The technology works. Now comes the hard part.
Over the past year, I’ve found myself working with some of the brightest founders I’ve ever met. They are building technologies spanning advanced diagnostics, climate resilience, advanced materials, semiconductors and scientific instrumentation, often after years of research, testing and engineering.
There have been plenty of moments when I’ve needed the science explained to me more than once, usually with a whiteboard involved. But then we move away from the technology and start talking about the business, and something interesting happens.
The questions become much simpler, but the answers often become much harder.
Who needs this most? Who will actually buy it? Is that the same person who will use it? Who controls the budget? What would make them change what they’re doing today? What evidence will they need to take a risk on something new? And when the technology could potentially serve five different markets, which one should come first?
These are very different businesses solving very different problems, yet I keep finding myself having versions of the same conversation. The technology works and the opportunity exists, but somewhere between proving the science and building a business that customers will actually buy from, things become much less certain.
I’ve started thinking of this as the commercialisation gap.
It’s the space between technical validation and commercial traction, where technical possibility has to become commercial priority. An application needs to become a proposition, an industry needs to become an actual buyer, and years of technical evidence need to become a compelling reason for someone to change what they’re doing and spend money.
Perhaps the most difficult challenge of all is that founders who have spent years discovering everything their technology could do suddenly have to decide what not to pursue.
That’s one of the things that has surprised me most. We tend to assume that a technology with multiple applications and enormous market potential has an advantage, but commercially, that abundance of opportunity can become one of the biggest barriers to gaining traction. When everything looks possible, very little gets prioritised.
After working through this with startups across very different areas of deep tech, one thought keeps coming back to me: the science is rarely the weakest part of the business; more often, it’s the translation.
Over the next few weeks, I’m going to share some of what we’re learning from inside these mentoring conversations. Not the startups themselves, or anything commercially sensitive, but the patterns that keep emerging as brilliant technical ideas make the difficult journey towards becoming scalable businesses.
If we’re seeing the same challenges appearing across completely different technologies and markets, I suspect there are many more founders wrestling with them too.
So I’ll start with one of the biggest contradictions we’ve encountered: what happens when your technology has too many potential customers?
That’s where we’ll go next.
Linkedin: https://www.linkedin.com/pulse/inside-deep-tech-part-1-numinara-ltd-vj5ie/
