The funding of science and venture capital in a non-linear world
December 22, 2011
Thought provoking post by Lucy P. Marcus on venture capital and science funding: A perfect storm: global shifts in venture capital and science funding. Lucy writes,
The whole spectrum of sciences, including vitally important areas such as cleantech, life sciences and biotech, and engineering, is facing extreme upheaval, particularly related to the funding of scientific research. In an overall difficult economic situation, cuts by governments in the area of blue-skies research and less funding available from corporates have created an environment in which the funding of science that is not immediately of commercial value is seen as unnecessary, imprudent, and wasteful.
At the same time, scientific advancement has been very rapid, and tremendous progress has been made in all areas of science. But this has come at a price, quite literally: scientific research is expensive, it takes place at a very high level of complexity, and some of it is speculative with often long and rarely direct routes from idea to commercialization.
A sustainable answer?
Finding a sustainable answer is important, Lucy points to the complexity of funding science, its long gestation, and the increasing desire by VC’s for short-term gain and a decreasing appetite for “risk” as they perceive it. Informed and prudent investment decisions thus require a new level of sophisticated scientific expertise, and most venture funds are not well equipped to do this. As a consequence, they seek the comfort and greater certainty of later-stage investment that comes with a proven idea and income stream on its side. The question arises then is the VC model broken, or broken enough to be rethought?
Innovation eco-systems and architectures
Lucy argues: If retaining their positions as world leaders in scientific exploration and its commercialization is vital to the G7 economies, what needs to be done and are we willing to do it? The gap that needs to be covered is between the origin of an idea and that stage in its development where its successful commercialization is more likely than not. Early-stage investment funds can play a vital role in bridging this gap: they pick up where notional research leaves off but well before the commercial value of a discovery has been completely verified. Early-stage investment funds thus provide the answer to the question of who decides what gets funded because they bring together scientific experts with venture capitalists — those who understand the complex science behind the idea right at the point of due diligence and those who have the business acumen to vet business plans, fund them, and guide their implementation.
And one cannot argue with that, so what to do? Those economies, argues Will Hutton prepared to stay open and create national innovation architectures that support a diversified landscape of vigorous firms, institutions and technologies will repeat the amazing feat of the British Industrial Revolution at the end of the 18th Century – But such innovation eco-systems will not be created spontaneously we need to develop an interconnected eco-system that can respond to these dilemma’s by designing answers that today do not exist. Something that the many people I met in Boston recently were at pains to point out to me. This eco-system is created out of networks or networks which are both local and global. These new models of entrepreneurship, argues John Seely Brown, are built upon also the human talents of deep listening, recipricocity and embedded trust in networked knowledge flows. The eco-system in Boston has a thriving situated community around Boston (academia, entrepreneurs, mentors that want to give back and angel + VC funding, and whole support infrastructure), they use mentoring extensively, in a recent conversation with Sherwin Greenblatt of the MIT Venture Mentoring Service, he explained to me how anyone at MIT (staff or students) can use the service, and that recently a great success was the sale of a drug delivery system innovated at MIT which had been in gestation for 8 years. In fact the eco-system for funding innovation and bringing that innovation to market is central to how science is funded. Equally the MIT Industry Liason program is very good at attracting inward investment into MIT. This is structured in such a way to be of huge incentive for academia to engage with the commercial world. And a case in point is a large company investing $70m over 5 years into a particular form of life sciences, and then hiring quite a few MIT grads consequently.
In a post I wrote on the challenges with big pharma, funding, accelerating innovation I quoted John Martin who was writing in New Scientist,
There is another way to fund the development of new treatments. Many innovative ideas that have changed society have arisen from the combination of curiosity and academic freedom found in universities. This is where small amounts of funding can produce big results. In recent years, university research has been exploited by industry to produce new drugs, such as blood clot-busting “tissue plasminogen activator”, courtesy of the Catholic University of Leuven (KUL) in Belgium.
Now, while big pharma has so much money it doesn’t know what to do with it, universities are being starved of resources and research funding has decreased in real terms. At the same time, university research strategy is under-organised and there is ignorance of how to exploit intellectual property and utilise patents. Nevertheless, the potential of universities is enormous.
So the problem is not just VC’s – its the eco-system they exist in and the way in which innovation and scientific breakthroughs can be made – it is essentially a design problem. Gordon Brown, our recent PM visited MIT and consequently wanted to create something similar in the UK – but we have not been successful, and that has a great deal to do with culture.
Another aspect which we should consider is the emergence of new platforms for venture funding, and new approaches to innovation. The answer is yes, and it comes from an unexpected and unrelated corner of the universe: open source software development, argues Karim R. Lakhani, an assistant professor at Harvard Business School. His research leads to these conclusions:
- Practices in the open source software community offer a model for encouraging large-scale scientific problem solving.
- Open up your problem to other people in a systematic way. A problem may reside in one domain of expertise and the solution may reside in another.
- Find innovative licensing ways or legal regimes that allow people to share knowledge without risking the overall intellectual property of the firm.
TopCoder is one very good example: TopCoder is a company which administers contests in computer programming. TopCoder hosts fortnightly online competitions — known as SRMs or “single round matches” — as well as weekly competitions algorithm in design and development. The work in design and development produces useful software which is licensed for profit by TopCoder. Competitors involved in the creation of these components are paid royalties based on these sales. The software resulting from algorithm competitions — and the less-frequent marathon matches — is not usually directly useful, but sponsor companies sometimes provide money to pay the victors. Statistics (including an overall “rating” for each developer) are tracked over time for competitors in each category.
Karim Lakhani believes,
Open source collaboration is a very different model for innovation and product development than most firms are used to. I began to wonder where we might see similar patterns occur outside the software domain. In open source communities we see a vast degree of openness in which everybody can participate, but also the practice of broadcasting your work to everybody else. People continually broadcast their problems, others broadcast solutions, and the person with the problem is not always the one with the solution. Oftentimes, somebody else can make sense of both what the problem has been and what people are proposing as solutions, and can come up with a better answer.
Something I explore in a summing up presentation I gave at the conference Competing to Innovate which was held at MIT/Sloan School of Management in Boston 12 January 2011.
Further reading  Out of Control: The new biology of machines  Technologies of cooperation  The Origin of Wealth: Evolution, complexity, and the radical remaking of economics  Theory U: Leading from the Future as it Emerges  What Technology Wants