Podcast Insight: Applying "Endgame" Strategy to Deeptech Investing
A recent asset management podcast explored the concept of applying long-term "endgame" strategies, typically used for pension funds, to illiquid deeptech investments. The discussion highlighted the need for VCs backing university spinouts to define success upfront and work backwards to create operational and capital plans. This approach emphasizes milestone-based funding and hands-on support to navigate the long commercialization path for technologies like quantum hardware.
- The "endgame" approach requires a long-term investment horizon, which makes deep tech a suitable, albeit higher-risk, allocation for pension funds and family offices that can wait 7-10 years or more for returns. This contrasts with traditional VC funds that often have a mandated exit window that is misaligned with the longer development cycles of deep tech. - In Turkey, the deep tech sector includes 653 companies, with 117 having secured a collective $1.31 billion in funding. The Türkiye Technology Fund (TTF), a fund-of-funds program by the Türkiye Wealth Fund, is actively investing in local VC funds that support deep tech startups in sectors like AI, health tech, and machine learning. - Milestone-based funding is critical in deep tech, where capital is released in tranches tied to achieving specific, predefined goals like technology readiness levels (TRLs) or securing pilot programs. This approach de-risks the investment by linking capital deployment to tangible progress, a practice historically common in the pharmaceutical industry. - University spinouts are a primary source of deep tech innovation but face significant commercialization challenges, including a lack of access to proof-of-concept funding and the difficulty of pairing technical founders with experienced business leadership. In Europe, only 23% of deep tech startups are spinouts, and they account for just 11% of the total deep tech valuation. - Quantum computing, a key deep tech area, faces a long road to commercial viability, with estimates suggesting the first commercial applications that outperform classical computers are likely a decade or more away. Major hardware challenges include increasing the number and stability of qubits and developing effective quantum error correction, with companies like IBM and Microsoft pursuing modular hardware and more resilient topological qubits to accelerate progress. - While often described as needing "patient capital," some investors argue that each funding stage for a deep tech company requires "impatient capital" obsessed with hitting the next proof-point to secure follow-on funding. This creates a dynamic where the entire financing stack provides long-term patience, but individual phases are driven by intense, milestone-focused urgency. - Globally, deep tech now accounts for an estimated 20% of all venture capital funding, up from 10% a decade ago, with the market projected to reach over $700 billion by 2031. Deep tech funds have also shown resilience, with European deep tech funding falling only 28% from its peak during the recent VC downturn, compared to a 60% collapse for regular tech funding.
