#1
Not Enough Capital Allocated Towards European Deep Tech

My first answer is what I’ll call the Occam’s Razor explanation. It’s simple: there isn’t enough funding going towards European Deep Tech. We can get into policy, culture and incentives in a moment, but without the requisite capital, there will be persistent challenges in scaling this high-potential ecosystem. While the combined valuation of EU Deep Tech startups grew roughly 3.7x over a decade (‘10-’20) venture funding for this category remains at a paltry €7B. That’s roughly 21% and 43% of the total amount deployed in the United States and China, respectively. Deep Tech tends to be capital intensive, higher risk and requires longer time horizons to commercialization. 

So, while there is an appetite to invest in the next SpaceX or OpenAI of Europe, investors need to put their money where their mouth is. This is easier said than done. In deep tech, especially in the early stages, it is often the case that the business consists of prototype and a few academic papers. To properly evaluate these opportunities requires a specific yet multi-disciplinary set of skills. Which brings me to my next point…

#2
Not Enough Investors with Scientific and Entrepreneurial Backgrounds

Only one-quater of European VCs have a scientist on their team. Less than 25% of European GPs have been startup founders themselves. In pre-seed and seed investing, it is essential, irrespective of sector, to have a sense of what it takes to actually build a company from the ground up. There’s no better way to acquire that experience than to be a founder or high-level operator yourself. The venture capital industry in Europe is composed primarily of former bankers and consultants who have no doubt acquired a valuable skill set, but arguably less applicable in the world of early-stage venture. Deep tech adds another layer of complexity: scientific credentials. Not only do you need to understand the dynamics of a startup, but have a firm command of the scientific breakthroughs behind the product. At the intersection of entrepreneurial experience and scientific reasoning lies a huge potential for backing the next ground-breaking deep tech company. 

Deeptech isn’t lean. It takes time to do proper science, often years. The typical time to market any breakthrough technology is 3-5 years. Most companies who try to commercialize before their technology actually works end up doing a bunch of PoCs that never convert to ARR. Companies need to go through a proper R&D phase before they can make real revenue. These are the types of lessons you learn by doing – as a founder, a scientist, or a technical co-founder. Europe produces best-in-class scientists every year from top-tier science and engineering universities. There isn’t a supply issue. There is, however, a bottleneck in the ecosystem that has slowed the maturity of scientific entrepreneurship.

#3
Friction in the University Spinout Process

A large proportion of deep tech startups have links to university labs or research programs. Afterall, this is where the bleeding edge of science is taking place. So it’s only right that universities expect compensation for incubating said research. Nevertheless, the trials and tribulations of working with the dreaded Tech Transfer Office (TTO) come up on a regular basis with deep tech founders around Europe. The TTO is a department within the university responsible for overseeing how intellectual property developed at the university spins out. More specifically, they negotiate the terms of use. This can be structured in myriad ways: royalties, in exchange for equity, a contract for exclusive rights etc. Typically, this all happens before venture capital investors get involved, yet it has serious implications on the financial viability of the company in the long run. Generally speaking, it’s best practice to fairly compensate the university for facilitating the research while preserving enough equity for founders to be incentivized, future investors to be interested, and to retain an equity pool for future employees. 

I loathe to make the classic Europe is years behind the United States argument (one that gets tossed around quite loosely); however, in this case, I think it’s justified. Surely, the process isn’t perfect in the US. That said, institutions like Stanford and Harvard have been in the venture game for some time and recognize that outsized returns, in a long run, outweigh short-term gains from stringent spinout agreements (it also probably doesn’t hurt that these universities have multi-billion dollar endowments, a distinctly American approach the higher education). By comparison, the European TTOs appear rigid and anachronistic.

Spinout.xyz is an open-source database created by Nathan Benaich of Air Street Capital to bring transparency to the university spinout process and empower inventors and scientists to launch startups from the research they conduct. A quick glance at the table, and you’ll see that most US universities take relatively small equity stakes (mostly in the single-digit percentages, with a few exceptions). In the most extreme case, Oxford University took 70% equity and a 3% royalty, rendering the company effectively dead on arrival. While some European TTOs are better than others, the general consensus is that they are difficult to work with, even adversarial. And it shows in their NPS scores from founders. This is a system issue that needs resolving if deep tech startups are to be set up for success.

#4
Incentives and Exits

At the end of the day, everything comes down to incentives. Capital allocators need incentives to invest in early-stage deep tech startups. Academics need incentives to leave the creature comforts of university. Tech Transfer Offices need to be reassured that long-term gains will put them in a position to fund future research without compromising near-term innovation. Policy-makers and politicians need to create and foster these incentives at a macro level to keep the ecosystem thriving. It’s all interconnected, which makes this an enormous coordination challenge. 

At the surface level, investors and founders make money one of two ways from a startup: an acquisition or an initial public offering (IPO). Generally speaking, these two exit strategies incentivize startups to succeed by offering liquidity to those involved. In either case, founders and investors are rewarded, but other dynamics have a downstream impact on domestic innovation and further capital deployment. 

In terms of acquisitions, European companies don’t have the mindset of “let’s acquire this company at a premium” — they’d rather build in-house. Oftentimes, top European companies get acquired by foreign blue chips. This means talent, IP, and the surrounding ecosystem goes abroad with it. Furthermore, EU companies don’t want to list in Europe, opting instead for exchanges like the NASDAQ or NYSE (for various reasons, including expertise, visibility, and market opportunity). A lot of the long-term value accrues overseas as a result.

Macro economic incentives are only one piece of the puzzle. It’s also important to understand human behavior and decision-making at the micro level. Professorships in Europe are high status but are paid comparatively poorly. Highly funded labs and startups in the US, for instance, can easily poach them with promises of high salaries and upward mobility. Creative compensation is also a factor. Pay packages at top-tier startups in the United States include things like Restricted Stock Units (massive upside); however, stock-based compensation is less common or legally straightforward across Europe.

These problems persist across disciplines. Yet it has an outsized effect on the deep tech sector, one that is already saddled with complexity, technological risk, and enormous challenges one encounters working in the worlds of atoms instead of bits. The challenges outlined here aren’t only pressing for deep tech founders and investors. Rather, it’s a problem of national security and sovereignty. Europe needs innovation to take place in Europe. Potential for innovation shouldn’t be limited to software and machine learning but extend to fusion, cryptography, biotech, and beyond. What we need is a collective will to incentivize innovation and retain it as it scales. In a 2-sided technological world order (US-China Axis), we need a movement towards European Dynamism.