Beyond the Lab: The Critical Difference Between R&D and Innovation

John H Howard, 2 Aug 2024

This blog is written from 25 years of experience as an analyst and adviser in science, research and innovation policy, and innovation management. To many readers, the perspectives are not new, but it is still important that the different concepts are understood and appreciated so that both R&D and Innovation can drive Australia into the future.

The conflation of research and development (R&D) and innovation is a widespread issue in innovation policy, frequently leading to misconceptions about how policy is developed, designed, and executed. Understanding why this confusion exists requires an examination of the fundamental distinctions between R&D and innovation, the nature of innovation as an economic, social, and management concept, and the pervasive mindset of the "linear flow" model of innovation.

The OECD Frascati Manual (OECD, 2015) defines research and development (R&D) as fundamental, applied, and experimental. Basic research aims to generate new knowledge without regard for application, whereas applied research seeks to achieve a specific practical goal or purpose. Experimental development is a methodical process that uses prior research and practical experience to create new materials, products, or gadgets or improve existing ones.

The Oslo Manual (OECD/Eurostat, 2018) expands on this definition, defining innovation as "a new or improved product or process (or combination thereof) that differs significantly from the unit's previous products or processes and has been made available to potential users (product) or brought into use by the unit (process).

The difference between the two concepts is that R&D focuses on creating knowledge and technologies, whereas innovation focuses on the commercial and practical application of these creations. In this regard, and in the context of SRI policy, innovation is simply the successful application of new ideas, which may or may not originate in scientific research (Dodgson et al., 2015).

Innovation is commonly associated with change, whether within organisations or in the broader economic and socio-cultural context. It could entail creating value by repurposing existing tangible assets, like land and buildings, as well as intangible assets, such as knowledge and organisational capabilities.

In addition to social and cultural innovations, the definition of innovation has grown to include specific contexts such as soft innovation, hidden innovation, design innovation, service innovation, open innovation, disruptive innovation, and even dark innovation.

In all of these contexts, a scientific discovery or technological invention emerging from a research laboratory is not an innovation. They remain in that state until (if at all) they are adopted, applied, and used to create value for customers, businesses, or the broader community by meeting economic, social, and environmental objectives. Furthermore, knowledge creators and inventors may adopt and apply them in ways they did not anticipate.

One of the primary causes of terminology confusion is a focus on the concept of technological innovation (Godin, 2015), which typically relies on R&D as a foundational input. Economists widely acknowledge that technological change, whether external or internal, is a key driver of economic growth, productivity, and prosperity. However, conflating R&D with innovation ignores the critical stages of need, market validation, adoption, and scaling that define successful innovations.

Nonetheless, this critical transformation between scientific discoveries and technological inventions into adoption, application, and use is where true technological innovation takes place. This emphasises the importance of distinguishing between R&D and innovation in science research and innovation policy. It also highlights a cross-over between the science and technology paradigm and the management and organisational paradigm.

Distinguished management scholar Peter Drucker famously stated that new technology is the least important predictor of business innovation (Drucker, 1985). This viewpoint reinforces the belief that innovation has long been recognised as a critical business process (Ganguly, 1999) aimed at acquiring and retaining customers and end users. This critical aspect of management practice includes goal setting, strategic planning, and market-oriented actions (Drucker, 1955).

More recent management scholars argue that successful innovation necessitates not only technological advances but also effective business models, leadership, and a positive organisational culture (Agarwal et al., 2022; Tidd & Bessant, 2018). Research shows that some leadership styles, such as transformational leadership (Bass & Riggio, 2006) and servant leadership (Greenleaf, 1977), are more conducive to innovation than others.

The State also has always played an important role in paving the way for corporate innovations by enacting the principle of limited liability, establishing the principles of private property and intellectual property ownership, providing risk capital, and facilitating financial innovations (Mazzucato, 2013; Perez, 2002).

Policy commentators, advocates, and lobbyists who are swayed by the visible results of R&D activities may overlook these less tangible but equally important aspects of management and organisational change and the role of the State in driving innovation.

The linear model of innovation has long appealed to scientists and policymakers. This model depicts a sequential process from basic research to market introduction (commercialisation). It has shaped an understanding of innovation, owing in large part to its simplicity and ease of representation in diagrams and flow charts. Metrics are easy to define and capture, such as publications, patents, venture capital attracted, and so on.

Many people still argue that increasing funding for basic research will magically improve innovation performance through this logical sequence. It might, but it is now recognised that other policy interventions will be required. For example, representations of the linear flow frequently highlight the "valley of death" as a major barrier to research commercialisation, which has become a major focus of policy interventions.

The innovation systems model, based on knowledge economy concepts, is far more difficult to represent in a two-dimensional diagram. Attempts frequently result in complex wiring or circuit diagrams that provide little insight into where policy interventions can or should be made, particularly in the case of a systems failure—which is entirely different from the economist's concept of a market failure.

Failures in the innovation system are much more difficult to identify, address, and evaluate. Currently, there is a great deal of policy focus on collaboration, communication, connections, and relationships, as well as the need to build social capital among actors—people work with people they trust. Innovation system integrators are playing an increasing role in building and sustaining these connections.

Still, the linear model represents a fixed mindset, notwithstanding its failure to capture the complex, iterative, and interactive nature of real-world innovation processes. By extending the linear flow concept to prioritise technological innovation in businesses, Australian scientists and policymakers have for many years overlooked the critical role of management capacity and capability, failing to ensure that performance meets global standards.

Management capacity is frequently covered by glib notions of absorptive capacity, but innovation policy in Australia rarely addresses the fundamental deficit in Australian businesses' ability to embrace innovation strategically. As mentioned in a previous blog, Australian corporate boards, particularly their non-executive directors, frequently see their role as ensuring compliance, exercising control, securing government assistance, and managing (avoiding) risk. A capacity to lead through innovation is often missing.

Policymakers in Australia have largely ignored the spatial dimension of innovation, which frequently appears as a rhetorical validation in urban infrastructure and urban renewal initiatives spearheaded by State planning agencies and the property development industry.

Political and economic pressures encourage policymakers to prioritise R&D, which is frequently viewed as a commitment to future technological leadership and economic competitiveness. This is to be commended, but without corresponding investments in developing and strengthening innovation ecosystems, R&D's potential to drive economic and social value will go unrealised.

The confusion between R&D and innovation has serious consequences for economic development, policy effectiveness, and the overall innovation ecosystem. Misallocation of resources can occur because of disproportionately allocating funding to R&D activities, which may not yield the expected benefits. This results in an innovation ecosystem that may be rich in knowledge but poor in economic, social, and environmental returns, limiting job creation, prosperity, equity, and social inclusion outcomes—and potentially working against them.

Moreover, prioritising R&D over innovation can be stifling for innovation. Policymakers may unintentionally create environments that benefit large research institutions and corporations while ignoring the specific needs of start-up and scale-up entrepreneurs, small businesses in general, and social enterprises. This imbalance may result in a lack of diversity in the innovation ecosystem, with large, established firms dominating and smaller, more agile entities struggling.

There is now a widespread understanding that innovation covers socio-cultural innovations that address societal and community concerns. Without this broader perspective, policymakers may overlook opportunities to support innovations that can have a significant impact on health, education, environmental sustainability, and social inclusion. This is being recognised, for example, in the food innovation subsystem as concerns grow about nutrition, human health, and impacts on vulnerable communities.

Innovation is currently playing a critical role in addressing pressing societal issues such as climate change and sustainable development. Among its many benefits, it promotes the development of renewable energy technologies, advanced medical treatments, and environmentally friendly agricultural practices. However, the emergence of innovations with dubious ethical, social, or environmental consequences gives policymakers the difficult and unenviable task of distinguishing between innovations that truly benefit society and those that have undesirable consequences.

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The concepts of R&D and Innovation have a complex and mutually beneficial relationship. Each plays an important role in driving advances in technology, economic growth, natural capital protection and preservation, and societal progress.

Understanding this connection is critical for developing effective policies and building a strong innovation ecosystem.  

Countries with a strong R&D infrastructure maintain a competitive advantage in the global marketplace by attracting investment and fostering high-tech industries. Innovation, or the successful application of new knowledge and ideas, not only stimulates economic growth and increases international competitiveness but also makes a significant contribution to achieving social and environmental goals.

Policymakers are increasingly recognising the distinct but interconnected roles of R&D and innovation, providing funding for scientific research, incentivizing innovation, and creating environments that encourage collaboration among researchers, businesses, and stakeholders.

References

Agarwal, R., Patterson, E., Pugalia, S., & Green, R. (2022). Innovation. Routledge, Taylor & Francis.

Auerswald, P. E., & Branscomb, L. M. (2003). Valleys of Death and Darwinian Seas: Financing the Invention to Innovation Transition in the United States. The Journal of Technology Transfer, 28(3-4), 227-239. https://doi.org/10.1023/A:1024980525678 

Bass, B. M., & Riggio, R. E. (2006). Transformational Leadership (2nd ed.). Lawrence Erlbaum Associates.

Godin, B. (2015). Innovation Contested: The Idea of Innovation Over the Centuries (Kindle Edition). Routledge.

Greenleaf, R. K. (1977). Servant Leadership: A Journey into the Nature of Legitimate Power and Greatness. Paulist Press.

Drucker, P. F. (1955). The Practice of Management. Pan Books.

Drucker, P. F. (1985). Innovation and Entrepreneurship: Practice and Principles. Harper & Row.

Dodgson, M., Gann, D., & Phillips, N. (2015). The Oxford handbook of innovation management. Oxford University Press.

Ganguly, A. S. (1999). Business-driven R&D: managing knowledge to create wealth. Macmillan.

Mazzucato, M. (2013). The Entrepreneurial State: Debunking Public vs Private Sector Myths. Penguin Books.

Mulgan, G., Tucker, S., Ali, R., & Sanders, B. (2007). Social Innovation: What It Is, Why It Matters, and How It Can Be Accelerated. The Young Foundation. https://youngfoundation.org/wp-content/uploads/2012/10/Social-Innovation-what-it-is-why-it-matters-how-it-can-be-accelerated-March-2007.pdf 

Organisation for Economic Co-operation and Development, & Eurostat. (2018). Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation (4th ed.). OECD Publishing. https://doi.org/10.1787/9789264304604-en

Organisation for Economic Co-operation and Development. (2015). Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development. OECD Publishing. https://doi.org/10.1787/9789264239012-en

Perez, C. (2002). Technological revolutions and financial capital: the dynamics of bubbles and golden ages. Edward Elgar Pub.

Tidd, J., & Bessant, J. (2018). Managing Innovation: Integrating Technological, Market and Organizational Change (6th ed.). Wiley.