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This week on the startup to scaleup journey:
Why DeepTech founders must think differently about funding strategy
DeepTech is often seen as the poor cousin of mainstream venture markets. It represented just under 20% of total European investment at the peak in 2021, according to Dealroom. But in 2023, it grew its share to 30%, making it the single largest funding category.
And whilst investment into mainstream Tech - dominated by software - dropped by 46% in the past year, DeepTech proved remarkably resilient, dropping only 7%. DeepTech founders looking to raise capital in 2024 can therefore do so with greater confidence.
But there is one big proviso. The funding strategy must target a particular class of investor that will resonate with the proposition. These are rarely the classic VC names and many are US- or Asia-based.
What is DeepTech? DeepTech is all about the commercialisation of new scientific and engineering breakthroughs. Their impact goes way beyond just business improvement - they propel humanity forward and have planetary scale. The underpinning technologies are highly disruptive and can dramatically change or even create entire industries. Think about the invention of electricity, the transistor, the internet, or genomic sequencing.
In the current era, we are witnessing breakthrough innovations across a host of rapidly evolving sectors. Not all have the magnitude of the examples above, but they are still reshaping global industries. Some of the most profound examples can be found in Agriculture, Artificial Intelligence (AI), Aviation, Climate, Mobility, BioTech, Quantum Computing, Robotics, and Space.
To be clear, not all innovations in these sectors are 'DeepTech'. After the initial scientific or engineering breakthrough is commercialised, it can spawn a plethora of further developments and applications. These can quickly become part of mainstream venture, especially if they leverage established business models, like SaaS. Generative AI applications are a great example.
Different risk/reward profiles. DeepTech startups have a very different risk/reward profile to mainstream or 'traditional' startups. This strongly influences their funding journey and the investors that want to come on board.
On the downside, DeepTech startups - especially those developing hardware - face higher technology risk, longer development timescales, and greater capital intensity than their mainstream peers. In addition, they often have greater team risk: Founders with strong scientific backgrounds rarely also have deep commercial experience.
On the upside, if a DeepTech startup can crack the huge technological challenge, it's almost a given that the market will be enormous and customers will be desperate to adopt it. And it will have a much stronger defensibility moat towards competition. This will often be enabled by novel engineering techniques, the related know-how, and an extensive IP portfolio. As a result, investors often see huge valuation potential.
On the other hand, mainstream software startups typically face much higher market and competition risks. i.e. Is the market big enough for this new offering? Can we get to product/market fit and start scaling before others can?
But for all the differences between DeepTech and mainstream software, there is one big point of commonality on the journey: Both must reach product/market fit before they can successfully scale.
The Pre-PMF phase. The pre-product/market fit phase is more challenging for DeepTech startups. Initial R&D can take years and contain very big unknowns. For many startups, the main measure of early progress will be the Technological Readiness Level (TRL), measured on a scale of 1 to 9. (In Pharma, the sequential phases on the clinical trial pathway provides a similar measure).
The product generally needs to be at TRL level 6 (engineering prototype) or 7 (full scale prototype) before any meaningful early adopter engagement is possible. It may take level 8 or 9 (final product proven 'in the field') before PMF can be achieved. This is all after a great deal of time, expense, and uncertainty.
Founders of DeepTech companies often come from related industries or academia where they have already established deep insights into the technology. They are confident that the market opportunity will be huge and are betting very much on their own intuition that their first product will crack it open.
One of the biggest risks is not having an initial application target. Some DeepTech startups get caught in a loop of a 'technology looking for a problem'. As market timing is everything for a startup, getting the burn equation wrong can dramatically increase the amount of capital required to reach PMF. That's why in the initial stages, venture investment is often so hard to secure.
By comparison, in mainstream software markets, an MVP can often be developed in months or sometimes just weeks. Software architectures are generally well understood. Early adopters can be providing feedback shortly after receiving the MVP. Using lean startup principles, startups can often quickly develop a first product in a highly time- and cost-efficient manner.
Founders in mainstream software startups can come from almost any walk of life. They are confident that they can build the product and are betting on this to create a new market 'category', guided by customer feedback. What is often misunderstood is that, rather cannily, they are iterating more around the ideal customer profile rather than the product itself, before hitting the scaling button.
The Post-PMF phase. The post-product/market fit phase can also be difficult to optimise. Unlike mainstream software, it’s often hard to establish the best growth and go-to-market metrics with DeepTech. Each case is so different. If hardware is involved, there can be big operational and cost considerations. Figuring out how to economically scale is often one of the toughest challenges.
Conversely, in mainstream software, SaaS investors have standardised most of the core financial metrics to make them almost independent of market sector. The SaaS model has become so dominant that it is almost viewed as vertical market in its own right. Investors will often say they are SaaS investors first, followed by their industry segment preferences second. Anything that isn't SaaS, no matter how compelling, will not be of interest.
Different funding pathways. Governments are often the prime movers in catalysing DeepTech startups with non-dilutive funding (e.g., grants and loans), as well as other policy means (e.g., tax credits). For example, Innovate UK is one of the most prolific providers of very early, non-dilutive funding, which is critical in mitigating future financing risk.
Then, there are the 3 main sources of equity financing:
1. Pre-Seed and Seed funds, for financing the balance of the journey to PMF
2. Early-stage funds at Series A/B, for financing early commercialisation
3. Growth stage funds at Series C and beyond.
According to Dealroom, there are only around 20 European institutional funds exclusively dedicated to DeepTech at the Pre-Seed and Seed stages. Many of these also have geographic (country) restrictions.
By early-stage, the options narrow further for Series A/B, with only a handful of dedicated European DeepTech funds having any appreciable firepower.
By late-stage, European options become very limited, with the share of funding coming from the US and Asia increasing to around 50%.
This is why UK DeepTech founders have to think further ahead on funding strategy than their mainstream counterparts. The funding pathway should, in addition to the dedicated funds, take into account:
In the case of sector-agnostic funds, it's important to find the specific partner(s) that has the DeepTech brief. Only they will fully appreciate the special profile of the opportunity and have the wherewithal to pursue it. Unfortunately, many of these funds shy away from Seed stage and only really start to show interest at Series A.
In summary:
DeepTech is growing in prominence, driven by an increasing number of industries that are being disrupted. Getting to PMF requires a significant product bet, but the payoff is huge market and valuation potential.
Funding pathways are more complex and dedicated funds offer the strongest chance of alignment. Few generalist funds are able to truly understand the different risk/reward profile vs mainstream software. This is especially true in the very earliest stages.
Europe has a limited venture capacity for DeepTech, especially at growth. US and Asian funds will almost certainly need to be part of the strategy. Developing those relationships can never start soon enough.
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