Technology Startup: Deep technology companies are different from your average internet startup. Their risks are different, development timeline is different and cash needs are very different. I wanted to take the opportunity to share a framework we use internally at Propel(x) to conduct diligence on deep technology startups.
Starting at a high level – our goal is to identify companies that could yield favorable outcomes for tech startup investors; companies that potentially maximize sustained profitability. We frame our diligence on deep technology startups in terms of the model below:
This model helpfully combines external risks (e.g. market risk, competitor risk) as well as internal risks (technology risks, execution risks, etc.). The outermost circle represents the total addressable market, some of which is taken by competitors (shaded lightest yellow), the remaining, being taken by our technology startup in question.
Our technology startup then expends costs to deliver the goods (shaded darker yellow). These costs could include technology development costs, IP protection costs, regulatory costs, sales and delivery costs etc. The innermost circle (darkest yellow) represents the profit that is left after costs and the potential for sustained profitability. Our goal is to evaluate the risks that will make this innermost circle bigger or smaller.
Starting at the outermost circle, a key risk is market risk – the probability that there will exist demand for our product. Often, deep technology companies do not carry a higher market risk (e.g. if a new therapy is discovered for cancer, there will likely be a market for it). Interestingly, it is not always important for the market to run in several billions of dollars for a tech startup investment to make sense. I emphasize this point because it runs contrary to many venture capital investment philosophies – VCs typically invest in very large markets.
But that is not the only way to grow successful companies. Our goal is not to maximize addressable market; our goal is to maximize sustained profitability. It is very possible that a single company may dominate a relatively small market worth several hundred million dollars (several medical devices and drug companies exhibit this characteristic). In that case, this company would be able to create sustained profitability and could be worth investing in. Besides, very large markets always come with intense competition. Competing in these environments can be hard.
Deep technology startups/companies do carry competitor risk – the chance that much of the market will be cornered by competition. The reason is that usually there are more than one approaches to solve a problem (e.g. many people are attempting energy storage technologies, therapies for cancer, etc.). One can understand competitor risk by:
- Talking to customers (Q: What other alternatives do you use to solve your problem? Are you aware of other new products coming to market to solve your problem?)
- Talking to experts (Q: Who else is doing this? How far along are various technologies? Who will be first to market? What are the relative advantages of each technology?)
Assuming our diligence on deep technology startups suggests a great market potential and limited competition, we are encouraged to start asking questions which help us determine risks related to delivery of the product:
- Technology Risk
- Regulatory Risk
- IP risk
- Execution Risk
Finally, and importantly, we want to evaluate Exit potential – the likelihood that tech startup investors will make money from a tech startup investment! Let us tackle these topics one-by-one below:
Because deep technology startups are often based on breakthrough deep technologies, they carry very significant technology risk. For example, new drugs may or may not perform well in clinical trials; an AI system that learns a natural language may not be able to learn at planned speeds; a highly efficient battery system may or may not perform as predicted at scale.
These are significant risks and may be understood by talking to the management and to experts. Surprisingly, we have found that very few people ask for data! That is the first question one must ask of the management: Q: Please share data from your experiments/tests. What is the evidence that this technology will succeed? What tests have you run? How did your system perform under stress testing? Questions for experts should include: Q: What parts of this technology have been proven at scale? Which parts of this technology are breaking new ground? What are they key risks to this technology succeeding at scale? What data exists to prove this technology can succeed at scale? Which experiments/tests have failed to achieve these goals in the past? Why did they fail? What needs to be done differently in order to succeed?
At Propel(x), our unique diligence capability connects tech startup investors with Experts. Investors may also refer their own experts for tech startup investment. Ultimately, our goal is to get 3-5 experts to participate in the discussion, so that tech startup investors may get a well-rounded picture of the specific technology risks.
This is typically high for companies that are regulated by the FDA. The risk may be evaluated by talking to the management and also external experts. We are trying to understand here the chance that this new device or drug will pass FDA scrutiny. Drugs are high risk, as clinical trials may fail for a variety of reasons (This topic is vast and I will not go into details here).
In general, it is important to understand what similar therapies/devices have been approved by the FDA before, under what conditions and how similar is this therapy/device to previously approved applications. It is important to do some research here, ask the company to provide you with data, talk to experts and of course, common sense helps!
Much is made of patents and such. IP can be valuable, but there are many ways to solve the same problem. In some cases, patents may give you a 2 year head start (if that). In the case of therapeutics, patents are of paramount importance and deserve expert scrutiny. However, for angel investing purposes, it is helpful if you simply read the claims carefully. Sometimes the claims are so narrow as to be quite useless. Again, common sense helps here! Although IP risk and regulatory risk are somewhat important, they are overshadowed by execution risk.
Here we are evaluating the team, the plans for technology development/production at scale/sales marketing & distribution etc. – the potential of the team to achieve great things! Business plans often change in response to market conditions. So this is a highly subjective judgment. But it does require meeting with the team.
Because this is so important, at Propel(x) we host investor calls where the team makes an on camera pitch and fields questions for 60 minutes. Our investor calls happen most Wednesdays. These are lively discussions where investors, technology startup and experts participate – the startup management responds to a range of questions. All calls are recorded and are available on our website.
Assuming everything looks great, there is still the matter of being able to make money from an investment. The ability to make money depends on many stars aligning – low valuation at investment, high exit multiples, favorable terms of investment, favorable future terms from other investors etc. All of the details are beyond the scope of this post! However, an important point is to gauge exit potential – what is the chance that this company will be acquired or will go public for lots of money?
Because this is so hard to gauge, we use a simple technique as a proxy: we try to quickly list at least 5 companies that would acquire our technology startup. If we can think of 5 companies that would acquire our startup, then it is presumably creating something valuable. If, on the other hand, we cannot think of anybody who would acquire our startup, then it is a much harder sell! [irp]
Overall, our framework for diligence on deep technology startups comes in handy to quickly gauge companies. It also helps us to structure our conversations with experts, customers and the management to ensure we are being systematic and exhaustive.
