Commercialization of federally funded research at universities faces a bewildering array of obstacles. The reason: innovation — the translation of knowledge into value (or money) — emerges from continuous knowledge flows. Unfortunately, these knowledge flows can be easily blocked in multiple ways.
Taken together, these knowledge flows form an “ecosystem”, networks embedded in other networks, that support and accelerate commercialization. From the perspective of an ecosystem, we can reframe our challenge. Accelerating commercialization involves improving the productivity of start-up and innovation ecosystems that both surround universities and are fueled by federal research.
From this perspective, we are not trying to fix old systems that were never intended to work together. We are not “removing barriers”. Rather, we are designing new, more productive networks of collaboration.
We need to start down a new pathway. We can reframe the challenge by focusing on three categories of solutions to strengthen start-up and innovation ecosystems.
- Collaboration solutions among all the actors in the ecosystem;
- Administrative solutions led by federal agencies; and
- Legislative solutions led by Congress.
Where we stand
Researchers have documented the many obstacles to commercializing university-based research. These include insufficient faculty time, weak faculty incentives, the absence of a commercialization infrastructure within or adjacent to the university, restrictive regulations and policies, lack of commercialization skills and entrepreneurial thinking among the faculty, and weak interactions with industry representatives. (See, for example, Vanderford, et.al., 2013).
Congress and federal agencies cannot fix these problems with new directives. Major increases in federal funding are equally unlikely. Yet, they can be partners in designing “what’s next”, in rethinking their role within the ecosystems surrounding universities. In short, they can take important steps to Improve the productivity of commercialization.
Moving in this direction requires a new mindset from all actors in the ecosystem. The linear model of technology transfer is inadequate to capture the complexities of an ecosystem. Knowledge from university to industry flows through social networks (Ostergaard, 2009). That’s why understanding how to design and guide the knowledge flows through ecosystems and clusters becomes important to understand.
Federal agencies are already moving in this direction. In 2010, the National Science Foundation’s Directorate for Engineering issued an important white paper on the role the NSF plays in innovation ecosystems. NSF has subsequently funded like like Engineering Research Centers to stimulate the formation of these ecosystems. Other agencies are moving in a similar direction. Cluster-based initiatives by the Economic Development Administration and the Small Business Administration focus on designing networks of collaboration. NIH has funded three Research Evaluation and Commercialization Hub sites to accelerate commercialization and technology transfer in the life sciences and biomedical technology.
Defining Start-up and Innovation Ecosystems
For the past two years, Purdue has been working with Fraunhofer IAO, based in Stuttgart, to understand how to strengthen ecosystems surrounding universities by following “market-facing” principles of design. Universities operate with two overlapping ecosystems, one focused on generating start-ups and the other focused on innovation among established firms.
In our work with Fraunhofer, we are exploring how to design new collaboration platforms for universities following Fraunhofer’s market-facing principles. With our partners at New Jersey Institute of Technology, we piloted these approaches with the New Jersey Innovation Institute.
At the same time, we are using this approach to explore how we can transform engineering education within the university to strengthen innovation and entrepreneurship. We have been engaged in two NSF funded initiatives: Pathways to Innovation, managed by Stanford University, and Revolutionizing Engineering Departments.
Based on our experience in designing guiding new networks, collaborations and clusters, we see three focus areas or “solution sets” emerging from this work. We can strengthen the ecosystems surrounding universities in three ways:
Collaboration solutions. – Three types of collaborations are emerging: collaborations within the university; collaborations between the university and industry; and collaborations among federal agencies.
- Within the university new solutions are emerging to expand incentives for commercialization activity among faculty and students. The NSF funds an initiative led by Stanford University and VentureWell provides an insight into how universities are creating new collaborations to stimulate innovation and entrepreneurship in undergraduate engineering programs.
- Collaborations between the university and industry arise in a number of different ways. They can be led by industry, such as GlaxoSmithKline’s Discovery Partnerships with Academia; designed by universities, such as the Deshpande Center for Innovation at MIT; or stimulated formally or informally by federal agencies, such as the workshops conducted under the sponsorship of the National Nanotechnology Initiative.
- Collaborations among federal agencies are most clearly expressed in joint funding proposals to stimulate start-ups and innovation.
Administrative solutions.— Federal agencies can take a wide range of actions within current statutory frameworks. These actions span from regulatory interpretations and guidance letters to rule makings and executive orders.
Legislative solutions.— Congressional authorization and appropriations can create new collaborative initiatives, such as those found in the America COMPETES Act, and the Workforce Investment and Opportunities Act.
Our Next Steps
We are focused on building an Indiana Innovation Platform with ur colleagues at Indiana University and the University of Notre Dame: How do we pilot an innovation platform in Indiana? In addition, we are exploring how we might move forward with the Federal Laboratory Consortium: How could we start using these insights to design and guide the development of innovation ecosystems surrounding federal labs?