In April 1970, NASA’s Mission Control Centre in Houston received a communication from astronauts onboard Apollo 13: “Houston, we’ve had a problem”. Perhaps, one of the most quoted problems of all. After a few minutes, it was clear that this was not a simple glitch or an instrumentation problem, but some kind of monster system failure.
When problems appear in complex situations, in which many elements are interconnected and the relation between them is uncertain and non-linear, finding solutions requires a special set of analyses and approaches. As Apollo’s 13 flight program director put it: “We realised we’d got some problem we didn’t fully understand, and we ought to proceed pretty damn carefully”.
Knowledge and value creation is a complex system, with many moving parts and emerging properties that cannot be predicted by looking at its building blocks separately. Despite the challenge, it is important to navigate the system to identify improvement opportunities given the system’s production of innovations with potential economic and social impact. In particular, deep technologies sit at the difficult end of the R&D spectrum and are associated with a particularly challenging set of conditions: long development cycles, high-risk investments, and uncertain market adoption paths.
Discovery, publication and dissemination of new knowledge are important parts of the system, but focusing only on that side of the coin leaves a lot of value unrealised.
Academic researchers are a central part of the knowledge and value creation system and therefore have a key role in its functioning. They have deep domain knowledge and understanding, which instils trust in other stakeholders or partners that are required for increasing the technological and commercial readiness level of their ideas. Researchers are also at the front line of what is known, and by being the closest to that edge they are very well-positioned to discovery and innovation.
However, being in the right place at the right moment is insufficient. The mindset through which researchers address the challenges and discoveries is very important to maximize the transformational potential of their discoveries.
While finding themselves in front of new knowledge with potential for social impact, researchers may be unable to identify the extent of the opportunity or unwilling to dedicate themselves to the entrepreneurial career, being too focused on scientific impact. The lack of such an entrepreneurial culture is an important aspect of the research commercialisation problem.
Although discovery and innovation are not only compatible but synergistic, it could be argued that they are two different full-time jobs that require a distinct set of skills. Researchers need to be surrounded by a whole ecosystem that supports and facilitates knowledge transfer, but researchers themselves also need to embrace the skills, tools and models that will allow them to transition from discovery to innovation modes. To this purpose, researchers would benefit from acquiring entrepreneurial skills and business acumen to navigate technology commercialization, market validation, intellectual property and fundraising.
Researchers would also benefit from initiatives that provide them with more visibility into industry challenges through frequent and facilitated knowledge exchanges, both formal and informal, and with support networks of other academic peers who successfully or unsuccessfully attempted the entrepreneurial transition. Unfortunately, these trainings and initiatives are not sufficiently popular among academics and this is a problem if we collectively want to maximize and accelerate the transformational impact of research.
Lastly, it is important to acknowledge that there is also a lack of incentive alignment between research and commercialisation. Most researchers and academic institutions focus the majority of their time and resources on academic objectives, overlooking the practical implementation of their work beyond the lab to address societal and industry challenges.
Research incentive structures are deeply rooted in academic organizations and are supported by well-sedimented layers of culture that define what is a prestigious and excellent researcher. However valuable these incentive structures have been in the past, it is important to acknowledge that maybe these are not the best anymore for today’s world and we may need to adapt them.
These key aspects of culture, knowledge and incentives form the base of the wicked three-body problem of research commercialization. However, diagnosis is only the first step to real problem solving, which also requires the definition of a coherent set of actions designed to overcome the specific challenges identified and their real-world communication, implementation and monitoring.
Just as in the Apollo 13 situation, given the complexity and interconnectedness of the academic and entrepreneurial systems, also here “we ought to proceed pretty damn carefully” when implementing solutions to the research commercialization problem to avoid unintended consequences.