Apart from his updates on how we’re doing in our battle against the virus, there were two pieces I wanted to call out. One interesting, and one insightful.
Why are some countries containing COVID-19 better than others?
Scott evaluates the different theories for why some countries are doing better than others.
Stay at home orders: Don’t seem to have mattered at all.
General government policy: Also seem to matter much less than we’d imagine. We thought Korea and Taiwan are doing well because of their brilliant governments. Japan, on the other hand, denied the problem for a long time so they could still stage the Olympics. Yet, they’re not doing too shabbily.
Clearly, there’s still a lot to discover about this virus.
Lockdowns and taboo tradeoffs.
Second, and I found this far more insightful: He also talks about the importance of framing.
Coronavirus has killed about 100,000 Americans so far. How bad is that compared to other things?
Well, on the one hand, it’s about 15% as many Americans as die from heart attacks each year. If 15% more people died from heart attacks in the US next year, that would suck, but most people wouldn’t care that much. If some scientist has a plan to make heart attacks 15% less deadly, then sure, fund the scientist, but you probably wouldn’t want to shut down the entire US economy to fund them. It would just be a marginally good thing.
On the other hand, it’s also about the same number of Americans who died in the Vietnam War plus the Korean War plus 9/11 plus every school shooting ever. How much effort would you exert to prevent the Vietnam War plus the Korean War plus 9/11 plus every school shooting ever? Probably quite a lot!
Sure, you say, “This is a good example. But I already know the importance of framing, and anchoring.”
Great. Then let’s try another one for size.
Suppose you reopened the economy tomorrow. You tried as hard as you could to put profits above people, squeezed every extra dollar out of the world regardless of human cost. And then you put a 1% tax on all that economic activity, and donated it to effective charity. Would that save more people than a strict lockdown?
If a lockdown costs $5 trillion, then the 1% tax would make $50 billion. That’s about how much the Gates Foundation has spent, and they’ve saved about ten million lives.
Ten million is higher than anyone expects US coronavirus deaths to be, so as far as I can tell this is a good deal.
Large companies are unusually well-equipped to survive, and they’re better able to benefit from monetary interventions—which have been far faster and more effective than fiscal ones.
Meanwhile, small companies, individuals, and municipalities just don’t have the cash reserves or flexibility to react.
There are two ways in which this could play out:
The pessimistic scenario is front-end corporatization: small businesses just evaporate, their real estate is taken over by big companies.
Amazon and Walmart (and Jiomart in India) are the villains of this story.
The optimistic view is back-end corporatization: that software companies and lenders launch an all-out sprint to modernize and recapitalize small businesses, applying the scale advantage of big companies to solving the problems of local ones.
In that happier outcome, small companies hang on for dear life, and come back leaner and ready to fight. Unlike big companies, they won’t necessarily respond to efficiency growth with layoffs.
Shopify, Square, and fintech lenders are the heroes of this story. As are the SMEs that struggle through and survive.
Hypothesis #2: Everyone’s buying ETFs.
The Relentless Bid, Explained posits a different model. It’s an article from 2014, but it’s rung true throughout the crazy bull run of the last decade.
The [stock market] dips have become shallower and the buyers have rushed in more quickly each time. Sell-offs took months to play out during 2011 – think of the April-October peak-to-trough 21% decline for the S&P. In 2012, these bouts of selling ran their course in just a few weeks, in 2013 a few days and, thus far in 2014, just a few hours.
Why is that?
75% of the wealth business in this country [US] is largely driven toward fee-based strategies and accounts.
The vast majority of this snowballing asset base being reported by both wirehouse firms and RIAs is being put to work in a calm and methodical fashion: long-term mutual funds, tax-sensitive separately managed accounts (SMAs) and, of course, index ETFs.
What does this mean for the character of the stock market?
It means that, almost no matter what happens, each week advisors of every stripe have money to put to work and they’re increasingly agnostic about the news of the day. They’re well aware that their clients are living longer than ever – hence, a gently increased proportion of their managed accounts are being allocated toward equities. And so they invariably buy and then buy more.
In short, it means a relentless bid as the torrent of assets comes flowing in every day, week and month of the year.
The lighter volume on the NYSE in recent years also suggests this. Trades are only taking place at the margin and about half of it is ETF creation-redemption related.
Hypothesis #3: Zero Interest Rate Policy (ZIRP for the hip crowd).
Money is always swimming towards yield. All of Capitalism rests on this constant flow – of investments in search of return.
At an individual level, most of us have become accustomed to bank savings accounts effectively returning zero. That wasn’t enough for us though. Our money felt antsy, so it found index funds and other passive funds, to once again, find a bit of yield.
That same, tiny behavioral shift takes place at every level of the risk curve, from your savings account to the trillions of dollars managed by large pension funds.
So all these dollar-organisms all start swimming towards riskier waters. Treasury investors shift to corporate debt. Public equity hedge funds shift to late-stage private equity. Late-stage private equity shifts to mid-stage, mid-stage to early stage. Seed rounds become bigger. Angel investors become a thing. Unicorns, unicorns, and more unicorns. Ashton Kutcher.
Blackrock gets jealous of KKR who gets jealous of a16z who gets jealous of YC. There is just so much money looking to do so many new, riskier things.
Where does this take us? It takes us to bike graveyards.
If there’s any ideology that’s gone from radical idea to article of faith in less than a decade, it’s “Lean Startup”.
When the idea was first proffered by Steve Blank in the early 2000s, it took the world by storm. A simple idea. That generated so much momentum for a startup.
And by 2007, everyone could point to Facebook – or even better, Twitter – as proof that Lean Startup works. Facebook at least scaled with a consistent vision. Harvard → other universities → the world. Twitter was the original clown car that pivoted its way into a gold mine .
I’m a strong believer in starting up lean.
It’s how, in a past life, I iterated my consumer loyalty app to 200K users… with zero marketing dollars. Or how we launched a new lending segment at Indifi, and made it our top segment in 6 months.
So yes, Lean Startup works. And it is an article of faith. The word “lean” is almost redundant today. Of course a Startup has to be Lean. Of course you first build an MVP and test it with customers. Raise serious money only when you find product/market fit.
And then there’s Quibi.
Quibi raised USD 1.75 billion two years before launching its first product.
It then went on to raise another USD 750 million a year after that. Still a relaxed one year before launch.
If you haven’t heard of Quibi, you’d be forgiven to think it was a rocket company to rival SpaceX. But no, Quibi is a mobile content platform (short for Quick Bites), which launched a month ago.
The antithesis of Lean Startup. Will it work? Is this how we’ve got to do it now?
Get Big Fast Baby
The first insight about Lean Startup is that it bootstraps leverage from scratch.
There are only two priorities for a start-up: Winning the market and not running out of cash
Every start-up is in a furious race against time. The start-up must find the product-market fit that leads to a great business and substantially take the market before running out of cash.
That’s where leverage helps. Maximize the ROI on the cash, people, or other resources you bring to the business. Win the market as fast as you can, before you run out of cash.
Now, there are many types of leverage a startup can have.
Proprietary IP / best-in-class technology
Regulatory capture: Microsoft scaled only because of their hilariously one-sided deal with IBM.
The product itself: Instagram has in-built virality. In its early days, Instagram’s core use-case was to touch up photos, and post them on Facebook or Twitter. So, by simply using the product, you were marketing it to your friends.
Network effects: Uber
The revolutionary suggestion of the Lean movement was that the process itself could generate leverage.
That’s how Lean Startup works. Start with a hypothesis: product X solves problem Y for consumer Z. Test it in the most basic way possible, and iterate and refine.
Such a simple process, but generates such strong momentum.
It’s like you try to lift yourself by your shoelaces. You wouldn’t expect it to work, but magic, it does!
Now here’s the thing – the leverage could simply be intuition.
The founder of Quibi is Jeff Katzenberg.
His catalogue of accomplishments is stunning. He oversaw The Lion King (the original), Beauty & the Beast, Aladdin, etc. at Walt Disney Studios. Then he co-founded DreamWorks, and produced Shrek, Kung Fu Panda, Madagascar, and several other massive hits.
Jeff knows more about film-making than 99.9% of the world’s population. Combined.
And the CEO of Quibi is Meg Whitman, ex-CEO of HP and eBay. A tech veteran.
Katzenberg and Whitman have boatloads of intuition, sharpened by decades building large media and tech companies.
“I said to Meg that, until day one, every decision that we make around content will be driven by instinct,” Katzenberg said. “Minutes after we launch, everything will be driven by data.”
And it’s true. They’ve doubled down, extracting every ounce of instinct from their extensive experience.
Everything was so meticulously planned. From the same interview:
A launch date a year in the future (and they were bang on time)
Crystal clear financial model for funding content production
Firm view on pricing tiers for the app
No testing hypotheses with an MVP. Just dive right in. With a few billion dollars in the bank.
What do you do when there’s no leverage?
The second insight about Lean Startup is that it was an answer to a specific question, posed at a specific point in time.
As Steve Blank says, the idea of the Lean startup was built on top of the rubble of the 2000 Dot-Com crash.
Most entrepreneurs today don’t remember the Dot-Com bubble of 1995 or the Dot-Com crash that followed in 2000. As a reminder, the Dot Com bubble was a five-year period from August 1995 (the Netscape IPO) when there was a massive wave of experiments on the then-new internet, in commerce, entertainment, nascent social media, and search.
After the crash, venture capital was scarce to non-existent. (Most of the funds that started in the late part of the boom would be underwater). Angel investment, which was small to start with, disappeared, and most corporate VCs shut down. VCs were no longer insisting that startups spend faster, and “swing for the fences”. In fact, they were screaming at them to dramatically reduce their burn rates. It was a nuclear winter for startup capital.
The Lean movement started during a nuclear winter for venture capital.
When capital is scarce, you have no choice but to go Lean.
When capital is not scarce, it’s worth considering whether other forms of leverage can help you win the market faster.
Well, today, capital is not so scarce. And it’s chasing fewer good deals.
If you can raise the capital, it makes sense to go big, and go fast. Correct mistakes along the way. Figure out product/market fit as you go.
Thin was in, but fat is where it’s at.
It’s tempting to say that Lean will have a resurgence post COVID-19, as the world tips into recession.
But many funders have raised large funds at the top of the market. 10 of the largest 15 VC funds ever raised, have been since 2016.
And tech startups will be especially hot, seeing the resilience of tech in this downturn (NASDAQ is inching back towards its peak!).
So capital is available, searching for “fat” tech startups that can absorb a lot of their capital. The number of seed deals will continue to fall, as they have since 2015.
Let’s talk about Quibi.
OK, we’ve discussed why fat startups like Quibi will be the norm going forward. Now it’s time for the punchline.
I don’t think Quibi will work. Despite all the leverage (or “fat”) it has.
It won’t go bust. But the value of the company will trend towards the value of the content it has bought / licensed. The platform itself will have limited value at best.
Let’s get the obvious first-level problems out of the way.
The battle between every startup and incumbent comes down to whether the startup gets distribution before the incumbent gets innovation.
But the more important reason Quibi will fail is…
What is Quibi’s Seinfeld?
Content follows a Power Law distribution. You can have a million shows, but viewership will concentrate around a few.
I couldn’t find a chart on TV shows, but here’s a chart about movie viewership from Michael Tauberg.
Netflix paid 6 years (!) of its content budget for Seinfeld, because Seinfeld is a “whale”. Like The Office and Friends, this is what people will subscribe to Netflix for. Not for Altered Carbon or Too Hot to Handle or whatever else.
That’s the math of the streaming video industry.
Consumers will pay for 2-3 subscriptions, and you do what you can to be one of them. You need proven hits like Seinfeld, not hit-or-miss new shows.
It’s like the SEO Red Queen Effect – if you aren’t in the first three results on Google, you don’t exist.
Quibi has some solid content. But unless it unearths a Seinfeld or Sopranos or Big Bang Theory in its first try (possible, it’s Katzenberg after all), it’s down for the count.
Well, that’s how the Quibi crumbles.
Related: Teledesic was the original fat startup. Raised two billion dollars for a satellite network… and then didn’t even launch.
As Tren Griffin writes in this short memoir, some investors received many times their original investment. Even though the company never provided service!
Have you ever received an email from a Nigerian prince, going somewhat as follows?
I’ve received a bunch of these over the years.
It’s a standard template. Someone in Nigeria or Congo or Dubai, is dying or is dead. They have several million dollars that they want you to help safekeep. They need you to make a small payment first for some ridiculous reason.
Would you fall for an email like this? Of course not. Come on, this is 2020! No one would fall for it.
One of the questions I like to ask my students is, “If you and I both owned a hamburger stand and we were in a contest to see who would sell the most hamburgers, what advantages would you most like to have on your side?”
Some people say they would like to have the advantage of having superior meat from which to make their hamburgers. Others say they want sesame seed buns. Others mention location. Someone usually wants to be able to offer the lowest prices. And so on.
After my students are finished telling what advantages they would most like to have, I say to them: “OK, I’ll give you every single advantage you asked for. I, myself, only want one advantage and, if you will give it to me, I will whip the pants off of all of you when it comes to selling burgers!”
“What advantage do you want?”, they ask.
“The only advantage I want, ” I reply, “is a STARVING CROWD!”
Material becomes more valuable as it moves through the production process. So, fix any problems at the lowest value stage.
To quote from the book:
All production flows have a basic characteristic: material becomes more valuable as it moves through the process. A boiled egg is more valuable than a raw one… A college graduate to whom we are ready to extend an employment offer is more valuable to us than the college student we meet on campus for the first time.
A common rule we should always try to heed is to detect and fix any problem in a production process at the lowest value stage possible.
Thus, we should find and reject the rotten egg as it’s being delivered from our supplier, rather than permitting the customer to find it. Likewise, if we can decide that we don’t want a college candidate at the time of the campus interview rather than during a plant visit, we save the cost of the trip and the time of both the candidate and the interviewers.
Let’s say you run an apparel factory. If the input cloth you received has quality defects, when would you rather find out? When the shirt is ready, or before the shirt goes into production?
Or you run a SaaS business. If your prospect is going to drop off the funnel next week, wouldn’t you rather find out today? Instead of after inviting them to an online workshop, doing a 1-1 free consulting call, and mailing them three times?
Or let’s say you have your team working on a complicated analysis. If they are making a basic assumption that’s wrong, would you like to find out once the analysis is complete? Or would you rather align at the start, and save a lot of time?
That’s why it’s always a Nigerian prince.
It’s easy to send that first email to thousands of people.
The next steps are more labor-intensive. A person has to talk to the target, persuade them to wire money, and cajole them to jump through other assorted hoops.
Labor = costly.
Wouldn’t it be nice if there was a way to spend time only on the most qualified customers (i.e., the most gullible targets)?
Far-fetched tales of West African riches strike most as comical. Our analysis suggests that is an advantage to the attacker, not a disadvantage. Since his attack has a low density of victims the Nigerian scammer has an over-riding need to reduce false positives. By sending an email that repels all but the most gullible the scammer gets the most promising marks to self-select, and tilts the true to false positive ratio in his favor.
That’s why phishing emails have spelling mistakes.
To self-qualify the funnel.
It’s not that the phishers struggle with English. That would be funny if it were true. Masterful confidence tricksters, but struggle to put together rudimentary sentences.
No, they speak English fine. It’s just that they don’t want people with high attention to detail to click on the link. If you notice such minutiae as spelling errors, then you’d notice other more suspicious details later and stop responding anyway.
They want only gullible prospects, with the least attention to detail.
They want to have a high percentage of such people pass through the next steps of the funnel. Share their passwords in a mindless fog. Click on executable links as an afterthought. Download Trojans in utter oblivion.
Fascinating. So is there a lesson in all this?
Yes, three in fact.
Lesson 1 – qualify your funnel as early as you can. And if possible, create a way for your audience to self-qualify. Don’t do sales calls with every visitor who stumbles across your website and shares their email. Instead, make them do the work of qualifying themselves. Have them join a webinar or download two white papers (both have zero marginal cost to you), before you do the hard pitch.
Lesson 2: Catch errors early. If your team is working on a complex analysis, first agree on the basic assumptions and logical flow. If it’s an investor presentation for next week, agree on the key messages and storyline today.
Lesson 3: Don’t click on emails from Nigerian princes.
Many pundits call COVID-19 a Black Swan event. And I have done the same. In countless conversations with clients, suppliers and others, ruminating wisely, “yes, it’s a black swan event. All bets are off.”
But is it really?
Black swans are supposed to take us by complete and utter surprise. Unpredictable before the fact, inevitable after.
But, a lot of people have predicted this pandemic. Not only predicted it, but also highlighted how unprepared we are. Among the famous examples, here’s Bill Gates, warning of a pandemic that could kill 33 million. And the resemblance of the current situation to the 2011 movie Contagion is eerie.
So, no – the epidemic was foretold.
What wasn’t foretold though, was the immediate and devastating economic armageddon. That was the Black Swan.
That spike at the far right of the graph – from 300K jobless claims to 3.3 million? That was the Black Swan.
The video in the tweet below illustrates this vividly.
COVID-19 was foretold. But the economic impact wasn’t.
Experts (and movies) predicted, sometimes in frightening detail, how medical capacity would run out. How we’d wait, interminably, for a vaccine.
But they didn’t think – what will happen if everyone has to sit at home for two months? What will happen if every business closes, all at once?
Like all Black Swans, seems blindingly obvious after the fact. Hindsight, especially in the case of Black Swans, is 20:20.
Politics is about getting and keeping political power, not about general welfare. Leaders do what they can do to come to power, and stay in power.
That’s what happened.
In the early days of the pandemic, COVID-19 was an unknown quantity. Many hoped prayed fervently that it was “just another flu”. On the other hand, every head of state knew what a lockdown meant. Unemployment.
And in any democracy, unemployment means one thing for sure – the leader in power crashes out in the next election.
Like Upton Sinclair said:
“It is difficult to get a man to understand something when his salary depends upon him not understanding it.”
Digital advertising is one of the biggest new industries of the Internet era. In 2018, USD 273Bn was spent on digital ads globally.
What if I told you it was all fake?
Or more accurately, what if this article told you it was all fake?
The article has several examples of real-life experiments – e.g., when eBay stopped all its ads on Google for 3 months, the drop in online sales was 0%. Yes, you read that right – zero, nada.
But how? Aren’t people clicking on those ads? How can the impact of removal be zero?
Two factors drive this surprising outcome.
Do you remember the last time you searched for an app on Google? For example, I searched for “Spotify” last week. The first link was an ad, for Spotify.com. So I just clicked on that. And an ad-click counter somewhere in Google went up. This is called Selection Bias. Of the people who clicked on any given ad, you don’t know how many were looking for that item anyway.
Search engine algorithms are trained to show a given ad to people who are most likely to click on it. This Algorithmic Bias magnifies the selection bias. As the algorithm gets better (and Google’s algorithm is pretty mature now), increasingly, the people who are shown an Amazon ad are the ones who were planning to go to Amazon anyway.
In fact, some skeptics believe that ads don’t work at all. That no one is convinced to change behavior based on ads. Could it be true?
Well, do you remember the last time you clicked on an ad while not looking for that exact item? Me neither. (except for that banner selling N95 masks last week, but it was sadly out of stock).
But surely, you say – if digital ads didn’t work, why are marketers still spending hundreds of millions on them?
As the article says, quoting Steve Tadelis, “marketers actually believe that their marketing works, even if it doesn’t.” Good old Cognitive dissonance.
Yes, cognitive dissonance does play a role. But I think there’s a second element too. You know the saying, “what gets measured gets managed“. Google and Facebook report clicks and impressions, not actual incremental purchases. That’s what is available, so that’s what marketers track and optimize. They don’t track incremental purchases, because there’s no way to monitor that.
A powerful book, that changed how I thought about entrepreneurship. I’ve written about the importance of the Power Law before, and what it means for what you choose to do.
What do you know that others don’t?
What valuable company is no one building?
Creating value is not hard; capturing enough of that value is harder
In 2012, when the average airfare each way was $178, the airlines made only 37 cents per passenger trip. Compare them to Google, which creates less value but captures far more. Google brought in $50 billion in 2012 (versus $160 billion for the airlines), but it kept 21% of those revenues as profits—more than 100 times the airline industry’s profit margin that year.
Progress can take one of two forms
Horizontal or extensive progress means copying things that work—going from 1 to n. Horizontal progress is easy to imagine because we already know what it looks like
Vertical or intensive progress means doing new things—going from 0 to 1. Vertical progress is harder to imagine because it requires doing something nobody else has ever done. If you take one typewriter and build 100, you have made horizontal progress. If you have a typewriter and build a word processor, you have made vertical progress.
If you focus on near-term growth above all else, you miss the most important question you should be asking: will this business still be around a decade from now?
In March 2001, PayPal had yet to make a profit but our revenues were growing 100% year-over-year. When I projected our future cash flows, I found that 75% of the company’s present value would come from profits generated in 2011 and beyond—hard to believe for a company that had been in business for only 27 months. But even that turned out to be an underestimation. Today, PayPal continues to grow at about 15% annually, and the discount rate is lower than a decade ago. It now appears that most of the company’s value will come from 2020 and beyond.
LinkedIn is another good example of a company whose value exists in the far future. As of early 2014, its market capitalization was $24.5 billion—very high for a company with less than $1 billion in revenue and only $21.6 million in net income for 2012. You might look at these numbers and conclude that investors have gone insane. But this valuation makes sense when you consider LinkedIn’s projected future cash flows.
The overwhelming importance of future profits is counterintuitive even in Silicon Valley. For a company to be valuable it must grow and endure, but many entrepreneurs focus only on short-term growth.
Thoughts on Monopolies
Monopolies vs. Perfect Competition
Monopoly is the condition of every successful business
Under perfect competition, in the long run no company makes an economic profit. Capitalism and competition are opposites. Capitalism is premised on the accumulation of capital, but under perfect competition all profits get competed away.
If you want to capture value, don’t build an undifferentiated commodity business.
Non-monopolists exaggerate their distinction by defining their market as the intersection of various smaller markets; monopolists, by contrast, disguise their monopoly by framing their market as the union of several large markets
In business, money is either an important thing or it is everything. Monopolists can afford to think about things other than making money; non-monopolists can’t.
If the tendency of monopoly businesses were to hold back progress, they would be dangerous and we’d be right to oppose them. But the history of progress is a history of better monopoly businesses replacing incumbents.
A monopoly like Google is different. Since it doesn’t have to worry about competing with anyone, it has wider latitude to care about its workers, its products, and its impact on the wider world. Google’s motto—“Don’t be evil”—is in part a branding ploy, but it’s also characteristic of a kind of business that’s successful enough to take ethics seriously without jeopardizing its own existence.
Winning is better than losing, but everybody loses when the war isn’t one worth fighting.
Just as war cost the Montagues and Capulets their children, it cost Microsoft and Google their dominance: Apple came along and overtook them all. In January 2013, Apple’s market capitalization was $500 billion, while Google and Microsoft combined were worth $467 billion. Just three years before, Microsoft and Google were each more valuable than Apple. War is costly business
When Pets.com folded after the dot-com crash, $300 million of investment capital disappeared with it.
Sometimes you do have to fight. Where that’s true, you should fight and win. There is no middle ground: either don’t throw any punches, or strike hard and end it quickly.
Monopolies and Moats
Every Monopoly is unique, but they usually share some combination of the following characteristics: proprietary technology, network effects, economies of scale, and branding.
Proprietary Tech – As a good rule of thumb, proprietary technology must be at least 10 times better than its closest substitute in some important dimension to lead to a real monopolistic advantage. The clearest way to make a 10x improvement is to invent something completely new.
Network effects: Network effects can be powerful, but you’ll never reap them unless your product is valuable to its very first users when the network is necessarily small.
Network effects businesses must start with especially small markets. Facebook started with just Harvard students — Mark Zuckerberg’s first product was designed to get all his classmates signed up, not to attract all people of Earth.
This is why successful network businesses rarely get started by MBA types: the initial markets are so small that they often don’t even appear to be business opportunities at all.
Economies of scale: A good startup should have the potential for great scale built into its first design.
Strong brand: other monopolistic advantages are less obvious than Apple’s sparkling brand, but they are the fundamentals that let the branding effectively reinforce Apple’s monopoly.
Beginning with brand rather than substance is dangerous.
Building a Monopoly as a Startup
Every startup is small at the start. Every Monopoly dominates a large share of its market. Therefore, every startup should start with a very small market. Always err on the side of starting too small. The reason is simple: it’s easier to dominate a small market than a large one.
The perfect target market for a startup is a small group of particular people concentrated together and served by few or no competitors. Any big market is a bad choice, and a big market already served by competing companies is even worse.
It’s always a red flag when entrepreneurs talk about getting 1% of a $100 billion market. In practice, a large market will either lack a good starting point or it will be open to competition, so it’s hard to ever reach that 1%. And even if you do succeed in gaining a small foothold, you’ll have to be satisfied with keeping the lights on: cutthroat competition means your profits will be zero.
Sequencing markets correctly is underrated, and it takes discipline to expand gradually.
The most successful companies make the core progression—to first dominate a specific niche and then scale to adjacent markets—a part of their founding narrative (related to Crossing the Chasm – I’ll add book notes soon)
As you craft a plan to expand to adjacent markets, don’t disrupt: avoid competition as much as possible.
Control over distribution
Superior sales and distribution by itself can create a Monopoly, even with no product differentiation. The converse is not true. No matter how strong your product—even if it easily fits into already established habits and anybody who tries it likes it immediately—you must still support it with a strong distribution plan.
In between personal sales (salespeople obviously required) and traditional advertising (no salespeople required) there is a dead zone – the distribution doldrums.
Suppose you create a software service that helps convenience store owners track their inventory and manage ordering. For a product priced around $1,000, there might be no good distribution channel to reach the small businesses that might buy it.
Even if you have a clear value proposition, how do you get people to hear it? Advertising would either be too broad (there’s no TV channel that only convenience store owners watch) or too inefficient (on its own, an ad in Convenience Store News probably won’t convince any owner to part with $1,000 a year).
The product needs a personal sales effort, but at that price point, you simply don’t have the resources to send an actual person to talk to every prospective customer.
This is why so many small and medium-sized businesses don’t use tools that bigger firms take for granted. It’s not that small business proprietors are unusually backward or that good tools don’t exist: distribution is the hidden bottleneck.
Advertising can work for startups, too, but only when your customer acquisition costs and customer lifetime value make every other distribution channel uneconomical.
Whoever is first to dominate the most important segment of a market with viral potential will be the last mover in the whole market.
If you can get just one distribution channel to work, you have a great business. If you try for several but don’t nail one, you’re finished.
Power Laws (the most interesting part of the book)
Never underestimate Exponential Growth, Compounding, and the Power Law distribution. The Power Law distribution—so named because exponential equations describe severely unequal distributions—is the law of the universe. It defines our surroundings so completely that we usually don’t even see it.
Venture Investing returns are Power Law distributions
The error lies in expecting that venture returns will be normally distributed: that is, bad companies will fail, mediocre ones will stay flat, and good ones will return 2x or even 4x. Assuming this bland pattern, investors assemble a diversified portfolio and hope that winners counterbalance losers. But this “spray and pray” approach usually produces an entire portfolio of flops, with no hits at all. This is because venture returns don’t follow a normal distribution overall.
Our results at Founders Fund illustrate this skewed pattern: Facebook, the best investment in our 2005 fund, returned more than all the others combined.
Palantir, the second-best investment, is set to return more than the sum of every other investment aside from Facebook.
This highly uneven pattern is not unusual: we see it in all our other funds as well.
The biggest secret in venture capital is that the best investment in a successful fund equals or outperforms the entire rest of the fund combined.
This suggests two very strange rules for VCs
First, only invest in companies that have the potential to return the value of the entire fund. This is a scary rule, because it eliminates the vast majority of possible investments.
Second: because rule number one is so restrictive, there can’t be any other rules.
Consider what happens when you break the first rule. a16z invested $250,000 in Instagram in 2010. When Facebook bought Instagram just two years later for $1 billion, a16z netted $78 million—a 312x return in less than two years. That’s a phenomenal return, befitting the firm’s reputation as one of the Valley’s best. But in a weird way it’s not nearly enough, because it has a $1.5 billion fund: if they only wrote $250,000 checks, they would need to find 19 Instagrams just to break even.
This is why investors typically put a lot more money into any company worth funding; investors who understand power laws invest in as few companies as possible
The power law means that differences between companies will dwarf the differences in roles inside companies. You could have 100% of the equity if you fully fund your own venture, but if it fails you’ll have 100% of nothing. Owning just 0.01% of Google, by contrast, is incredibly valuable (more than $35 million as of this writing).
What you work on matters far more than doing it well
Every university believes in “excellence,” and hundred-page course catalogs arranged alphabetically according to arbitrary departments of knowledge seem designed to reassure you that “it doesn’t matter what you do, as long as you do it well.” That is completely false. It does matter what you do. You should focus relentlessly on something you’re good at doing, but before that you must think hard about whether it will be valuable in the future.
If you do start your own company, you must remember the power law to operate it well
The most important things are singular: One market will probably be better than all others
One distribution strategy usually dominates all others, too
Time and decision-making themselves follow a power law, and some moments matter far more than others
in a power law world, you can’t afford not to think hard about where your actions will fall on the curve.
Seven questions every business must answer
The Engineering Question: Can you create breakthrough technology instead of incremental improvements?
The Timing Question: Is now the right time to start your particular business?
The Monopoly Question: Are you starting with a big share of a small market?
The People Question: Do you have the right team?
The Distribution Question: Do you have a way to not just create but deliver your product?
The Durability Question: Will your market position be defensible 10 and 20 years into the future?
The “secret” Question: Have you identified a unique opportunity that others don’t see?
The book also illustrates how very few cleantech businesses have survived, using these seven questions.
[Note: I shared this mental model with my email subscribers on Feb 12, 2017. If you want to receive a new mental model every week, join the club.]
What it is:
Margin of safety is a critical principle in engineering.
Let’s say we’re building a bridge, and the maximum weight of vehicles we expect on the bridge is 5,000 tons. So do we build it to withstand 5,000 tons? 6,000 tons?
No. We build it to withstand 20,000 tons. That’s the margin of safety.
When you save “for a rainy day”, that’s what you’re doing. Building a contingency fund. A margin of safety for your lifestyle, should you lose your job.
As Seth Godin explains in Breakpoints: when laying a sidewalk, workmen don’t put long slabs of concrete in place. Instead, they keep small gaps every few feet. That’s a margin of safety too – in case the concrete breaks or expands in unpredictable ways.
[Tweet “”You build a bridge that 30,000-pound trucks can go across and then drive 10,000-pound trucks on it.”]
Examples from business:
Investing: Margin of safety is a core tenet of value investing, popularized by Benjamin Graham and David Dodd. As Warren Buffett, a long-time protege of Ben Graham, says: “If we calculate the value of a stock to be only slightly higher than the price, we’re not interested.”
Startup fundraising: You don’t raise just enough capital to get to your next round of funding. If you want to raise your next round at $1Mn in revenue, raise enough now to get to $2Mn. Better still, raise enough to become profitable. Similarly, don’t start looking for investors when you have one month of cash in the bank. Start when you have six.
Capacity planning: Most services organizations keep a bench (idle employees) of up to 20% of their total headcount. So that they can service any sudden requirements. Same goes for manufacturing – as they say, if you have 20% spare capacity, you have no spare capacity.
Project planning: When drawing out a project plan, always put in a few buffer days / weeks.
[Aside: we almost never do this. There’s even a name for it. The planning fallacy – how we believe that this time, unlike all previous times, we’ll finish the project on time.]
[Tweet “”If you have 20% spare capacity, you have no spare capacity.” #marginofsafety #mentalmodel”]
Rules to follow:
Always build a margin of safety. Whatever you’re doing, estimate how long, how much money, etc. it’ll take. Then add a buffer.
Expect your plans to go awry. Do a premortem. And then build redundancy / backups.
As Seth Godin says in the article above, there’s no doubt the ground will shift. The question is: when it does, will you be ready?
[Note: I shared this mental model with my email subscribers on Feb 5, 2017. If you want to receive a new mental model every week, join the club.]
Why is it so hard to persuade people with facts?
You feel like their argument stands on three key pillars, and you’ve destroyed all of them with hard data. Still, it remains standing. In fact, they’ve dug their heels in even more!
Why does being corrected trigger feelings of anger and dismay? Short answer: Cognitive dissonance.
What it is:
Why does cognitive dissonance happen? As this article says, there are two main reasons:
Our brains don’t store facts as standalone pieces of information. We remember data points as a network of interrelated “facts”. So, when one of them is called into question, it feels like the entire network of beliefs is threatened. Loss aversion kicks in.
When an argument threatens your world view, self concept, or your very identity, facts can even backfire. You become more convinced of your erroneous stand, when you hear you’re wrong.
Strange things happen when you think your identity is attacked.
[Note: I shared this mental model with my email subscribers on Feb 5, 2017. If you want to receive a new mental model every week, join the club.]
Or as more ancient stoics said, “Premeditatio malorum”. Or “premeditation of evils”.
What it is:
We’ve all heard of the postmortem in business. When something goes wrong, all the decision-makers get together to diagnose what happened. And learn how to prevent it from happening again.
In theory, at least.
What really happens though, is an advertisement for hindsight bias. Everyone suddenly remembers how they “always knew it wouldn’t work”.
As Amos Tversky said, “The writing may have been on the wall all along. The question is: was the ink invisible?”
[Tweet “”The writing may have been on the wall all along. But was the ink invisible?” #hindsightbias”]
A premortem asks the same question as a postmortem, but before you embark on your endeavor. “It’s two years from today, and our plan has been implemented. But it’s been a disaster. What went wrong?”
Explicitly going through such a thought experiment can help avoid the overconfidence and groupthink that team decisions can suffer from. We all love “playing the devil’s advocate” – here’s an executive license (and order) to do so!
[Tweet “We all love “playing the devil’s advocate” – a #premortem is a clear license to do so! #mentalmodel”]
Examples of premortems / thought experiments:
Here are a few examples of thought experiments to try.
1 Year from Now:
We haven’t hit product-market fit yet. We took too long to launch our initial product. What features could we have left out?
Half our customers didn’t renew their contracts. Why? What went wrong?
3 Years from Now:
Our startup has just shut down. We just couldn’t hit a growth trajectory. What are the reasons for this failure?
When you’re making a big decision, make sure you think about what could go wrong. And protect against it. Don’t only think about what happens when the plan works – you’ll fall prey to the focusing illusion.
Every few months, revisit and repeat the premortem. Have you covered for the main risks? Have any new risks opened up?