Understanding is different from Exploitation

This week I gave a talk at the Praxis Unico Annual Conference.  The nice people at Research Fortnight invited me to write it up as an article, but it is behind their paywall.  They have, however, allowed me to post it here.  Aren't they lovely?

With the increasing political emphasis on innovation-fuelled growth, the question of how to turn the UK’s scientific capability into commercial success is becoming more and more important. With past efforts largely unsuccessful, what is the relationship we need to build between universities and companies to enable a successful UK economy?

In my career, I have never encountered a successful product or service that did not have its basis in research of some kind—but the time between the research and its application can be long. Also, the most successful products or services meet a need, at the right price, and their provenance is often complicated and multi-disciplinary.

The term 'science' usually refers to the exploration of the world around us with the intent of understanding it. We observe and measure how things work and construct models to explain what we see and predict what might happen outside the realm of our experience.

This approach applies to the traditional sciences of mathematics, physics, chemistry and biology. It also appliesto the engineering and design that make things work in the real world, and to the social sciences that give insight into how humans respond to all these wonders.

For many years, the assumption was that good science gave good economic returns. This led successive governments to invest in the science base and assume that growth would ensue. This linear model, however, has been largely discredited—but so far there are no persuasive alternatives.

During my time in industry—and then, with a larger data set, at the Technology Strategy Board—it became clear that pushing a new piece of understanding as the simple basis for a product or service did not usually make money. For example, I worked on conducting polymers in the 1980’s – they offered a wide range of novel properties, but it wasn’t until those properties met the needs of specific markets that they were applied. Commercial success came from understanding what people would pay for and seeking a solution from within the knowledge base science had provided. It also seemed to be the rule that no product or service was based on a single piece of science.

The relationship between business and universities has altered over my career—but not evolved. In the day, most larger companies had parts of their R&D activities devoted to engagement with the research base, many with “corporate laboratories” devoted to scouring the universities for component parts of the understanding they needed to bring products and services to market that they knew, or at least strongly believed, would sell.

For reasons that probably involve a shorter-term business focus and the use of the internet to access knowledge, this seems to have died as a widespread core activity. Meanwhile, universities have been driven to try justify their funding, and generate income, by pushing their scientific expertise into the commercial arena, either by licencing their expertise to larger companies or setting up new ones to exploit it.

This seems to have been less than successful – very few of the companies spun out over the last 25 years have made serious money and many have died or become zombies. Once again, it is a manifestation of the linear model's false assumption that investment in understanding leads seamlessly to exploitation that drives this unsuccessful behaviour.

As often happens, lack of success has led to redefinition of the process, and there are now a number of ways to describe what is going on. We 'translate' scientific understanding into business; this at least suggests that there is a difference between understanding and exploitation, but the term is mostly used to describe how universities push their ideas into commerce. We 'transfer' knowledge from universities to businesses—again the assumption seems to be that passing across a piece of understanding will unlock commercial potential.

We need to recognise that the process of gaining understanding and the process for exploiting it are different. They draw different people to their goals. They should be assessed according to different criteria. And they require different mindsets.

Scientific researchers are driven by inspiration and competition from people in their own field. In business, the requirement is to consider all aspects of the product or service. You need the basic science of the underpinning technology, you need the engineering skills to make the same complex system thousands or millions of times over, and you need the design skills that make assembly cost-effective and ensure the customers get what they paid for.

These differing needs make for a difficult interaction. Universities, and the research councils, are generally organised by disciplines. But, without their own internal capability, businesses now want an integrated answer when they come seeking knowledge. Those companies that are capable of understanding the potential of the knowledge in the university base will exploit it better. Those universities that either organise their interaction with the outside world or, better still, organise at least part of their activities by focussing on outputs rather than component disciplines tend to have smoother interaction with business.

Maybe what we need is not translation or transfer of information, but a transformation of how universities and business work together.