The Valley of death in Horizon2020 and national innovation systems has changed from being a problem of translation to a problem of system design. Should that make us think differently about how to bridge it?
In one of my first posts here at according2research.com I addressed the question if Horizon2020 had closed one valley of death, only to open up another. My thinking was that Horizon2020 had created a new gap in the innovation chain by focusing too much on either blue sky research or the market, leaving the “long haul” research – done after new discoveries are made but before they are turned into sexy new products – behind.
Although the idea seems to resonate with people I have talked to before and after, perhaps it isn’t simply that the valley of death has moved. An article in today’s Berlinske (article in Danish) made me think about this.
In innovation theory, the valley of death occurs when the research isn’t translated into a product or service. The knowledge created in the scientific community isn’t transferred to the business community. Think of it as a relay race where the first runner fails to pass the baton to the next.
The problem that has been created with the new valley of death in Horizon2020 as well as in national systems isn’t like that.
The problem now isn’t between the runners, rather its with the way the race is setup. If we imagine a relay race with three runners on the team, the analogy would be that the funding agencies have removed the 2nd runner. Hence, runner No.1 and runner No. 3 might be world class, but they are missing the middle guy to make it work.
Got the point?
Good, so enough with the sports metaphors.
The new valley of death is created simply because funding for the mid-TRL research (to stay in the current lingo) is drying up.
The valley of death we are now seeing is consequently a question of system design rather than a problem of translation and the fault of this is consequently with those making the game rather than the players (aii, I can’t get rid of those sports metaphors…).
Why does this happen?
I’m sure there are many reasons, but I will cut to the chase and suggest a simple diagnosis that consists of four parallel components which are:
- The development in politics,
Politicians seems to be working in ever shorter cycles and hence the need to show results that resonates with the constituencies makes them prone to support the kind of activities – including in R&D – that delivers easily communicable results. TRL 3-5 research doesn’t fit that recipe.
- The fallacy of mixing means and ends
A lesson from the education system can serve as an illustrative example here. In educational politics there is a tendency to turn problems in to school subjects: The failing social fabric and the crisis of the “moral standards” or common values are translated into calls for citizenship education; the failure of Europe to create the next Google, Apple or Amazon puts innovation on the school curriculum in order to teach kids about innovation. in both cases you could argue that the rush for a solution results in a case of mixing up the end with the means. Although citizenship education might help clarify the understanding of society and innovation classes might help heighten awareness about entrepreneurship, neither is learned that way. It’s learned by doing it or living it and the introduction of a school subject is a meager substitute for that.
In the same way, increasing the output of the innovation system isn’t strengthened by supporting more product development, but instead by ensuring that the entire innovation chain (or R&D eco-system) is in place.
- The swing of the historic pendulum
Just like the preferred size of consortiums have changed forth and back in Horizon2020 or democracy vs autoritarianism seems to swing forth and back, so the trend in research policy changes. The old and the usual is somehow always unsatisfying and as we try to address shortcomings in the existing system we tend to swing to far in the other direction. C’est la vie.
- The inclination of those involved in any system to favour outcome that delivers a sense of gratification and purpose
Perhaps a less sinister and more psychological explanation of the politicans’ and policy makers’ recent urge to favour the next Nobel prize winner or the next Steve Jobs is simply that we like to see the effect of what we do and steer systems in the direction of where we have a visible influence. Picking breakthrough research or supporting the next smart product or service does that; allowing a mid-career researcher hone her skills, dig a little deeper into an area of research and add a piece to the puzzle does not.
In combination these four components have led the innovation system to overemphasize the kind of research that either makes us marvel at the world (blue sky) or increase national or regional competitiveness (product development).
That changes how we address the valley of death.
In the “traditional” innovation approach, the problem was that the research communities and business/innovation communities didn’t interact. As the idea that science and technology drives growth developed during the post-war period, a number of initiatives were taken to enable the research results to be communicated and translated to the business community. Elizabeth P. Berman has tracked how this developed in the US in her book Creating the Market University: How Academic Science became an economic engine.
In the new valley of death, the problem isn’t one of proximity, cross-fertilisation or communication between science and industry.
The new problem arises because the policy makers and politicians have perhaps become too eager to solve the problem and in doing so they are creating new ones. In the old valley of death, the political system would create incentives and opportunities for collaboration; now they are simply forcing collaboration through funding schemes – but with the effect that part of the innovation food chain is weakening (to put things a bit dramatic).
The paradox of this is that while everyone is talking about being more innovative and more strategic, I’m at the same time picking up signals from different stakeholders in that system that the current funding landscape is in fact less conductive to real strategic research: the kind of groundbreaking, mission driven long haul research that delivers the next generation technologies rather than push incrementally improved product out on the market.
Perhaps we need to enable our innovation policies the room to support the boring, the tedious, the repetitive and the absolutely necessary research nestled in the middle?
Or perhaps the problem lies elsewhere; in the challenge that truly strategic research priorities requires the system to bet on somethings and leave other things behind and that is a hard thing to do in a democratic system.
I’ll write another blog post to pick up that baton.
*Image of Baton falling is image 4975888229 by tableatny licensed under the Creative Commons Attribution 2.0 Generic license on flickr.