You Don’t Know What You Can’t Know

In early-stage startups, the future is unknown and can’t be predicted.

Whenever angels, VCs and other early-stage investors gather to discuss startups they’ve invested in (or are considering), there will undoubtedly be a myriad of speculative phrases thrown around:

“This one’s gonna get picked up by Google / [Large Company in their Industry] / [Large Local Fortune 500 Company] within a year or two — no doubt”

“I just know this entrepreneur is going to make it happen — I’m gonna invest double our usual amount”

“It may not be a unicorn, but it’s a sure early exit within 18 months”

“I know the guy at [Large Company], and he said they’re going to buy this within a year”

“The guy on their board, [Name of Respected Person], is very involved / has so many connections / knows the industry so well / etc. and will drive the company forward.”

Most of the speculation is based on quick and/or large exits, usually on the premise that the investor has some inside information or a specific advantage. While early-stage venture capital is by no means an efficient market, I would argue that the future holds an enormous amount of uncertainty for technology startups — rendering these hypotheses little more than SWAGs, useful only for entertaining cocktail banter.

For most traditional investments, there is a relatively high degree of control and/or a low degree of risk. It is unlikely that the value of your stock or real estate will lose all of it’s value OR increase by an order of magnitude, even over a decade. If you start a traditional SMB, you have a high degree of control over the success of your enterprise. But for technology startup investments, the principles a traditional investor takes for granted do not hold true. Even if you have worked your entire life in the industry AND are so involved you effectively control the company’s decisions, you are only negligibly more likely to positively impact the outcome. This is because exogenous variables dominate the formula for projected outcome in a high risk startup. Let me explain…

Please note that the percentages are only directional.

Investing in a new technology is not based off of the opportunity today but what the opportunity will be in 5, 7 or even 10 years down the road. And most of the time investors will be wrong in these predictions. Y Combinator, which sees (~8K startups) every year and invests in 200, only has a (0.7) unicorn hit rate. While unicorns aren’t the only measure of success, it is safe to say that even the prestigious Y Combinator is wrong a lot more than it is right. Other VC firms can have higher success rates, but it’s still up to chance which specific companies ultimately succeed. There are several paths to a winning exit, but they are all very narrow and their cumulative probabilities are much less than 50/50. Here’s a list of some of the unforeseeable that goes wrong in even the brightest of scenarios:

  • Key supplier becomes unusable (because they go out of business or refuse to work with you by turning off APIs/buying your competitor/etc.)
  • Founder gets sick / gets married / dies and stops showing up for work
  • Patent trolls suck up all of your company’s cash
  • Product failures delay your company’s launch
  • Corporate turnover at a key customer in your company’s pipeline resets the sales timeline
  • Mistiming of key contracts (startups only ever have at most 18 months to prove a stage out)
  • On top of all that you still have to successfully exit your investment, and there’s lots of ways that can go wrong and you can get cut out (legal loopholes with immoral founders, notes not converting to capture the upside, liquidation preferences from later-stage VCs)

When you view early-stage venture investing in the aggregate, all of these unfortunate events show up, but a few companies find those long, narrow roads that don’t have journey-ending crashes (or are able to duct-tape themselves together and soldier on) and are able to exit at huge multiples. And many respected angels and VCs probably passed on these companies (some several times).

Fortunately, the early-stage venture investment scene has strongly positive returns on average, and the larger the portfolio, the tighter the confidence interval converges around the mean. This leads to the conclusion that while you can’t predict which of your investments will be a success, you can predict that a large enough sample size of the market as a whole will be a success. At M25 we lean heavily on this thesis, and invest the same initial amount into each startup in our portfolio; and these are startups which we’ve tied to a specific range of valuation to keep them all in the same stage, or “asset class”. This allows us to not rely on the “good luck” of our fund managers to pick the best company (though the companies still need to be “investable” by objective standards — see our prior blogpost), but instead to ensure strong, positive returns with our portfolio strategy. Using this thesis, it makes little sense to overweight investments at the same stage — that only increases the variance of your returns, as you might hit it big with that outsized investments — or you will probably lose twice as bad.

But, some might say, what about the ability some prestigious firms have in:

  • attracting the best companies?
  • helping companies with their impressive knowledge/connections in a space?
  • extra special method of picking the best companies?

Well I’m very impressed (and jealous) at how well they can optimize the controllable piece of the outcome, and they should continue to do so. However, any effort on the controllable 10% without at least as much thought in distributing risk across the 90% of the outcomes that’s uncontrollable leaves a portfolio hopelessly exposed to the whims of statistical fluctuations. And that’s not something I (nor our more risk-averse Midwestern LPs) would tolerate.


About the Author

Victor Gutwein is the managing director of M25 Group, a micro-VC firm he started with his family in 2015. M25 Group’s focus is on seed and Series A rounds for Midwestern startups. He has worked in corporate retail in both the fashion and ecommerce industries in a wide variety of cross-functional experiences, from marketing to merchandising, international to omnichannel retailing. Victor has a passionate history with startups, including a vending machine business and kick scooter company, along with being on the board of the University of Chicago’s first student-run venture fund.

Victor lives with his wife on the South Side of Chicago and loves staying active with backpacking, water polo, rugby, ultramarathons, and triathlons. If he can’t convince you to workout with him though, he’ll usually succeed in getting you to try out a Euro-style board game (like Settlers of Catan) with his friends.

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