As people, we experience life at the human-scale. This gives us pretty good intuitions for things that are roughly our size and speed. Looking at mountains, we can get an intuitive sense of their mass because they’re still more or less at our scale. This effect starts to weaken when we look across the ocean. It’s hard, but not impossible, to “feel” the difference between two or three sea miles. At bigger scales, such as outer space, our intuitions hit their limits. If an astronomer tells us a star is a million miles away, or a hundred million miles, we have to take their word for it.
I bring this up because we’ve built our own telescope, of sorts, but instead of looking at stars we look at companies. Instead of an actual telescope, our tools are big data analytics. Through data we do our best to observe, understand and predict company behavior.
Lately we’ve been struck by a jarring realization: almost everywhere we look, our tools are revealing markets to be far bigger and more complex than we would have imagined. They’re no longer human-scale and, as a result, we’ve realized efforts to understand them can’t be human-scale either.
To paint a better picture, let’s use an example. Most people know that telemedicine has been a “hot” market, especially since COVID. You may know some telemed companies, like Amwell, Teladoc, Lemonaid, Goodrx, MeMD, Virtuwell, PlushCare, HealthTap, MDLive or Doctor on Demand.
If you had to guess, how many telemedicine companies would you estimate there are in the world? Take a second. Do you think there might be 20? 50? 100? 300? 500?
All these guesses are reasonable at the human-scale. Try to think about the intuition and logic you just used to make your estimate. You may have started with a base number, on a hunch, that you multiplied by another number, also based on a hunch. Or maybe you just made a one-step guess.
Regardless, now imagine you’ll earn $100 million if you can foresee which of these telemed companies will ultimately win.
Seen this way, suddenly the difference between 20 competitors and 500 is, pragmatically speaking, a big deal. How would you go about finding the future winner? How would your approach change depending on the market’s scale? You’d probably want to know who all the various competitors are, plus their strengths and weaknesses. How would you do that? Assuming you could find and meet them all, or at least a lot of them, you’d probably want to analyze whatever data they can show you, talk to outside experts, get to know all the founders and then make your best educated guess.
We’ve just described a human-scale strategy to solve a human-scale challenge.
The problem is, as of last month our analytics found the actual number of telemed companies in the world to be more than 11,000. Eleven frickin’ thousand!
Suddenly the idea of meeting them all, taking in all the pros and cons, and thinking really hard to spot the winner is untenable. You no longer have a human-scale problem where human-scale solutions make sense.
Making things worse, the more than 11,000 telemed companies aren’t identical. Some are B2C, others are B2B or even B2B2C. Some are meant for doctors, others for patients. Some focus on clinical outcomes while others focus on billing, drugs, clinical trials, healthcare workflows or just about anything else you can think of. The mixture of direct competitors, substitutes, quasi-competitors and adjacent complements are nuanced, dynamic and constantly changing. You’re dealing with both a volume and combinatorial complexity far beyond human-scale.
True market galaxies are daunting.
While not every market is 11,000 competitors deep, almost everywhere we look markets are in the thousands rather than in the tens or low hundreds. We’ve found more than 9,000 industrial IOT companies, 2,000+ brain health device companies, 5,000+ carbon capture companies, 1,000+ portable ultrasound companies, 10,000+ insurance-tech companies, 7,000+ home ducting and sealing companies, 4,000+ cosmetic/skincare app companies, 20,000+ fintech companies, 2,000+ aquaculture companies. Every day we look at more markets, every day we’re awestruck.
I’m sharing this for three main reasons:
- Human-scale efforts to understand and navigate markets ignore the realities of their size and complexity.
As a businessperson, it’s your job to understand the world around you. If you’re in the field of innovation, M&A, venture capital, corporate strategy, marketing, scouting, partnerships, alliances, supply chain or anything else involved with identifying and capturing external value, your efforts are exacerbated by the fact that market complexity is no longer human-scale. Even for the world’s biggest companies or investors, growth strategies that rely on human-scale activities such as personal relationships, industry events, Googling, alliances and trusted referrals are inadequate given today’s market sizes, speeds and complexity.
- To understand big markets, you need big data.
You can build analytics yourself or find a technology partner, but without them you’re shooting blind. Given the scale involved, without a robust data-centric ability to analyze markets, you’re effectively taking a random human-scale walk through the tiny fraction of the market that’s most immediately visible, rather than comprehending your true opportunities and threats. As a result, ad hoc success is best-case-scenario whereas frequent failure, mediocrity and inconsistency are the most likely outcome. You can’t hit what you can’t see.
- Once you’ve seen it, you can’t un-see it.
As we come to terms with the true sizes and complexity of markets, we’ve started to realize how new governing math and dynamics arise at larger scales. Expanded universes involve new physics, as it were.
For example, the more crowded a competitive field grows, the more that luck (vs skill) becomes a factor in who ends up winning.[i]
If you have one company in a market, it’s likely to win so long as it doesn’t trip over its own feet. If you have two companies in a market, now the winner is likely to be the one (of two) with the best strategy and execution. If you have five competitors with relatively good strategies and execution, luck begins to play a bigger role as small advantages can create outsized gains. One of the five companies may have a founder whose cousin helps land a big customer, tipping its adoption over rivals. If you have 2,000 competitors, with tons of subtle, nuanced similarities and differences between them, it’s harder to know exactly which details, or luck, will ultimately create the winning edge. In turn, each individual company has increasingly less ability to control competitive outcomes through superior planning, resources and execution.
So now what? If the market is far bigger, more complex and less control-able than human-scale efforts can reasonably address, do we just close our eyes and throw a dart? Do we go back to pretending the world small and simple? Apologies for the rhetorical questions, of course not.
Instead, as businesspeople, we look for more insight, not less. We start addressing big-scale problems with big-scale solutions. We stop pretending human-scale solutions can fix non-human-scale problems. We adjust our strategies to the realities at hand. It really matters if there are 2,000 competitors in a market rather than the 20 you care to acknowledge. For example, don’t try to enter a market head-to-head against rivals in the belief that your superior planning, resources and execution will defeat all 2,000 of them. Your product may be better, but that fact may not matter in the end due to the systemic odds against you. Any ounce of luck could fall on any of your 2,000 similarly smart, capable, hard-working rivals and kill your business. It won’t be your fault when it happens, but it will be your fault for putting yourself on a low-odds tightrope in the first place. Whatever strategy you choose will need to sail with this current rather than against it.
Our telescope of big data and analytics continues to show us things that rock my foundations and redefine my fundamental understanding of markets.
Sometimes I don’t fully appreciate what I’m seeing. For example, I knew most companies weren’t publicly traded, but it didn’t stop me in my tracks until I realized more than 99% of companies aren’t public – meaning there’s almost no visibility into markets, period. Similarly, when we first started finding huge markets everywhere it seemed like a problem – irritatingly big ecosystems got in the way of trying to isolate winners. Then it dawned on me that this “problem” was a clue about what any viable solution would need to look like. Whatever we developed would need to embrace large-scale market complexity rather than treating it as a nuisance.
I’m not sure what the next lessons are going to be and I don’t want to sound too sentimental, but the word “awe” keeps coming to mind. I’m in awe of the markets we’re finding and the vast scale of human innovation we’ve begun to see. Behind each of those 11,000+ telehealth companies, 5,000 carbon capture companies, or whatever the case may be, is a story of inspired people risking it all to improve the world. It’s tragic that they can’t all win. The true scale of innovation galaxies and their downstream implications are changing what we thought we knew about business. Each time we improve our telescope, we see more stars.
[i] For more on the effects of population size on luck, see Robert H. Frank (2016), Success and Luck: Good Fortune and the Myth of Meritocracy, p. 55. Princeton University Press, Princeton, NJ, or Scott Barry Kauffman (2018), The Role of Luck in Life Success Is Far Greater Than We Realized, Scientific American; Beautiful Minds