University Innovation & Entrepreneurial Ecosystems in Challenging Environments
reblog of my LinkedIn Pulse post of 1/9/2015.
When global leaders seek to build “knowledge economies,” they often look to universities for answers. Universities have historically been the primary generators of new knowledge, and have infrastructures and resources in place to drive innovation. Around the world, academic institutions are grappling with how to foster ecosystems that fuel technology-driven growth and address development challenges. They are logical places for the seeds of new innovation ecosystems to be sown.
But how exactly are universities doing this, and what are the results? The success of an entrepreneurial and innovation (E&I) ecosystem is notoriously difficult to gauge. Above all, there is a tendency to measure what is easy to measure. Technology transfer offices have a host of metrics ranging from invention disclosures per 100 fulltime STEM faculty and number of issued USPTO patents, to licensing revenue and industry-sponsored research as a proportion of overall R&D funding. These metrics are easy because they quantify success in distinct units: disclosures, patents, and dollars.
Two measures of success
These metrics don’t tell the whole story, however. A two-part report published in 2013 and 2014 by Dr. Ruth Graham with the MIT Skoltech Initiative summarized a survey of university leaders and a series of case studies on global E&I efforts. A key finding: according to experts, intellectual property-based metrics not only do not reflect a university’s true knowledge transfer capability, they may actually impair E&I strategy at an institutional level.
Patents and money aren’t a true reflection of what’s really important for university-centered E&I ecosystems. Using metrics like these for an E&I ecosystem is like measuring the vigor of a biological ecosystem by counting nonliving factors only. It prioritizes the wrong things and misses the whole point.
What, then, should leaders pay attention to? In assessing the health of an E&I ecosystem, we should look at both intellectual and human capital. Intellectual capital is the discrete embodiment of new knowledge in a technological development. It is protected through legal constructs, or patents, that enable the originator or owner to maintain a monopoly on the use of that knowledge for a period of time, or grant exclusions to that monopoly through licensing. Intellectual capital is, in this sense, a closed loop.
Human capital, in contrast, is all about people, the world’s most underutilized resource. People are the conduits for gaining and transferring knowledge and realizing the potential of new knowledge through E&I. They are nodes in an E&I network. As nodes connect, innovation capacity grows. Graham characterizes the difference in building human versus intellectual capital as the act of “creating fishermen and not the fish.”
So much of the vibrancy of an ecosystem depends on the human factor. Jason Bloomberg, President of Intellyx, emphasizes the role of how people interact in organizations in achieving exponential innovation:
“…even for the most technical of innovations, the most important component systems of the complex system of systems we call an organization are people, not technology subsystems. Innovation, after all, is a human endeavor. Technology innovation is itself a set of organizational processes.”
To effectively catalyze robust Entrepreneurial and Innovation Ecosystems, universities need to focus on people, developing and leveraging a diversity of human capital, the real fuel that drives the innovation economy.
Bringing the ivory tower to the grassroots
There’s another problem with relying on cold, intellectual capital-based metrics to determine an ecosystem’s worth. Because they are focused on universities, and in particular on universities’ technology transfer operations, they undervalue the contributions of local entrepreneurs.
Graham points out that there are two typical forms that E&I ecosystems tend to take. The first model is “bottom-up” and community-led, catalyzed by students, alumni, and entrepreneurs in the regional economy, with “loose IP control.” The second model is the opposite: it is “top-down” and university-led, working through established university structures, with “tight IP control.”
I believe that there are other pathways: middle ground between these two models. This pathway includes community and industry engagement efforts, localized to the specific needs of the region. It represents a tremendous opportunity for universities looking to catalyze an E&I ecosystem. The key to success is not duplicating existing models. As the World Economic Forum prescribes:
Often these efforts involve a university engaging to build absorptive capacity, thereby enabling local, entrepreneurial SMEs to recognize the value of, assimilate, and commercialize new technologies coming out of university research. Absorptive capacity is an acute problem in developing and transition economies, and a significant barrier to spillovers of university research into local environments.
Indeed, Graham notes that “an entrepreneurial university is one that supports and integrates both (the top-down and bottom-up) … domains.” This requires adaptation of traditional university technology transfer models. A new set of metrics and benchmarks. A new paradigm that balances the value of technology and intellectual property with people and their interactions.
Creating models that work
In the E&I ecosystem space, everyone talks about replicating the Silicon Valley model. Silicon Valley is the textbook setting for E&I growth, and certainly has many lessons to teach. But it’s time we recognize that the factors at play in Silicon Valley don’t apply everywhere.
The environments most in need of E&I ecosystems are challenging places. These places are often vastly different from Silicon Valley, places where key factors that led to success in the Bay Area are nowhere to be found. Furthermore, when the world desperately needs to decarbonize the global economy and provide adequate food, water, and healthcare for a burgeoning population, Silicon Valley’s focus is of questionable relevance.
Instead of emulating others’ successes, it is critical to leverage local strengths and regional needs, and summoning the institutional will to challenge and adapt global “best practices” to suit a unique ecosystem. A culture of experimentation needs to be nurtured not only in the research labs, but also in university administration – part of Bloomberg’s admonition to extend exponential innovation to the organization.’
University-centered E&I ecosystem-building is a balancing act, making top-down meet bottom-up and recognizing the preeminence of human capital. Mechanisms for bridging the two models—and measuring their success—should be localized. Universities can use what is applicable from others’ efforts, but should also embrace the opportunity to create new structures, networks, and solutions all their own. More thoughts on this in my next post.