Lab to Market Leadership Reflections: Does the Starting Point of a Deep Tech Company Matter?

On this week’s bite-sized Reflections episode of the Lab to Market Leadership podcast, Deep Tech Leaders CEO Chris Reichhelm explores a vital question: ‘Does the starting point of a deep tech company matter?’

Through lessons learned from previous podcast guests like Peter Collins (Permasense) and Henrik Hagemann (Puraffinity), Chris reflects on the importance of a company’s starting point—whether it's driven by technology inspiration or a market problem. How does the initial approach affect commercial validation and long-term success? And what can founders do to better position their deep tech startups for funding and product-market fit?

Tune in to learn more about the lab-to-market journey and the critical decisions that can define a startup’s trajectory.

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Podcast Production: Beauxhaus

Transcript

[00:00:00] Chris Reichhelm: So I've been reflecting on discussions that I've had recently with clients, investors, other individuals I know in the marketplace who are currently looking for finance. [00:00:20] And there are a lot of groups looking for finance right now.

This won't surprise you in the slightest, but a lot of them are struggling, and when you ask or when I ask, what's the problem? Why aren't, why aren't you [00:00:40] breaking through the question? The answer invariably comes back to one around commercial progress. They don't think we're quite at the point where they're ready to invest because.

We don't have enough validation yet. We don't have that [00:01:00] elusive first contract win, or we don't have that elusive second contract win, or the figures aren't big enough, or whatever. But it's basically around that commercial progress and the state of, of, or the perceived state of their commercial progress.

And, [00:01:20] and that's understandable from the investor perspective. You want to be sure if you're going to make a bet, you want to make sure that thing you're going to bet on has a better even chance of making it. And Commercial validation is a pretty good test of that. But because so many [00:01:40] companies are going through this and have this issue, it makes me, it makes me think about something else.

It makes me think about a deeper question and it makes me think about whether or not we're starting these companies off in the right way. [00:02:00] Now, what do I mean by that? I'm talking about the initial catalyst for the business. In most cases, when a deep tech company starts, it starts in a research lab. It starts because of [00:02:20] researchers, academic or professional That's They are in a lab, they've, uh, it's sometimes, uh, an extension of their PhD work, uh, and they've been, and they've been building or developing, uh, a path and approach based on certain science or [00:02:40] technology that starts to get them excited, uh, about the problems their technology poses.

might be able to solve. And that excitement can extend to technology transfer units and early investors and incorporation and eventually investment and, you know, the start [00:03:00] of a business. At which point the company then has to go and has to say, okay, we've got something that's potentially interesting here.

Let's see if we can find someone who's interested. Let's see if we can find a place where we might be able to park this technology and get it to work for someone where it can. [00:03:20] It can act in the way that it was originally designed for, but they may not have all the answers yet regarding potential industry or target companies or even specific applications.

Researchers are, are generally picking up on research that's [00:03:40] demanded, that's in demand, different. Bodies or groups or occasionally companies come to labs, be they in universities or other labs, requesting that particular research is done in particular areas because they have needs. And so, it's not necessarily that the researchers are, [00:04:00] uh, just going on blind inspiration.

Some of that inspiration is very much informed. But nevertheless, it is not uncommon for a very young company to get to the point where they've got an interesting platform technology, but they don't necessarily have the market [00:04:20] that's ready for it. And the situation they have to enter into there is one of technology push.

We've designed this interesting platform. We, it solves, in theory, it solves all these great problems. We now have to find people who are going to be willing to validate that, [00:04:40] our approach and the technology solution, and are going to be willing to support us. And so then we have to go into this technology push situation.

Can you use what we have? Can it solve your problem? And that's, We see that a lot in my, in my [00:05:00] time as an executive search consultant, I've seen that an awful lot, not at that very, very early stage, but, but, but often at, at much later stages where the company's already raised substantial funds, they've been around for a while, they're still struggling to hit that product market fit.

And I often [00:05:20] think it comes back to this very initial stage because we've developed something that we think is great for whatever reason, it probably is. We haven't found anyone who sees it in the same way that we want them to. And I contrast that with a different path, a different path that [00:05:40] other companies have gone on.

And that is the path where it's not the company making the first move. It's The target, it's the, it's, it's, it's the corporate making the first move. Where they approach a researcher in a [00:06:00] university or the university itself and say, we have a very big problem. And that very big problem is this. And if we don't solve that problem, we're going to get sued.

Or we're going to lose, you know, we're going to, we're going to get sued. We're going to face big charges. We're going to have really big problems. It's a nasty, horrible [00:06:20] problem. We need someone to fix it for us. And there aren't any obvious solutions on the market. So we need some innovation. Can you help us?

And so the university goes away or the professor goes away and looks at her or his team and they start to build something to, uh, [00:06:40] they start to build something for that problem. And when I've seen companies build out from that, with that approach, their time to market and their lab to market journey have been hugely, and I mean hugely accelerated.[00:07:00] 

It's a, it's a completely different. Um, I'm thinking of an example from one of our early guests on the Lab to Market Leadership podcast, Peter Collins, and how, at the start of his then [00:07:20] company Permasense, and Peter talked about the, how BP did exactly that. 

[00:07:28] Peter Collins: They were making prototypes in the lab for BP, who had funded The, uh, technology development in the first place and had come up with a modest sum of money to take [00:07:40] a modest, uh, number of sensors to be deployed in their facilities to see how they, how well they, they worked in a real life environment.

[00:07:49] Chris Reichhelm: You know, I think you listen to that, you listen to what, to, to the intention that BP had coming to Imperial College at that [00:08:00] time. And it's the ideal, it's the ideal setup for a business. Now it was tricky for Peter and for Permasense generally because they had to convince BP, we're not just going to be your contract manufacturer, that's not what we are here.

We want to become a business, we want to serve other customers. [00:08:20] And BP ultimately had to relent on that. And they did. And so that is, uh, you know, that's down to the skillful negotiation of the Permasense team, namely Peter Collins, who did a great job with that. He was able to get through that and then win their first customer beyond BP within the [00:08:40] first 12 months.

And they had, and so they had two customers, just to put this into perspective, they had two customers by the time they were TRL 5, TRL 5, okay? We've got advanced prototypes, but they're prototypes, they're not real pilots, they're just [00:09:00] prototypes. And he had two paying customers by the time they were TRL 5.

Permasense, in case you don't know, Never raised any external equity finance. They didn't need to because their contracts were big enough for them to be able to bootstrap their lab to market journey. There may be other examples out there. If [00:09:20] you know of any, let me know, write to me, tell us. I'd love to hear these stories, but that is a situation that has been significantly de risked because from day one, we know about the intensity of the problem.

And then it's [00:09:40] easier to respond to a solution. It's easier to build a solution. When you've got a problem that's that intense and you can build in a more certain way, obviously you have to build something that's going to be effective, that's going to work. You've got to build a team and there's still risk [00:10:00] in all of those different things, but you're not building a platform and then going to market hoping someone likes what you've got.

It's a different relationship and I wonder if we had more of those Permasense type examples. Would we, [00:10:20] would we be more successful at building deep tech companies? Would they get to market faster? Would they have as many financing problems as they do? Now, the reality is that most companies still take the technology first path.

That acts as the catalyst. It always, you know, it does. And so, [00:10:40] uh, and that, as I mentioned earlier, that inspiration from the researcher can still be informed inspiration. and, and reasonably well qualified inspiration. But then, are there things we can do, even if Let's assume it's informed inspiration of some kind, [00:11:00] we develop our platform, we get it to a TRL 4 or 5, we want to start getting out and having some early conversations, which is typically when young companies start to think about getting out there.

Are there things we can do that can increase the probability of us having success? [00:11:20] Of us really being able to define and clarify, get crystal clear on the problem we're trying to solve. And for that, I'm reminded of my conversation with Henrik Hagemann from Puraffinity, [00:11:40] uh, when he spoke about, because this was the situation they found them, uh, he and his co founder found themselves in when they had their initial platform technology developed, uh, at Imperial.

And they were thinking of exactly where to go [00:12:00] and the problem to solve. 

[00:12:02] Henrik Hagemann: So they were pushing this program where you have, even if you're a science based company, you have to go and talk to 10, uh, for 10 weeks to talk to more than a hundred customers to learn about. Who are you going to sell to? What's the value chain?

How is this going to operate at scale? [00:12:20] We even had to, so we did that, you know, painful process for 10 weeks, and I gotta say the first time we did it, we kind of struggled. We didn't get easily to a hundred customer interviews. Some of the backstory that most people don't know is we actually did it twice.

So we did it once in [00:12:40] 2015 to find out, okay, we are going to do water treatment. And then in 2016, we did the whole thing again for 10 weeks. That time we hit 117 customer interviews. And I felt a lot more comfortable sort of with the pain of talking to [00:13:00] customers and learning and teasing out what are the wants, what are the needs, what are the challenges.

[00:13:08] Chris Reichhelm: 216 meetings is a lot. And I think it is, that's extreme. Henrik [00:13:20] is a bit extreme. Uh, he's got, he's a man of enormous discipline and he's willing to do extreme things in order to get results. And, uh, and so I think I, I don't know of many examples like that, but I think it's, [00:13:40] I think it is definitely the kind of activity and the volume of activity.

Maybe the volume is a little extreme. It's certainly heading in that direction. And I think for so many founders and. You know, for so many young teams [00:14:00] getting out and speaking to potential industrial partners or customers, it's the scariest thing they have to do. Just getting out there, knowing what to say, knowing how to structure the meeting, knowing when to, knowing how to manage the balance between pushing the thing that you've got, that you're quite proud of, [00:14:20] knowing when to shut up about that, and listen.

Listen. With the intent of, of building a solution, um, and knowing the right questions to ask and, uh, and [00:14:40] listening better and asking better questions and, uh, continuing to do that and doing that, uh, and, and actually never really stop doing that until you're, until you're further down the lab to market journey.

Always refining your understanding, always seeking to understand more. Uh, that is a, it's a big [00:15:00] challenge for founders, but it is so important. And I think through that, what I know Puraffinity was able to eventually make those two trajectories meet. Their trajectory associated with the development of their platform and their trajectory associated with the problem that they ultimately went out to solve.[00:15:20] 

So, but it was, it was the, it was the high volume. Deeply rigorous nature of that activity that allowed them to, frankly, not have to push their tech on the market, uh, without feeling confident it was going to land in the right way.[00:15:40] 

Deep tech companies are, and, and their journey from lab to market is fraught with risk. Uh, these are really hard things to get right. And, uh, If we're involved in building, or supporting, or financing, [00:16:00] uh, or giving life to these important companies, naturally our job is to look for ways we can decrease risk.

And so, it makes me wonder whether there's A better way of setting up these [00:16:20] companies from day one. Do we look at the Permasense way where you're reacting in a sense to what, and responding to what a client's truly acute need is, or do we continue to lead with technology inspiration and then [00:16:40] hope that inspiration somehow finds a home in the marketplace with problems to solve?

I would love to know what you think.