Open Innovation: R&D or not?
Open Innovation: R&D or not? An academic point of view
Whenever I read or discuss about Open Innovation, I have a feeling that the artifact, has a lot of different meanings to a lot of different practitioners or scholars. In this article I want to examine the origins of such a diversity of meanings, by starting with a common denominators, and then exploring the many elements and meanings of Open Innovation.
Open Innovation, what is generally agreed on
1.Evolutionary path to Open Innovation
In the past 25 years have evolved from closed to collaborative, to open innovation (S. M. Lee, Olson, and Trimi 2012; Chesbrough 2006b). In a nutshell:
- Closed Innovation: in line with Nelson and Winter’s view of innovation as function of internal capabilities, R&D is an internal and core process, with the objectives of developing a sustainable competitive advantage, mainly supported by the now-archaic strategic wisdom of “first mover advantage” (Suarez and Lanzolla 2005). All projects are managed internally and with a high level of secrecy, even within other business units of the organizations. The ability of developing Intellectual Property is mostly contained internally, albeit there are opportunities of licensing and/or exploiting external patents.
- Collaborative Innovation: in a collaborative environment, suppliers are elevated to co-developers, and participate in the innovation process together with internal R&D (Tether 2002). The objective is to develop leaner and more agile organizations, working towards a Just-in-Time approach.
- Open Innovation: based on the assumption that useful knowledge resides outside the boundaries of the company, and that Internal R&D can build value on external R&D. The traditional innovation funnel is more porous, with projects inflow and outflow at multiple stages of the process (see visualization in Table 1). In a nutshell a project can be generated internally but then spun off, licensed or transferred to a Joint Venture or corporate incubator at any stage of the development process. At the same time externally generated R&D can be introduced in the internal R&D process, nurtured until launch or externalized again. Firms – like Procter & Gamble – developed an external R&D function, called Connect and Develop, with the objective of scouting and closing deals on both the acquisition of external IP and the prospective licensing of own patents.
2. At the core of Open Innovation is knowledge
The theory is the fruit of Chesbrough research and is presented in 2003. When beginning our journey into OI, the first insight we need to embrace refers to the increasing diffusion of knowledge (Chesbrough 2003a), whereby a larger number of – and smaller in size – organizations have the ability to develop – and are already building – Intellectual Property (IP); in addition to that, more and more universities and research centers have both the intellectual capital and the financial resources to embark in patenting their knowledge, and more and more researchers, at those universities, have international background. The increasing diffusion of knowledge is antithetic with the traditional operating model of central R&D functions – used to rely on a vertically integrated logic or even on knowledge monopolies – and therefore shutters into pieces the pillars on which closed and collaborative innovations are built upon.
3. Open Innovation is a revolution for R&D
But what exactly is OI? Chesbrough envisions a new R&D ecosystem, characterized by:
- Internal R&D: which first of all needs to connect with the wealth of external knowledge, and at the same time, fill the know-how gap through traditional research and development, when required. Moreover it needs to integrate own and external knowledge in a common platform, while scouting for licensing opportunities of own IP.
- External R&D: it has the dual objective of scouting external IPs or prospective licensees of internal IP, and implementing the innovation through a combination of internal and/ or external processes, including joint ventures, internal and external incubators, corporate venture capital and/or independent spin-offs.
OI is conceived around three process archetypes (Gassmann and Enkel 2004): the outside-in (e.g. bringing external knowledge from customers, suppliers and partners inside the firm), the inside-out (e.g., generating revenues from the exploitation of internal knowledge through licensing, incubators, knowledge-transfer) and the coupled-process (e.g., joining the previous processes in alliances/ joint-ventures with external partners and/ or competitors). From an operational point of view these processes entail that the two R&D functions deal with either inbound or outbound OI activities (Chesbrough and Crowther 2006): the first is the set of tasks to bring external discoveries, innovation capabilities and IP, through the own innovation process for own commercialization; the latter is the process through which internally originated projects – or externally originated projects that have evolved in the internal innovation funnel – rely on external organizations to find their way to market
4. Open Innovation governance is not straightforward
In the exploitation of the inbound and outbound OI activities, whether the focus is on IP or on Innovation Capability, the firm might attempt to establish relations with the external world either directly or through a partner (Feller et al. 2009). From the intersection of focus (e.g. IP or Innovation Capability) and configuration (e.g. direct or indirect approach), four governance archetypes are derived:
- Solution Hierarchy: in this segment firms both work directly on licensing external IP for internal usage, as well as, generating revenues by licensing out their own IP.
- Solution Brokerage: intermediaries act as market makers collecting interested buyers/ licensers of IP with sellers of IP. Brokers also tend to advise the supply side on IP portfolio assessment and licensing services, and the demand side on needs specifications and search strategy.
- Solver Market: the firm is going directly to a specific group of experts sourcing innovation capability, not necessarily a pre-existing IP.
- Solver Brokerage: an intermediary acts as market maker for innovation capabilities, rather than existing IP. The intermediary helps the solution seeker in developing a proper call for proposal and then works with solution providers to help them in improving their chances of being selected for the task.
While each of these archetypes is distinct from the others, a generic company in an OI eco-system, might decide to use multiple archetypes for different type of innovation projects, for examples by being a direct seller of IP (Solution Hierarchy), while crowdsourcing a particular solution through Innocentive or NineSigma (e.g., Solver Brokerage).
5. Open Innovation is also for Small and Medium Sized Enterprises
While the initial focus of the empirical research on Open Innovation was either large industrial firms or big high tech companies, evidence of Open Innovation has been later posited (Chesbrough 2010b) and found in Small and Medium Size enterprises: either as a catalyst of commercialization of innovation, as in the example of Korean (S. Lee et al. 2010) and British firms (Wynarczyk 2013), or to meet customer needs and/ or to match competitors moves, as in the case of Dutch SMEs (van de Vrande et al. 2009; van Hemert, Nijkamp, and Masurel 2013).
Open Innovation in a nutshell
With OI proven to be independent from a firm industrial sector or size, and with the increasing adoption of OI by service firms (Chesbrough 2011; Chesbrough 2010a), it is important to understand what really makes Open Innovation as unique. Prof. Chesbrough comes to the rescue himself, by highlighting – ex-post – which are the main points of differentiation of OI (Chesbrough, Vanhaverbeke, and West 2006), as follows:
- External knowledge as important as the internal one, validated by the introduction of an external R&D function/ group.
- The centrality of the business model in converting R&D into commercial value, with IP and Capabilities that can find, in external entities with a more fitting business model, their ideal route to market.
- Lack of Type I and Type II measurement errors, with the mother company business model becoming a lesser threat to R&D investment decisions.
- Exit flow of knowledge and technology, towards partners, incubators, Joint Ventures.
- The widespread external knowledge landscape, based on the observation at the beginning of the chapter.
- The increased role of IP management, which is a key condition to transferring knowledge outside-in and inside-out.
- The rise of innovation intermediaries, as presented by Feller.
- Emergency of new metrics in assessing innovation capability and performance, e.g., with the expenses in internal R&D becoming irrelevant in the context of assessing innovation activity of a company.
It is pivotal to highlight that previous conclusions 2) and 3) include in the OI eco-system the concepts of Business Model (BM) and Business Model Innovation (BMI). Both concepts originate in corporate practice, and there is no commonly accepted definitions, at scholar level (Schneider and Spieth 2013). To this extend I will introduce a definition of BM which fits with the OI landscape (Chesbrough 2007):
Every company has a business model, whether they articulate it or not. At its heart, a business model performs two important functions: value creation and value capture. First, it defines a series of activities, from procuring raw materials to satisfying the final consumer, which will yield a new product or service in such a way that there is net value created throughout the various activities. This is crucial, because if there is no net creation of value, the other companies involved in the set of activities won’t participate. Second, a business model captures value from a portion of those activities for the firm developing and operating it. This is equally critical, for a company that cannot earn a profit from some portion of its activities cannot sustain those activities over time.
On the other end, BMI can be defined as (Amit and Zott 2010):
Business model innovation, […] involves defining a modified or new activity system, relies in recombining the existing resources of a firm and its partners, and does not require significant investments in R&D.
The bottom line is that what begins as a revolution for R&D, goes well beyond the technical functions, to embrace non-technological aspects. But is that really true in practice?
Not all Open Innovation approaches are born equal
Beyond BM and BMI, it should be clear that OI can be conceived as a set of diverse activities, (Chesbrough and Brunswicker 2013), in which it emerges that – among the many – customer and consumer co-creation and crowdsourcing are core activities in the OI inbound spectrum
While Open Innovation is often regarded as the Holy Grail of innovation, most large firms adopting it, do so selectively (Birkinshaw, Bouquet, and Barsoux 2012), because the openness comes with the complexity of managing the internal and external knowledge flows, as well as, the increased intricacy of licensing agreements. In the next paragraph, the author of this dissertation proposal will focus more in detail on the research on Open Innovation, which is the last part of our wider review of innovation literature.
Nevertheless co-creation and crowdsourcing are not perceived as equally important from OI companies. A recent survey of large European and American early adopters of OI (Chesbrough and Brunswicker 2014), reveals that customer co-creation – defined as involvement of customer and consumers into the innovation process – and crowdsourcing – defined as outsourcing of innovation problem-solving via open calls – rank at two extremes of the range. While co-creation is considered the most important activity among the inbound OI practices, with a better than peers increase in importance in the four years reference period, crowdsourcing ranks second-last with almost no improvement in the observation period.
The bottom line is that many firms have embraced certain aspects of Open Innovation more than others (e.g. inboud vs. outbound, co-creation vs. crowdsourcing, intermediaries vs. consortia), which is why our understanding of Open Innovation is limited by the point of view of our experience.
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