How to pick startups (audio only)

In this webinar we start with a short presentation about due diligence followed by a fireside chat with two experienced healthcare venture capitalists.

Key Takeaways:

1. Have a structured due diligence process.

2. Market risk: timing and a big market opportunity are both important.

3. Technology risk: better, faster, cheaper.

4. Team risk: clear founder vision, unique insight, strong leadership and resilient.

5. Execution risk: go to market strategy and business model.

6. Exit risk: what is the potential exit size or channel.

7. You will never get to 100% conviction in early stage investing, you are making decision based on incomplete information.

8. Do both personal founder and customer reference checks

9. An option pool is a must.

10. Interest over background, ability to acquire knowledge is more important than your background.

11. During a pitch introduce yourself, what are you building, what problem are you solving and the market opportunity first.

Transcript

 Hi, everyone. Thanks for joining me on this webinar today. Today, we'll talk about how to do due diligence for healthcare startup. This will be a short presentation followed by a conversation with our guests Liu Zhang and Shubra. I'll be talking about what I look for in the team, the product, the market metrics, and the regulatory framework I look at.

If it's your first time investing in a startup, generally, I would advise you to have a screening criteria. My screening criteria is fairly Simple and it's mostly based around the team. The founders must have known each other ideally for more than six months. It's better if they've worked together in the past and they must be full time in the startup either as a type of investment or shortly thereafter.

I'll make some exceptions for clinical founders if their clinical role adds value to the startup but even in that case the majority of their time commitment and capital commitment should be towards the um, Because it's just, it's so difficult to, to grow a startup and there's so many ups and downs.

Commitment, uh, to the problem they're solving and commitment to the startup is critical. If they pass the screening criteria, I'll ask for their deck. I'll go over what I look for in the deck, but if I am interested in what their deck says, I'll meet with them. After I meet with them, I'll think about the meeting, I'll reflect on it, I'll do some more research.

Generally, when people talk about problems they're solving, they're making a bet about the future of healthcare. And I need to ask myself, am I comfortable with the same bets? AI is a great bet. A lot of people are making right now in clinical decision support tools and replacing or helping our workflows.

And, um, my, um, my thinking on this is AI will help. With patient engagement and help with clinical workflows. I don't think it will replace a decision making in the next five years again. The time frame for venture and the time frame for early stage investing. If you're an angel investors was generally, um, you want returns within 5 to 10 years.

So sometimes you'll see startups are way too early for this, uh, for their stage. And if you don't think they will come to market and if you don't think they will get market adoption within 10 years, At least for venture capital, it doesn't fit the framework. After the research, I'll do deep, deep diligence.

I use my network, um, to do diligence in different aspects. And if I'm still interested in the startup, I will go through the legals and do reference checks. Reference checks are critical. Um, generally a reference check with a previous investor and one to two customers, um, is important. If there's anything I want you guys to take from this talk, it's having a decision making framework.

It's having a balance of intuition and structure. Usually, it's good to have a structured approach and use intuition at the end. I don't invest against my intuition, but I don't rely solely on my intuition for decision making. Thinking is a, it's a very taxing, uh, endeavor. We don't think of thoughts and thinking as energy expenditure, but a chess player burns about 6, 000 calories a day.

A professional chess player, whereas a marathon runner will burn about 2, 600. So you're burning twice as many calories thinking than you are playing chess. Worry of your biases of assumptions you're making, um, a good framework for this. I like Danny Kahneman's framework of when to use your intuition and when not to.

Essentially, he says if you're an expert in something and it is a high validity environment. So, a high validity environment is an environment which is somewhat stable. You're doing an action repeatedly and you know if you're right or wrong fairly quickly. I'm a physician, so working in urgent care is a high validity environment.

Investing is a low ability environment because after you invest in a startup, we don't know if we're doing well really till exit, which is in healthcare generally a minimum of five years. So it's important to have a structure in place. That being said, within the structured process, you can use intuition, um, if you're an expert and it fits that a team?

The two main things I would say I look for is founder problem fit and team dynamics. Why is this founder working on this problem? And why will they stick with this problem? Why will they continue to iterate on their solution until they find product market fit? I look for founders who have a story. I ask them how they became familiar with this problem.

And then I just go deeper into, you know, why are you working on this? Um, why aren't you working on something else? Why aren't you working on something easier? Healthcare is a very difficult industry. I look at team dynamics. I want to know the team has somewhat of a history that will stick together. I want to know what every co founder has the founder problem fit.

So I speak with all the co founders. Mark Andreessen famously says, um, Strong ideas loosely held. There is a balance of humility and conviction. You need to have the conviction that your solution is a solution that will solve this massive problem you're trying to solve. You also need to have the humility to pivot when you're recognizing you're not meeting your metrics or whatever metrics you have where your solution isn't working.

Which is why, again, Founder Problem Fit commitment to the problem you're solving is important because it will, you will continue to iterate to get Product Market Fit or Founder Market Fit. I am not too keen on Founder Market Fit. I know other investors, um, Index founder market fed previous exits very heavily.

I don't. There's very few founders who have two unicorns, especially within one industry. Um, there was a Harvard study in 2004 that says you have a 30% more chance of success if you're a previous founder. But, you know, that's still, that leaves a 70%, um, which you don't need to be a previous founder. And ideally, your previous exit, if we are sticking to data.

Should be a small exit. Um, that's when you, you still have the hunger and you want to do something big. So in terms of product, the founder has to be product problem focused. Lose Lee held strong ideas and customer obsessed. They should have an in depth knowledge of their product, but they need to be focused on the problem.

They're solving a scalability roadmap is important. How will this scale? Early stage investing, following the power law, is a, is a game of outsized returns. It's a game of maximizing your upside while essentially not worrying too much about your downside. What that means is the startup must grow to immense revenue.

Um, usually when I invest either they don't have revenue or they have a couple hundred thousand in revenue. I need a path for them to grow to at least 50 million, if not 100 million in revenue. Um, and, and they need to show me what products, what other verticals we're going to go into, what other products we'll make, or just the product they have right now.

How will this scale to bring that revenue? Idealab did a study in which they, they were asking what is the biggest predictor of startup success? If you ask, um, first time founders, they will often say, Their product or their team. If you ask second time founders, they will usually say distribution or how will they scale.

What this study found is why now. Is the market ready for your product? There's a startup in the 90s that made the iPhone before the iPhone came. There are tons of different versions Instacart. There's countless examples of startups that were too early for the market. The infrastructure wasn't there, people weren't ready to pay for it.

Um, Google was the 17th search engine. So, you know, is the market ready for your product? Are people ready to pay for your product is important. Identifying market tailwinds is critical. And this is why so much money is put into market research. Some market tailwinds I'm banking on is a digital front door hybrid home care model.

AI focused on patient engagement and in the near future I think patients will make their own clinical decisions with the help of AI. Now that requires reimbursement and regulatory changes which I'm backing on but essentially you're making these big bets and that's how you get these outsized returns and especially if you're making bets that other people are missing.

Now, you need to have conviction in your bets. You need to have substance behind it. You need to have research about, okay, how were the previous tailwinds, and why am I predicting this one? Most tailwinds are not predictable. So, COVID, you know, is a perfect tailwind. It blew a lot of startups to success.

We're not doing so well right now, but strictly from an investing perspective, we get our, you get your money out on exit. Um, So, you know, you can't predict Covid, but there are other tailwinds, like when will AI reach adoption in healthcare? Is there precision medicine? It will pay a big part. Will epigenetics pay a big part in medicine And again, stick to the next five to 10 years?

You know, we can all say maybe we will live in the metaverse, but if you don't think we will live in the metaverse within the next five to 10 years, I would advise staying away from investing in it. In the venture model. If you're an angel investor and your timeline is 50 years. Sure. Um, I think you can, you can take a more, a longer timeline approach to investing.

So I look at the business model in general as a B2B B2C. There's pluses and minuses to both B2B is longer sales cycle, but the contracts are stickier. B2C. You know, it depends what you're, if you're competing on price, that is, it's very difficult and, and it opens the door or the door is open for others to kind of just drive their price lower.

And it's, uh, you don't want to be a loss leader, um, in a market competing on value is much better. And I think lots of people who are much smarter than me have talked about this. So I'm not going to get into too much, but essentially do they have a scalable business model or profitable unit economics? Is their customer acquisition cost going to go down?

Are they having more organic growth? What's their cost of goods and will it go down? And cost of goods essentially is, you know, how much does it cost to make your, your good or your product. In competition, startups should have a deep understanding of their competition. Why will they weigh into their better product, their better distribution?

What is their differentiator? I don't worry too much about incumbents, Google, Microsoft, Amazon, stealing their idea. It rarely happens. And generally, there's a competition between the startup getting to distribution before one of these incumbents, if they think this idea is valid enough, the market is big enough, and they want to devote their resources building their product.

Generally, the startup will win, I would say. Um, but again, it's a good question to ask, but I don't index. Why won't Google do this or why won't Amazon do this too much unless they're building something that directly competes with what the incumbent, um, is doing at this point or that they plan to do in the public sets over the next year or two.

So, traction is incredibly important and it essentially validates all the hypotheses that the founders are making, all the assumptions they're making. Ideally, they validate before they build and then they start selling their product in some capacity while they're building. This is more of a mindset. I just want them to value the sales process and not just the product process.

If you build it, they will not come. You have to sell it. You have to have a sales marketing strategy in place. Branding is incredibly important here. Some metrics I look for, what is their run rate, um, which is how much money they're making, what's their burn rate, how much money are they spending, what's their LTV to CAC ratio, um, LTV is the customer, CAC is the customer acquisition cost, a ratio of 3

to 1 or higher is good. In terms of legals, uh, I won't go into too much depth here. The main thing is the CAB table. Which is the breakdown of who owns what in the company. At my stage, the founders must have at least 60%, if not 80%. And this includes, uh, employee stock option tool, which is, uh, some equity set aside for future employees.

They bring on as a company skills, usually 10 to 20%. Um, they should have some intellectual property. Defensibility can be in the distribution. But for biotech, um, medical device, I want to know why is this different from other startups in their space or from people who have done this in the past. And the difference could be that now is the right market timing.

Um, but I want to know why is now the right time and what's different about you. All, um, equity for the founders should be vested, which means they're given the equity usually over four years, sometimes six years. And there's a one year cliff, which means if they leave before 12 months, they don't get any equity.

What you'll see often is they get 25% after a year, and then the remaining 75% over the next 36 months. Which is standard. I'm happy with that. I'll speak a little bit about regular trades. There's three classes, um, that FDA uses. Class 1, 2, 3. Class 1 is low risk. Class 3 is high risk. Class 2 is in the middle.

If you're investing in medical device, most startups will fall into Class 2. And either they will say they're de novo or 510k again, most will be 510k. 510k means that there's a predicate. Someone has done this before and they're using their, um, FDA approval to piggyback on. Now, if they're using a 510k, I would ask them, well, why are you different?

Why didn't the previous one succeed? Or if they succeeded, why will you succeed if they're the market leader currently? Um, in terms of, uh, how much it costs to go through FDA approval and including clinical trials and how long it takes to know, I would say 3, 000, 003 years, 510k, 5, 000, 005 years, class three, you need massive clinical trials, pre market approval, you know, tens of millions, eight years or so.

And again, there's, there's a lot of variance there, but that's, that's in general. So in brief, use an intuition guided structured decision making process. And we'll get started with our questions and answers now. Thanks everyone.