The first part of research led by Inventya under WP2 reviewed existing segmentation methods to identify their shortcomings and gaps. This highlights how identifying different segments of innovation, however important, has proven to be a very complicated process. Several researchers have attempted to measure innovations in a systematic manner and, while each methodology presents researchers with valuable insights, none of them are flawless. Moreover, even though Joseph Schumpeter outlined the theory of innovation back in the 1930s, up until 2018 there is no universally accepted technique to segment SMEs in terms of their innovation activities. At best, innovation economists employ several methodologies in order to understand what makes some companies more innovative than others.
Perhaps the most popular way of measuring innovations is by reviewing patents. Patents deal with exclusively new ideas – patent databases are accessible worldwide and are easy to use and contain a detailed description of innovative ideas. However, despite these favourable traits, patent analysis has its flaws. While patents address inventions, it is often hard to assess the economic value of these inventions. Hence, not every patented idea is worthy to be called an innovation. Yet, there is no way to evaluate the economic value solely by performing a patent analysis. In addition, the patent analysis will likely produce results with a substantial lag of up to 5 years in relation to current market trends. Nevertheless, patent analysis could be one of the best tools for SMEs innovation segmentation.
Another popular tool for innovation research is the EU Community Innovation Survey (CIS) which is conducted in every European Union Member State to collect data on innovation activities in enterprises, i.e. on product innovation (goods or services) and process innovation (organisational and marketing aspects). CIS questionnaires, however, have been evolving each year since the inception of the Survey and thus the data can be difficult to compare. Also, not every member state has reported CIS data throughout the years and several data gaps exist.
Innovation counts is an interesting methodology that the U.S. Small Business Administration (SBA) came up with in the 1980s. The SBA manually reviewed multiple trade and scientific journals identifying thousands of innovations across selected industries. While this database is now obsolete, it could be possible to reproduce the innovation counts methodology semi-automatically by pulling out data from online databases such as Angel List and Crunch Base where tens thousands of SMEs self-report innovative products and services in order to attract talent and investors.
Firms’ growth rate has been proven to be a good, if imperfect, indicator of high-quality innovation. According to NESTA in the UK, truly innovative firms tend to grow twice as fast as traditional businesses (4% vs 2% on average). One of the best ways to gain a competitive advantage is through improving products and/or services. NESTA used datasets available solely in the UK and it might be rather difficult to replicate their success in at the wider European level due to reporting disparities between Member States.
Other methodologies based on innovation inputs (R&D counts, R&D expenditures) have also been examined. However, inputs-based segmentations are often unreliable as it is impossible to accurately determine the relationship between R&D capacity and innovation outputs. There are many historical examples of highly funded companies going bankrupt despite having spent millions of Euros on building their R&D capacity.
For more detail on this part of the research see Inventya’s report D2.1 SME Market Segmentation
A key aim of WP2 was to develop a comprehensive database and dataset of variables around SME innovation to support a new segmentation. A confidential bespoke database was compiled to enable a realistic segmentation of innovating SMEs including new parameters such as smart specialisation priorities of the regions.
As highlighted in the SME Market Segmentation Report (above), market segmentation is well established as a theory but remains challenging when dealing with innovation because no consensus exists on how to benchmark innovation activities. SME policy interventions have shown attempts at segmentation, some quite sophisticated. However, there is now evidence that segmentation needs to be based on value and requirements rather than administrative definitions such as size and sector. This can help improve the incentives made available, support the development of customised marketing messages and help focus on the opportunities that can provide the best return on investment for the public sector. Consideration should be given to best value for money that would be created by supporting a group of SMEs. Value can translate into economic profitability, employment, social and environmental impact or a combination of these.
The purpose of the segmentation is to identify common characteristics that define the ‘good’ innovative SMEs; the ones that, if they benefit from incentives and support, will translate into value. A key challenge in developing the segmentation was access to key data that could represent the abilities of SMEs to translate support into economic value. Therefore, a set of simple variables was identified that could be used to develop a modern version of the ‘innovation count’, incorporating commercialisation aspects. The variables were then used to produce a quality score.
Data was collected through an online survey questionnaire across ten EU countries. Following a lightweight clustering analysis, four segments were identified and tested. The data gathered as part of the survey was then used to create a profile of the four segments:
Ground-breakers are found to be the most innovative SMEs, producing strong, patentable IP that they successfully commercialise. They are the largest recipients of R&D incentives.
Conservatives take more calculated risks but are the most successful at introducing new business models. Their innovation is not as strong, limiting their opportunities for patenting but also to access funding, making them the most dissatisfied with government R&D funding.
Casuals undertake innovation but don’t necessarily commercialise it. They are unsure of what R&D incentives are, find them complicated and time consuming.
Traditionalists are the lowest innovators in R&D. They innovate on an ad-hoc basis and don’t generally use either public or private R&D finance.
The ‘conservatives’ are the neglected SMEs because their innovation is not sufficiently strong to be patentable and ground-breaking. Further research is suggested to better understand how measures specifically targeted at this segment could boost value creation for these SMEs. A focus could be the identification of methods to support business model innovation.
For more detail on this part of the research see Inventya’s combined report D2.3/D2.4 Segmentation Methodology/Segmentation Report