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Want to build a deeptech startup? Throw out the VC playbook

Every startup founder needs a good dose of grit, stamina and endurance to take a startup from idea to the heights of unicorn status. But deeptech entrepreneurs need to dig particularly deeply into their own resources to create something exceptional.

Building a startup isn’t easy. Despite the vast number of business births each year, business deaths match them almost like-for-like. As VCs, we’ve seen a large number come and go, but working with deeptech founders at the very fringes and edge cases of technology is even more of a challenge than almost any other type of startup.

“As a deeptech entrepreneur you can feel that everything is against you. That’s because it is.”

This is because building a deeptech startup, particularly in the early phases, largely goes against everything VCs typically look for. Metrics make way for value. Revenue makes way for loyalty. Fast growth makes way for patience. The traditional playbook is effectively thrown out on a gamble — just because a smart person has a smart idea.

It’s hardly surprising that transforming industries with cutting-edge tech is hard. As a deeptech entrepreneur, constant difficulties can make you feel that everything is against you.

That’s because it is.

The fit is hard

Deeptech is often born out of research that hasn’t started with an insight into a market-fit or need. It starts further out and requires more and larger iterations as it hones in on its target.”

“Technology enthusiasts give deeptech entrepreneurs the illusion of need but melt away once you try to unlock any sort of budget.”

The process will be clouded by technology enthusiasts who will give deeptech entrepreneurs the illusion of need, wowed by their amazing tech. Yet these fans will often melt away once you try to unlock any sort of budget.

UCL’s data over sound company Chirp is a great example of this. It is a super interesting technology that had tech enthusiasts from gaming companies, energy providers and even toy makers dreaming up imaginative ways to use the tech — but all in super-specific niche ways that were very cool but not scalable. After lots of dead ends, they finally found traction with wireless setup protocols and were quickly snapped up by Sonos.

The build is hard

Deeptech is not bolting together off-the-shelf components and putting a lovely UI on top. Deeptech requires experts to put time and space into developing stuff that isn’t going to work the first time. Most iterations will be costly and time consuming. Sometimes these experts will think they’re ready, but they won’t be. Sometimes they’ll see a customer’s needs but not be able to solve them.

Hazy, an amazing synthetic data company in our UCL Technology Fund portfolio, found this when they first engaged with the market. It became clear that to sign bigger contracts with the financial services industry they needed to produce flawless synthetic time-series data, something that had never been done before. Their customers were crying out for the product, but they couldn’t serve them until they cracked it last year and now are signing exciting contracts with great clients.

The market is hard

Deeptech typically uses new technologies to create entire markets. Unlike in regular startup circles, the market isn’t looking for this product. It often doesn’t even know it needs it. Many clients have already found low tech, inefficient alternatives and will treat these as sticking plasters, inadvertently damaging productivity and profitability in the process. They’re innately sceptical to new ideas. They’re going to want to test and pilot (several times) before they commit. They’re going to need educating, probably several times at different levels in the organisation. They don’t know whose budget pays for a solution like this, and sales cycles can be mammoth.

The value of bringing in deep and senior domain expertise here to help cannot be underestimated. Another UCL spinout company Nozzle.ai, which helps brands use Amazon more effectively, has used a focused content marketing strategy to own its space and educate customers in this market at scale — shortening sales cycles and bringing motivated customers.

Focus is hard

The beauty of new technologies is they often provide opportunities to solve more than one problem. From a growth perspective, this is great, but it’s also a distraction. Clients will see entrepreneurs developing on-the-fly. They’ll notice that the product isn’t fully built and want the startup to develop for their super-specific problem. Cashstrapped entrepreneurs may see a need or want to cash in on this offer, even if it risks going against their initial vision and roadmap. And even if it takes extra time and cash to achieve this new outcome.

“Clients want startups to develop for their super-specific problem. This is a distraction.”

Such distractions are mostly red herrings, and you’ll need guts to stick to your original plan (and hopefully you have funders who have properly financed that plan). But don’t be dogmatic, you might have inadvertently uncovered a better route — you’ll need to get quick at sizing opportunities and convincing your company and stakeholders.

These frictions all slow growth. Best laid plans to hit monthly recurring revenue numbers needed to raise the next round are often missed. Bringing a deeptech startup to launch is an ongoing, uphill struggle: every bit of progress requires significant months of detailed effort.

How do you make the journey less arduous?

Accept that it will be hard and lean into it.

The fit might be a struggle and take longer, but you have something no one else in the world can create and it can’t be done quickly. The build might be hard but, done right, you’re creating a moat around your value.

The market might also be hard, but a ruthless process of identifying the real problem owners with budget will create your first valuable reference clients and further your growth.

“Don’t get stuck in innovation teams and R&D departments at large enterprises.”

Don’t get stuck in innovation teams and R&D departments at large enterprises. Look for corporates with an innovative culture across the organisation. Interrogate end-budgets and champions who really own the problems you are solving and the right attitude to risk.

Focus may be difficult to sustain. But by capitalising the business properly, and partnering with VCs that share your passions and understand the unique deeptech pain points, you will have the freedom to make informed choices. That way you’ll need only change direction (on your terms) when you can validate the size of the opportunities presented and deliver them within your runway.

Only work with investors who understand the road ahead, are expecting it to be bumpy and prepared to help you navigate it. At the UCL Technology Fund we spend lots of time talking to the first users, unpicking the problems that the university’s technology is solving and how much it really matters to them. This allows us to understand our companies better and invest well ahead of revenues.

“Increasingly I’m keen on personal coaching for my deeptech founders and making sure that we speak openly about mental health.”

Yes, deeptech is hard. It’s where the most incredible technologies are, solving the most pressing problems and creating huge transformations. Deeptech founders are made of tough stuff, but there are moments when it’s overwhelming — that’s when it’s important to have not only patient capital but kind capital too. Increasingly I’m keen on personal coaching for my deeptech founders right from the early days, helping them to grow into the difficult role and making sure that we speak openly about mental health.

It’s important to remember that all things that are worth doing are difficult and acknowledging — like the long-distance runner — that this can be lonely and profoundly hard can help you ultimately thrive rather than just survive.

 

This blog post was originally published in Sifted 11 March 2021.

 

 
David Grimm