Upskilling Business Actors – The Missing Piece in Switzerland’s Deep-Tech Ecosystem

Switzerland is widely recognized as a leading innovation economy. It performs strongly in international innovation rankings. Notably, it is the world’s most innovative country for the 14^th consecutive year in the Global Innovation Index (GII), produced by WIPO. Moreover, Switzerland benefits from a dense concentration of high-quality universities, research institutes, and technology-related talent.

Institutions such as ETH Zurich, EPFL, University of Zurich, EMPA, and university hospitals, together with a broader network of applied research organizations, generate a steady stream of scientific and technological advances with commercial potential. In fields such as biotech, medtech, robotics, advanced materials, energy, and artificial intelligence, Switzerland has the credentials required for a strong deep-tech economy. Companies such as Anybotics and Climeworks show that successful deep-tech commercialization is possible.

At the same time, scientific excellence does not automatically lead to business success. Many promising deep-tech ventures make substantial technical progress but encounter difficulties when moving toward product-market fit, commercialization, and scaling. The problem is therefore not primarily one of invention, but translation, namely the conversion of scientific potential into viable and growing firms.

Several barriers in this context are already well known: (1) Access to significant amounts of capital, especially in later stages of the ventures’ lifecycle. (2) Connections to established industry are often limited or developed too slowly. (3) Another widely discussed issue is that scientists and engineers who become founders often lack the relevant business-related capabilities. As a result, most support programs in the Swiss ecosystem focus on developing business capabilities among scientific founders. In these programs, they are encouraged to engage with potential customers, sharpen their value proposition, refine their business model, and improve their investor readiness. These efforts are useful and, in many cases, necessary but incomplete.

However, our research suggests a significant blind spot: Most existing support structures in Switzerland are designed to help founding scientists understand business. Far less attention is given to the reverse challenge, namely, where and how business actors can learn to work effectively with deep-tech ventures. This matters because the commercialization of deep tech does not depend on scientist founders alone. It is also fundamentally shaped by the many business co-founders, employees, investors, coaches, board members, innovation managers, corporate partners, and other actors who are all key business actors and may influence strategic decisions throughout the venture’s journey.

Deep-tech ventures push science-based entrepreneurship to the limit, where the usual startup playbook no longer applies, characterized by long innovation cycles, breakthrough inventions, and costly iterations to reach product-market fit. Thus, when business actors rely on assumptions and tools suited to conventional digital startups and follow a standard entrepreneurial toolbox such as the lean startup approach, they may struggle to support deep-tech ventures effectively on their commercialization journey. They may expect clarity on markets and applications too early, interpret technical uncertainty as a weakness rather than a normal feature of the process, or encourage organizational and commercial choices that fit software-based ventures better than deep-tech startups. In this sense, the problem is not only that scientists need stronger business capabilities. It is also that many business-side actors lack a sufficient understanding of the logic of deep-tech invention and commercialization.

Insights from the Ecosystem

To better understand the needs of the Swiss deep-tech ecosystem, we conducted more than 30 targeted interviews and follow-up conversations with science-based technology teams, university innovation offices, Innosuisse program managers, and innovation parks in Switzerland. The purpose was to identify where current support structures are effective, where they fall short, and which capabilities are missing.

A clear pattern emerged from these interviews. Current support structures do recognize that deep-tech ventures require entrepreneurial and business capability. Yet the expectation and burden of adaptation is placed largely on the scientific founder’s side. The dominant question is how scientists can learn about business. Much less often, support structures ask how business actors can be equipped with the necessary skills and tools to work effectively with deep-tech ventures.

This asymmetry has concrete consequences because deep-tech ventures differ in important ways from many other startup settings. The technology is often still under development while commercial opportunities are being explored. Development cycles are significantly longer. Technical uncertainty is higher. The eventual application and target market may still be unclear, and significant pivots are required. In addition, regulatory demands, production requirements, and capital intensity often shape the path to market. Under such conditions, standard startup advice cannot simply be transferred without adjustment.

Our interviews suggest that many business-side actors enter deep-tech settings without the skills needed to interpret and handle these conditions well. They may have substantial business experience, but not the specific knowledge required to assess and support science-based ventures. As a result, deep-tech founders often carry an additional burden. They must not only advance the technology and build the firm, but also repeatedly explain the basic logic of deep-tech development to those around them, while being matched with coaches, co-founders, or investors who apply standard entrepreneurial playbooks.

This has practical consequences. Investors may assess progress against inappropriate timelines or milestones. Potential business co-founders expect minimum viable products. Business-trained first employees face communication hurdles with deep-tech founders and do not understand how to support them effectively. Coaches may apply frameworks that encourage premature market narrowing. Innovation managers may underestimate the time and uncertainty involved in moving from scientific discovery to commercial application. Corporate partners may misjudge the maturity of the technology or the nature of collaboration required at early stages. These are not failures of commitment, but rather failures of fit between the needs of deep-tech ventures and the capabilities of the business actors supporting them. This often leads founders to remain in homogeneous, tech-oriented teams and narrow ecosystems, which in turn forces them to handle business tasks in their startups as a side hustle, despite limited resources and capabilities, rather than focusing on their core strength: continued technological innovation.

So what?

The implication is straightforward. If Switzerland wants to strengthen commercialization of deep tech, it requires greater attention to the preparation of business actors who engage with those technologies.

This includes investors who need stronger capabilities to evaluate science-based opportunities amid uncertainty. It includes coaches and mentors who need to be able to provide advice tailored to the specifics of deep tech, not just applying the standard startup approaches that they use with non-deep-tech startups. Business co-founders and employees who are eager to team up. It includes innovation managers, who need more realistic assumptions about development timelines, market formation, and the interaction between technical and commercial milestones. It also includes corporate actors, who need a better understanding of how emerging technologies mature and how collaboration with early-stage deep-tech ventures differs from engagement with more established technologies.

Switzerland already has many of the conditions needed for deep-tech success: scientific strength, institutional quality, technical talent, and examples of successful deep-tech firms. In our view, the missing element is not additional resources offering business coaching to scientists, as such support is already well established in the Swiss deep-tech ecosystem. Rather, the more neglected issue is that business actors also need to understand how deep tech works.

If Switzerland wants more science-based ventures to grow and scale domestically, it must stop locating the commercialization challenge primarily on the founder side. The more important next step is to strengthen the business side of the ecosystem, namely the investors, coaches, employees, managers, partners, and support actors who shape whether scientific promise becomes commercial success.

Acknowledgment 

This research project was supported by Leadership Lighthouse.