Theodore Seem (MBA ’20) introduces the idea behind Outsiders Fund, an early-stage venture capital firm focused on identifying opportunities where technology will disrupt traditional, incumbent industries.
The world of start-ups is complex. It is hard to organize and harder to analyze. But one simple way to look at the world is to sort companies into two categories, those that operate on the frontier and those that disrupt established industries. The companies building on the frontier are usually the ones that make splashy news headlines. Today, they are developing virtual reality, blockchain technology, and new age pharmaceuticals. They stretch the limits of human possibility and attract great attention from the venture community. But when it comes to investing, these companies tend to be the ones that overpromise and underdeliver. That is because the risk of these companies is often underestimated and mispriced, while the expected return is inflated and aggrandized. As such, an investor may be better served by backing the companies disrupting established industries to find the risk-adjusted returns they desire. My business partner, Austin McChord, and I founded a venture capital firm based on this thesis. So, let’s understand why we believe strongly enough to put this idea into practice.
Before going any further, it is necessary to discern what distinguishes these two segments. Disruptors seek to displace established players through improved customer experience, an enhanced product, or a superior business model. A few well-known examples are Facebook, Slack, or Dropbox. Each took an established industry—social networking, multi-user messaging, and file storage—and improved the user experience and functionality to create companies superior to those of established players. On the other hand, companies operating on the frontier seek to develop breakthrough technologies or create new products, usually with a goal of capitalizing on first-mover advantage. An example here would be Magic Leap, which is working to develop glasses that superimpose 3D computer-generated images over real world objects. Each segment faces a unique set of challenges and opportunities, and when Austin and I took an empirical view of the world, we saw a drastically different set of outcomes between them.
The venture capital model is one predicated on swinging for the fences with the understanding that there will be many strikeouts between successive home runs. Investors do this with the hopes that the winners will be more than enough to make up for all the losers. The problem with this model is that by swinging for the fences, investors largely ignore the risk, and the entire focus goes to an investment’s potential return. The reason for this problem stems from the inability to properly calculate a venture investment’s true risk, given it is almost impossible to properly assess the confluence of factors which determine a new company’s chance of success. But what if we could solve this problem by assessing risk not on a single investment, but on an entire segment. Going back to the analogy, instead of swinging at every pitch that looks auspicious in the moment, we can take a step back and assess pitches on an aggregate level, swinging only at the set of pitches we know to be most promising. Therefore, if we could calculate risk for an entire segment and find one with an optimal risk profile, we could construct a better portfolio comprised of companies only from this segment.
At this point we have already divided the world into our two segments of interest and determined that it may be possible to find one that offers a better set of risk-adjusted companies. The next step is to look at the way to assess the risk on an aggregate basis. Given that venture investments do not have historical data and the historical data of comparable companies is not marked to market on a frequent basis, we cannot calculate any type of volatility and are going to have to think a little outside the box. One way to think about the problem is that, instead of being backward-looking with data, we could turn our attention forward and look at the probability of company failure. One way to approximate this probability is by looking at the number and severity of known obstacles in a company’s path to success. The greater the number and severity, the more likely the company is to fail and thus, the riskier the investment. If we can assign a number to each obstacle which affects a segment based on severity and add them up, we can get to a rough, yet useful, measure of a segment’s overall risk.
When running this analysis, we looked at all the obstacles that would generally apply to each segment and concluded that disruptive business models were less risky than those operating on the frontier. If we turn to our previous example, Magic Leap faces far more hurdles than the likes of Facebook, Slack, or Dropbox. For Magic Leap to succeed, it needs to have technological breakthroughs, generate new user demand and find consumer use cases—all lofty challenges not faced by Facebook, Slack, or Dropbox. While these three companies also faced their own unique set of problems, such as maintaining data consistency at scale or battling head to head with deep-pocketed incumbents, the problems seem comparatively less insurmountable than those faced by Magic Leap.
As a sanity check, we also ran an analysis of the return profile of both segments to make sure that by focusing on risk, we were not compromising on return. To do this, we categorized the top 100 funded companies of each year between 2008 and 2013 into each of the two categories and then ran a regression analysis on their valuations as of 2020. Surprisingly, we found that not only did the disruptors not compromise on returns, even though we had deduced they were inherently less risky, but being categorized as a disruptor actually had a statistically significant positive effect on valuation. While we understand this analysis is fairly narrow and that there is more to be done to expand the scope to isolate additional variables such as funding year, check size, and industry, we do take this as preliminary evidence in support of our thesis.
This simple idea, that disruptive business models have higher risk-adjusted returns than those operating on the frontier, was the genesis of Outsiders Fund. The fund focuses on early-stage investing and looks to back companies disrupting the status quo in long-standing, incumbent industries. In addition, we look to practice what we preach and become one of the players disrupting the traditional venture capital model in the future. We are already doing things largely unheard of in the venture world and hope to continue on this path to shake things up from the way they have traditionally been done.
If you have any questions or want to learn more, we would love to hear from you. You can reach us at email@example.com or find us at www.outsidersfund.com.
Theodore Seem (MBA ’20) spent just under a year prior to HBS spearheading the artificial intelligence initiatives at Resonance Companies, a start-up reimagining the product lifecycle management of clothing manufacturing. Before Resonance, Teddy worked at Bridgewater Associates, where he held roles as a Product Integration Engineer and then an Investment Engineer on the foreign exchange research team. He completed his undergraduate degree at Amherst College where he played varsity lacrosse and was president of the computer science club.