The UK’s House of Commons Science and Technology Committee recently published its report on Managing Intellectual Property and Technology Transfer, a process that began life as an inquiry into the commercialisation (or more accurately, the lack of commercialisation) of graphene.
Starting with graphene made sense. It’s one of the clearest examples of a familiar UK pattern: world-class academic research, plenty of patents, and then most of the actual industries and economic value created somewhere else. What the report really highlights, though, is that this isn’t just a graphene problem – it cuts across almost every branch of science and engineering where UK research is strong, but the benefits leak overseas.
A dozen reviews, no real progress
One of the most worrying parts of the report is that none of this is new. The committee itself points out that the challenges around commercialisation and technology transfer have been studied to death – at least a dozen major reviews over the last 15 years – and yet very little has changed.
We now have an excellent evidence base and a whole shelf full of reports, many of them government-sponsored, all illuminating the same obstacles. What we don’t have is implementation. As the committee puts it, there’s a thriving “review culture” and a very visible “implementation deficit”. The enthusiasm seems to evaporate at exactly the point where action is required.
So the latest recommendation – that UK Research and Innovation (UKRI) should publish annual progress reports – risks becoming another layer of meta-review: reports on how previous reports are being digested. More watching, more counting, but not necessarily more doing.
Some genuinely useful ideas
Buried among the familiar complaints – universities saying industry isn’t interested, investors saying there aren’t enough “de-risked” opportunities – there are some constructive suggestions that are worth taking seriously.
First, there’s a call to earmark a slice of the Industrial Strategy Challenge Fund specifically for business training and mentoring to sit alongside the technology funding. That’s a quiet but important recognition that successful technology businesses are built around people and teams, not just patents and prototypes. Technical brilliance without the right leadership, governance and commercial skills rarely scales.
Second, the report suggests that Local Enterprise Partnerships (LEPs) should be required to work properly with their local universities, building on the strengths of university enterprise zones – or risk seeing part of their funding reallocated to roll out a national programme instead. That’s an attempt to join up regional economic planning with the innovation assets that already exist, rather than treating universities as separate, academic islands.
My own experience with the Northern Powerhouse agenda has not always been encouraging. Too often the focus has been on pouring concrete into big infrastructure projects that will be outdated before they’re finished, rather than nurturing the companies that will actually define tomorrow’s economy.
The “magic sausage machine” view of innovation
My biggest concern, though, is the underlying mental model of innovation that sits behind a lot of these discussions. For many policymakers and academics, innovation still looks like a kind of magic sausage machine: government funding goes into universities at one end, and high-tech products, jobs and growth emerge neatly at the other.
In that worldview, the messy middle – everything that happens between research and a real business – is treated as a black box. At best it’s hand-waved away; at worst it’s regarded as something suspicious, chaotic or even faintly distasteful. But as anyone who has actually built or backed companies knows, the “sausage making” in the middle is where all the hard work, risk and value creation really sit.
Technology almost never transfers cleanly from a university lab into a large company. There are multiple awkward, failure-prone stages: getting IP out on workable terms, building a founding team, raising early-stage funding, iterating on the proposition, finding a first customer, surviving the first few pivots. Technology transfer offices can help, and some are excellent, but just as often they become another barrier that only very determined founders can push through.
The messy bits that policy still ignores
Early-stage funding is one of those messy bits that rarely fits well into tidy policy frameworks. Valuations can kill a good idea before it ever leaves the campus. After twenty years sitting on both sides of the table, I’ve seen founders so reluctant to give up equity that they effectively strangle their own growth, and investors so aggressive on ownership that the founding team would be better off, financially and psychologically, working at McDonald’s.
Large organisations are generally not set up to manage this kind of uncertainty and experimentation. That’s one of the reasons they effectively outsource innovation to start-ups and later acquire the ones that work. It’s a healthy division of labour: corporates avoid trying to run fragile early-stage projects inside bureaucratic structures, and entrepreneurs with their investors get a route to exit.
But that only works if the pipeline of new ventures – the real sausage machine of innovation – is properly understood and supported. At the moment, much of the policy conversation still behaves as if you can tweak levers at the input (more research funding) and simply expect better outputs (more innovation, more high-value jobs) without getting your hands dirty in the middle.
Open up the black box or repeat the cycle
Until policymakers are willing to look inside the “magic sausage machine” and really engage with how innovation happens in practice – the people, incentives, governance, capital structures and market realities – we’re likely to see the same movie again and again.
We’ll commission another round of reviews into research commercialisation and intellectual property. We’ll get another set of carefully worded conclusions and another list of recommendations. And then, a few years down the line, we’ll be back where we started, with the same structural problems and another report explaining why progress has been so slow.
If we want a different outcome this time, we have to stop treating innovation as an abstract process that starts and ends in universities, and start treating it as a messy, human, entrepreneurial journey that runs right through the heart of the economy.