Weekly Thoughts

Here are three things that caught our eye this week:

Unicorns at Series A

We recently read a fascinating Medium post that evaluated the characteristics of so-called “unicorns” when they were merely ventures pursuing Series A funding. Posted by Tod Francis, Managing Director at Shasta Ventures, the article summarized findings based on the evaluation of 32 high-value consumer companies — 25 billion dollar companies and 7 “high-flying private companies with billion dollar potential.”

The research — led by Francis and Shasta partner Nikhil Basu Trivedi — evaluated the “funding history, user traction, growth, monetization, network effects, regulatory hurdles, market dynamics and team characteristics” of companies across a multitude of industry sectors, and included well-known names such as Uber, Twitter, Groupon, Square, Lending Club, Eventbrite, Airbnb, Instagram, Pinterest, and Waze.

Francis and Trivedi’s findings were surprising, and somewhat confusing, at least by traditional business standards. Despite being destined for unicorn greatness, when pitching their company to Series A investors, the majority of these companies exhibited the following unremarkable characteristics: easy to dismiss ideas, direct targeting of competitive markets, a desire to reinvent existing consumer behavior, untested founders, and zero monetization strategy. Francis expanded on these findings:

“If this study made anything clear, it is that potentially big ideas are often not obvious at the Series A stage. Some startups that seem poised for greatness go on to crash-and-burn, while others that are slow to get off the ground surprise everyone with their triumph. There is no formula, expectations are often wrong, and each success story is unique and unprecedented… but that doesn’t mean there are not patterns worth paying attention to. Our analysis did reveal one clear, underlying theme: There are large companies to be built by offering new, innovative and superior customer experiences to large markets, regardless of how competitive the sector already is or how successful the founders have been before.”

For us, Shasta’s findings are a great reminder that in today’s environment, regardless of industry — whether it be taxis, hotels, credit card processing, photo sharing, or something else entirely — if your business is not laser focused on delighting your customers, somebody else is likely to enter your market and do so for you. While the majority of today’s unicorns are positioned to capture consumer facing markets, we suspect it’s only a matter of time before the same trend comes to the B2B market as consumer services inevitably create heightened service expectations for the individuals making capital allocation decisions within corporations.

Medium

The Paradox of Unanimity

In our experience, the ultimate goal of group decision making has been to arrive at consensus. Different parties may disagree in the moment, but eventually we want everyone to get on the same page. The approach is the same when we look at information. We have a general preference for clean data sets in which the narrative is clear and outliers are either absent or easily explained away. However, what if those outliers, rather than detracting from the effectiveness of the data, were actually a sign of strength?

That data or group consensus can, in fact, be too good to be true is the conclusion of a new research paper we spent time reading about this week. Published in Proceedings of The Royal Society A by Australian and French researchers, the paper notes that for many types of information, an increase in the unanimity of a result is actually a better indication of some sort of systemic bias than of a strongly valid conclusion. A synopsis of the paper expands on this concept, called the Paradox of Unanimity:

“The researchers demonstrated the paradox in the case of a modern-day police line-up, in which witnesses try to identify the suspect out of a line-up of several people. The researchers showed that, as the group of unanimously agreeing witnesses increases, the chance of them being correct decreases until it is no better than a random guess.

In police line-ups, the systemic error may be any kind of bias, such as how the line-up is presented to the witnesses or a personal bias held by the witnesses themselves. Importantly, the researchers showed that even a tiny bit of bias can have a very large impact on the results overall. Specifically, they show that when only 1% of the line-ups exhibit a bias toward a particular suspect, the probability that the witnesses are correct begins to decrease after only three unanimous identifications. Counterintuitively, if one of the many witnesses were to identify a different suspect, then the probability that the other witnesses were correct would substantially increase.”

The point, according to the researchers, is that most people don’t fully appreciate how statistically unlikely it is to get completely uniform data in a realistic setting. The modern world is complex and messy and the Paradox of Unanimity is a reminder that when we attempt to isolate signal, we shouldn’t view the accompanying noise as useless, but instead as a valuable indicator that our results have real meaning and applicability.

phys, Cornell University Library

A Calorie is Not a Calorie

For those of us that had to make weight for a sport in college, the diet plan was simple. Eat less, work out more, be hungry. More scientifically, the accepted dogma was that if one expended more calories than one consumed, weight loss would naturally occur, which it turns out is the basis for the vast majority of diet advice available today. Almost universally, the calorie is a treated as a unit of account to be deposited or withdrawn from the body in the same way we treat money in a checking account.

However, there is an increasing body of research that suggests the precise focus on calories is misplaced for a variety of procedural, biological, and informational reasons. The first problem is that the techniques for determining caloric content are old and imprecise. According to a recent digg article, the bomb calorimeter, the standard tool for measuring caloric content, was created in the mid-1800s. There were some updates in the 1950s to accommodate new nutritional science, but companies retain the right to choose their method of calorie measurement, which means the same food produced by two different entities could end up on the shelf with two different calorie counts on the label.

The second problem concerns food preparation. Put simply, cooking causes more calories to be released from food, but this isn’t accounted for in most nutritional information. Again from digg:

“If [a dieter] likes his porterhouse steak bloody, for example, he will likely be consuming several hundred calories less than if he has it well-done. Yet the FDA’s methods for creating a nutrition label do not for the most part account for the differences between raw and cooked food, or pureed versus whole, let alone the structure of plant versus animal cells. A steak is a steak, as far as the FDA is concerned.”

Finally, and most importantly, nutritional science is increasingly acknowledging the role individual variation plays in caloric absorption. Genetic factors, and others like an individual’s gut microbe and metabolome (the body’s chemical compound profile) can create significant differences in the way two different people respond to the same food. Again from digg:

“It increasingly seems that there are significant variations in the way each one of us metabolises food, based on the tens of thousands — perhaps millions — of chemicals that make up each of our metabolomes. This, in combination with the individuality of each person’s gut microbiome, could lead to the development of personalized dietary recommendations. Wishart imagines a future where you could hold up your smartphone, snap a picture of a dish, and receive a verdict on how that food will affect you as well as how many calories you’ll extract from it. Your partner might receive completely different information from the same dish.”

While useful in some cases, there is enough variability in individual biology and nutrient measurement quality to suggest that the calorie is an antiquated metric. The reference to individualized dietary recommendations also reinforces a key point, one we highlighted in our N of 1 post previously. While currently unavailable, it’s not hard to imagine a world where the traditional one-size-fits-all approach is discarded in favor of hyper-specialized diet advice. We look forward to following the development of the broad trend, and experimenting with this particular one ourselves.

digg

Have a great week,

Your Chenmark Capital Team