Deeptech startups have the potential to revolutionise our society and help tackle some of the existential challenges we face today – from climate change to resource scarcity. At a time when software revenue multiples and funding have started to decline, deeptech offers a unique opportunity to founders and investors to create enormous amounts of value alongside real technological innovation. However, the relative immaturity of the deeptech ecosystem can also pose significant challenges to businesses and investors operating within this space.
Part one of this project examined the scale of the deeptech opportunity, deep diving into the current UK deeptech and venture ecosystems, and analysing what our history might tell us about the future potential of deeptech.
Now in part two we break down the challenges limiting deeptech growth and adoption and lay out a roadmap for capturing this opportunity. This report has been divided into founder-facing and VC-facing challenges and includes initiatives to begin addressing these challenges and opportunities for deeptech operators to get involved. It was written with a focus on the UK venture ecosystem, but many of the learnings may be globally applicable.
This report was written with the help of Christina Franzeskides (Lakestar); Dave Neumann (Molten Ventures); Marek Chalupnik (IQ Capital); Pete Hutton (Cambridge Angels and Equity Gap); Rick Jingchun Hao (Speedinvest); Robin Dechant (Kwest and Point Nine Capital); Simon Thorpe (Cambridge Angels); and Zoë Reich (Octopus Ventures) who kindly shared their insights and views.
VCs looking to interact with deeptech businesses should first understand the unique range of challenges faced by deeptech founders as they grow and scale: raising capital from VCs, managing cap tables, different routes to funding, and hiring talent and finding support.
Differences in founder profile, business model, and product journey can complicate the deeptech funding journey and change when and how they engage with VCs.
As a result of the relative nascency of the deeptech ecosystem and the prevalence of technical, STEM and product-oriented backgrounds, deeptech founders are much less likely to have fundraising experience. This can create difficulties when:
VCs who wish to support and invest in more deeptech businesses can use university schemes as a stepping stone into academic and technical networks – providing fundraising knowledge to these fledgling founders and forging relationships which can develop into deal flow over time. Investors can also make a real difference by taking the time to provide honest feedback on pitches and outreach they are declining, to help founders learn and iterate faster.
Because deeptech products are so technical, it can be difficult for founders to explain their idea to investors without a similarly technical background. According to the Boston Consulting Group, 81% of founding teams and investors thought investors lacked the expertise to assess a businesses potential, and there has been a lot of discussion, particularly in AI, about the impossibility of both explaining complex scientific processes in layman’s terms and of then making an informed investment decision from this explanation.
Lack of investor familiarity with the markets deeptech businesses may address can also complicate the funding process (especially in the case of generalist investors). Correctly judging the scope and credibility of a business often requires a good grounding in the size of a potential market and the needs of its customers. However, deeptech businesses often address specialised and industrial markets which outsiders may find difficult to assess.
We have seen deeptech VCs take one of two tacks to bridge this expertise gap and meet founders in the middle:
Long-term, some of the more consumer-facing areas of deeptech may become more widely understood, just as today’s average consumer can be expected to understand more about a software product now than in the 90s. However in other sectors the increased specialism is likely here to stay, as industrial applications and infrastructure (just like the hardware behind computing) tends to be naturally less accessible than cleantech or consumer-facing AI.
Deeptech products take a long time to bring to market. This means that most deeptechs will have to go through multiple rounds of funding before they sell their first unit – and that traditional funding milestones centred around product-market fit, revenue growth, and customer numbers may not be applicable until a much later stage in the process.
This presents obvious problems to founders trying to find funding, and to VCs trying to assess the viability and value of a business venture. It is less problematic at the seed stage, where investors are often comfortable with providing capital pre-product, but at Series B, a partially constructed product and no sales can be a much harder sell.
Y-combinator suggests its deeptech or ‘hard-tech’ participants think creatively about routes to prove product concept and demand, from developing smaller, scaled-back versions of the product, to LOI’s (Letters of Intent to buy), or even to building models to help investors visualise the finished product. They also break down strategies for dispersing the cost over multiple funding rounds, to ensure that at each stage the VCs can see that a certain amount of progress has been made. For example, they highlight Solugen, a deeptech startup which had found a novel way to produce hydrogen peroxide at a large scale. To actually sell the product at a profit required a large and expensive factory, so the founders instead produced a tiny working version in a beaker as their minimum viable product at seed and then scaled up this production line for each subsequent stage of funding. This allowed them to provide investors with physical proof that the concept worked at each stage of scale, and to visualise the progress the business was making with their capital.
VCs investing in deeptech need to establish similarly product-focused milestones (often in conversation with each business they support) to assess the investment’s progression and determine whether follow-on funding is appropriate.
Deeptech cap tables can look quite different to other startups. A significant percentage of deeptech companies start as university spin-outs and receive their initial funding from the institution where they did their first research. This funding is vitally important in encouraging innovation and provides seed-stage capital to many incredible businesses (while encouraging further university investment). However, while most university spin-outs will give some equity to the institution that supported them, figures vary wildly. In fact, according to TenU, an organisation linking technology transfer offices internationally across many top universities, the amount of equity universities take can range from 5% to 50%.
There are obvious complications to this level of equity-dilution at such an early-stage, and while such large chunks of equity are generally given in return for substantial support and use of university IP, founders are not necessarily educated enough about the risks to make an informed decision. At this stage, founders may also be unaware of normal conventions around seed funding and equity shares, as well as their other options to acquire it.
The result is that some university spin-outs struggle to find further funding due to investor concerns around equity dilution, eventual returns, and keeping the founder adequately invested. This harms both founders and the universities themselves, and can lead to excellent businesses failing to find necessary funding.
Increased transparency around spin-out and seed-stage funding could help founders, investors and institutions make more informed investment decisions to start solving this problem. This can be done largely organically in the long-term as university and deeptech ecosystems develop and mature, but in the short-term action clearly needs to be taken to provide more information on the risks and rewards of different kinds of deeptech funding.
More information around market sizes and breakout winners could also have a significant impact, by allowing investors to more accurately judge whether the equity dilution is worth it.
Alongside VCs, Angel Investors, university grants and other forms of academic and institutional funding, deeptech businesses can access a couple of other major sources of funding.
Deeptechs tackling major social and environmental issues may be able to take advantage of government grants, carbon credits, and tax breaks, among other schemes. We have seen startups harness these advantages as a major engine of growth, but many founders may not even be aware of these potential funding options. As these programmes are generally a result of governmental or international bodies, the availability of these schemes can also vary according to geography, political support and awareness.
Many deeptech businesses will also find funding with Corporate Venture Capital (CVCs). These can be valuable strategic investors, bringing in a significant capital pool at the later stage – where there is currently a gap in deeptech capital. CVCs operating in similar or complementary fields to the deeptechs can also often provide expertise, industry experience and connections which VCs may struggle to provide to their portfolio.
However, CVCs come with their own risks and practicalities, which deeptech founders often are not informed enough about. For example, a startup receiving investment from a CVC in the industry they wish to disrupt may find their growth limited where their priorities differ from their investors. Having a CVC as an investor can also increase the probability of a business being acquired early, even before a final product is produced if the technology looks promising. This can be great for shareholders, as the cap table for an early acquisition will be fairly undiluted and provide good returns. However, early acquisition offers also inevitably lead to some founders selling out too early and prevents some real breakout stars.
Founders alone cannot build a business. Every great startup is built not just of the expertise and passion of the founder, but with an incredible team, and a network of support from informal mentoring to NEDs and topical specialists.
However the relative scarcity of the technical expertise many deeptechs require can make hiring even more difficult. This increases the probability of deeptech businesses struggling to fill key roles and of having to hire internationally, which has reportedly become much more complex since changes in EU visa rules.
To overcome this, deeptech businesses need to take the time to clarify their mission. Increasingly, top talent is taking environmental and societal aims into account when making employment decisions – as well as the usual salary and benefits considerations. In fact, one climate tech jobsite has reported over 500,000 active users since it launched in 2020 as increasing numbers of tech workers look to make a more positive societal impact. This can benefit businesses with a clear ethical or sustainability focus – particularly where this focus matches topical concerns. But appropriately harnessing this driver requires that employers think carefully about their employer brand and impact so that they can capture and retain this talent.
External support for deeptech businesses is also vitally important – and a key area where investors can make a difference. While many investors find it more difficult to advise deeptech businesses, due to what may be a very different product journey and business structure than other investments within the portfolio, the investor perspective can still be integral – particularly when it comes to advice about issues from negotiating further funding rounds or making network connections. But one area in which deeptech specialists excel (and new entrants into this market will have to invest) is in the quality of their wider network, allowing them to help portfolio businesses find advisors and receive more specialised support.
In order to find and support the best deeptech investments and make great returns to LPs VCs need to consider: fund structuring, sourcing, team expertise, follow-on funding, and the role of LPs.
One of the more pressing issues for VCs looking to shift into deeptech, is the current average VC fund structure is not ideal for this purpose. Most generalist funds operate on a 10 year cycle, deploying capital for the first five or so years, and exiting matured investments in the following five.
This fund structure has been under pressure for years, with average time to exit increasing 3 years in the last decade:
Average time to exit from incorporation of first deal since 2012
Beauhurst, How and Why VCs Are Becoming More Like Hedge Funds, 2022
This trend has placed pressure on fund structures and made it harder for investors to realise the full value of their investments.
But in deeptech this problem can be even more pronounced.
Deeptechs tend to work to different timescales – for example, many might not have a predicted exit opportunity until year 15, five years after the average fund is supposed to have been closed out with all money returned. If this is the case, many VCs might find themselves structurally incapable of investing, regardless of how incredible the opportunity is, because it doesn’t fit the terms of their LPs’ investment criteria. This conundrum was cited by Sequoia when they announced their move to an open-ended investment vehicle, with Roelof Botha commenting that:
Ironically, innovations in venture capital haven’t kept pace with the companies we serve. Our industry is still beholden to a rigid 10-year fund cycle pioneered in the 1970s. As chips shrank and software flew to the cloud, venture capital kept operating on the business equivalent of floppy disks. Once upon a time the 10-year fund cycle made sense. But the assumptions it’s based on no longer hold true, curtailing meaningful relationships prematurely and misaligning companies and their investment partners.
While Sequoia is pursuing quite a different strategy to the likely path of many VCs, it does readily demonstrate the increasing sense that the 10-year model might be due a review. It’s common to see specialised deep-tech firms using a 12 or 15-year model, and many also have the ability to be flexible with promising businesses.
As other VC firms start to branch out into deeptech and hire deeptech specialists as partners, we have also begun to see a hybrid model emerge. These VCs are still generally using a 10-year fund structure (discounting certain areas of deeptech from investment), but are pairing slower maturing deeptech investments with aggressive growers like SaaS to create mixed portfolios. When successful, these models allow the firm to return some LP money early, with an exit from a SaaS or ecommerce business at year 4-6, but also to justify the length of the LP commitment with further lucrative exits in years 8-10.
Traditional VC dealflow tends to come from only a few sources. Research by Harvard Business Review found that:
…more than 30% of deals come from leads from VCs’ former colleagues or work acquaintances. Other contacts also play a role: 20% of deals come from referrals by other investors, and 8% from referrals by existing portfolio companies. Only 10% result from cold email pitches by company management. But almost 30% are generated by VCs initiating contact with entrepreneurs.
Where Do Investors Get Their Dealflow From?
Invigorate Platform, 2022
Broadly speaking, this roughly translates to about 70% of dealflow as inbound, and only 30% outbound dealflow stemming from VCs own research. But as most of that inbound dealflow is network driven – from recommendations from other VCs to businesses seeking the VC firm out – it will tend to deliver only quite a small subsection of possible investments. In short, unless you are Sequoia or a16z, you’ll only get access to a small percentage of the overall dealflow, because you only touch a small percentage of the startup network.
Because deeptech founders networks may contain fewer connections with VC networks, the chances of them finding any single VC firm are statistically lower, making it even harder for investors to connect with these founders. Instead, deeptech VCs have to spend more time on outreach to locate enough high-quality dealflow.
We’ve seen VCs utilising a number of approaches to find the highest quality talent:
These techniques all work to improve the firm’s reach and increase deal flow. The below illustration by Andre Retterath, a partner at Earlybird Venture Capital demonstrates the improved coverage investors can access by diversifying their outreach:
Data Driven VC #2: How to not miss an investment opportunity any more
Andre Retterath, The Data Driven VC, 2022
Reaching out like this does put the burden on VCs to interact with more businesses, many of which may not be at the right stage yet for their funding. However, by reaching founders early, investors can not only reach more startups, they can begin to establish themselves as a trusted partner – not just a source of capital.
Current studies of VC backgrounds suggest that only 8% of VCs started as founders, just 10% have worked for a startup, and even fewer have worked in industrial or technical fields. This is frequently cited as a cause of difficulty in founder-investor relationships and a shaping factor in VC investment strategies.
However, while communication difficulties might be common between investors and founders, this dynamic can be exacerbated in the case of deeptech founders – where milestones, business models and industries can all be more specialised and less standardised. This can reduce what a VC without specialised knowledge has to offer, and make them a less active part of the portfolio’s success or failure. It also (as we have discussed earlier) can make it more difficult for the VC to make an informed investment decision.
It’s another reason why it’s important for VCs to make an effort to hire individuals with both relevant technical expertise and commercial experience in startup and scaleup businesses.
VCs can also utilise a wider network of experts to assess markets, opportunities and potential applications. Already, many sector agnostic VCs have started taking opportunities on the recommendation of trusted partners, or the due diligence of earlier stage VCs. This can be a risky strategy, but it does demonstrate the potential value of expert advice.
Root Ventures, a seed-stage deeptech fund, have published some of the due diligence they undertake on potential investments. While they admit some of these sections are fairly heavily redacted, they do provide a sense of how some deeptech investors assess product viability and market size for unfamiliar markets through industry contacts.
Overall, in order to de-risk investment decisions and improve the accuracy of investor assessments of businesses, deeptech investors need access to three main kinds of expertise (whether from inside the firm or from trusted experts):
While many deeptechs can struggle to reach their Series A, for all the reasons we have discussed under founder-facing issues, those that successfully close a second round of funding show a higher than average graduation rate in subsequent rounds:
Graduation rates between rounds
Dealroom, 2021 The Year of Deep Tech, 2021
This suggests that deeptechs which can establish investor connections have a higher probability of landing their next few rounds than other kinds of tech startup – really emphasising the potential value investors can add to their portfolios.
This means that VCs who can form relationships with later sources of deeptech funding can secure a real advantage for their investments.
There is currently a shortage of later-stage specialist deeptech investors, and many deeptechs report real difficulty finding VCs with this focus. However, CVCs might represent a potential solution for many scaling deeptech businesses. CVCs often have more capital for investment, are comfortable investing at later-stages, and can possess handy specialised knowledge when they operate in adjacent industries. Their connections and industry knowledge can also prove very valuable to deeptechs, providing them with helpful steer on everything from enterprise sales to links to regulators. Given most successful deeptechs will be acquired by larger corporates, CVCs can also provide a route to eventual acquisition.
In this very different deep-tech driven investment landscape, LP support and buy-in are integral.
While interest in the high returns of tech startups has driven a boom in LP capital in recent years, the surfeit of VCs and increasing availability of other forms of investment in the space have also increased competition. You can gauge an idea of the increasing competition from the below graph, which plots the number of new funds investing in a UK business each year:
Number of funds investing in a UK business for the first time
Beauhurst, How and Why VCs Are Becoming More Like Hedge Funds, 2022
Against this backdrop of increased competition, finding LPs to support a longer-commitment, slower returning deeptech portfolio might seem a rather hard sell (particularly as more flexible investment models like hedge funds enter the market). However, conversations with VCs specialising in deeptech have revealed a market in LP investors who find this longer commitment and investment profile attractive, such as pension funds, endowment funds, and multi-generational family offices.
These sources of so-called ‘patient capital’ control vast funds (for example a government survey estimated the market value of UK pensions to be £2.2 trillion in 2019) but currently have little exposure to the tech markets – and to the returns it can bring. If these funds were to diversify even a small fraction of their portfolios into deeptech, it would bring significant capital into the market. At the moment there are some structural barriers preventing this investment from pension funds, but government plans to change the regulatory charge cap might make this possible very soon.
Beyond this, there are many reasons LPs might be interested in deeptech, including:
Top of mind issues such as medtech and cleantech can also be important levers to investment in the deeptech field, as LPs seek out ways of supporting businesses tackling social and environmental challenges.
Eventually, healthy returns from a maturing deeptech sector should draw in a wider pool of LP capital – just as software did – but for now VCs looking to construct more deeptech focused funds may need to start nurturing new LP relationships.
While we’ve discussed some of the benefits VCs can reap by providing a certain amount of early-stage support, ultimately deeptech innovation at this stage is dependent on government policy and funding. In fact, policy can drive changes at all stages of the deeptech ecosystem. So how can the government further support deeptech innovation in the UK?
Given recent economic and policy uncertainty, it has also become increasingly important that deeptech stakeholders can make their voices heard to ensure past progress is not lost. For example, changes to VISA rules for EU citizens have been frequently blamed for a shortage of talent in many deeptech fields, as startups struggle to hire the right expertise.
Tech has a longstanding problem with diversity. In 2021, Tech Nation data revealed that only 26% of people working in tech in the UK identified as women (the national labour gender split is 50/50). By contrast, 15.2% of tech workers are BAME (Black, Asian, or Minority Ethnic), less than the 20% of UK residents, but better than the national average 11.8% of all workers. These figures become much starker when looking specifically at representation in leadership roles, with only 9% of C-suite leaders identifying as women, and 68% of VC funding going to all-male teams. Analysis of top tech firms reveal over 70% of boards and senior executive teams did not have a single BAME member, and BAME women make up only 2% of senior executives and boards.
There is less data for deeptech businesses, but with only 35% of STEM students identifying as women, and only 24% of the core stem workforce, it seems likely that gender imbalances in deeptech are even more stark. Deloitte notes that, globally, women’s representation in technical roles tends to lag 8 percentage points behind women’s representation in tech generally. Perhaps most tellingly, only 3% of Chief Technical Officers are female.
There is also evidence BAME workers may be underrepresented, with only 8.1% of engineers identifying as BAME and research by BCS revealing that despite BAME workers in IT possessing higher average qualifications than their white co-workers, only 32% were in managerial roles (compared to 43% of white workers).
These inequalities are very significant for deeptech.
Lack of diversity tends to lead to an inequitable distribution of benefits – both in terms of capital generated, but also in terms of which challenges tech tackles and how it addresses them. For example, crash test dummies are all based on the average male body – making it somewhat unsurprising that women involved in car crashes are up to 3 times more likely to suffer from whiplash than men. Likewise women’s health matters, such as the menopause, remain comparatively unresearched. Examples abound of how lack of diversity in teams – from traditional markers such as gender or race to economic background and schooling – can have a negative impact on decision making and problem solving, leading to strange oversights and wasted resources.
By contrast, diverse leadership and product teams can have significant benefits – allowing businesses to troubleshoot and spot problems much more effectively (for more on this, check out our diversity report). In fact according to McKinsey, businesses with diverse leadership teams outperform peers by up to 36%:
The Business Case for Diversity in Executive Teams Remains Strong
McKinsey, Diversity Wins: How Inclusion Matters, 2020
So how do we actually encourage more diversity in deeptech, and particularly within decision-making and founding teams?
1. Increase the percentage of women studying STEM subjects. With research now suggesting children may absorb gender roles concerning science and maths as young as six, government and school initiatives tackling stereotypes and encouraging interest in maths and the sciences at an early age are key. More affirmative action schemes and programmes encouraging girls to take STEM subjects, or university efforts to hire more female researchers as lecturers and professors could also help address the gender imbalance.
2. Improve the diversity within VC firms. While VC is slowly becoming more diverse, it is still overwhelmingly white and male. Richard Kerby at Equal Ventures broke down the data for the US VC market below, revealing how white men vastly outnumber every other demographic:
Richard Kerby, Where Did You Go to School?, 2018
What’s more, while white men might represent 58% of VC partners, they control 93% of venture capital dollars. This has a direct impact on founders. In the UK, between 2009 and 2019, only 3% of VC funding went to all-female teams but 68% of funding went to all-male teams. With many minority founders reporting investor bias, VCs have a significant responsibility to reflect on how they find, communicate and invest in founders. There are many routes to doing this, but one great start is to address internal gender and diversity imbalances within the VC firm and hire more female and BAME partners.
3. Create more grants and mentoring schemes. These can have a huge impact, giving more founders the tools, confidence and expertise to start developing their product and help more senior employees capitalise on their expertise to start and scale technical businesses.
4. Hire more diverse voices into existing deeptechs. Founders who hire diverse candidates into leadership positions within their business can improve their team’s problem-solving capabilities while also helping more future founders get into deeptech.
Diversity remains a massive challenge to be tackled, but by including and encouraging more diverse voices, founders and VCs can create more value, and ensure their products make a real difference.
While there are many challenges to be overcome and plenty of work to be done, it is clear that deeptech will be a very significant force in the innovation landscape in the years to come – and an important part of the future of VC.
This report set out to lay out some of the challenges and potential of the deeptech ecosystem as it stands (and in the future). It was compiled with help of VCs, founders and operators from across the deeptech landscape with the aim of increasing the visibility of key challenges and considerations – and to kickstart real work towards potential solutions. After all, it is only through increased awareness, networks, and VC, governmental and institutional support that the deeptech wave can truly accelerate.
Here at Invigorate, we’ve been working to improve the availability of resources on fundraising (as well as on building and scaling a startup) and help deeptech, or simply more technically-inclined, founders develop their fundraising strategy and investor proposition. We also help founders, advisors, and investors stay up-to-date with data and insights into the scaleup and venture ecosystems through our newsletter and social media channels.
This report identified a number of challenges facing deeptech businesses and investors. If your business, portfolio or community could benefit from support overcoming these obstacles, you can access more information and support below:
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