How can deep tech entrepreneurship solve the world's biggest problems?

What do big ideas require to get off the ground? Patience, cash and space to experiment. This is something science-driven deep tech innovation is lacking and we, at Imperial College Business School, are trying to create solutions to this problem

Capital markets are flush with trillions of dollars ready to invest but it’s hard to match money to ideas that don’t offer rosy prospects within a short time frame.

By their nature, big ideas linked to deep tech are a shot in the dark for entrepreneurs. Nascent technologies which emerge from scientific advances can be complex, costly and time consuming to develop. It takes a vast amount of capital to experiment and discover what works. Too often deep tech innovations founder before they have a fighting chance for commercial success because they can’t muster the cash for early experimentation – and that’s before entrepreneurs can find out if there’s a viable market for them. As a result, we might be missing out on some of the best ideas of the future.

From experimentation to viable products

Consider for a moment, a world without a coronavirus (COVID-19) vaccine – without long-term investment in mRNA technologies, we’d still be decades away. But biotech is an exception among deep tech endeavours, because once a new drug, vaccine or health technology is approved, investors know there will be a guaranteed return. Meanwhile software is relatively easy and cheap to test and tweak, and that’s why it has mopped up most of the venture capital flooding into the market over the last decade. 

But we desperately need to find solutions to energy storage, carbon sequestration and alternative fuels – without these, we won’t be able to tackle climate change. To do this, we urgently need a different investment model for deep tech entrepreneurship.

When deep tech entrepreneurs raise money, they need to know how to approach investors and what they want from them

There’s a “valley of death” between scientific results and a viable product with a potential market. Consider this process as an innovation relay race with four stages. The first stage is the research taking place inside university labs before it has been turned into a product. The second is to translate that research into a piece of technology or hardware that works in the wild rather than in a controlled environment, something with a potential revenue model and a customer base. The third is to take this and work towards a market fit; and the fourth and final stage is to expand the business to a wider customer base. 

Venture capitalists and commercial investors take care of the third and fourth stages very well. They typically focus on mature technologies which means they only need to enter the innovation relay at the third stage but we’re missing a funding model for the second stage. Venture capitalists rarely focus on startups that need to get over this hurdle, and rightly so, as de-risking these ventures is often time consuming and costly. Only by delivering high quality entrepreneurship opportunities on a risk-adjusted basis will you find investors for deep tech innovations. 

Solving the lack of funding for deep tech

Happily, universities can play an important role in helping to discover and develop an application for fundamental science as well as a robust funding model for the second stage of the innovation process.

This means helping scientists make the transition from working in a supportive university lab to the world of entrepreneurship: learning how to run a commercial lab, source equipment, meet regulations and accept liability. Fixed costs of setting up these labs mean early experimentation might be difficult, but models such as Imperial’s, where we rent space to startups making the transition, provide space and time to experiment. 

And we can help unlock undiluted funds to help early-stage entrepreneurs. Money brings more time and with that comes the potential to unlock deep tech solutions. 

So, how do we encourage philanthropic investment? By designing and pre-registering experiments, for instance, so the cost of experimentation is known in advance and results are validated by a neutral party. If an innovation meets a certain threshold, there’s a higher probability it will work. And if it doesn’t, we share the knowledge of why or how it failed so other innovators can learn. 

We desperately need to find solutions to energy storage, carbon sequestration and alternative fuels

This helps persuade philanthropists that their cash isn’t going into a black hole. If it works, they’ll reap rewards, and if it doesn’t, it will nonetheless have furthered development of good deep tech solutions to global problems. That’s the goal of our Institute for Deep Tech Entrepreneurship at Imperial College Business School: to help entrepreneurs with regulation, policy advocacy, and a proof-of-concept pilot fund to enable these experiments to run.

When deep tech entrepreneurs raise money, they need to know how to approach investors and what they want from them, including how much experimentation will cost, and how to generate as much information for as little cash as possible. These are important insights for students and something I teach on the MBA and the MSc in entrepreneurial finance. 

This is how research, the teaching and the practice of this institute really come together. We’re developing a model to help entrepreneurs navigate the roadblocks and be proactive. If we don’t, how will we confront climate change and other global problems?