Why Companies Across All Sectors Should Turn to Deep-Tech Ventures – and How They Can Benefit

In their recently published article in the MIT Sloan Management Review, the authors examine why it can be beneficial for companies in all sectors—not just traditionally research-intensive industries—to engage with deep-tech ventures and how they can specifically benefit from innovations at science-driven startups. Through their work with deep-tech ventures in the US and Europe, they have identified three fundamental characteristics of such startups that often pose challenges for companies looking to leverage deep tech but have limited R&D budgets and are not accustomed to working with science-based technologies. These characteristics are:

1. Complex technology and commercialization risks,
2. High capital investment, and
3. Extended timelines.

For each of these characteristics, they share key practices aimed at helping managers address these challenges.

3 questions for Stefan Raff

Why is deep tech also playing an increasingly important role for companies with a traditionally low R&D focus?

Firstly, it is important to understand that deep tech innovation can benefit a wide range of sectors, not just the traditionally ‘science-heavy’ industries. Sectors such as financial services, infrastructure and retail - where spending on research and development is traditionally comparatively low - can also benefit. Deep tech start-ups are working on solutions to key challenges facing today's companies. A few examples:

• For the construction industry, the emergence of new eco-friendly cement and steel variants can help improve its environmental footprint by burning less carbon in production.
• For the financial services sector, quantum computing offers significant medium-term opportunities in terms of data analysis and security improvements.
• For the fashion sector, the introduction of innovative materials has great potential to improve customer experience while reducing waste.

The challenge now is to show these companies, which are not used to working with science-based start-ups, low-threshold ways and practices of how this can be achieved. It is particularly important to take into account the special features and challenges of deep-tech start-ups, such as complex technology and commercialisation risks, high capital requirements and long development times.

Can you give us an example of which practices can help managers to address these challenges?

Collaboration with academic partners is key to addressing technology and commercialisation risks, for example. It offers a low-threshold opportunity to better understand specific technologies and key milestones based on initial experiments. It is also a way to recognise their potential added value before committing to a longer-term partnership or even an investment. For example, when the sneaker company New Balance wanted to expand into new fibres and fabrics, it first partnered with the non-profit organisation Advanced Functional Fabrics of America and worked with faculty members from MIT and the Fashion Institute of Technology to explore potential solutions together. 

Are there any unanswered questions for you that you were unable to answer in your discussions? If so, will you pursue these questions further?

There are still many unanswered questions, for example: How do we manage to get deep-tech start-ups from research institutions to the market more efficiently and achieve product-market fit? Our research into deep tech start-ups is still in its infancy. I look forward to working with a dedicated team of researchers over the coming months and years, for example as part of our project funded by the SNSF and the DFG, to further investigate this exciting topic.

The full article with all the insights can be read at MIT Sloan Management Review.