If access to innovation assets is critical for firms to compete in a knowledge-based economy, the challenge is particularly acute for SMEs. SMEs face specific barriers in finding and managing the technology, data and networks that enable innovating. SMEs also engage less in R&D and, while they are more dependent on external sources of knowledge, they are also less well integrated into knowledge networks. This chapter presents recent developments in innovation diffusion in SMEs. It explains how SMEs can benefit from new business models and organisational practices that require greater product differentiation and shorter time-to-market. It takes stock of SME digital transformation through cloud computing or big data analytics. The report explains the importance of data as a source of competitiveness and the specificity of SME strategies in terms of data protection, as well as the role of open innovation and the platform economy in scaling up SME networks. The chapter concludes with recent policy developments for innovation diffusion in SMEs, e.g. by accelerating their digital transition, better targeting innovation support packages to smaller firms, often on a place-based or sector-wide basis, building clusters, incubators and accelerators, enacting open data and adapting intellectual property rights framework to SMEs.
OECD SME and Entrepreneurship Outlook 2019
Chapter 7. Access to innovation assets
Abstract
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
Highlights
SMEs are primary sources of innovation but struggle combining different innovation modes that would require a larger portfolio of innovation assets.
The rise of customer-centric business models is likely to benefit SMEs, digitalisation allowing greater mass customisation and new strategies (e.g. commercialisation of beta versions, lead time advantage) reducing radically the distance and time to markets. Business-to-business (B2B) practices are to adapt with more integrated and reactive supply chain systems and smart factories.
Yet SMEs’ lag in digital technologies adoption could jeopardise their transition towards the next production revolution. The greatest acceleration in digital diffusion in recent years has been in the conduct of big data analysis and the purchase of cloud computing (CC) services. SME use of CC is likely to intensify if trust-related barriers to adoption are overcome.
Open innovation (OI) is on the rise. Large firms are taking active part in the transformation of business ecosystems through business accelerators and innovation labs involving innovative SMEs and public research. Open sourcing has spurred a democratisation of innovation.
Data is the new gold. Data access and protection are more than ever strategic to the firm. Hyperconnectivity, sensors and internet-based activities are creating an unprecedented volume of data. But digitalisation also makes trade secret protection increasingly difficult. Progress in SME patenting may remain limited for lack of awareness, interest and a limited SME participation in business R&D.
Governments aim to ensure SMEs keep pace with technological change and the industrial transformations at play through SME-targeted financial support and technical assistance, often on a place-based or sector-wide basis.
SME policy considerations are increasingly mainstreamed in innovation policy making. Innovation support packages are revamped for better targeting SMEs. Cluster policies are evolving with a view to scaling up innovation networks through stronger industry-science and more cross-sectoral interactions. Accelerators and incubators are also popular instruments for supporting start-ups.
Open Government Data (OGD) initiatives bring opportunities for SMEs to access new data at reduced costs. At the same time data protection is being legally reinforced and efforts are made to harmonise legislations across jurisdictions and assist SMEs in using intellectual property rights (IPRs).
Whys is it important?
Innovation results from a process of knowledge accumulation. Firms create, acquire and recombine innovation assets1 which allows them designing and introducing new products and services, implementing new processes or adopting new organisational and marketing practices (OECD/Eurostat, 2005[1]).
The changing nature of innovation has altered the conditions under which firms innovate and modified the range and importance of the innovation assets they use. The shift towards more 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 scale actors. Innovation modes have diversified as firms increasingly combined different approaches and invested in complementary assets, such as technology, firm-specific skills and know-how, data and brands, organisational settings and processes, and business models and networks (OECD, 2009[2]; OECD, 2015[3]).
Small and medium-sized enterprises (SMEs) are primary sources of innovation. Based on national innovation surveys that cover firms with 10 employees or more, SMEs account on average for over 90% of the innovative firms (as broadly defined in the Oslo Manual (OECD/Eurostat, 2005[4])) and incur between 20% and 60% of business expenditures on product or process innovation (EU data, 2016) (Figure 7.1). Their contribution to innovation remains however subdued as compared to the large population of firms they account for. In addition data gap makes it difficult to extrapolate on the participation of micro firms in innovation.
SMEs play a key role in shifting innovation models by adapting supply to different contexts or user needs and responding to new or niche demand (see also the chapter on market conditions). Innovative start-ups bring new ideas into the market by tapping into knowledge generated but not commercialised by existing firms (Acs et al., 2009[5]; OECD, 2016[6]). Smaller firms also have a competitive edge due to their higher risk acceptance, greater flexibility, greater ability to integrate complex sets of information and technologies, more agile and adaptive organisational culture, as well as greater cohesion and sense of collective purpose, that help them overcome their size-related disadvantages (OECD, 1998[7]). In some strategic sectors such as software, nanotechnology, biotechnology and clean technologies, new and small firms are also important drivers of the sector’s growth, as they bear the risk and costs of early market developments.
Figure 7.1. SMEs are primary sources of innovation
SMEs as a percentage of total innovative firms (bars) and innovation expenditure (diamonds), 2016
Note: Covers firms with 10 and more employees.
Source: Eurostat (2019[8]), Eurostat Community Innovation Survey (CIS‑2016), https://ec.europa.eu/eurostat/web/products-eurostat-news/-/DDN-20190312-1.
In fact, SMEs are comparatively less at difficulty in performing a specific type of innovation than in combining different innovation modes that require mobilising a larger portfolio of innovation assets (Figure 7.2). Business innovation surveys show that SMEs are more engaged in new organisational or marketing practices than large firms and in some cases even more innovative for developing new products and processes. With few country exceptions, the percentage of firms engaging in non-technological innovation (to the exclusion of other modes of innovation) is notably higher among SMEs than among large firms, reflecting also a sectoral bias towards services where SMEs concentrate and where innovation is in essence more incremental and non-technological.
If access to innovation assets is critical for firms of all sizes, the challenge is particularly acute for SMEs that confront specific barriers in finding and using the technology, data, information and networks that would enable them participating in and benefiting from innovation activities. For instance, small enterprise owners are often unaware of the potential new digital tools could offer for improving their business or they consider the upfront costs of upgrading towards more sophisticated digital technologies as too high (OECD, 2017[9]). Smaller firms are less likely to engage in R&D, for both lack of capacity and incentives. Acquiring frontier technology and advanced skills for performing increasingly costly and multidisciplinary research (OECD, 2016[10]) remains out of the reach of smaller players or require them high specialisation that limits the scope of R&D spillovers and ultimately reduces the financial incentive of taking risks. In addition SMEs tend to be more dependent on external sources of knowledge but they are also less well integrated into the local, national and global innovation networks that would help them capture knowledge spillovers (OECD, 2013[11]).
Figure 7.2. SMEs struggle to combine innovation modes that require larger knowledge endowment
Percentage of innovative firms in each size category by mode of innovation, 2016 or latest available year
Note: Technological innovation includes product and process innovation; non-technological innovation includes organisational and marketing changes (OECD/Eurostat, 2005[1]). Size is calculated on the basis of numbers of persons employed. SMEs are defined as businesses with 10 to 249 employees and large firms as businesses with 250 employees or more. International comparability may be limited due to differences in innovation survey methodologies and country-specific response patterns. Data for non-EU countries are drawn from the OECD STI Scoreboard 2017 based on the 2017 OECD survey of national innovation statistics and national sources, http://oe.cd/inno-stats, June 2017 and refer to 2012-14. Please refer to http://dx.doi.org/10.1787/888933619353 for further information.
Sources: Eurostat (2019[8]), Eurostat Community Innovation Survey (CIS‑2016), https://ec.europa.eu/eurostat/web/products-eurostat-news/-/DDN-20190312-1; OECD (2017[12]), OECD Science, Technology and Industry Scoreboard 2017: The digital transformation, http://dx.doi.org/10.1787/9789264268821-en.
Innovation and knowledge diffusion in SMEs: Recent trends
Socio-economic systems and business environment worldwide are going through deep and irreversible transformations driven by fast digitalisation and technology convergence (OECD, 2016[10]; OECD, 2018[13]).
Combined together, the Internet of Things (IoT, i.e. hyperconnectivity of devices, sensors and systems that supports machine-to-machine communication and enables the generation of unprecedented volume of data), cloud computing (CC, that allows storing and processing more information at more affordable cost) and data analytics (that leverages machine learning and new algorithms for data exploration and market intelligence) are likely to increase firms’ capacity for simulation, prototyping, decision making and automation (OECD, forthcoming[14]). These three emerging technologies hold the premises of the next production revolution (OECD, 2017[15])
This fast-changing environment is creating unprecedented opportunities for SMEs to scale-up their internal capacity, reach scale without mass and embrace new business perspectives, provided they succeed managing their own transformation.
SMEs are to benefit from the rise of new business models and practices
ICT have been major disruptors of business practices, firms increasingly using the Internet for operational matters, including ordering, selling, marketing or online banking, and for interacting with business partners and public authorities (OECD, 2017[16]). ICT have also contributed to change consumer behaviours and expectations by enabling the rise of a more sophisticated and better informed demand and by shortening innovation cycles and time to market.
Customer demand has evolved towards more personalised, tailor-made and on-demand products and services. The fragmentation of final demand into a myriad of business segments has prompted firms to develop more customer-centric strategies and to adopt a ‘segment-of-one’ approach in marketing products and services.
In this changing landscape, SMEs have new opportunities to position and compete on niche markets and to take advantage of the closer proximity to demand that new consumption models require. But customisation also raises difficulties, especially for smaller scale firms, as regards their capacity to increase variety while reducing unit costs.
Digital technologies provide opportunities for greater mass customisation. The IoT and big data analytics can help enhance customer behaviour analysis and create new knowledge for product differentiation and customisation, for better anticipating user expectations and for improving customer experience. 3D printing is possibly another main driver of mass customisation and the range of applications is likely to further expand as the technology matures, printing costs reduce and access to printing materials broadens2. Examples of digital-driven business innovation spread across all sectors and are already transforming traditionally SME-dominated industries3 (Box 7.1).
For instance, the retail sector is experiencing a deep digital transformation. E-commerce has been a game changer and a major driver of disruptive innovation in business-to-consumer (B2C) and business-to-business (B2B) markets. The number of firms engaging in e-retail has increased over the past years, increase observable across all firm size classes and countries (OECD, 2017[16]). The turnover generated by e-retail has grown (OECD, 2017[12]) and Internet-based companies such as Amazon and Alibaba have entered the top of capitalisation markets in positions that used to be hold by the giants of the oil and bank industries. E-retail has disrupted B2C practices but less so because of its –all in all- minor contribution to the sector’s turnover (less than 10% in the United States and Europe in 2015 (OECD, 2017[12])) but because of its strong influence on customer shopping decisions and the incentive it gave to traditional “brick and mortal” shops to reshape their business models (Box 7.1).
Box 7.1. Disruptive innovation in business models and organisational practices: selected examples in three SME-dominated sectors
E-commerce has been a major driver of changes in trade business practices. Most brands already propose smart applications to check product availability, shop and plan delivery at the consumer convenience. The NikeID platform enables customers to design and shop personalised sportswear online. The Dash Replenishment Service of Amazon allows measuring product usage at home and reordering through connected devices. Alibaba’s new chain of grocery stores integrates offline and online shopping by combining smart apps, big data, mobile payment service and in-house transportation system (e.g. Hema, China). This new generation of groceries proposes big-data-optimised offerings, product traceability and cashierless payment with on-the-spot services (e.g. cooking).
Physical shops are also at the dawn of a revolution as they adapt to new market conditions and offer customer experience that cannot be replicated online. New business models target and follow shoppers from their entry to their exit from the stores and along the entire path-to-purchase. Beakons transmit Bluetooth signals to nearby smartphones proposing promotional offers even before customers enter the stores (e.g. Macy’s, USA). Shopping assistant robots provide in-store services, check stocks and collect data on customer behaviours (e.g. Walmart, USA; SoftBank Mobile, Japan). Smart fitting rooms equipped with virtual augmented reality mirrors and sensors enable customers to create an outfit, try it without underdressing and share for comments on social media via their mobile phone (e.g. Van Heusen, USA). Cameras and sensors track what shoppers remove from the shelves and charge them as they walk out with the products in hand, removing checkout lines and waiting queues (e.g. Amazon Go Store, USA).
Emerging consumption practices require revamping supply chains. Wholesale business is to adapt its operational capability accordingly. The radio frequency identification (RFID) technology supports integrated business intelligence system. Combined with the IoT and sensors installed along the supply chain it allows tagging and tracking each piece or product from factory to distribution platforms to the shop until its final sale and enables real-time inventory and greater visibility on product availability (e.g. Inditex, Spain).
In the construction sector, the Building Information Modelling has changed the way construction professionals work together by reinforcing co-ordination. The structures, pipes and other building components are integrated into a smart 3D model that evolves as work progresses. This digital twin allows collecting and sharing information over the life cycle of the building and improving construction and future maintenance (e.g. Grand Paris Express, France). Sensors on construction sites help gather real-time data on people, materials and displacements and improve preventive maintenance and efficiency. Drones are increasingly used to monitor and secure construction sites, making the construction industry one of the main business sectors for drone tech application.
In the accommodation services, the famous short-term lodging model introduced by AirBnB creates a substitute offer to hotels by providing a marketplace where travellers and local home owners can connect. In food services, the use of tablets in restaurants is picking up, allowing speeding up orders, sending commands to kitchen in real time and improving service while collecting consumer data. Self-driving cars and drones are also poised to open new avenues for food delivery.
Sources: See web references.
Shopper experience is being radically altered by combined applications of IoT, artificial intelligence, facial and move recognition, virtual reality and smartphone and data technology. As to meet the expectations of the next consumer generation, the retail trade is likely to extend its physical presence, via different partnerships, store formats and mobile applications, offering differentiated and inventive experiences to attract customers back into stores on a regular frequency (Deloitte, 2018[17]).
B2B practices and wholesale services are to adapt accordingly. Digitalisation is transforming supply chain operation technologies and processes and shifting the frontiers of manufacturing systems. Smart factories are moving away from the traditional linear and sequential automation processes towards a more interconnected, open system of supply operations with enhanced integration of operational systems, manufacturing and end-to-end value chain (Mussomeli and Gish, 2016[18]). Customer data that are increasingly collected through feedback on social media and digital platforms is also more and more integrated in product conception and early phases of development.
As demand is increasingly met at the individual level, reducing distance and time to markets has become critical with implications for transportation systems, modes of delivery or corporate location strategies (Backer et al., 2016[19]). In addition paths from research and design to experimentation to market introduction have shortened, with businesses moving faster to commercialisation through beta versions of products that could give them the first mover advantage, by setting industry standards, raising their visibility and increasing user costs of switching to alternative models or branding.
Organisations are restructuring accordingly. Firms re-organise internal functions along agile management principles, i.e. smaller cross-disciplinary teams working in less hierarchical settings and covering end-to-end process cycles, with a view to foster cooperation between teams and speed decision making process.
Cloud computing is a pivotal asset for SME digital transition
Digital technologies offer a number of opportunities for SMEs to better integrate their operations, reduce costs and expand into new markets. Information and communication technologies (ICT) empower SMEs, as they alter market conditions, reduce the structural size-related disadvantages SMEs face in accessing resources and business partners, reduce the level of production needed to reach minimum cost per unit, enabling reaping economies of scale without mass, and create new market outcomes and marketplaces (OECD, 2010[20]).
Cloud computing allows SMEs accessing extra processing power or storage capacity, as well as databases and software, in quantities that suit and follow their needs. In addition to its flexibility and scalability, CC reduces costs of technology upgrading by exempting firms of upfront investments in hardware and regular expenses on maintenance, IT team and certification (see chapter on infrastructure). Overall, the first uses for which firms turn towards CC are email services and storage capacity, then accessing office software and hosting databases (OECD, 2017[21]).
Likewise, Enterprise Resource Planning (ERP) systems enhance back office efficiency as they integrate the management of internal and external information flows, from material and human resources to finance, accounting and sales, and automates planning, inventory, purchasing and other business functions. On the other hand Customer Relationship Management (CRM) and Supply-Chain Management (SCM) software are used for managing a company’s interactions with its customers, clients, prospects, employees and suppliers and help enhance front office integration (OECD, 2017[22]; Andrews, Nicoletti and Timiliotis, 2018[23]).
Nonetheless, although the majority of businesses are connected, ICT are still primarily seen as a communication tool and adoption rates tend to decrease as technologies become more sophisticated (Figure 7.3). Having a website has become a common practice (73%-94% of firms) and using social media for business purposes is frequent (48%-71% of firms). Firms performing data analytics are conversely less widespread (10%-33%).
Figure 7.3. Digital diffusion tends to slowdown as firms get smaller
OECD unweighted average, 2018 or latest year available
Note: Adoption rates are the percentage of firms using the related software, tools or services. Gaps in technology diffusion are the difference between the OECD average diffusion rate for a size group of firms with the OECD average diffusion rate for another size group of firms. Digital transformation speed is the average annual growth rate in technology adoption rates between 2014 and 2018. Unweigthed averages are computed for countries for which data are available. Firm size classes are defined by employment size. Small firms employ [10-49] employees; medium firms [50-249] and large firms more than 250 employees.
Source: OECD (2019[24]), OECD ICT Access and Usage by Businesses Database 2019, http://stats.oecd.org/Index.aspx?DataSetCode=ICT_BUS (accessed on 15 February 2019).
Adoption patterns tend also to differ across firm size classes and technologies. Small firms are particularly less likely to use ERP systems than large firms (Figure 7.3). Firms adopt ERP systems when they reach a critical size that allows them dealing with the complexity and the significant amount of time, financial resources and reskilling required for ERP implementation (Andrews, Nicoletti and Timiliotis, 2018[23]). Consequently, the ERP diffusion gap is significantly larger between medium and small firms than between large and medium-sized firms. The reverse is true for supply-chain management software, cloud computing or big data analytics for which the digital gap enlarges between medium and large firms.
Although small firms appear comparatively less at disadvantage in using cloud computing services or performing big data analytics, the digital gap with larger firms remain striking (Figure 7.4). Nordic countries show higher adoption rates across all firm size classes. Turkey, Korea and Mexico show the lowest adoption rates for all firms. In Belgium, Japan and Slovenia, the digital gap between large firms and SMEs is particularly marked.
Digital transformation occurs at different speeds (Figure 7.3). SMEs are catching up larger enterprises in using social media whereas the adoption of business intelligence and supply-chain management software have little progressed between 2014 and 2018, especially among smaller firms.
Figure 7.4. SME lag in adopting cloud computing could hold back their digital transformation
CC adoption rates in 2018 and increases in adoption rates over 2014-18 by firm size class
Note: Small firms employ [10-49] employees; medium firms [50-249] and large firms more than 250 employees. Adoption rates are the percentage of firms purchasing CC services in 2018. Increases in adoption rates are computed as average growth rates between 2014 and 2018. Data for Japan are collected following a different methodology and exclude firms with less than 100 employees. Data refer to 2014 and 2018 or nearest year available. Countries are ranked by descending order of 2018 diffusion rates in medium-sized firms.
Source: OECD (2019[24]), OECD ICT Access and Usage by Businesses Database 2019, http://stats.oecd.org/Index.aspx?DataSetCode=ICT_BUS (accessed on 15 February 2019).
The greatest acceleration in technology diffusion over a couple of years only, has been observed in the conduct of big data analysis albeit starting from low levels. Firms have also increasingly turned towards the cloud for accessing emails, storage or data management capacity (Figure 7.3). The acceleration in CC diffusion has been uneven across firm size classes and patterns of diffusion vary from one country to another (Figure 7.4). CC diffusion among large firms has steadily outpaced diffusion among SMEs in countries achieving technological catch-up (e.g. Czech Republic, Lithuania and Slovak Republic). In Nordic countries, there are rather consistent increases of absorption rates across all firm size classes while in Belgium, Latvia, Spain and the UK small firms seem to have moved faster to CC than their larger counterparts.
Reasons for the rapid diffusion of CC are manifold. In addition to its intrinsic values, cloud computing serve the dissemination of other technologies (Annex Figure 7.A.1) and enable technological catch-up. New mobile forms of work have also contributed to increase its popularity as firms were able to adopt platform-independent technologies that could be accessed anywhere and from any device (e.g. smart phones, desktops, laptops etc.).
SME use of cloud computing services is therefore likely to expand in a near future, especially as SME owners get increasingly aware of CC potential for gaining flexibility and reducing costs, general diffusion increases pressure from competitors and business partners to follow the trend and barriers to adoption are progressively overcome.
In that respect, trust issues remain a major obstacle to CC adoption, SMEs showing more reluctance than large firms (OECD, 2017[22]). It has become apparent that the preservation of data sovereignty, integrity and security is a key reason for SMEs not to abandon on-premise IT and data solutions. The loss of data control is indeed closely associated to the uncertainty of data location that raises uncertainty around the data protection regulation that applies and the jurisdictions under which it is enforced. Likewise the lack of open standards within the cloud providers’ community increases the difficulty for CC users to switch between providers and the risk of technological lock-ins. As a consequence, users can become extremely vulnerable to providers’ price policy, especially as new development in data analytics will allow them profiling their users and discriminating prices. Fears are further exacerbated by the current high market concentration of the cloud industry (Kushida, Murray and Zysman, 2011[25]).
Data is the new gold
Data has become a strategic asset for a firm’s and a country’s competitiveness. Data are increasingly generated along business operations, e.g. production and delivery (process data), and compiled at various stages of business transactions (user, consumer and supplier data). Process data can improve stock management, logistics and maintenance, and business reactivity to just-in-time production requirements. They also increase the scope of efficiency gains including in terms of energy and resource consumption. User, consumer and supplier data are crucial for developing market knowledge, improving customisation and shaping new products and business models.
Consequently, data access and protection are more than ever strategic to the firm.
Although Intellectual Property Rights (IPRs) are instrumental for firms to ensure they can appropriate the full benefits of their innovations, they are not popular among SMEs (Box 7.2). Even when active in innovation, SMEs use less formal IP instruments than large firms (OECD, 2011[26]). And when they adopt formal IPRs, they tend to use copyright or trademarks above all other instruments, particularly patents. A recent study by the European Patent Office (EPO) shows that SMEs and individual inventors account for only 28% of all applications filed at the office in 2016, up to 26% the year before (European Patent Office, 2017[27]).
Box 7.2. Trade secrecy and IPRs: How SMEs protect and appropriate knowledge
IPRs range from patents to copyrights, to trademarks or to design, each instrument offering exclusive rights to their owners on different forms of tangible and intangible assets (OECD, 2015[28]). This variety reflects the multidimensional nature of innovation and innovation assets.
IPRs can help SMEs position themselves competitively vis-à-vis large enterprises in global markets, open up new or existing segments in markets, gain additional revenues and serve as collateral or guarantee for bank lenders and investors.
Yet few SME filed patent applications. There are several reasons behind this low popularity of IPRs among SMEs. SMEs lack awareness and expertise, as well as resources, for applying and managing an IPR portfolio. And in response, there are few regulatory frameworks or specific instruments directed to SMEs (OECD, 2011[26]). Obstacles also arise when SMEs operate internationally and have to deal with legal overheads, cross-country filings, regulatory and technical differences, as well as differences in local IP enforcement practices (OECD, 2011[26]). Not specific to SMEs but to the business environment they evolve in, technological change and innovation cycles in some sectors (e.g. software) are more rapid than IP and patent application process, reducing the economic advantage of patenting and licensing (OECD, 1998[7]).
Trade secrecy is confidential business information that can cover new manufacturing processes, improved recipes, business plans or commercial information on whom to buy from and whom to sell to (e.g. customer list). Unlike patents, trade secrets are protected by law on confidential information, e.g. confidentiality agreement, or non-disclosure or covenant-not-compete clauses.
Trade secret popularity holds on its relative ease of use (due to low technicity and the absence of formal registration requirements), lower costs incurred for administration and the absence of definite term of protection. Trade secrets apply to a range of approaches used by SMEs and can help them capture the value of their innovations, reinforce strategies such as lead-time, product complexity and customer-driven innovation, or support innovation modes emphasizing incremental change and open collaboration: (Brant, 2014[29]).
In fact trade secrecy and patents complement each others. Trade secret law “plugs several holes in the patent statute” (Friedman, Landes and Posner, 1991[30]) and both offer SMEs distinct tools for a comprehensive IP protection. Trade secrets are more likely to be used (often without patents) for process innovation and for innovations in services (where SMEs are majority) while patents are more likely to be used (alone or in combination with trade secrets) when the innovative product is a physical good (EUIPO, 2017[31]). Trade secrets can also be more suitable for inventions that do not meet the criteria for patentability, especially in profitability terms and at the early stages of product development. On the downward side, trade secret law is more difficult to enforce than a patent; it does not protect from fair discovery or reverse engineering and the secret is lost when disclosed. Also trade secret laws are set within national legal frameworks limiting transnational knowledge transfers.
Sources: OECD (2015[28]), Enquiries Into Intellectual Property’s Economic Impact, http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=DSTI/ICCP(2014)17/CHAP1/FINAL&docLanguage=En (accessed on 13 March 2019); OECD (2011[26]), Intellectual Assets and Innovation: The SME Dimension, http://dx.doi.org/10.1787/9789264118263‑en; OECD (1998[7]), Technology, Productivity and Job Creation: Best Policy Practices 1998 Edition, http://dx.doi.org/10.1787/9789264163416-en; Brant, J. (2014[29]), “Trade Secrets: Tools for Innovation and Collaboration in Innovation”, https://cdn.iccwbo.org/content/uploads/sites/3/2017/02/ICC-Research-Trade-Secrets-english.pdf; Friedman, D., W. Landes and R. Posner (1991[30]), Some Economics of Trade Secret Law, https://www.jstor.org/stable/1942702?seq=1#metadata_info_tab_contents; EUIPO (2017[31]). Protecting Innovation through Trade Secrets and Patents: Determinants for EU Firms, https://euipo.europa.eu/tunnel‑web/secure/webdav/guest/document_library/observatory/documents/reports/Trade%20Secrets%20Report_en.pdf (accessed on 13 March 2019).
Instead, SMEs tend to privilege trade secrecy as their default mode of data protection. Past surveys have showed that small firms consider trade secrecy as an important means for protecting innovation (Cohen, Nelson and Walsh, 2000[32]; Jankowski, 2012[33]; Hall et al., 2014[34]), with the lead time advantage -that is a primary mechanism of IP appropriation in some industries- and on-purpose complex product design -that aims to discourage competitors from engaging in counterfeiting (Rujan and Dussaux, 2017[35]; Hughes and Mina, 2011[36]).
Nonetheless the protection of trade secrets is becoming increasingly difficult. Digitalisation and the revolution in data codification, storage and exchange (i.e. cloud computing, emails, USB drives) are prime drivers of a rise in trade secret infringements. Increasing value given to IP (and de facto its misappropriation), staff mobility and changing work culture and relationships (e.g. temporary contracts, outplacement, teleworking) or the fragmentation of global value chains (with more foreign parties involved within more diverse legal frameworks and uneven enforcement conditions) also contribute to increase exposure and risk of disclosure (Almeling, 2012[37]).
Although estimating the economic costs of trade secrets remains challenging, the literature provides converging figures on the large damages incurred by firms whose know-how and confidential information were unduly misappropriated. The cost of trade secret theft to US firms was estimated to USD 300 billion annually (Almeling et al., 2010[38]). Based on interviews with members of the European Chemical Industry Council, misappropriation of confidential business information is estimated to costs a firm 30% of its revenue or more (CEFIC, 2012[39]). Trade secret litigation in US federal courts has grown exponentially over the past three decades, roughly doubling every decade, with colossal sums conceded in damage awards (Almeling, 2012[37]).
Increases in SME patenting in a near future are likely to remain limited. Some improvements might be observed as SMEs get increasingly aware of the benefits of patenting and licensing for consolidating partnerships and attracting investors. And increases might be more substantial in sectors that are traditionally prone to file patents, such as ICT, chemicals and medical devices, or in technology areas that are currently experiencing patent burst, such as digital data transfer or payment protocols (OECD, 2017[12]). But the still limited SME participation in business R&D will (somehow mechanically) weight on their patenting interests and intentions.
Digitalisation could however bring new solutions for IP protection. Blockchains technology could offer a secure and efficient alternative form of IP protection as they support data encryption, proof of existence and transactions with total disintermediation and transparency. Typically trade secret protection is provided through confidentiality provisions in contracts. Blockchain enables the design, execution and enforcement of smart contracts that can protect trade secrets at no additional cost.
SME participation in R&D remains limited overall, with large country differences
Business research and development (R&D) activity is typically concentrated in a relatively small portion of the business population, especially large firms (see chapter 4 on infrastructure). Even if one cannot exclude that an important part of SME total R&D may be informal, performed outside R&D department or ill-captured by official statistical system, SMEs hardly average 17% of total corporate R&D expenditure in the OECD area (Figure 7.5).
Country situations differ though. In Iceland and Latvia, SMEs contributed in 2016 to over 70% of total business efforts whereas they account for less than 10% of total business expenditure on R&D (BERD) in large industrial R&D players such as Germany and Japan. In the United States, according to the definition used, 10% of BERD is performed by firms with less than 250 employees and 14% by firms with less than 500 employees.
Cross-sector specificities also matter. In science-driven sectors (e.g. biotechnology or nanotechnology), small businesses are often the source of radical innovations and bear the risks of the research endeavour, their greater flexibility enabling them to work outside of dominant knowledge paradigms.
Figure 7.5. Few SMEs participate in R&D with little progress made in recent years outside Europe
Share of business R&D expenditure performed by SMEs, 2016 and trends in main regions, 2010-16
Note: SME definition includes firms with less than 250 employees, except for the United States where data also include firms with 250-499 employees. Data for Australia refer to 2011. OECD and EU totals are estimates.
Source: Author’s estimates based on OECD (2019[40]), R&D Statistics Database, March, www.oecd.org/sti/rds (accessed on 08 March 2019).
Overall little progress has been made in increasing SME participation in R&D since 2010 in the OECD area. R&D survey data show increases in SME share of total BERD in Australia and most European countries with more significant shifts in Finland, Latvia or Portugal. Drops have conversely been recorded in the Czech Republic, Estonia, Greece or New Zealand.
Future developments remain uncertain but radical improvements in SME contribution to R&D are unlikely for structural reasons. Progress made in some EU countries might however consolidate under the impulsion of the EU Horizon 2020 framework programme that gives SMEs particular attention. SMEs accounted for 20% of total H2020 participations in 20174.
SME capacity of building and scaling up networks is determinant for their growth outlook
Business innovation, no longer confined to corporate R&D labs, is increasingly the results of collaborative efforts between business partners that interact, exchange knowledge and information and share standards and infrastructure. This shift towards an ‘open innovation’ (OI) paradigm has considerably reduced the investments needed to access innovation assets, making the innovation endeavour more accessible to SMEs (OECD, 2010[20]).
Business linkages act as channels for accessing technology, skills or for fostering data exchange and knowledge spillovers (OECD, 2018[41]). Firms engaged in buyer-supplier relationships can enter in collaborative arrangements for undertaking innovation, for competition or internationalisation purposes or for workforce training. Integration into global value chains (GVCs) is of particular relevance for small firms that can proceed to capacity upgrading through the exchanges that take place within the value chains. However integration does not automatically translate into upgrading and upgrading trajectories are shaped by various factors, including economic competencies of the firms, replicability of the value chain business models and the mode of GVC governance that determines the relationships –and the scope of knowledge spillovers- between lead firms and more or less ‘captive’ suppliers (Gereffi, Humphrey and Sturgeon, 2005[42]). Collaboration with customers can also be a channel, especially as SMEs tend to enjoy close relationships with end-users and better understanding of near-by market.
In some cases licensing in technology or other forms of IPRs is an alternative to performing and developing in-house knowledge and an integral part of a SME’s growth strategy. And SME types of co-operation involve non-private stakeholders such as universities or research organisations. In its annual survey the US Association of University Transfer Managers show that 70% of university innovations were licensed to start-ups and small companies in 20175.
However a key challenge for many SMEs is to identify and connect to appropriate knowledge partners and networks at the local, national and global levels, as well as to develop appropriate skills and management practices for co-ordinating and integrating knowledge created by external partners with in-house practices and innovation processes (OECD, 2015[43]) (see also the chapter on access to skills).
Large firms have been taking actively part to the OI transformation by developing strategic partnerships with smaller actors or by deploying specialised accelerators where start-up and individuals can access office infrastructure and supportive business environment for nurturing new ideas and incubating projects that could be profitable to their sponsors’ business ecosystem. Business accelerators tend to address some of the main challenges high-growth firms can face (e.g. managerial competences, professional networks, equity finance). Barclays6 expanded its accelerator programme to London, New York and Tel Aviv to help innovators develop new disruptive business models in the investment banking and wealth management industries. Fintech companies get access to Barclays technology and data, as well as mentorship programmes and co-working spaces. Likewise Microsoft7 offers a go-to-market support to start-ups via its accelerator programme that gives them access to Microsoft technology and local and global community spaces. It also foresees a joint sales engagement between partners.
Large firms also increasingly set up innovation labs, often outside their own premises and close to high-tech clusters, with a view to encouraging “out-the-box” thinking and new collaborations within the firm. The Volkswagen Automotive Innovation Lab (VAIL) provides a state of the art research facility and community space where interdisciplinary teams work on moving vehicle technology forward and developing new mobility solutions. Located on the Stanford University campus, VAIL partners with the university on research projects on drive-by-wire, driver assistance systems or solar cars.
As OI initiatives are sprouting worldwide, cities are turning into hubs for data-driven innovation and testbeds for experimentation and prototyping (OECD, 2017[22]), not without consequence on housing market and land-use planning (see also the chapter on institutional and regulatory framework). 340 European cities are part of the European Network of Living Labs that encourages cross-fertilisation, co-creation, exploration of emerging usages, behaviours and market opportunities, experimentation and evaluation of concepts, products and services. Station F opened in Paris in 2017 with the ambition to become the biggest start-up hub in the world. The hub hosts incubators and accelerators for large multinationals like Facebook, Microsoft, Ubisoft, Airbnb, or L’Oreal and spans sectors from medicine, to food, fashion, software, beauty, and e-commerce.
Open sourcing and more intense knowledge sharing have also spurred a democratisation of innovation. Market outsiders (e.g. citizens, new-to-the-market firms) have entered existing markets (e.g. Uber, AirBnB), increasing the competitive pressure on traditional actors and incumbents (e.g. taxis, hotels). The rise of the platform economy has been instrumental to the deployment of these new OI practices as industry platforms, marketplaces and crowdsourcing platforms allowed to various degrees enhancing system integration, interoperability and data sharing and openness (OECD, 2017[22]).
Main policy approaches and recent national policy development
Conditions under which business innovation emerges and reaches the market have changed, leaving room for SMEs to increase their contribution. More niche market demand, more responsive supply chains, more open sourcing of knowledge, data and technology enable SMEs to strengthen their comparative advantages and reduce the structural constraints they used to face in accessing resources and achieving economies of scale (OECD, 2017[44]).
Policy approaches for fostering SME innovation vary across countries, but governments have been placing strong emphasis on ensuring SMEs keep pace with the industrial transformations at play. Unless specified differently in the notes, policy examples presented below are drawn from country responses to the OECD Digital Economy Surveys 2017 and the EC/OECD STI Policy Survey 20178.
Accelerating the SME digital transition
The uptake of digital technologies is a key lever – and prerequisite- to the SME transition towards the next production revolution.
In addition to their efforts to upgrade and consolidate digital infrastructure (see also the chapter on infrastructure), policy makers have been active in providing SMEs targeted financial support and technical assistance in conducting technology and problem-solving diagnosis or implementing new e-business solutions, often in the form of small-scale and place-based initiatives (Table 7.1).
Table 7.1. Accelerating the SME digital transition: Selected country examples
In some cases financial and technical support is supplemented with training and guidance on the skillset and organisational changes that are required to support technological change (see also the chapter on access to skills).
Sector-wide approaches and solutions are also often instrumental for accelerating technology diffusion within specific business ecosystems.
Revising national innovation policy support packages for SMEs
Ministries and departments in charge of the national innovation policy agenda are increasingly taking into consideration SME constraints and potential in policy making and implementation. Although cross-country differences exist, government responses to the 2016 OECD survey on Science, Technology and Innovation (STI) Outlook indicate a clear move towards greater use of population-targeted9 instruments over the last decade. And the trend towards more targeted approach in STI policy making is likely to strengthen in the five years to come (OECD, 2016[10]).
For example the integration of SME policy imperatives into innovation policies has been noticeable in the design of R&D tax incentives. R&D tax incentives have become a popular instrument in support of business innovation across the OECD area over the past decade, governments revising their tax schemes to make them more available and generous (Appelt et al., 2016[45]). R&D tax incentives are non-discretionary instruments by nature but have been increasingly geared towards SMEs. The introduction of carry-forward and refundable options aimed to compensate for insufficient tax liability of smaller and young firms. SMEs have been granted preferential tax deduction. And particular efforts have been dedicated to simplify tax schemes, increase predictability and reduce compliance costs (OECD, 2016[10]). The marginal tax subsidy rates for SMEs exceed 30% of the expense incurred in Canada, Portugal or Spain or up to 40% in France. Although SME shares in tax support for BERD vary significantly across countries, they tend to be aligned with SME share in BERD (OECD, 2018[46]). But in countries where refundable options are proposed, such as Austria, Canada, France, the Netherlands, Norway and the United Kingdom, SMEs capture a disproportionate share of tax support.
Despite the growing relevance of R&D tax concessions in funding business innovation, governments keep using direct funding, especially competitive grants, for supporting business R&D, particularly by SMEs (see Table 7.2). Direct funding schemes have become more market friendly, simpler to claim for and more competitive over the past years (OECD, 2016[10]). SMEs have got over 90% of direct government funding of BERD in Latvia and Slovenia in 2016 and over 70% in Chile, Greece, Hungary, Portugal and the Slovak Republic (Figure 7.6). Whether through tax incentives or direct support, SMEs have received more financial support in relative terms than what they have contributed to total business R&D expenditure. This is true for all countries to the notable exception of the United States where larger firms captured more support as compared to what they contributed.
Another example of shifts in innovation support policies towards more SME-targeted schemes relates to pre-commercialisation public procurement programmes (see the chapter on market conditions).
SME policy considerations are also pervading national innovation policy agenda as reflected in countries’ strategic orientations and high-level documents (Table 7.2). SME contribution to innovation dynamics is a key axe of STI policy action in Belgium (Wallonia) through the Smart Specialisation Strategy (2015-19), in Chile through the Innovation Plan (2014-25), in Estonia through the Entrepreneurship Growth Strategy (2014-20), in Germany through the new High-Tech Strategy (since 2014) or in Norway through the Action Plan for Entrepreneurship (since 2015).
Figure 7.6. SMEs receive more public support to business R&D than what they spend on R&D
SME share as a percentage of BERD and government support for BERD in each category, 2016 or latest year available
Note: This is an experimental indicator. International comparability may therefore be limited, e.g. due to variations in SME definitions for business R&D vs. R&D tax relief reporting. For BERD and government-funded BERD, SME figures generally refer to enterprises with 1-249 employees (i.e. excluding firms with zero employees). However a number of countries have additional criteria to define SME status, for instance independence (e.g. Canada, United Kingdom). In Figure 7.6, SME definitions are harmonised across direct funding/BERD and tax support country by country. Therefore data on SME share of BERD in Figure 7.6 may not be comparable with the data presented in Figure 7.5. Countries are sorted by descending order of SME share in direct government funding of BERD.
Source: OECD (2019[47]), OECD Time-series Estimates of Government Tax Relief for Business R&D, http://www.oecd.org/sti/rd-tax-stats-tax-expenditures.pdf, based on OECD (2019[48]), R&D Tax Incentive Indicators, http://oe.cd/rdtax (accessed on 15 February 2019) and OECD (2019[49]), Research and Development Statistics (RDS) Database, http://oe.cd/rds (accessed on 15 February 2019).
Table 7.2. Innovation policies for SMEs: Selected country examples
Scaling-up business innovation networks and involving SMEs
Connecting SMEs and entrepreneurs to national, subnational and international innovation networks is a key condition of their transformation and growth.
Industrial and cluster policies are preferential channels of policy intervention for technology upgrading and integration into GVCs (Kergroach, 2018[50]). Cluster policies have long been implemented in OECD countries and non-OECD economies, with different features though, depending on the stage of development of a country (or a region) and the level of maturity of the cluster itself. The industrial cluster landscape is constantly evolving as a result of changes in market conditions, technologies, and competition. About one fifth (20%) of European clusters significantly changed their market position between 2008 and 2014 (Ketels and Protsiv, 2016[51]). Clusters that are increasingly exposed to global competition are also prompted to further specialised (OECD, 2016[10]).
National cluster policies are evolving worldwide with the emergence of a network-based development model along which clusters located in different areas and active in different industrial sectors are pushed to establish cross-cluster linkages domestically and internationally. This network-based approach often includes the strengthening of the cluster research component, stronger industry-science linkages, enhanced interdisciplinary capacity within the cluster and more cross-sectoral interactions (OECD, 2016[10]).
In this vein, the ten Baltic countries (Denmark, Sweden, Norway, Finland, Germany, Lithuania, Estonia, Latvia, Poland and Island) have jointly developed the BSR Stars project with a view to establishing the Baltic Sea Region (BSR) as a functional region with an internationally competitive position in a number of strategic areas. The BSR Stars project will link strong research environments, clusters and SME-networks from the different countries into new strategic alliances with a global potential. Government have relayed multilateral efforts with further cluster developments at national level (Table 7.3).
Governments are also active in deploying and connecting accelerators and incubators (Table 7.3).
Table 7.3. Strengthening SME access to innovation networks: Selected country examples
Opening and protecting data and innovation assets
Governments have been increasingly promoting Open Government Data (OGD) approaches with a view to making the data generated by public administration available to the general public and offering firms, including SMEs, an opportunity to leverage large quantities of data for business purposes at relatively low cost (Ubaldi, 2013[52]; OECD, 2018[53]). The 2017 OECD Survey on Open Government Data 3.0 shows that creating economic value for the broad economy (e.g. new business opportunities for the private sector, facilitating business start-ups) is the main objective of open data policies and initiatives across OECD countries and partners (OECD, 2018[54]).
Countries reviewed under the 2017 OECD Survey on OGD are increasingly moving away from the test-and-learn approach adopted in the early stages of OGD development towards more structured and systematic dedicated strategy embedding action plans. Yet, open data policies appear to be mainly related to digital government and open government strategies and are less frequently included in overarching government agendas for public sector modernisation, innovation and economic growth, potentially limiting efficient implementation and economic benefits (OECD, 2018[54]).
In parallel, data protection is being reinforced while efforts are made to harmonise legislations across jurisdictions and help smaller firms navigate through different regulatory frameworks.
Trade secrets have been the subject of increased domestic and international policy attention and trade secret laws have been simultaneously strengthened in Europe10 and the United States.
The European Trade Secrets Directive (2016) aims to standardise existing and diverging national laws against the unlawful acquisition, disclosure and use of trade secrets (EC, 2016[55]). The new Directive is to bring into force in the course of 2018 and will enable companies to exploit and share their trade secrets with privileged business partners across the Internal Market. Under the new EU Directive, registering trade secrets on the blockchain could be considered as a “reasonable step (…) to keep [the information] secret”.
The United States strengthened trade secrecy protection through the Defend Trade Secrets Act of 2016 that creates federal civil cause of action and provides a choice between treating localised disputes under state laws or treating disputes under federal law (US Patent and Trademark Office, 2017[56]). Courts can protect trade secrets by enjoining misappropriation, ordering parties that have misappropriated a trade secret to take steps to maintain its secrecy, or ordering payment of royalties, award damages, court costs and attorneys' fees.
The EU is also engaging reforms of IPRs laws as part of its package of measures for creating a Digital Single Market.
The Copyright Reform aims in particular at more cross-border access to content online, wider opportunities to use copyrighted materials in education, research and cultural heritage and a better functioning copyright marketplace.
The planned Unitary Patent will offer uniform protection in up to 26 EU member states, and enact for patent holders an alternative pathway to the existing European and national patent systems, a centralised procedure at the EPO and a uniform litigation system (Unified Patent Court) that is poised to increase legal certainty at reduced costs.
SMEs are prompted to acquire and manage growing data stocks in a context of increased regulatory scrutiny, in particular with respect to data protection and confidentiality. Concerns about data privacy are likely to raise new barriers to smaller firms that have less internal capacity to deal with complex regulatory environment. The General Data Protection Regulation introduced by the European Union in May 2018 intends to harmonise data privacy laws across Europe with the explicit goal of protecting and empowering EU citizens’ data privacy and reshaping the way organisations approach the issue.
In addition governments promote IPR use among SMEs through information, financial support and technical assistance (Table 7.1).
Other relevant aspects of SME access to innovation assets are related to:
Institutional and regulatory framework conditions, e.g. simplification and transparency of administrative procedures for easing access to public support for business innovation and ensuring consistency and neutrality in competition, RIA for gaining knowledge on efficient SME innovation policies, land-use planning and the rise of a new generation of smart cities acting as innovation hub and catalyst, taxation of innovation equipment and highly skilled talents, efficient product market regulation enabling an optimal reallocation of innovation assets etc.
Market conditions, e.g. first as a primary driver of innovation, market concentration and competition in digital industries, trade facilitation for importing knowledge-intensive capital, FDI-related policies and policies for fostering GVC integration, SME access to public procurement etc.
Infrastructure, e.g. the deployment of high speed broadband, accessibility and affordability of digital platforms and networks, cybersecurity and the protection of data and privacy, smart mobility solutions for narrowing the distance to markets, energy supply for responding to just-in-time production requirements and meeting energy demand peaks, large-scale public investments in R&D on general purpose technologies etc.
Access to finance, e.g. with regard to the funding of innovation asset investments, but also the use of innovation assets as collateral for accessing funding, venture capital markets and the financing of entrepreneurial ventures etc.
Access to skills, e.g. adult skill gap in view of the digital transition, digital, transversal and soft skills including managerial skills for supporting organisational change and technological transformation, emerging skills needs, especially in new technology areas (artificial intelligence, big data analytics, data scientist), SME access to training systems, leveraging the potential of women and disadvantaged populations etc.
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Annex 7.A. The diffusion of digital technology packages
Annex Figure 7.A.1. Diffusion rate by firm size class, 2018 or latest year available
Note: SCM stands for supply-chain management, CRM for customer relationship management, ERP for enterprise resource planning. The diffusion rate refers to the percentage of firms using these software in 2018.
Source: OECD (2019[24]), OECD ICT Access and Usage by Businesses Database 2019, http://stats.oecd.org/Index.aspx?DataSetCode=ICT_BUS (accessed on 15 February 2019).
Notes
← 1. In the following, the term of innovation assets will encompass technology and physical (or tangible) assets on the one hand, and knowledge-based capital (KBC), i.e. knowledge assets of an intangible nature including: i) computerised information (e.g. software and databases); ii) innovative property (e.g. patents, copyrights, designs and trademarks); and iii) economic competencies (e.g. brand equity, firm-specific human capital, networks of people and institutions, and organisational know-how) on the other hand. The KBC definition is drawn from (Corrado, 2005[4]) and (Andrews and Criscuolo, 2013[5]).
← 2. https://www.wired.com/brandlab/2017/07/stepping-3d-printing-game-leveling-playing-field/. https://www.wired.com/story/ideas-jason-pontin-3d-printing/, accessed 17 September 2018.
← 3. Wholesale and retail trade, construction and accommodation and food services account on average for about 50% of SME employment in OECD countries. These sectors are the primary sectors where SMEs concentrate (see Chapter 1).
← 4. H2020 statistics, https://webgate.ec.europa.eu/dashboard/sense/app/93297a69-09fd-4ef5-889f-b83c4e21d33e/sheet/PbZJnb/state/analysis, accessed 17 September 2018.
← 5. https://www.autm.net/resources-surveys/research-reports-databases/licensing-surveys/fy2016-licensing-survey/, accessed 17 September 2018.
← 6. https://www.barclaysaccelerator.com/, accessed 16 September 2018.
← 7. https://startups.microsoft.com/en-us/, accessed on 16 September 2018.
← 8. https://stip.oecd.org/stip.html, accessed 17 September 2018.
← 9. Population-targeted instruments are those targeted towards specific types of firms, especially SMEs or new technology-based firms.
← 10. Within the EU, Sweden is the only Member State with specific legislation on trade secrets (EUIPO, 2017[31]). All the other Member States offer protection to trade secrets through different pieces of civil and criminal legislation. Austria, Germany, Poland and Spain rely on unfair competition law, while Italy and Portugal have specific provisions included in their Codes of Industrial Property. The Netherlands and Luxembourg use civil liability law with a quantification of damages in the form of loss suffered and foregone profits. In Ireland and the United Kingdom, trade secrets are protected by the common law relating to breach of confidence and/or equity and by contract and employment law. Most EU Member States have actually specific related provisions in national labour laws or in their Civil Codes.