Over the last decade, a niche slice of the tech sector has delivered some of its most impressive breakthroughs. Deep-tech innovation — the practice of harnessing the most recent advancements in scientific understanding to create technologies that were previously inconceivable — has delivered groundbreaking companies like SpaceX and products such as mRNA vaccines.
Deep tech’s share of venture capital has doubled over the last decade, growing from approximately 10% to 20%. Deep tech-focused investment funds outperform traditional venture capital, delivering an average internal rate of return of 26% compared to 21%.
But deep-tech startups come with their own unique set of business challenges. Their products often involve prolonged R&D periods and substantial upfront costs, making it hard to iterate quickly and maintain cost efficiencies. The stringent regulatory landscapes and the technical complexities of deep tech necessitate a more sophisticated approach.
The lean startup methodology emphasizes quick iteration cycles, allowing startups to rapidly test and refine their products based on customer feedback. However, for deep-tech ventures — which often face prolonged R&D periods, high upfront costs, and complex technologies — this approach can sometimes be challenging to implement.
Deep-tech ventures face different kinds of risk. Their technologies do not yet exist and must navigate a labyrinth of technological uncertainty that goes beyond the scope of market feedback loops. De-risking a technology is fundamentally different from de-risking a market.
To reduce technological uncertainty, deep-tech founders can:
Deep-tech startups face greater complexity and resource demands than their low-tech counterparts. These tailored approaches mitigate the inherent uncertainty and pave the way for groundbreaking innovations that can transform industries and society.
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