The New Innovation Paradigm: Superclusters and Economic Complexity
INNOVATION ECOSYSTEMS EMERGE AS PARADIGMATIC
Key Takeaways
Improving innovation ecosystem outcomes – and transplanting those success factors everywhere they are needed – addresses a critically important, global opportunity.
This article identifies key ingredients innovation ecosystems require for maximal success. Included is a discussion of “superclusters” which we then link to economic complexity: “building complex capabilities is a superior development strategy to chasing the ability to produce high-priced goods.”
In 2017, the Canadian government announced nearly a billion dollars of investment in the Innovation Superclusters Initiative. The government described this as an “investment in Canada’s five Superclusters [that] will help build first-rate innovation ecosystems with a competitive edge.”
The five superclusters – digital technologies, artificial intelligence, ocean industries, protein industries, and advanced manufacturing – are intended to provide the conditions for academics, entrepreneurs, government, not-for-profit organizations, and capital providers to produce outcomes well in excess of what was considered to be poor national performance in the commercialization of world-leading research and development.
Beaudry and Solar-Pelletier’s report notes the supercluster program is best viewed as investment in innovation ecosystems, “providing all stakeholders with a unique opportunity to identify the factors that facilitate the emergence and success of innovation ecosystems, and allowing policy-makers to better design and fine-tune innovation policies and programs.”
Innovation ecosystems and the superclusters are networks built to integrate different strong science communities, well-integrated sectors and supply chains, as well as other organizations and firms interested in the use of common key technologies.
The Superclusters Initiative: An Opportunity to Reinforce Innovation Ecosystems
Innovation ecosystems comprise elements like infrastructure (physical and digital), knowledge (know-how) and proximity (with the latter term evolving beyond geographic proximity to include forms like organizational, cognitive, and social proximity), fused together by degrees of collaboration; the higher the better. While “collaboration, cooperation and open innovation are of paramount importance to well-functioning ecosystems,” because innovation ecosystems contain a wide range of activities spanning applied research, newly commercialized technologies, nascent startups, and scaling firms, it follows that networking and information sharing often change in nature and extent from one end of the spectrum to the other. An innovation ecosystem truly behaves like an ecosystem when it demonstrates self-sustaining, organic activity. From its platform of shared knowledge, expertise, and resources issues a pipeline of products and services, which replenishes the ecosystem itself. Current measures of ecosystem success – number of startups, number of patents, dollars invested – do not capture the self-sustaining concept, requiring more advanced metrics.
Beaudry and Solar-Pelletier note that metrics like overall employment levels can sometimes operate as an innovation contra-indicator – that falling employment can be a time of great innovation. (Necessity being the mother of invention.) “We suggest that measures of the quality and innovative capacity of human capital in relation to the stage of development of the technology be added to the indicator list.” The authors highlight the threat of discontinuous innovation – wherein the twin concerns of a relentlessly high pace of change and high risk of creative destruction combine to cripple the value of current research. Innovation ecosystems address this problem: the probability of value creation via knowledge transfer, adaptation, commercialization and scaling increases when certain foundational methods and resources are open and available to ecosystem participants. These include research facilities, colleges and universities, information sharing and networking, commercialization methodologies (e.g. agile, rapid prototyping, minimum viable product), and specialized programs, taxation and regulation policies designed to remove impediments and incentivize entrepreneurial activities.
They emphasize not only the critical need for proper measures but that nations, firms, universities and colleges, and entrepreneurs should view innovation ecosystems as paradigmatic: The speed at which discontinuous and potentially disruptive technologies such as AI and industry 4.0 emerge forces all stakeholders to be involved from the beginning in well-coordinated collaborative entities, such as innovation ecosystems or superclusters.
Working together could yield a collective performance that is larger than the sum of its parts, a win-win situation for the ecosystem and its constituents.
The Superclusters Initiative: An Opportunity to Reinforce Innovation Ecosystems
GUIDANCE
Note the connection between Beaudry and Solar-Pelletier’s innovation ecosystem research and economic complexity. The latter is important because it is the platform upon which innovation ecosystems are built. Public and private sector administrators manage growth, development, technological change, and resilience while seeking to minimize income inequality and spatial disparities. Focusing on better results in each of these socioeconomic measures enables us to minimize inequalities and disparities while maximizing growth and resilience.
Innovation is a socioeconomic process. Successful innovation ecosystems benefit from diversification (Beaudry and Solar-Pelletier); diversification is an outcome of economic complexity. (Balland, Broekel et al) Diversification (a widening range of new products, services, IP etc.) is observable at the firm, region and national level; specialization at the level of the individual. Diversification and specialization are the outcomes of critically important inputs like tools (e.g. a computer), codes (e.g. a programming language or application), and know-how (individual expertise, training, competence). Tools and codes are comparatively easy to acquire, know-how, however, is very hard to acquire. (Balland, Broekel et al)
Making things more complicated, the “division of knowledge across many individuals allows us to overcome individual human limits and makes the technological progress of modern societies possible.” That is, individuals may develop an astonishing degree of know-how but, given the complexity of modern technologies, cannot possibly know all there is to know. They must collaborate with other individuals holding different specializations. This leads to the complicated part: “The whole knows more because individuals know different, which is to say that the growth of know-how happens thanks to specialization.” Specialized solutions emerge beyond the know-how of the individual specialists. Completing the loop: specialized solutions created by collaborating individuals feed back to the individual level, raising their know-how, empowering them to create new initiatives based upon their newfound knowledge. This is innovation writ large, a self-perpetuating ecosystem continuously producing new technologies, firms, and intellectual property.
When we put this all together, the elements and process become more clear. We know what we want: successful innovation ecosystems. We know that improving innovation ecosystem outcomes and transplanting those success factors everywhere they are needed addresses a critically important, global problem. “Supporting economic upgrading by building complex capabilities is a superior development strategy to chasing the ability to produce high-priced goods.
As Beaudry and Solar-Pelletier note, we lack the advanced metrics which would enable us to make declarative statements about the optimal innovation ecosystem formula. But if we accept that regions and municipalities all aspire to be the “Silicon Valley of X” and we know we want nascent innovation ecosystems to be able to thrive and replenish, then ingredients leading to economic complexity must be present in innovation ecosystems.
INNOVATION ECOSYSTEMS EMERGE AS PARADIGMATIC
We can assemble this into a simple feedback loop, with the caveat that devil is always in the details:
Tools (infrastructure, e.g. universities, research parks), codes, and know-how produce individual specialization
Collaborating specialists + infrastructure lead to the whole (e.g. firms) knowing more because individuals know different
Specialization at scale (firms, regions, countries) leads to diversification
Specialization and diversification lead to increased levels of innovation, and the growth of know-how
Specialists possessing greater know-how seek out innovation ecosystems
Innovation ecosystems, including superclusters, offer the tools current and future specialists require
SOURCES:
Beaudry, Catherine, and Laurence Solar-Pelletier. 2020. The Superclusters Initiative: An Opportunity to Reinforce Innovation Ecosystems. IRPP Study 79. Montreal: Institute for Research on Public Policy.
Pierre-Alexandre Balland, Tom Broekel, Dario Diodato, Elisa Giuliani, Ricardo Hausmann, Neave O’Clery, David Rigby; 2020; The new paradigm of economic complexity; Volume 51, Issue 3; Research Policy.