenue (DeStefano, Kneller and Timmis, 2020[12]). The importance of data use for business has grown in recent years and the COVID‑19 pandemic reinforced the crucial role of digital activities for businesses of all kinds (OECD, 2023[13]). Data governance is still an emerging policy area. Most OECD countries focus their actions on horizontal instruments (such as national strategies or action plans), thus concentrating on broader governance considerations. Improvement of the internal processing and exploitation of data is the aim of almost 3 out of 4 SME and entrepreneurship digitalisation policies mapped in OECD countries, while 1 out of 4 address access to external data (OECD, 2022[10]).
Navigating the digital transition requires SMEs to develop new skills and adapt or recombine existing skills to seize growth opportunities. Yet, SMEs still face significant challenges in responding to their increasing digital skills needs, while limited financing options make investment in skills, technology and even data management difficult (OECD, 2022[10]). Many of the current SME and entrepreneurship digitalisation policies have been introduced in the wake of the COVID‑19 pandemic and have been maintained at least through 2024 (Figure .12), in particular those supporting digital skill development. Confinement measures due to the spread of COVID-19 have accelerated uptake in e-commerce and digitalisation of administrative and business processes among SMEs (OECD, 2021[14]; OECD, 2021[15]). Yet many SMEs struggled as they lacked the resources to undertake this transformation promptly.
Policy count by year of introduction of the policy
Note: Numbers refer to all OECD countries and to policies for which a start year could be identified. Policies can aim to develop several skill areas at the same time. Based on a mapping of 244 policies and 132 institutions across the 38 OECD countries.
Source: OECD SME and entrepreneurship policy dashboard
About 40% of skills policies support SMEs in developing advanced digital skills in areas such as cybersecurity, the use of big data or machine learning.5 For example, in 2020, the Flemish government launched the Flemish AI policy plan and established the Flanders AI Academy to educate professionals on generative AI risks (Flanders AI Academy, 2024[16]). In the United States, the 2022 Cybersecurity for Small Business Pilot Programme offers financial support for small businesses to improve cybersecurity through training and counselling (U.S. Small Business Administration, 2022[17]). Austria’s Federal Ministry of Labour and Economy launched KMU Digital in 2017 to enhance SMEs’ IT and cybersecurity skills (Ministry of Economy and Labour, 2024[18]).
About one in ten skills policies aims to upskill SMEs and entrepreneurs with transversal and digital skills, highlighting an emerging complementarity between these two skill sets.6 For instance, Canada's Digital Skills for Youth Program connects unemployed graduates with SMEs, providing them with essential digital and transversal skills (Eco Canada, 2024[19]). In Austria, the public employment service agency (AMS) released a report titled "New Digital Skills," which explores future digital skill demands and emphasises the importance of both digital and transversal skills (Public Employment Service Austria (AMS), 2024[20]). Luxembourg also adopts a forward-thinking approach, incorporating elements that anticipate future skill needs and occupational trends in the labour market through its Future Skills Initiative (Lifelong-Learning.lu, 2024[21]).
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Share of scalers that reduced employment or turnover to below their initial size, 2017-20
Note: Three cohorts of scalers are observed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. The charts show the share of scalers that scaled back to a size below their initial size as of the beginning of their scaling-up period in the three years following the scaling-up period. Shares are calculated by using unweighted averages of the three cohorts for each country.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
Note: Data for Denmark separates the Missing info category into “Missing info” as for other countries and “Acquisition” in dark grey at the bottom of the bars for companies that exit the market due to being acquired. Three cohorts of scalers are observed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. The charts show the share of scalers that become untraceable in the three years following their initial scaling-up period. Shares are calculated by using unweighted averages of the three cohorts for each country. Scalers are SMEs with at least 10 employees that grew in employment or turnover by at least 10% per year, on average, during three consecutive years. Growing scalers continue to increase in employment or turnover, HG again do so by at least 10% on average per year over the three years after initially scaling up (i.e. they scale up again), partial reversal means a reduction in employment or turnover after scaling up but higher employment or turnover than before scaling up and full reversal means that the SME has lower employment or turnover three years after scaling up than it had before scaling up.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
Share of scalers that cannot be traced (and likely exit) in the three years after scaling-up, 2017-19
Note: Three cohorts of scalers are observed: SMEs that completed their three-year scaling-up periods as of 2014, 2015, and 2016. The charts show the share of scalers that become untraceable in the three years following their initial scaling-up period. Shares are calculated by using unweighted averages of the three cohorts for each country.
Source: Calculations based on microdata sources from 15 countries. See Annex of Chapter 1 for more information.
Share of skills policies by domain
Note: Unweighted shares based on a mapping of 2 578 policy elements and 517 institutions across the 38 OECD countries.
Source: OECD SME and entrepreneurship policy dashboard
Share of network policies by network type
Source: OECD SME and entrepreneurship policy dashboard
Share of network policies that use digital platforms
Note: Based on a mapping of a total of 2 578 policy elements and 517 institutions in support of SME scale-up across OECD countries.
Source: OECD SME and entrepreneurship policy dashboard
← 1. An exit rate of 1 in 10 firms is broadly in line with exit rates across OECD countries and regions (OECD, 2017[31]).
← 2. See Fackler, Schnabel and Wagner (2013[28]), Coad et al. (2018[29]) and the discussion on up-or-out dynamics in Chapter 2.
← 3. Additional efforts requiring data linking could significantly expand the number of countries with information on acquisitions as exit states, see e.g. OECD (2023[30]) for evidence for Nordic OECD countries.
← 4. Turnover scalers in knowledge-intensive sectors are also more likely to continue hiring after the scaling-up period, compared to other sectors.
← 5. Skills policies that provide either support for IT and cybersecurity (data security, IT security, cybercrime prevention etc.) or advanced digital technologies (AI, 3-D printing, use of big data, IoT, etc.) or both, according to the OECD SME and Entrepreneurship policy dashboard.