Workshop's blogs

This page gathers views from speakers on the topics of discussion of the Workshop "Innovation and the digital economy: What role for innovation policies?" that was held on 14 June 2017.

The opinions expressed in this page are those of the blogs' authors and do not represent the views of the OECD or its member countries. 

Robert Atkinson, Founder and President of the Information Technology and Innovation Foundation (ITIF)

Innovation Policy for Digital “Installation” 

While the next major “Schumpeterian” wave grounded in artificial intelligence and robotics is in the media, it won’t likely be in the market for at least a decade until price comes down and functionality goes up. This means that over the next decade progress will depend on broader and deeper “installation” of existing ICTs. Despite the vast improvement of ICT over the last two decades, many nations, industries, organizations, and consumers lag in ICT adoption. This means that innovation policy needs to be oriented to spurring widespread adoption of ICTs in all industries; what Carlota Perez has termed “installation.” This implies a focus on a different set of tools than the traditional development tools (e.g., R&D tax incentives, grants, etc.).

Digital Adoption Policy Agenda

Many of the policies needed to spur digital adoption are not traditional “innovation policies”, but rather are in other policy areas. The first concerns “doing no harm.”  If policy raises the costs of ICT goods and services or limits access to global best in class products or services ICT adoption decreases. At least 31 countries impose combined ICT tax and tariff rates greater than 5 percent of product or service costs. Likewise, a growing number of nations impose local content requirements, limits on foreign direct investment, restrictive ICT certification and licensing requirements, national ICT standards, government procurement preferences for domestic ICTs, data center localization requirements, barriers for cloud computing services, and limits on cross-border data flows. All of these policies reduce domestic adoption.

Second, overreaching product market regulations can limit digital adoption. This is a particular risk with regard to ICT-enabled business models that disrupt incumbent businesses and where the latter seek protection from government. We see this in an array of industries, including real estate and legal services (opposing online realtor and legal services), financial services (resisting Fintech), telecommunications and cable providers (opposing “over the top” digital services), and transportation and lodging (taxis opposing Uber and hotels Airbnb).  

Third, social regulation, particularly in the area of privacy, often limits digital adoption. It is widely believed that strong privacy regulations spur adoption by raising trust. But there is little empirical evidence for this claim. Moreover, overly strict privacy regulations like the EU’s General Data Protection Regulation make it difficult for digital producers to provide more and higher-quality or lower-priced services, which will reduce adoption. In addition, the European Parliament’s proposal to heavily regulate robots (e.g., giving them legal status) will only slow down their adoption. 

Fourth, policy should enable the growth of digital platforms such as smart grids, mobile payments, digital signatures and electronic IDs, the Internet of things, health IT systems, and others. Many platform technologies suffer from a chicken-or-egg problem. For example, few people will digital signature technology if no counterparties will accept them. Few organizations requiring identification will switch to them if few of their customers have them. Governments can spur platforms by being a lead adopter. Governments could provide digital signature capabilities for individuals getting a passport or other government ID, use mobile payment systems for their own payment processes, and support smart cities and intelligent transportation projects.

Fifth, when it comes to digital adoption a focus on SMEs can lead to perverse outcomes because ICT enables an increase in average firm size as it allows more firms to gain scale. We see this in the fact that from 1997 to 2012 average firm size in the United States increased 6.6 percent and in that nations with larger firms have higher rates of ICT investment. This matters because larger firms are more productive and pay higher wages than small firms. Therefore, nations should adopt size-neutral policies and work toward regulatory, fiscal, and tax parity between large and small firms so that their economy’s firm size structure is not artificially tilted toward SMEs.  This does not mean that policy should not help SMEs gain ICT capabilities. Technical assistance programs can help SMEs determine how to incorporate ICT, help them acquire those technologies through supportive financing, and show them how to use them.

Sixth, one of the defining features of the digital economy is that the role and use of ICT products, services and systems differs significantly between industries.  ICT in construction is quite different than ICT in financial services, for example. This means that ICT policy needs to focus on sectoral analysis and policies. For example, ICT is poised to transform financial services through Fintech.  Generic ICT policies (e.g., tax, skills, infrastructure, R&D) will not be enough to drive Fintech transformation in part because financial services is subject to its own regulatory system, has significant network systems where coordination and interoperability are required and have incumbents using their power to resist Fintech innovators. Nations will not maximize ICT-based Fintech innovation without a Fintech strategy. The same is true for many other industries, including construction, health care, higher education, transportation and electric utilities.

Seventh, achieving the full benefits of ICT requires advanced communication networks, so nations need policies to support the deployment of robust wireline and wireless broadband networks. Policymakers should craft national broadband plans, ensure that tax policies allow providers to depreciate network investments more quickly; subsidize build-out to high-cost areas and schools and libraries; ensure adequate spectrum availability while using spectrum auctions as a way to allocate a scarce resource, rather than as a way to raise revenues; and provide flexible pole attachment and tower citing policies, all the while ensuring that broadband regulations, including “net neutrality” does not limit innovation and broadband subsidies not artificially spur competition. 

Finally, R&D policies can play a role, but the focus should be on areas where the private sector is not very active. Large ICT firms invest considerable resources into ICT R&D.  Public R&D can complement that if it is focused on areas the private sector is less active in (e.g., R&D related to privacy protective Internet technologies), in high risk, more earlier stage research in areas such as machine learning, and in areas of public private partnership, such as the U.S. manufacturing USA center Digital Manufacturing and Design Innovation Institute. 

In summary, there is no reason to assume that the current global slowdown in productivity growth is due to a Robert Gordon-like stagnation of technological opportunities. More widespread and deeper  installation of existing ICTs should be able to power growth until the emergence of the next innovation wave, as long as supportive policies are in place.


Paola Bonomo, Digital Business Advisor and Early-Stage Investor in Technology Companies, Italy

A Marshall plan for science and technology

Over the last 20 years we have seen a startling increase in the ease of starting a business, perhaps no better epitomized by the rise in availability and the decrease in the cost of cloud computing. 

Entire industries have been upended by digital consumption formats (music, movies, newspapers, TV); asset-light platforms matching demand and supply have emerged as serious challengers to established companies (from BlaBlaCar to AirBnB, from Alibaba to Uber, Lyft and Didi Chuxing); renting, not owning, has become a lifestyle for many consumers, and not just for millennials (Rent the Runway); machine learning platforms are crowdsourcing artificial intelligence algorithms and setting them loose in financial markets in order to outperform traditional hedge funds (Numerai, Quantopian). Even mining – as traditional an industry as can be – has demonstrated it can  strike gold by crowdsourcing diverse skills over digital platforms, starting as far back as 2000 (Goldcorp Challenge).

In the meantime, in the developing world, entrepreneurs are leapfrogging wires and computers to build entire webs of trade and services on wireless networks and mobile phones. Cryptocurrencies, having no legal jurisdiction or permanent establishments, are posing unique regulation challenges. Blockchains enable new and self-regulating distributed economic entities, and autonomous software agents emerge from rules that are written in software only.

Tesla makes not just battery-powered cars, but information devices that carry people around in traffic and will soon drive themselves; that’s why its market cap recently grew bigger than GM’s.

Amazon’s retail business makes Walmart shopping trips less and less necessary, or even desirable. Its enterprise cloud business is a formidable competitor to Microsoft’s and Google’s; IT providers from another era, such as IBM, are left quite far behind. 

Nor is the revolution confined to services and to B2C. The disruption is less advanced in manufacturing and B2B sectors, particularly in agriculture, basic materials and process industries: but AgTech and “Industry 4.0” are already making a difference.

My country, Italy, is a very stark example of the opportunities and challenges that digitalization brings for economic actors. Some industry clusters (from medical devices to hydraulic pumps, from packaging machines to car brakes, from eyeglass frames to furniture and lighting), have won the challenge of globalization and completely reinvented themselves over the last 10-15 years: these are several hundred companies, often medium and small, who listen to their customers, move fast, export well over 90% of what they make and create a very large chunk of value added in the economy. And they are mostly B2B players. The rest? Not so much. And how about digital leaders? In the last several years, only a handful of Italian digital startups have evolved to take a leading position globally (perhaps the most notable being Yoox, the fashion platform, which subsequently acquired Net-à-Porter); other than that, the Italian digital consumer has ended up being largely served by multinationals. A certain laziness in riding the wave of opportunities such as eCommerce – once attributable to Italians’ mistrust for long distance sale and the postal system, slow takeup of broadband connectivity, and a penchant for handling cash instead of using credit cards and digital payments – has been overcome as soon as quality and speed of eCommerce services have dictated new standards.

More than the practicalities of adopting today’s technologies, though, what worries me is the ability to invent the technologies of the future. A certain cultural mistrust of science and innovation – perhaps artificially and malignantly stimulated in a humanistic culture, since I believe the two need not be, and should not be, in opposition – has taken root in the Italian mindset over the last couple of generations. As a symptom of this, look no further than an OECD indicator, Gross Domestic Expenditure on R&D (GERD). In Italy, in 2014, this amounted to 1.29% of GDP, vs. 2.38% as an OECD average); in the years 2009-14, it showed negative growth (-1.81% CAGR), vs. a CAGR of 2.3% in OECD countries on average. Another symptom of the same malaise, among others, is the stagnation in productivity that has held back the Italian economy for well over twenty years by now. And this gap is made worse by a family culture that traditionally wants to see the son in the family become an engineer, and the daughter to become a lawyer; we are building science and technology skills, broadly speaking, in half the raw talent we have at our disposal.

Overall, the lack of growth leads to the accumulation of public and private debt, and contributes in turn to low (public and private) investment in R&D. The vicious circle of scarce innovation and low growth is therefore hard to reverse.  

Our cultural and economic stagnation has its roots, I believe, in a crisis in science and technology education; and this has become a crisis in the human capital that is the main ingredient for building the economy of the future.

Many short-term measures have been implemented, sometimes with good success, in European countries to stimulate investment in innovative companies and especially in start-ups: I am thinking in particular, as far back as the 1990s, of the UK Enterprise Investment Scheme (EIS) and its many versions elsewhere. These are all well and good, but I believe we need something better. I have come to the opinion that, speaking from a European and especially Italian point of view, we will need a Marshall plan for science and technology. Given political realities as they are, no one will come and finance it for us: this time around we’re going to have to largely pay for it ourselves. And yet, it is the key for allowing our societies to survive and thrive in the long term.

We need to boost two levels of knowledge here: the advanced, sometimes revolutionary, insights of the researchers and innovators; and the basic and broad-based minimum competence that enables public understanding and acceptance of the changes that science and technology bring to our society. My dream is a society where everyone, from teachers to doctors to lawyers to judges to journalists to nurses to factory workers, can apply logic, computational thinking, and basic notions of probability and statistics (such as Bayes’ rule). My country has long held creativity in high esteem: but in today’s world we’re going to need to have the same respect for data and for code. Hollywood movies have maybe 5 people writing the script, and 100 people writing the special effects and the software tools to generate new ones. A blockbuster videogame has again maybe 5 people working on the characters and the story, and 100 people writing the code. We need to be able to have the 100 jobs in our creative industries, not just the 5.

Any country that is in Italy’s situation – and there are several – should, in my opinion, take a good, hard look at its national budget. Eliminating waste, chasing down tax evasion, shrinking the perimeter of public services, instituting ad hoc taxation (perhaps on real estate and, that great taboo, estates of the newsy deceased): these are all potential avenues – requiring tough political choices – to fund a revolutionary plan, worth approximately 2pp of GDP, with 1pp going to fill the gap in university and postgraduate research budgets, and 1pp going to re-educate the public – across the board, from schoolkids to ageing baby boomers - on the basic science and technology knowledge that everybody needs to be an informed citizen today. 

Of course we don’t just need more engineers and scientists. Ethicists, philosophers and law practitioners are all required to ensure that we lay out the groundwork for science to make a better society, not a more unequal one or one where social mobility is even more difficult than it is today. For example, AI has the potential for entrenching gender and racial bias instead of eliminating it: a robust dialogue is needed, and many more women and minorities should gain the skills needed to participate in this revolution. Therefore, the plan should be designed for inclusion. 

Advanced nations should not be deprived of Italian talent and genius. As an OECD nation, we should proudly restart the innovation engine in our country. 

Lars Frølund, Lab for Innovation Science and Policy, MIT Innovation Initiative

Digitalization has increased the speed of the innovation cycle for many traditional technology companies. To keep up with this speed they seek to embed themselves in regional innovation ecosystems to be close to research based starts-ups with the digital technology they need for their company. For most companies this means that they are adding “entrepreneurship” and “access to start-ups” as key criteria for their selection of university partners. Is also means that the companies are changing their collaboration format from problem-solving/extended workbench/contract research to instead focus their resources on “deep exploration” and “business incubation and acceleration”. In other words: the heightened speed of innovation driven by digitalization has made the research based start-up (by e.g. graduate students) just as valuable for a company as the professor and the university lab. An entrepreneurial mind-set is now equally important as “excellence” for university partnering. In this context, geography still plays a big role for most companies, especially when it comes to talent acquisition and being close to new start-ups. 

Regarding large consortia between industry and research, initiatives such as the Innovative Medicines Initiative can be very fruitful. Such large consortia normally work well when several companies can agree that there are challenges in an area that no single company can tackle and that the results of a collaboration will be precompetitive. The IP framework should reflect this. 

Dr. Harri Kulmala, CEO, DIMECC Ltd.

Co-creation is much more than research

European economy has a challenge since we Europeans have a very high standard of living, high-level educational profile, and high value-add in the industry. There is a need to innovate something even better, but we do not know, what the “better” might be. One of the ways to walk towards this “better” is co-creation. Co-creation is an activity or process, where heterogenous group of people cross-orgnisationally, cross-industrially, and cross-disciplinary do something, that has an objective and determined leadership, but which is free in defining all the details according to the needs that pop up during the co-creation.

Horizon2020 is one of the biggest and most systematically organised research and innovation programs in the world. It has been a success in many ways, and it seems to be the most accepted and respected one of all the EU framework programs in history. It has significantly increased the participation of Europeans in systematic innovation. There is a trend from traditional research funding towards funding innovation. Good. Now we live the phase where the next framework program, FP9, is under construction. Since Europe has a huge experience of European, national, and regional research and innovation policies, we should take all the lessons learned to shape the Future of European innovation. We can learn from statistics that Europe produces about one third of all scientific literature in the world. However, we Europeans produce only one tenth of all new businesses. The problem seems to be, that we do not transform our scientific knowledge to business as fast, impactfully, and efficiently as other nations. How can we change this?

Finland, my home country, offers an unfortunate field test of radical discontinuities in innovation policy. European Commission and our cooperation partners all over Europe have identified Finland as the European forerunner in the implementation of public private partnership (PPP) model. We have been noticed as a country that makes impact. We have had high scores in all the innovation performance metrics. Finland was the top scorer of EU countries in the 2010-2012 analysis on how European large companies collaborate with higher education and research institutes, and with their customers and suppliers. Finland really has co-created, and the most effective and impactful part of this co-creation has taken place through PPPs.

During the last two years, we focused the financially needed public spending cuts to the highest impact part of the Finnish innovation activities. Challenges in the Finnish public economy and this policy decision have led us to a situation where Finland is one of the few countries in EU without outspoken industry-led and publicly supported industrial digitalization strategy, and no governmental support to PPP. The public sector’s dominance in innovation funding directions has dropped Finland from the group of best performers. OECD gave a report to Finnish government in February stating that if the national competitive advantages and forerunner positions are not used as a fundamental basis for future development, there is no high probabilities to create success again and again from thematic white papers or public-sector driven exclusion of industry. 

We in Finland have provided Europe with a good field test, which, unfortunately for the Finns, had a bad outcome. Europe can now empirically learn that radical discontinuities in innovation policy, public funding structure, and abandoning the evident strengths provides us with negative turn. Europe should continue on the path towards versatile, systemic, and holistic co-creation that is not only research but much more. This path has already been selected in Horizon2020, and it can easily be continued. Not with radical changes but with evolutionary improvements and focus to produce more as an outcome than only scientific literature.

As an example of what co-creation is in practice, I use our “One Sea”. Finnish maritime industries launched an ecosystem for autonomous ships. This is called One Sea. The objective of One Sea is to create the world’s first autonomous marine transport system to the Baltic Sea. Ships will be fully autonomous in 2025. The first pilots and applications in months to come are cargo ships and freight. Finland has world-class marine technologies and ICT competencies. This DIMECC-led One Sea is a natural continuum to our long-term and determined R&D&I facilitation, where we boost cross-industrial innovations and lead the industry’s digital transformation. DIMECC co-creation platform makes significant innovation-based investment wave happen. This has been seen e.g. in Turku, where German-based Meyer Werft now invests in physical equipment while the needed intangible investments were made in DIMECC co-creation programs during 2009-2014. One Sea changes not only technologies, but also business logics, earnings, and behavior of the people in maritime industry. 

Widening and strengthening co-operation and increasing activities that cannot be positioned to the classical TRL scale may be the key. This may sound radical, but there is evidence on ideas “flying faster” within heterogenous groups. An idea is not an idea before it is shared. For FP9, this means consortia and cooperation, not single beneficiaries. Most of the new businesses have their origins in changing (radical) or improving (incremental) existing businesses. This means pressure to fund co-creation including all the possible organisations no matter what is their organizational form, size, or ownership structure. We should emphasize holistic set-ups, not research within a certain TRL “box”. 

A recent analysis performed by the ‘Small Advanced Economies Initiative’ using the Elsevier SciVal Scopus database of published papers in six high value-adding economies revealed that there are significant differences in the citations of scientific journal articles. If there are authors working and affiliated in industry and commercial companies, the Field-Weighted Citation Impact (FWCI) of the papers is about 2.0-2.5. If there is only a single institution behind the paper, FWCI is about 1.0-1.5. If there is only a single author, there was no country where the FWCI was more than 1.0, which is the global average and comparison number. Conclusion: If we want to have high quality scientific research, let’s fund collaborative projects, industry-inclusive consortia, and someone non-academic pressing scientists towards high performance.

There will be voices saying that fundamental research without commercial influence and everyday societal challenges present is needed. Yes, of course. The question is more about the trends and volumes. As we learn from the unfortunate Finnish innovation system field test, radical changes do not produce high quality. Europe should follow the already selected incremental change track from science and research towards innovation, and next slowly towards co-creation. Less and less scientific individualistic projects, no dramatic changes, and no touch on the very best and highly appreciated things no matter what is their formal status. We have to take more and more businesses inside the scientific work, and take the businesses into account when defining topics, work methods, and targets. 

Let’s co-create the better Europe!

Brian MacAulay, Lead Economist, Digital Catapult, UK

The times they are a changing

The collaborative environment is increasingly complex and dynamic and so needs to be viewed from an ecosystems perspective, where a diverse range of actors interact, react and ultimately shape the system going forward. This is even more so in digital technologies, where the rapid pace of technical change is not only re-shaping the economic landscape but may potentially strain the institutional structures of less agile actors, as they endeavor to keep up and continue to play an active role in driving innovation. In the case of university collaborations there needs to be a recognition of the institutions adapting processes to realise the new potential arising from digital technologies. 

In the UK Catapults play an enabling role, to bridge the innovation gap between high quality research, its successful commercialisation and the realisation of the broader economic benefits these deliver. While each Catapult specialises in a different area of technology, each offers a neutral space with the facilities and expertise to enable businesses and researchers to solve key problems together and develop new products and services on a commercial scale. 

Not so much the Invisible Hand…

Digital Catapult accelerates access to new digital markets and carries out applied research and development to identify new applications of emerging technology. With a deep understanding of the ecosystems of different sectors and technologies we have the ability to facilitate the introduction of key players to precipitate innovation. It occupies a distinctive agnostic position between multinational corporates, investors, start-ups, government departments, academia and other Catapults.  

Supporting a new digital product to market is not a straightforward process because the innovation in the business model is often more profound than in the product itself.  Digital Catapult understands how digital innovation disrupts supply chains and its model supports this characteristic. By bringing together the pure technical skill from academia with the novel applications that come from iterative start-up environments, Digital Catapult supports the creation of new disruptions and opportunities.

Academic collaboration

It is Digital Catapult’s nature to collaborate and this has been demonstrated with the number of research partners exceeding one hundred. Collaboration is essential to the innovative process, and to achieving Digital Catapult’s objectives and to scale its impact. It will continue to work closely with academia, the wider catapult network and organisations in the digital landscape.

The Digital Catapult undertake collaborations in a number of ways. We continue to pursue a strategy in collaborative R&D projects to position us at the heart of large European ecosystem development initiatives in IoT and trusted cloud and internet infrastructures, to disseminate its knowledge and fund growth of its capabilities.

Digital Catapult’s connection to the UK research base is strategically vital, and has been built to a significant strength over the previous four years of operation. However, the path to commercialisation in the digital and technology world is typically through the flow of people and formation of companies, rather than via licensing or long term industry-university collaboration. There are two reasons for Digital Catapult to engage with UK university researchers:

• to provide industrial context back into research and development and increase the impact of research; 

• to increase the speed and breadth of commercialisation of research. 

Digital Catapult will continue to create a broad base of engagement with the research base by focusing on activities designed to increase collaboration between its staff, projects and university researchers. This then  feeds into a pipeline of higher impact projects. 

Addressing the business challenge

In the case of facilitating business to business collaborations, the most popular proposition to date are the ‘Pit Stops’ which are structured around a specific challenge developed with the client, usually a large corporate. Digital Catapult recruit relevant innovators, presenters and participants from industry, the start-up community and research institutions and organises a customised two-day intervention, typically consisting of keynote speakers, lightning talks, panel sessions, workshops and brainstorming sessions, and networking.

The offering addresses two major challenges for clients. First, they can struggle to get visibility and up-to- date knowledge of emerging technologies, new business models, disruptive solutions and interesting small businesses in the space. Rather than the expense of hiring individuals whose knowledge will only cover a small part of what they need to understand, it is much more efficient for them to work collaboratively with experts, innovators and thought leaders, so that they can gather knowledge from across the ecosystem that they take forward to influence their business strategy. In turn many SMEs also benefit - a number have continued to develop relationships which are now beginning to be shaped into potential new business.

Second, clients use the engagement with Digital Catapult to define or refine their own approach to open innovation, and often to even get a first taste of working with startups. The process of challenge definition, objective setting, and workshop design walks them through a series of internal decisions that need to be taken to enable new partnerships and successful collaborations. These learnings extend beyond the immediate engagement topic and can be applied conceptually to their future innovation work.

The increasing potential of decentralized collaboration – Distributed Ledger

The potential for digital technologies extends beyond increasing technical efficiencies, to significantly disrupting business models. There are new ways of organising the production and distribution of knowledge which could lead to a shift from traditional business structures to looser collaborations of partners.  

Within our work we’re also seeing the potential of technologies that could radically disrupt existing models for managing collaborations. The Death of Distance is the byword for the overcoming of physical distance, which presents barriers and costs to the diffusion of information, knowledge and innovation between different places. It is most often applied to the idea of the reduced need for geographical co-location between collaborators, as communication and the sharing of information is increasingly delivered over networks. 

However, a greater driver may come through advances in distributed ledger technologies will facilitate the further decentralization of collaborative partnerships. A distributed ledger can be described as a ledger of any transactions or contracts maintained in decentralized form across different locations and people, eliminating the need of a central authority to keep a check against manipulation

One barrier to collaboration is the potential for information asymmetry arising from non-separability and uncertainty in developing innovative creative IP, which may result in lower levels of activity. A system of attributing reward for effort through distributed ledger in an open and trusted way could increase innovation and grow market opportunities. These new ways of organising and monitoring production can extend beyond commercial collaborations to be adopted by academic and commercial partenrships. The technology is still embryonic but emerging findings suggest these could have significant wider impacts on how collaborations are managed.

So, in conclusion the market for collaboration in innovation is changing and will continue to change. Organisations across the spectrum will need to anticipate and be adaptive to these changes in order to ensure meaningful participation. Digital technologies are not just enabling more effective coordination and communication for existing models of collaboration. They may irreversibly alter them and bring about a new and radically different approach to collaboration.

Prof. Dr. L.J.M. Nieuwenhuis, Lector, Fontys, the Netherlands

It’s all about services 

All companies are using digital technologies

In the past, digital economy meant companies using digital technologies. Today, every company in all sectors of our economies is using digital technologies. About twenty years ago we wrote strategic reports telling companies how the internet would impact our traditional way of doing business. It is only recently, that we really see that brick and mortal shops in our city centres are closing down and that banks are massively reducing their staff due to tele-banking. This is what we have envisioned more than two decades ago.

Productivity growth in manufacturing

If we want to understand innovation in the digital economy we need to understand innovation of services. Today’s economies are service economies. Almost 80% of our GDP originates in public and private services, more than 80% of us is working in the service sector. Does that mean that manufacturing is no longer important for our economies? Definitely not! The output of our manufacturing industry is still growing. We have seen a tremendous productivity growth in manufacturing firms. This is however, jobless growth. This is due to the continuous improvements and innovations in the industry, with information and communication technologies (ICTs) as an important driver. It is very likely that robotization will carry this through in the years to come.

Various forces have been creating our services economies 

In general, we see a clear trend that an increase in economic wealth goes together with increased need of services. Services growth is not only limited to consumers but also firms start to use more and more services. The developments of design processes, engineering processes and distribution have significantly improved and became more sophisticated, requiring more and more specialised knowledge and skills. The increased use of services by manufacturers can be explained by outsourcing, distribution and specialisation. The high percentages of people working in services industries can be explained by the shift from employment from agriculture and manufacturing industry towards services. Services have lower productivity growth rates then manufacturing.

Hybrid production systems and hybrid products 

Today, we see hybrid production systems and products. A manufacturing company uses a wide range of services provided by own and external specialists. Product design uses services like R&D, engineering and market research. Product manufacturing requires product development, production design, financial services, and quality control. Product distribution requires like marketing, advertisement, packaging, transportation. Servitization is the transformation of manufacturing companies from delivering only products towards offering services related to their products. Hence, manufacturing not only use services in their own production process but also offer services to their customers, either to another firm (B2B) or to consumer (B2C).


Servitization provides means to escape from a downward spiral of competition based on ever decreasing prices, e.g., through off-shoring to low wages countries (commodity trap). Servitisation is an alternative for product innovation only and creates opportunities to build unique, loyal relationships with customers. It is however not only in the interest of producers but is also for the producer’s customers. They can mitigate their risks by paying for the functional use of products rather than exchange of ownership. 

Digital technologies create new opportunities for servitization

Digital technologies connect people, systems, companies, products and services. The Internet of Things combined with Big Data, as well as Cloud Computing provide great opportunities for manufacturing companies to create new value propositions with products and services. Social media technologies provide means to create new ways for communication with customers, e.g., through Facebook, Twitter, and LinkedIn.

  • Digital technologies (either used internally or used externally by production related service providers) can improve the firm’s efficiency (resource planning, automation, robotozation, …) and the firm’s offerings for the customers (e.g., give some possibilities to influence the firm’s production processes).
  • Digital technologies provide the means to create new ways of interaction with the firm’s customers and hence, opportunities to obtain more in-depth understanding of the customer’s preferences and needs.
  • Digital technologies provide the means to build sensors and actuators into products creating a whole new range of functions, services and product enhancements to better serve the customers (monitor usage, maintenance, distant repair,…)

Servitization is a profound Business Model innovation

Servitization does not only change the firm’s value propositions, but also the customer relationships and in many cases also the revenue model. Manufacturing companies need to develop new activities and acquire other resources with new competencies. New partnerships are needed. This might change the position in the value network as part of the ecosystem the firm is part of. 

In practice, firm’s while servtizing also encounter various internal and external barriers. It is difficult to start offering services and at the same time protect core product position. In case of difficulties the product side is likely to win. Promoting services may also undermine a possibly strong product position. Difficulties may occur when pursuing scale in skill-based services and - vice versa - offering specialized skills in economies of scale markets.

Small and Medium Size Enterprises

There are many well-known examples of servitization in large companies, e.g., Rolls Royce, IBM, Philips, MAN, Alstom, General Electric, Michelin. Often servitization results in new business models, where customers pay for the use of the products rather than for the change of ownership. In practice, investments in servitization do not always result in financial returns within reasonable periods of times. For high value products like airplanes, trains, or even cars, financial services are required to create a viable product-service system. SMEs lack deep pockets and the wide range of knowledge areas to deal with these challenges. 

During the last five years, I have been actively involved in servitization programs for SMEs in the Province of Limburg in The Netherlands. I have seen very nice examples of servitizing manufacturing SMEs. I have also seen SMEs not aware of the opportunities that servitization could bring them. 

Services Policy making

The Province of Limburg in the Netherlands is one of the few regions in the EU with advanced policy thinking in terms of developing its manufacturing industry through service innovation. Limburg has developed four campuses, bringing large firms together with industrial and academic research partners, one of them being the Brightlands Smart Services Campus. Further, there are development program specifically targeted on manufacturing SMEs. Close co-cooperation exists between academic universities and universities of applied sciences. Public-private projects have been conducted to support SMEs in their servitization ambitions. Also at the national level there are policies, e.g., the Netherlands is providing service design vouchers to buy advice on service development for manufacturing SMEs.

Frédéric Oru, co-founder and International Director at NUMA

What are the new business model developments and trends brought by the digital economy? What are their implications for how innovation is conducted? 

The digital economy breaks down the barriers between industries: Apple started as a computer company, revolutionized the music industry, disrupted the telecommunication industry, developed financial services... Google is seen as a competitor or a threat to almost every industry (transportation, finance, leisure, etc.).  

Learning from the example set by the digital natives,  traditional industries are exploring outside of their usual businesses: telecommunication companies are becoming banks (M-Pesa by Vodafone had 21 M users in 2016), insurance companies are becoming service providers (MAIF invested 3M€ in the startup Cozy Cloud, a solution for personal data management). 

As a consequence, competition is fiercer and more unpredictable than ever. Many corporations are desperate to innovate just to maintain their competitive advantage. Unfortunately moving by fear only produces incremental innovation, and is more often than not choked by the legacy business. Thus, innovation remains theoretical.

Corporate innovation should look to implement radical changes in their business models, opening their company assets to external innovators, who can use them to solve problems that the corporate didn’t even dream of tackling (examples below).

What are the challenges that firms in different traditional sectors of the economy, including industry (such as car manufacturing, chemicals) and services (such as retail and business services) face in the digital economy? 

Digitalisation has recently entered the field of heavy brick and mortar industries, General Electric leading the way with the objective of entering the top 10 of software companies. The CEO decided to gather the disseminated IT assets in a new business line, GE Digital, and develop an open source platform, PREDIX, to provide data analytics for industry. Similarly, Siemens has launched their own platform Mindsphere, Hitachi has launched LUMADA, etc. 

The challenge is particularly high in this sector because it requires a drastic cultural shift. Industries traditionally value long term investment, intellectual property, process, product, whereas digital companies value jugaad innovation, shareable knowledge, flexibility, services. As of matter of fact this transformation is so difficult that many companies create new business lines, outside of their legacy businesses (like SNCF voyages, the digital travel agency of the almost 70 year old French railroad company).

The digitalisation is easier for Service companies, because the cultural shift is not as deep, they are used to adapting quickly to market shifts. However, they still struggle to implement a continuous innovation strategy to keep pace with the ever increasing speed of change in the market. Many are testing different ways of collaborating with an ecosystem of entrepreneurs (vertical accelerator programs like Unibail Rodamco UR Link, Hubraüm in Germany, open innovation program like Airbus Bizlab, sourcing platform like Amadeus Next, etc.)

What are the opportunities and challenges that digitalisation brings for different actors in these sectors, including small and medium-sized enterprises? 

Digitalisation brings to large corporations the opportunity to reach out of their traditional market, where they compete on low margins with a steady set of incumbents, and develop entirely new business models, with less competition and higher margin. For instance, MASTERCARD has created a department called ‘Mastercard Enterprise Partnership’ in charge of identifying new areas where the asset of the company (secure transaction of information) can solve an efficiency problem by partnering with a startup (eNett for travel, Basware for e-invoicing, etc.) 

SMEs can theoretically adopt the same strategy and achieve even sharper transformation since they have less legacy to deal with. However they often have far less investment capacity than large corporations and consequently affect change on a smaller scale. Yet, the availability of massive amounts of data and computing power represents a new opportunity to participate in the AI revolution. In a new era of intelligent software, SMEs need to rethink how they manage supply change and engage customers. Automation may very well disrupt their business models or greatly augment their reach and potential. Public innovation policy should support SMEs in experimenting new technologies.

What are views from industry on how innovation policy can best support a vibrant digitised innovation ecosystem? 

Public institutions face similar challenges to large corporations in terms of defining and implementing Innovation strategies: they need 1. a large cultural shift, 2. a quicker and more flexible mode of operation, 3. an open innovation mindset. 

  1. Our political representatives are not digital natives. They must be trained, preferably by digital entrepreneurs, to better understand the culture and ways of thinking of the digital era and drive the required change in their policy. We particularly advocate for “Learning Expeditions” in foreign countries, which has a proven impact on changing mindsets. 
  2. Innovation policy should adopt the startup motto “fail fast / learn fast”.  It usually takes 2 years from writing an EC work program to the actual start of a project, and 2 more years to be completed. Whatsapp took less time to be adopted worldwide and disrupt the way we communicate. The key is to have small amounts of money readily available with few constraints on its use, and focus on measuring the outcome (which is, by definition, not predictable). If it’s a failure, you have learned something for a low cost. If it’s a success, you can invest for growth and sustainability. 100 K€ given to 1000 pilot projects is more effective than 100 M€ poured into creating technopoles. 
  3. Public institutions should focus on making their information and services available and let the entrepreneurial ecosystem find solutions. Open Data Policy is gaining momentum worldwide but public institutions tend to focus on data sets that they believe can generate business. Let the innovators decide what can generate business, they know better. Focus on providing as much data as you can. Moreover, let entrepreneurs work upstream with you, modernize your IT, and benefit from their innovative mindsets. USA “Presidential Innovation Fellows” or the impressive Estonian government digital service platform are exemplary in this area.