By resolving the four paradoxes that hold them back. (See Exhibit 2.) The first has to do with the mindset of investors, who are less familiar with advanced science and breakthrough technology than many people expect them to be, especially considering the heritage of venture capital. The second involves risk and opportunity; deep tech is seen as a high-risk investment, but the greatest risks, as with many disruptive innovations, may come from ignoring it. The third reflects the contradictory nature of barriers in this field: barriers to fundraising are expanding, while barriers to innovation are falling. Finally, the fourth paradox recognizes that potential funding for deep tech is unprecedentedly large, but it has not yet found its connection to this field.
Resolving these paradoxes will require investors to think differently about deep tech. There is also a challenge for venture leaders, who must look beyond universities and governments as potential funding sources to form true ecosystems with nonprofits, venture capital, and private sector participants. Ultimately, the investment community has every reason to act. As was the case with mRNA vaccines, opportunities await to address social issues and to participate in the innovations that will shape the future of civilization.
PARADOX 1: THE MINDSET OF THE PAST IS BETTER FOR THE FUTURE
The economist and venture capitalist William Janeway, author of Doing Capitalism in the Innovation Economy, has pointed out that frontier innovation funds should ideally be led by contrarian investors—meaning those who invest “against the current mood of the market.” To fund deep tech in the future, we need to adapt the investment mindset of the past.
In the 1960s and 1970s, as the current wave of digital technology started to emerge, angel investors and venture capital firms took long-term positions in the companies they funded. This was needed to bring breakthrough technologies (such as semiconductors, personal computers, communications devices, and software) to a mature stage of development. Many VC firms made enviable reputations this way as leaders in an expanding field.
But the general mindset of many investment firms has shifted since then. Today, such firms tend to rely on the power of distributed returns. Since they don’t risk very much capital early in any single investment, they end up with moderate positions in multiple ventures, and then double down to support the ventures that yield rapid results. The result is often incremental investing on well-travelled paths.
This approach doesn’t work for deep tech, for which significant resources are needed in the early years. Many investors are open to innovation in the abstract, but in practice they seem to be reluctant to commit themselves to those breakthrough ventures that will make the most difference going forward.
To be sure, deep tech ventures can seem unfamiliar. They could be funded publicly or through grants, located in academic or research facilities without the trappings or network of a typical digital startup. Instead of being led by a close-knit group of entrepreneurs who all went to college together, the projects may be led by postdoctoral scientists, with colleagues across the world participating.
Investors can succeed in deep tech by going back to their historical roots, making a more focused commitment to their investments and remaining concentrated on the problems they address.
Investors can succeed in deep tech by going back to their historical roots, making a more focused commitment to their investments and remaining concentrated on the problems they address. To adopt the right mindset for deep tech, investors need to embrace a problem-solving orientation: a willingness to help address issues with a company rather than moving on to something else. They should also actively build their portfolios around urgent and fundamental issues: the problems that society needs to solve. These challenges are broad enough that ecosystems (with coinvestors, universities, public authorities, and corporate groups) can form to address them. IndieBio Founder Arvind Gupta stated it very clearly: “I invest in problems, not in solutions.”
Some deep tech deals are starting to experience competition, but investors shouldn’t passively wait for deal flow. They should actively seek and select ventures. The result will be a more focused portfolio of projects with clearly identified problems and strong magnetic pull, capable of attracting other resources and collaborators. The investors can then commit their attention and financial resources wholeheartedly, helping manage challenges as they arise—recognizing that in deep tech, even more than in other fields, necessity is the mother of innovation.
PARADOX 2: NOT ACTING IS RISKIER THAN ACTING
Of all the concerns investors raise about deep tech, the most frequently voiced have to do with risks and the vulnerability of their position.
In one sense, these concerns may be justified. Compared with a purely digital venture, like a software-as-a-service (SaaS) offering or platform, a deep tech venture has a higher barrier to entry. It has a longer runway to market, a higher initial investment cost, and fewer successful companies in the field to point to. Investors also associate deep tech with high risk because they have not developed the experience and practical knowledge needed to accurately assess a company’s potential.
But when you look more closely and understand risk-mitigation practices, deep tech opportunities tend to be less risky than their purely digital counterparts. When tackling a fundamental problem, often unaddressed for decades, the demand will be there. The risks, then, have to do with engineering execution and the business model, with the question being: “Can we produce this at an affordable, scalable price?” Investors are less attracted because they have not been exposed to these types of issues; they are less well-versed in the technologies and problems that deep tech addresses.
The riskiest move is avoiding deep tech, for the same reason that avoiding digital investments was risky in the late 1990s and early 2000s. At that time, many investors still felt digital ventures were unfamiliar, and the bursting of the internet stock bubble in 2000 made investors even more leery. But it was at that moment that several of today’s dominant digital companies really began to take off. The funders who prospered the most were those who got started early, persevered, built their networks, and took the trouble to learn about the industry.
Similarly, investors who stake out an early position in the deep tech space will be able to seize fast-growing opportunities and will be better prepared as deep tech investments become more attractive in the future. Incumbent companies, particularly in industries like energy, chemicals, and agriculture, will probably be disrupted by deep tech if they don’t climb aboard. Deep tech advances cross the boundaries between science, engineering, and design. They are here to stay. Ignoring them won’t stop them from challenging the status quo or taking down market leaders, just as similar advances have done in the past.
According to a survey by BCG and Hello Tomorrow, 69% of deep tech investors disagree with the idea that market risks, as well as those risks associated with science and technology, are “too high.” This can be explained in part by their own hard-won access to expertise: to assess deep tech potential, 79% of investors made use of external experts, 42% hired their own PhDs, and 37% hired graduate-level-science-degree holders or engineers. They also regularly consult with other investors (seeking coinvestment), with corporate leaders (often proposing collaborative ventures at a higher scale), regulatory institutions, and universities. The whole deep tech ecosystem needs to be activated and amplified—and more investors brought on board—to support ventures along the journey.
There are now efficient practices to mitigate risks further, which investors should master to best help deep tech ventures avoid market failure and technological overreach. (See Exhibit 3.) For example, the acceleration of a cyclical design-build-test-learn (DBTL) approach, borrowed from lean startup methodology, allows teams to continuously improve and test faster, even in highly original research and development efforts. This gives deep tech ventures the ability to introduce minimum viable products (MVPs). Synthetic biology companies, for example, have reduced their time-to-release cycles from months to weeks.