Deep Tech attraction: how can we get the right talent into early stage enterprises?

As an academic-turned-investor I feel I have a somewhat unique perspective on teams in spinouts and deep tech startups. I joined Octopus Ventures as my first job after working in academia and it took me a good two years to learn how to function in a commercial setting rather than an academic environment. 

Spinning out Success

Our recently published 2020 Entrepreneurial Impact Ranking report, ‘Spinning out Success’, tracks UK universities’ record at turning research into companies. The report collates best practice from the top-scoring research centres spinning out deep tech startups. This combines with our own experience at Octopus Ventures in the the nuances of these companies’ ability to attract both investment and talent.

An ‘Aha’ moment

The best technology does not always win. This was a stand out realisation for me, early on. Great product, UI/UX, marketing, messaging, salesmanship and luck all play their part in success and the simple fact is that technology never just sells itself. A classic example is Betamax (at higher resolution) losing out to VHS, but as a VC I have seen all kinds of amazing tech that has never made it to market because it wasn’t productized, marketed or sold properly. In the end, all that matters is that the technology is good enough to solve a problem someone will pay to fix. 

What does this mean for deep tech startups? They need to think about interdisciplinary teams right from the start. Highly technical teams will often lack skills on the business front for sales, marketing, management, financing and more. Getting these skills in a company early can mean the difference between success and failure. 

So what can we do to foster this view earlier in deep tech startups?

Academics are rarely the right people to lead a startup. There are exceptions of course, but in general the training and experience of academia does not set you up to be a successful entrepreneur or startup CEO. 

What are the critical areas of difference between the two roles?

One area of difference is the pace of execution, with startups moving much faster than academic research. Secondly, technologists can fall into the trap of aiming for perfection when solving a problem: in the commercial world, the minimum acceptable to customers is good enough. Lastly, ivory towers: often part of the skyline of academia, they don’t last long in the commercial world!

How can we improve things?

A good start would be to close the gap between academia and industry. Training and education in business skills and entrepreneurship exist, with the likes of Spin Up Science doing a great job. With the right training I believe there is a future in which PhDs and postdoctoral students could become an incredible source of startup talent in functions other than technology. After all, academics are typically smart folk trained to learn rapidly. People at this stage in their careers can often afford to take risks as they are less likely to have families and responsibilities. They’re resilient too, having often survived on small salaries (a typical PhD stipend in 2019 is £15k per year).

A more left-field play would be to allow academics to work more closely with industry directly. This will demand a change of attitude at universities, but early signs of progress are there. Some universities are beginning to move away from the classic ‘publish or perish’ way of judging academic progression, in which academics are promoted solely based on their research. A more holistic perspective is surfacing that includes experience working with industry. Taking this further, it would make sense to let academics spend large proportions of their time in industry, thereby gaining skills and experience directly. For there to be uptake on this they would need to be viewed as ‘first class citizens’ in their roles both in academia and industry.  

Entrepreneur First (EF) runs a programme that has helped found many deep tech companies. They have refined their model over more than 12 cohorts and found that having a technology leader (CTO) paired with a commercial leader (CEO) as the founding pair in a business is the best recipe for success. 

Other than technology experts, the right skills for deep tech companies overlap closely with those of any other startup. As the wider UK ecosystem develops and matures, more of these skillsets will become available. 

This is all part of a cycle in which successful startups hire and train people in different roles who are then recycled into more startups over time. The US has a much more mature ecosystem than the UK in this regard and the talent pool is subsequently much deeper. 

Thankfully, we are already seeing early signs of improvement in the UK.

At Octopus we have backed a number of teams for a second or third time and we also see many of the senior roles in our portfolio filled by people who have built their experience in junior roles in some of the UK’s success stories. In deep tech startups, we are increasingly seeing ex-ARM employees (post the Softbank acquisition) in executive roles, as NEDs and as Angel investors in companies like Bodle, Bamboo Systems, Agile Analog and Chargifi, among many others. 

With more deep tech unicorns developing all the time (the likes of CMR, Graphcore, Dark Trace), we are confident that the UK can now start to create a wonderful, deep pool of deep tech talent.