Deep Tech Investment Cheatsheet

TL;DR

Summary

Deep technologies have different impact in the world, and they also have different risks, potential return level, and technology readiness level. Therefore, we should ask different questions when making investments in different deep technologies.

Investors have different risk tolerance levels and competitive advantages, and therefore investors should know how to minimize the risks and maximize their competitive advantages by selecting the right deep tech domains.

Most of the startups we see everyday will fall into two categories: Deep Tech (tech-driven companies) and Business Model (operation-driven).

For the business model companiesif they are still in a very early stage, investing in them is simply a bet on the team — the company’s success will heavily depend on the team’s operation, marketing, and management experience; if they are more established, then the operational numbers will mostly guide the investment decision.

Moreover, for the business model companies, there is always a strong trade-off between return and risk. The potential return and risk are extremely high at the very early stage of a startup. As the startup scales up, every acquired user is part of the company’s assets, which can be sold even if the company does not work out. That being said, the result for investing in this type of companies is unlikely to be binary — 0 or 1, and the risk is therefore under control in some way. Therefore, when the startup grows up, people can relatively easily price the risk, and the potential return (by # of acquired users, CAC, and LTV) is also relatively accurately measured and priced.

For deep tech companies, the evaluation process becomes complicated, and it is not that easy to evaluate the return-risk trade-off. Different deep technologies will have different “enabling power”, total addressable market (TAM), and risk (technology-readiness-wise and competition-wise). As investors, we will face more variables. How can we decide what matters more? Which types of deep tech are more favorable for investors?

To have a better sense of how the deep technologies differ from each other and what matters most when making investment decisions, see the table below. (Read the PDF version here)

A detailed explanation is provided here to help investors understand these two tables.

Deep technologies are different from each other

For deep technologies, we divide them into three layers by the impacts that the technologies have:

  • Level 1: Technologies that can change how the world works fundamentally (e.g. new materials, AI/ML, blockchain, etc.).
  • Level 2: Technologies that are built on top of the Level 1 technologies and create new platforms or infrastructure for industries (e.g. cloud computing, edge computing, computer vision, AI tools, etc.).
  • Level 3: Technologies that are built on top of either Level 1 or Level 2 technologies and tailored for specific industries to improve industry performance (e.g. AI for finance, computer vision for security, computer vision for manufacturing, etc.).

For different levels of deep technologies, we really care about different things when evaluating investment opportunities.

For the Level 1 technologies, we do not need to worry much about the potential market size, as it is going to change the world entirely. However, the real risks here are:

  1. The technology is very far from commercialization.
  2. The technology has not solved the problem perfectly and the technology is evolving fast.
  3. The CTO/tech team is not legit.
  4. The technology may not bring much value to the potential customers.
  5. There is no IP.
  6. The technology will become a commodity quickly.
  7. The company has not secured enough funding for completing development.

Based on these risks, what we really want to examine when evaluating an investment in this domain will be:

  1. How far is the technology from commercialization?
  2. How fast is the technology evolving?
  3. Does the CTO/tech team have strong tech background & many IPs?
  4. Have any pilot customers validated the technology?
  5. How defensive is the technology?
  6. How likely is it going to become a commodity?
  7. Are there any existing investors with deep pockets?
  8. How many applications does the technology have?

For the Level 2 technologies, the market size is still unlikely to be a problem. However, we might worry about whether a cross-industry “platform” makes sense for this technology? For cloud computing, it makes sense because industry customization is not needed, and a scale of business can offer cost advantage. For AI tools, it might not make sense because different industries will need different AI tools.

Therefore, the risks for the Level 2 technologies will include:

  1. The product cannot compete with tailored solutions.
  2. The company is addressing market that’s too broad.
  3. The technology has not solved the problem perfectly and the technology is evolving fast.
  4. Technology has not been validated. Scale of business does not bring advantages to the company.
  5. The technology/product becomes a commodity.
  6. The company may face competition from Chinese companies.
  7. The company may have very low margin regardless of large ARR.
  8. The company may not have sufficient funding to scale up.

Accordingly, the questions that we need to ask when conducting due diligence are:

  1. How defensive is the technology?
  2. Has the technology been validated by the industry?
  3. How fast is the technology evolving?
  4. Does scale of business matter? Does customization matter?
  5. How does the company differentiate?
  6. How do you compete with similar Chinese companies, which may have much lower costs?
  7. How profitable will the company be?
  8. Is there any existing investor with deep pockets?

For the Level 3 technologies, as companies are tailoring the solutions for small/niche use cases, market size may become a problem. While technology itself might not be a big problem here. For example, when evaluating an in-car environment monitoring company, we do not worry about the computer vision technology but question the potential market size and exit opportunities for investors.

Risks around these technologies/companies include:

  1. The market size is too small.
  2. The team lacks experience in marketing, operation, sales.
  3. The team doesn’t have enough BD talents (pipeline & execution).
  4. The team does not provide the best “product” due to a lack of industry knowledge.
  5. The product is not differentiated enough.
  6. The market is too saturated.
  7. Exit opportunities are limited if the market size/business is small.

Accordingly, what we need to examine will focus on:

  1. What does the market size look like?
  2. Does the CEO/founding team have rich marketing, operation, sales experience and knowledge?
  3. Does the CEO/founding team have rich industry relationships?
  4. How does the company differentiate? How competitive is the target market?
  5. Will there be any potentially attractive exit opportunities?
  6. How do the comparable past deals look like?

Investors should choose the most favorable domains based on their preference and competitive advantages

Beyond the three levels of deep technologies, we further categorize the technologies based on their impact level and the space that they are impacting (physical or digital).

  • Category A: Level 1 technologies impacting the physical space
  • Category B: Level 1 technologies impacting the digital space
  • Category C: Level 2 technologies impacting the physical space
  • Category D: Level 2 technologies impacting the digital space
  • Category E: Level 3 technologies impacting the physical space
  • Category F: Level 3 technologies impacting the digital space

Apparently, the risks are different for these categories. For some of the risks, only God knows the answers. For some of the risks, we can do research and minimize them. Eventually, we will want to make the least “bets” and gain the maximum return based on what we can do — the competitive advantages as investors.

Overall, different investors will have different capabilities and competitive advantages. Some of them might have deep knowledge in material science, while some of them might have strong network in specific industries or have deep pockets to participate in long-term “battles”. To succeed, investors may need to choose the domains with fewer God-knows and a better fit with their competitive advantages.

For Category A/B technologies, there are relatively many unknowns that few people in the world can predict. These unpredictable issues include:

  1. The technology can be commercialized quickly.
  2. The technology will not be replaced quickly.
  3. The CTO/tech team is strong enough.
  4. IP can be fully protected.
  5. We can put more money into this technology than Google.

While, we can do our research to control the following risks:

  1. The value/applications of the technology

To succeed, if we want to invest in this domain, investors need to have the following competitive advantages:

  1. Deep knowledge around a specific area.
  2. Strong understanding of the evolution of the technology.
  3. Strong network in academia and industry to help validate the value of technology.
  4. Deep pockets to compete with giants.

For Category C technologies, the risks mainly come around the IP protection side — since it is not difficult to examine and copy a hardware design for Chinese manufacturers, which will have cost advantages.

  1. The technology will not be replaced quickly.
  2. The CTO/tech team is strong enough.
  3. Chinese companies will not have cost advantage.
  4. IP can be fully protected.

The risks that we can examine is also limited:

  1. The value/applications of the technology

Successful investors in this category will need:

  1. Deep knowledge around a specific area.
  2. Strong understanding of the evolution of the technology.
  3. Strong network in academia and industry to help validate the value of technology.

For Category D technologies, the main uncertain questions are:

  1. The speed of commoditization will not be too slow.
  2. The margin level will not be too low.

To control risks, we can research the following:

  1. The benefit from scale of business.
  2. The benefit of tailored solutions.
  3. The differentiation strategy & competitive advantage.

To make successful investments in this category, investors should have:

  1. Strong understanding of the potential customers.
  2. Solid competitive analytics skills.
  3. Strong industry network to validate the value of the technology.

For Category E technologies, the really uncertain things are:

  1. The team can lead the company to win in competitions.
  2. Chinese companies will not have cost advantage.
  3. IP can be fully protected.
  4. The underlying technology will not be replaced quickly.

While we can still do our research to verify:

  1. The market size.
  2. The value/applications of the technology.
  3. The competition level.

Successful investors will need to have:

  1. Strong industry network to help the business to scale up.
  2. Solid competitive analytics skills.

Finally, for Category F technologies, the true uncertainties mainly come around the team:

  1. The team can lead the company to win in competitions.
  2. The underlying technology will not be replaced quickly.

What we can examine to control risks include:

  1. The market size.
  2. The value/applications of the technology.
  3. The competition level.

Investors need to have the following competitive advantages to succeed in this domain:

  1. Strong industry network to help the business to scale up.
  2. Solid competitive analytics skills.

This research is drafted by Fan Wen and co-authored with Janis Skriveris under the help from Tarek ElessawiMarc Bouchet, and Addison Huneycutt at Plug and Play Ventures.

Disclaimer: The article is not, and should not be regarded as “investment advice” or as a “recommendation” regarding a course of action, including without limitation as those terms are used in any applicable law or regulation.

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