A small group of SMEs that grow fast over a short period of time, i.e. “scalers”, provide a large part of the growth in jobs and economic value in OECD countries. This section contains an overview of the recent trends in the number of scalers in Germany and benchmark their contributions to job and value creation with other countries.
In Germany, about 78 000 small or medium-sized enterprises (SMEs) became scalers between 2016 and 2019, accounting for 21% of the 371 000 SMEs in the non-financial business sector. Among those, about 43 000 were scalers in employment, 56 400 were scalers in turnover, and 21 400 were scalers in both employment and turnover.
Scalers in year 2019 are defined as enterprises with 10 to 249 employees (SMEs) that increased employment or turnover by at least 10% per year, on average, over the three previous years (2016-19). This means they grow by at least 33% over the three-year period.
The number of scalers in turnover grew by 18% from 2014 to 2019, reaching 56 400. The number of scalers in employment increased by 15% over the same period. The upward trend reflects a period of economic expansion across the OECD in the wake of the Global Financial Crisis.
In Germany, scalers in employment created 1 037 000 jobs over the 2016-19 period, which accounts to 8.8 jobs for every 100 workers in SMEs in 2016. Germany belongs to the group of countries in which scalers in employment made a particularly small contribution to job creation by SMEs. The group also includes Belgium, Estonia, and Austria.
The total turnover of German scalers in turnover in 2019 was EUR 333 billion larger than in 2016. The increase corresponds to 15% of the total turnover of all German SMEs in 2016. This compares to 20% on average across countries with available data, indicating that the contribution of scalers in turnover to value creation is about 25% lower in Germany.
All types of SMEs can scale up. This section describes the characteristics of scalers in terms of sector of activity, size, age, and geographical distribution. It also compares the likelihood of SMEs to scale up in Germany and in other countries across different groups of SMEs.
Most German scalers operate in non-tradable services, other tradable services, and advanced tradable services (20%, 19%, and 17%, respectively). The distribution of scalers across economic activities mirrors largely the distribution of SMEs across these activities.
However, in certain sectors scalers are overrepresented, particularly in advanced tradable services, which comprise 17% of scalers but 12% of SMEs. This reflects the higher probability of SMEs to scale up in these sectors.
Sector groups include the following two-digit NACE sectors:
• Low and medium-low technology manufacturing and extractive industries: food, textile, paper, wood, refined petroleum, rubber, plastic, basic metal products, mining.
• Medium-high and high technology manufacturing: chemical products, pharmaceuticals, computer, electronic/electrical equipment, machinery, transport equipment.
• Advanced tradable services: software, telecommunications, consultancy, legal services, accounting services, architectural activities, scientific research.
• Other tradable services: travel agency, services to buildings/landscape, employment activities, veterinary, accommodation/food services, services for transportation.
• Other non-tradable services: electricity, gas and water supply, waste management, wholesale and retail trade, repair of motor vehicles/household goods, real estate activities.
• Education, social care and health services: Education, human health activities, residential care, social work.
• Construction: construction of buildings, civil engineering, specialised construction activities.
Source: Manufacturing sectors are aggregated using Eurostat’s high-technology classification of manufacturing industries. The classification of tradable and non-tradable services is based on Piton, S. (2021). Economic integration and unit labour costs. European Economic Review, 136, 103746.
More than 52% of German scalers have between 10 and 19 employees at the beginning of the growth period, and 31% have between 20 and 49 employees. In contrast, SMEs with 100 to 249 employees represent only 6% of scalers. Compared to all SMEs, scalers are overrepresented among the smallest SMEs with less than 20 employees, as in Germany these SMEs have a higher likelihood to scale up than larger SMEs with 20 employees or more.
Most German scalers (63%) are mature SMEs that are more than 10 years old. 20% of scalers are less than 6 years old (i.e. young) and the rest (17%) are between 6 and 10 years old.
Most German scalers are located in (large) metropolitan regions (78%). This reflects the overall geographical distribution of economic activity in the country, as the shares of scalers and all SMEs are very similar across typologies of regions.
The OECD metropolitan/non-metropolitan typology for small regions (TL3) helps assess differences in socio-economic trends in regions by controlling for the presence/absence of metropolitan areas and the extent to which the latter is accessible by the population living in each region. TL3 regions are classified as “metropolitan” if more than half of their population lives in a functional urban area (FUA) of at least 250 000 inhabitants and as “non-metropolitan” otherwise. A “metropolitan region” becomes a “large metropolitan region” if the FUA accounting for more than half of the regional population has over 1.5 million inhabitants. The typology further classifies “non-metropolitan” regions based on the size of the FUA that is most accessible to the regional population. More specifically, “non-metropolitan” TL3 regions are subclassified into three possible types: i) with access to a metropolitan area, if at least half of the regional population can reach an FUA of at least 250 000 inhabitants within a 60-minute car ride; ii) With access to a small/medium city, if at least half of the regional population can reach an FUA of between 50 000 and 250 000 inhabitants within a 60-minute car ride; iii) remote, if reaching the closest FUA by car takes more than 60 minutes for more than half of the regional population.
Source: Fadic, M., et al. (2019), ‘Classifying small (TL3) regions based on metropolitan population, low density and remoteness’, OECD Regional Development Working Papers, No. 2019/06, OECD Publishing, Paris, https://doi.org/10.1787/b902cc00-en
While many SMEs consolidate at their new size after scaling up, rapid growth also brings new challenges, with some scalers failing to adapt. This section illustrates the growth trajectories of scalers in the three years following their (first) expansion phase.
Between 2016 and 2019, 18% of German scalers in employment continued to scale up in employment after a first scaling up in the previous three years. Among scalers in turnover, 20% achieved two high-growth periods in a row.
Despite the relatively small share of German scalers continuing to scale up in the following three years, the share of scalers that maintained their size or grew moderately are the highest among all countries included in the analysis. Specifically, 50% of scalers in employment and 48% of scalers in turnover maintained their size or grew moderately in the following three years.
Scaling up also brings challenges for SMEs. Firms may need to comply with stricter regulations, improve their managerial practices, or adopt a different financial model. Some scalers may struggle to adapt and experience a contraction after growing. In Germany, 27% of SMEs that scale up in employment between 2013 and 2016 reduced their workforce over the following three years. Similarly, 27% of scalers in turnover had a lower turnover three years after scaling up, underscoring the challenges inherent in maintaining an expanded scale.
For 5% of scalers in employment and 5% of scalers in turnover, there was no information available on their employment or turnover levels in 2019. This lack of information is open to different interpretations. First, the firm may be closed or about to close, which in most cases indicates that the business has not been successful. Second, the company may have been acquired by another entity, which often indicates success rather than failure. Third, the lack of information may simply be a “nuisance” in the data, e.g. due to reporting errors. It is not possible to know the exact incidence of each of the three alternatives. However, it is known that acquisitions are rare events even for growth-oriented businesses. Conversely, around 8-10% of businesses close each year. Therefore, it is likely that most former scalers with missing information have ceased operations.