Innovation and complexity
Andrew Wyckoff, Director, OECD Directorate for Science, Technology and Innovation
Since its creation in 1961, the OECD has influenced how governments approach science, technology and innovation, and how economics as a discipline tries to understand these phenomena. The OECD Working Party of National Experts on Science and Technology Indicators (NESTI) was created in 1962, and in 1963, Science, economic growth and government policy convinced governments that science policy should be linked to economic policy. In 1971 Science, growth and society anticipated (also called the “Brook Report” after the Chair, Harvey Brooks) many of today’s concerns by emphasising the need to involve citizens in assessing the consequences of developing and using new technologies.
For many experts though, the major contribution was the concept of national innovation systems, presented in 1992 in a landmark publication, Technology and the Economy: The Key Relationships. The origins of the concept go back to the 1970s crisis, which had provoked an in-depth re-examination of previous economic thinking on how growth came about and why growth in productivity was slowing. A 1980 OECD report, Technical Change and Economic Policy, is now widely recognised as the first major policy document to challenge the macroeconomic interpretations of the 1970s crisis, and to emphasise the role of technological factors in finding solutions, arguing for instance that innovation can be more powerful than wage competitiveness in stimulating an economy.
Economists working at the OECD were pioneers of a new approach that saw innovation not as something linear but as an ecosystem involving interactions among existing knowledge, research, and invention; potential markets; and the production process. In national innovation strategies, one of the key issues is the interactions among the different actors: companies, public research institutions, intermediary organisations, and so on. And contrary to the dominant thinking in policy circles in the 1980s and early 1990s, the OECD also saw it as something that governments should play a central role in – hence the term national innovation strategy.
Today, services are becoming the focus of innovation, with some companies even blurring the distinction between the value-added of products and services, smartphones being a good example. This is a logical outcome of the increasing digitalisation of the economy. Digital technologies are now so ubiquitous that it is easy to forget how recent they are. The World Wide Web we know today for example was created in the 1990s, and Microsoft thought it was possible to launch a rival to Internet (called MSN) as late as 1995. Google was only founded in 1998 and it would be 6 years before it went public.
With the digital economy and society coming so far in such a short time, it is hard to predict what they will look like in the future. We can however identify some of the drivers of change. Big Data will be among the most important. In The phenomenon of data-driven innovation, the OECD quotes figures suggesting that more than 2.5 exabytes (EB, a billion gigabytes) of data are generated every single day, the equivalent of 167 000 times the information contained in all the books in the US Library of Congress. The world’s largest retail company, Walmart, already handles more than 1 million customer transactions every hour. Because so many new data are available, it will be possible to develop new models exploiting the power of a complexity approach to improve understanding in the social sciences, including economics. Also, the policy making process may benefit from new ways of collecting data on policies themselves and vastly improving our evaluation capabilities.
The analysis of data (often in real time), increasingly from smart devices embedded in the Internet of Things opens new opportunities for value creation through optimisation of production processes and the creation of new services. This “industrial Internet” is creating its own complex systems, empowering autonomous machines and networks that can learn and make decisions independently of human involvement. This can generate new products and markets, but it can also create chaos in existing markets, as various financial flash crashes have shown.
Two sets of challenges, or tensions, need to be addressed by policy makers to maximise the benefits of digitally-driven innovation, and mitigate the associated economic and societal risks. The first is to promote “openness” in the global data ecosystem and thus the free flow of data across nations, sectors, and organisations while at the same time addressing individuals’ and organisations’ opposing interests (in particular protecting their privacy and their intellectual property). The second set of tensions requires finding policies to activate the enablers of digital-driven innovation, and at the same time addressing the effects of the “creative destruction” induced by this innovation. Moreover, there is a question concerning the efficacy of national policies as digital-driven innovation is global by definition. As a policy maker you can promote something in your country, but the spillovers in terms of employment or markets can be somewhere else.
With so many new technologies being introduced, more firms and countries being integrated into global value chains, and workers becoming more highly educated everywhere, you would expect productivity growth to be surging. In fact it is slowing. But that average trend hides the true picture according to an OECD study on The Future of Productivity . Labour productivity in the globally most productive firms (“global frontier” firms) grew at an average annual rate of 3.5 per cent in the manufacturing sector over the 2000s, compared to 0.5% for non-frontier firms.
Diffusion of the know-how from the pioneering frontier firms to the bulk of the economy hasn’t occurred – either because channels are blocked or because we are in a transformative period and the expertise for how best to exploit the technologies is still in the heads of a few. Most likely, it is a combination of the two. We therefore have to help the global frontier firms to continue innovating and facilitate the diffusion of new technologies and innovations from the global frontier firms to firms at the national frontier. We can try to create a market environment where the most productive firms are allowed to thrive, thereby facilitating the more widespread penetration of available technologies and innovations. And we have to improve the matching of skills to jobs to better use the pool of available talent in the economy, and allow skilled people to change jobs, spreading the know-how as they move.
In a complex system, you can’t forecast outcomes with any great degree of certainty, but many of the unintended outcomes of interactions in the innovation system are beneficial. The policies mentioned above would each be useful in themselves and would hopefully reinforce each other beneficially.
The Innovation Policy Platform (IPP), developed by the Organisation for Economic Co-operation and Development (OECD) and the World Bank is a web-based interactive space that provides easy access to knowledge, learning resources, indicators and communities of practice on the design, implementation, and evaluation of innovation policies.