Curated Insights 2019.06.28

Facebook, Libra, and the long game

And this is when this bet would pay off for Facebook (and the second point I missed in my earlier analysis): the implication that digital currencies will do for money what the Internet did for information is that the very long-term trend will be towards centralization around Aggregators. When there is no friction, control shifts from gatekeepers controlling supply to Aggregators controlling demand. To that end, by pioneering Libra, building what will almost certainly be the first wallet for the currency, and bringing to bear its unmatched network for facilitating payments, Facebook is betting it will offer the best experience for digital currency flows, giving it power not by controlling Libra but rather by controlling the most users of Libra.

Forget the mall, shoppers are buying Gucci at airports

For the first time last year, Estée Lauder Co. generated more revenue at airports globally than at U.S. department stores, which for decades had been beauty companies’ biggest sales driver … “Very few channels have almost guaranteed traffic,” said Olivier Bottrie, who heads Estée Lauder’s global travel-retail business. “When a department store goes away, it’s not a major catastrophe. But if a major airport went away, it would be a major catastrophe.”

Employees who stay in companies longer than two years get paid 50% less

Staying employed at the same company for over two years on average is going to make you earn less over your lifetime by about 50% or more …

In 2014, the average employee is going to earn less than a 1% raise and there is very little that we can do to change management’s decision. But, we can decide whether we want to stay at a company that is going to give us a raise for less than 1%. The average raise an employee receives for leaving is between a 10% to 20% increase in salary.

Curated Insights 2019.01.04

The customer acquisition pricing parade

“One spectator, determined to get a better view, stands on their tiptoes. It works well initially until everyone else does the same. Then, the taxing effort of standing on your toes becomes table stakes to be able to see anything at all. Now, not only is any advantage squandered, but we’re all worse off than we were when we first started.”

“Marketing is increasingly cheap. Trust is increasingly expensive. Attracting eyeballs no longer sets you apart. Building trust among those who have their eyes on you, does. Getting people’s attention is no longer a skill. Keeping people’s attention is.”

To decrease spending and increase profitability, the holding companies of tomorrow will shift their attention from controlling supply to controlling demand — from building around industries to building around audiences.  

Re-marketing to an existing customer is significantly cheaper than trying to persuade a first time customer to buy your product — sometimes nearly 90% cheaper.

Companies who cater to the needs of passionate customers will benefit from lowered customer acquisition costs and higher lifetime value (LTV), reduced churn and increased loyalty. Once a paying customer is acquired, companies can cross-sell and up-sell them into different products, categories, and even brands. The fight to find that customer will be much easier leading to an increase in transaction volume. As they reduce friction in the payment process and increase customer loyalty, they’ll accrue data behind customer cohorts leading to a customer-centric experience.

Companies who cater to their customers and develop direct relationships with them, will own the future.

Working more magic at Disney

Walt Disney has in a sense become more Disney-like in how it earns its profits. After 20 years of being dominated by television, especially cable, the company is returning to its roots in films and theme parks. Seven years ago, for each $1 in operating profit that Disney made from its parks and studios, it generated $3 in TV. During the fiscal year ended September, parks and studios retook the lead.

The coming streaming platform will be reported to Wall Street as a separate Netflix-like division within Disney. Investors will see how much cash the unit is paying for content. New Disney, so to speak, will pay this money to Old Disney. “What I’ve discovered is, businesses in a traditional space that want to innovate and spend money to do so, they park the cost of innovation in their traditional businesses,” Iger says. “Those businesses all kind of suffer from the cost of that innovation, because it’s not typically monetized right away. You can get impatient to the point of losing interest and abandoning innovation, because you don’t have the patience to wait for it to really pay off.”

For decades, Disney was largely a moviemaker with theme parks, although television has long been part of the mix; The Mickey Mouse Club, which began on ABC in 1955, helped finance Disneyland, and the Disney Channel has been a cable mainstay since the 1980s. But in 1995, Disney surprised investors with a $19 billion acquisition of Capital Cities/ABC, gaining a prosperous TV network and a thriving ESPN. As cable spread service across the nation, and TV producers learned how to extract higher fees from cable operators for their content, the small screen became Disney’s big earner.

Iger planted the roots of Disney’s growth spurt in its traditional businesses when he rolled up major story-telling outfits that weren’t for sale. He did that by visiting their bosses one-on-one: Steve Jobs, culminating in the $7.4 billion purchase of Pixar in 2006; Isaac Perlmutter, for a $4 billion acquisition of Marvel Entertainment in 2009; and George Lucas, in a $4 billion deal for Lucasfilm in 2012. What has followed has been a film boom for the ages.

This year, Disney will again become the only studio in history to reap $7 billion in worldwide box office receipts: $4 billion internationally and $3 billion in the U.S. It also did so in 2016. And Disney makes eight to 10 films a year; some big studios make two dozen.

Box office results relate to return on invested capital the way dunking a basketball relates to winning a game: The former gets the crowd’s attention, but people with stakes care mostly about the latter. The broader film industry operates with a single-digit return, Iger says. Yet there are years when Disney’s film returns top 30%. As a result, studio operating income has multiplied more than fourfold since 2011, to nearly $3 billion during the fiscal year ended in September.

Does AI make strong tech companies stronger?

First, though you need a lot of data for machine learning, the data you use is very specific to the problem that you’re trying to solve. GE has lots of telemetry data from gas turbines, Google has lots of search data, and Amex has lots of credit card fraud data. You can’t use the turbine data as examples to spot fraudulent transactions, and you can’t use web searches to spot gas turbines that are about to fail. That is, ML is a generalizable technology – you can use it for fraud detection or face recognition – but applications that you build with it are not generalized. Each thing you build can only do one thing. This is much the same as all previous waves of automation: just as a washing machine can only wash clothes and not wash dishes or cook a meal, and a chess program cannot do your taxes, a machine learning translation system cannot recognise cats. Both the applications you build and the data sets you need are very specific to the task that you’re trying to solve (though again, this is a moving target and there is research to try to make learning more transferable across different data sets).

So: as an industrial company, do you keep your own data and build the ML systems to analyse it (or pay a contractor do do this for you)? Do you buy a finished product from a vendor that’s already trained on other people’s data? Do you co-mingle your data into that, or into the training derived from it? Does the vendor even need your data or do they already have enough? The answer will be different in different parts of your business, in different industries and for different use cases.

This takes me to a metaphor I’ve used elsewhere – we should compare machine learning to SQL. It’s an important building block that allowed new and important things, and will be part of everything. If you don’t use it and your competitors do, you will fall behind. Some people will create entirely new companies with this – part of Wal-Mart’s success came from using databases to manage inventory and logistics more efficiently. But today, if you started a retailer and said “…and we’re going to use databases”, that would not make you different or interesting – SQL became part of everything and then disappeared. The same will happen with machine learning.


One giant step for a chess-playing machine

Most unnerving was that AlphaZero seemed to express insight. It played like no computer ever has, intuitively and beautifully, with a romantic, attacking style. It played gambits and took risks. In some games it paralyzed Stockfish and toyed with it. While conducting its attack in Game 10, AlphaZero retreated its queen back into the corner of the board on its own side, far from Stockfish’s king, not normally where an attacking queen should be placed.

Yet this peculiar retreat was venomous: No matter how Stockfish replied, it was doomed. It was almost as if AlphaZero was waiting for Stockfish to realize, after billions of brutish calculations, how hopeless its position truly was, so that the beast could relax and expire peacefully, like a vanquished bull before a matador. Grandmasters had never seen anything like it. AlphaZero had the finesse of a virtuoso and the power of a machine. It was humankind’s first glimpse of an awesome new kind of intelligence.

Tellingly, AlphaZero won by thinking smarter, not faster; it examined only 60 thousand positions a second, compared to 60 million for Stockfish. It was wiser, knowing what to think about and what to ignore. By discovering the principles of chess on its own, AlphaZero developed a style of play that “reflects the truth” about the game rather than “the priorities and prejudices of programmers,” Mr. Kasparov wrote in a commentary accompanying the Science article.

What is frustrating about machine learning, however, is that the algorithms can’t articulate what they’re thinking. We don’t know why they work, so we don’t know if they can be trusted. AlphaZero gives every appearance of having discovered some important principles about chess, but it can’t share that understanding with us. Not yet, at least. As human beings, we want more than answers. We want insight. This is going to be a source of tension in our interactions with computers from now on.

Maybe eventually our lack of insight would no longer bother us. After all, AlphaInfinity could cure all our diseases, solve all our scientific problems and make all our other intellectual trains run on time. We did pretty well without much insight for the first 300,000 years or so of our existence as Homo sapiens. And we’ll have no shortage of memory: we will recall with pride the golden era of human insight, this glorious interlude, a few thousand years long, between our uncomprehending past and our incomprehensible future.


Evaluating early stage startups — The three metrics that matter

Defining “fast growth” depends on stage, but for early (Seed or Series A), growing 100% YoY is typically pretty solid. Paul Graham (PG) famously looks for 5–7% weekly growth for companies in Y Combinator, and his rationale is pretty simple: “a company that grows at 1% a week will grow 1.7x a year, whereas a company that grows at 5% a week will grow 12.6x.” When you consider the compounding effects of this growth, it means a company starting with $1,000 in revenue and growing at 1% will be at $7,900 per month four years later, whereas the company growing 5% per week will be bringing in more than $25 million per month.


The founder’s guide to understanding investors

When we dig deeper, the degree to which early-stage investing is a grand slam business is shocking. First, amongst early stage investors, the returns are disproportionately distributed. The Kauffman Foundation, an investor in many VC funds, found the top 20 VC firms (~3% of VC firms), generate 95% of all venture returns. Second, outside of the top 20 VC firms, most lose money! A study found the top 29 VC firms made a profit of $64B on $21B invested, while the rest of the VC universe lost $75B on $160B invested.

As early-stage investing operates on a power law, Paul Graham (founder of Y Combinator) mentions “You [as an investor] have to ignore the elephant in front of you, the likelihood they’ll [the startup] succeed, and focus instead on the separate and almost invisibly intangible question of whether they’ll succeed really big.” He highlights there are 10,000x variations (!) in startup investing returns, meaning top investors must have the mindset of willing to strike out in order to hit grand slams.

There needs to be room for your startup to capture a large share of this market. Elad Gil (early investor in Airbnb, Coinbase, Gusto, Instacart, Stripe), explains this means i) the market is structurally set up to support multiple winners, but ii) if the market only supports one winner and customers are currently not served well – there is an opportunity to dominate the market.

At the Series A stage, investors are mainly looking to see if PMF is achieved. This evaluation can be qualitative – Marc Andreessen (co-founder of Netscape and Andreessen Horowitz, an early investor in Facebook, Twitter, Wealthfront, Slack) notes, on the inside, “you can always feel product/market fit when it’s happening. The customers are buying the product just as fast as you can make it — or usage is growing just as fast as you can add more servers. Money from customers is piling up in your company checking account. You’re hiring sales and customer support staff as fast as you can. Reporters are calling…”

When investors are evaluating for PMF, Rachleff notes that the best test is to see if the product is growing exponentially with no marketing, meaning the product is so good it grows through word of mouth. Top investors often don’t want to see marketing spend because it shows care for vanity metrics (things that don’t matter) rather than building an amazing product that people engage with (which does matter).

Not all buzzwords will fulfill their potential and result in a disruptive technology shift though. As a founder, you can reduce this risk by avoid starting a startup on that shift until the technology adoption is growing quickly and reaches a multi-hour per day level of usage. Sam Altman expands, “It’s very hard to differentiate between fake trends and real trends…If you think hard and you really pay attention, sometimes you can. The metric I use to differentiate between a real trend and a fake trend is similar to loving a product. It’s when there is a new platform that people are using many hours every day.”

To believe the startup can fulfill grand slam potential, investors want to see the startup has verified their assumptions on how users find the product in a repeatable and scalable manner. This is also called a go-to-market strategy (GTM).

Bill Gurley (major early investor in Uber, Stitch Fix, Zillow, etc.) called a unique GTM the most under-appreciated part about startups. It’s not about who did it first, but who did it right. Gurley looks to see if the startup has two things: (1) An interesting way to get into the market; (2) A way to establish themselves once in the market. The word ‘unique’ is important here. Replicating existing GTM strategies is often too costly because incumbents have already dried up the channel(s) to market and sell to customers. As a founder, you need to find a unique GTM that is repeatable and scalable. The good news here is that if you succeed, you’ll be able to keep out competitors by saturating the new channels.

Andy Rachleff has a second perspective on how startups can avoid competition. With his adaptation to Clayton Christensen’s (Harvard Business School Professor) disruption theory, startups can compete with reduced competition in either two ways. They can compete via new-market disruption – targeting a new set of users and competing on different characteristics (e.g. instead of price, focus on experience) than competitors, or they can compete via low-end disruption – targeting the same set of users as incumbents, but offering a greatly reduced product at a lower price point.

Along with the above quote, Bill Gurley tests if executives at the startup have a notion of insane curiosity – constantly learning new ways to win. To evaluate this, he asks questions on what information (e.g. books, podcasts) executives learn from, how they engage with it, and then probes if they are trying to use that information to majorly improve themselves or their business.

Curious folks tinker. Obsessively curious folks solve the hardest problems that require endless tinkering. If you are obsessively curious and fail with your original plan, odds are you will use your learnings and pivot into a big market that loves their product.

If a founder is obsessively curious, they can navigate the idea maze. By running a founder through the idea maze, investors evaluate if the founder understands all permutations of their idea, why their plan is superior to all other competitors, and which turns to lead to treasure versus which ones lead to certain death. It’s important for a founder to thoroughly know their idea maze, it can save years by not going down the wrong path, in addition to convincing investors you know can be a grand slam.

Rating citizens – can China’s social credit system fix its trust deficit?

In some Chinese cities, if you have wilfully defaulted on paying your debts, callers to your mobile phone will hear this message instead of the usual ringback tone: “This is a friendly reminder from the people’s court of XX city. The person you have just called has been declared a trust-breaker subject to enforcement by the court …”

Given that 80 per cent of respondents in a 2018 opinion poll conducted across China have approved of the social credit system, it seems that most Chinese, for now, do not consider the drastic surveillance scheme a violation of their privacy. Instead, most see the merit of the system in the perks they may enjoy and its potential in fostering trustworthiness in society.

However, the feasibility of this is highly questionable since the government is simultaneously the enforcer, the appraiser and the appraisee. For instance, many local governments in China have often failed to repay debt ranging from a few thousand to tens of million yuan, including loans, payment to contractors, and compensation for seized land. Since local governments are the ones that assess trustworthiness and mete out punishment, will they themselves be subject to the same penalties as other defaulters?

In this county, slandering others online will take 100 points off your social credit rating, while manufacturing and selling fake products will set you back by merely 35 points. Someone who may be rightfully seeking redress by occupying government offices may be slapped with a 50-point deduction, the same penalty as someone who has given or received bribes.

Curated Insights 2018.12.14

The Facebook Fed

I think a good analogy is that Facebook is the Federal Reserve of web publishing. It can turn its dial and blast millions of visitors to numerous publishers, allowing everyone to have more eyeballs to sell to and more rising traffic numbers with which to attract investment. Facebook turning on the traffic fire hose is like loose monetary policy that stimulates the economy for everyone.

Of course, Facebook could tighten policy, pulling traffic (liquidity) and leaving weaker players parched. When the Fed tightens policy, shaky borrowers who depend on ample lending are hit hardest. When Facebook tightens policy, second-tier publishers that totally rely on Facebook are hit hardest.

Digital divide is wider than we think, study says

Over all, Microsoft concluded that 162.8 million people do not use the internet at broadband speeds, while the F.C.C. says broadband is not available to 24.7 million Americans. The discrepancy is particularly stark in rural areas. In Ferry County, for example, Microsoft estimates that only 2 percent of people use broadband service, versus the 100 percent the federal government says have access to the service.

The hardest problem in finance

But here’s the catch, this table assumes you get this rate of return year after year after year. The real world is not so accommodating. The table above shows that you can earn 4% a year for 34 years before running out of money, but let’s look at what happens if a nasty bear market were to arrive as soon as you retire. The chart below shows one way in which an investor can arrive at a 4% CAGR over a 30 year period.

The danger of assuming compound annual growth rates when making long term projections can be seen in the chart below. The black line shows that spending a constant $40k annually, using the returns from the previous chart, an investor would run out of money in the 19th year. Spending 4% and assuming a 2% inflation rate, a more realistic assumption, an investor would run out of money in just 15 years. Side note, if the returns above were to happen in reverse, in other words the bear market comes at the end of the period, an investor with the same spending would be left with $1.3 million.

Curated Insights 2018.12.07

The money and math behind our newsletter headlines

That means that the winning headline results in 4,620 incremental opens per newsletter. Over the course of a month, that is 115,000+ incremental opens. If we apply a conservative estimate based on some of our data from 2015 of how many of those incremental opens try the CB Insights free product (0.09%) and that only 1% of those trials buy a subscription, we’re looking at nearly $625,000 of incremental revenue.

Facebook is undervalued

The result of billions of readers providing free content for each other is a massive network effect and a business that can serve each incremental ad at a very low marginal cost. The company’s 85% gross margin leaves a lot of meat on the bone that the company can spend on hiring new engineers and developing new technology that is needed to maintain and grow the business. But even after paying the engineers, growing the headcount, spending over $9 billion on R&D, and paying the tax bill, shareholders are still left with around 40 cents of profit for each dollar of revenue. Facebook reinvests these earnings into data centers, technology, and the occasional acquisition, but even so, the cash in the till has been piling up, and now exceeds $40 billion and counting ($14 per share). Facebook has spent $10 billion on buybacks in the last year, and this will likely accelerate in the coming years.

Facebook’s business is still growing fast (33% revenue growth last quarter), and despite the company’s large size, the runway is still long. Benedict Evans, a partner at the VC firm Andreessen Horowitz, recently pointed out that roughly $1 trillion is spent each year by businesses who are trying to reach customers who are asking the question: “What should I buy?”. Facebook has roughly 5% of this market, which I think is a share that will inevitably rise over the coming years as advertising dollars continue to shift from traditional media to the much higher ROI advertising platforms like Google, Facebook, and Amazon.

A strong network leads to Facebook grabbing a much greater share of the $1 trillion (and growing) global ad/marketing industry. Revenue from ads alone could easily be twice the current size, which means that Facebook is a $100 billion business before counting any of the possible upside from payments, messaging, or any of the other potential business lines that the company could develop on the back of its large network effect.


Accelerator demand should grow ten-fold according to top 500 supercomputers

If the data center market as a whole were to follow in the footsteps of HPC, accelerators could displace Intel CPUs as the workhorse of enterprise computing.

If processors were to grow to 50% of total server component costs, with accelerators capturing 70% of processors, as is the case in the HPC market today, the market for accelerators could scale from $4 billion1 today to $24 billion. Currently, the size of the computer server market is $80 billion globally, according to IDC. If manufacturers take a 15% cut, then $68 billion accrues to component suppliers such as Intel, Micron, and Nvidia. Today we estimate that processors account for roughly 35% of server component costs, the balance allocated to memory, storage, and networking. With HPC and AI, servers are evolving toward higher compute configurations, pushing processors and accelerators to 80% of total component costs.

As shown by the latest IDC data above, the server market as a whole continues to grow, driven primarily by higher average selling prices (ASPs). With denser configurations, server ASPs could climb from today’s price of $8,000 to $10,000. Even at the current volume of 10 million units per year, that would grow the server market 25% from $80 to $100 billion, pushing the accelerator total addressable market to $35 billion.

Today, the accelerator market is dominated by Nvidia’s data center products, which we estimate will generate $3.2 billion of revenue in 2018. Nvidia estimates that its data center business has a total addressable market of $50 billion—a figure larger than Intel’s data center business, which seems difficult to reconcile. That said, as the latest data from IDC and Top 500 shows, the server market is undergoing a fundamental shift. The decay of Moore’s Law has increased total server spend as compute intensive workloads migrate from CPUs to specialized processors. If CPUs and accelerators were to swap places in the data center, as they did in HPC, the accelerator market would approach Nvidia’s estimate, implying a 10x increase over the next five to ten years.

Artificial intelligence is giving rise to fake fingerprints. Here’s why you should be worried

In the new paper, the researchers used neural networks—the foundational software for data training—to create convincing looking digital fingerprints that performed even better than the images used in the earlier study. Not only did the fake fingerprints look real, they contained hidden properties undetectable by the human eye that could confuse some fingerprint scanners.

Julian Togelius, one of the paper’s authors and an NYU associate computer science professor, said the team created the fake fingerprints, dubbed DeepMasterPrints, using a variant of neural network technology called “generative adversarial networks (GANs),” which he said “have taken the AI world by storm for the last two years.”

Daniel Kahneman: Your intuition is wrong, unless these 3 conditions are met

There are three conditions that need to be met in order to trust one’s intuition. The first is that there has to be some regularity in the world that someone can pick up and learn. “So, chess players certainly have it. Married people certainly have it,” Kahnemen explained. However, he added, people who pick stocks in the stock market do not have it. “Because, the stock market is not sufficiently regular to support developing that kind of expert intuition,” he explained. The second condition for accurate intuition is “a lot of practice,” according to Kahneman. And the third condition is immediate feedback. Kahneman said that “you have to know almost immediately whether you got it right or got it wrong.”

The 80-hour workweek

Every year on Wall Street, first-year analysts who were once courted by college recruiters with lines about how they would be given meaningful, creative work and the chance to learn from top executives are shown the harsh truth: they are Excel grunts whose work is often meaningless not just in the cosmic sense, but in the sense of being seen by nobody and utilized for no productive purpose. Some of the hundred-page pitch books analysts spend their late-night hours fact-checking in painstaking detail are simply thrown away after being given a quick skim by a client. In other cases, the client doesn’t read the deliverables at all, and the analysts’ work is literally garbage.

Most days that winter, he had worked the “banker nine-to-five”—getting to work at 9:00 a.m. and staying until 5:00 a.m. the next morning, at which point he’d trudge back to his Murray Hill apartment, sleep for three or four hours, and do it all over again. Even the money he was making wasn’t cheering him up. Ricardo had once made the mistake of calculating what his hourly wage would be, given his salary and a conservative estimate of his year-end bonus. The result—which he estimated was something like $16 an hour, after taxes—was much more than minimum wage, but not nearly enough for Ricardo to be able to justify the punishment he’d been taking.

The question of in office hours versus out of office hours is a good one in thinking about a career in the finance industry. I knew basically nothing when I came into finance so a massive amount of my learning was done on my own after hours.

Curated Insights 2018.11.02

Steve Jobs had an incredible definition of what a company should be

The company is one of the most amazing inventions of humans, this abstract construct that’s incredibly powerful. Even so, for me, it’s about the products. It’s about working together with really fun, smart, creative people and making wonderful things. It’s not about the money. What a company is, then, is a group of people who can make more than just the next big thing. It’s a talent, it’s a capability, it’s a culture, it’s a point of view, and it’s a way of working together to make the next thing, and the next one, and the next one.


Fossil fuels will save the world (really)

That fossil fuels are finite is a red herring. The Atlantic Ocean is finite, but that does not mean that you risk bumping into France if you row out of a harbor in Maine. The buffalo of the American West were infinite, in the sense that they could breed, yet they came close to extinction. It is an ironic truth that no nonrenewable resource has ever run dry, while renewable resources—whales, cod, forests, passenger pigeons—have frequently done so.


Gundlach: People want to be told what to think. I don’t

My biggest lesson that I’ve learned… I have the same flaw that every human being has and that is: As you’re growing up and getting older, you believe that everybody’s like you. You just extrapolate your personality traits and proclivities on other people. Then you start to realize increasingly, that that’s not true. And I believed, therefore, that everybody was intellectually objective and honest and wanted to figure things out for themselves. And I didn’t understand, for probably as long as 20 years, why I couldn’t convince people of almost mathematically analytical arguments regarding markets. And it was finally after years of this that I realized that people actually want to be told what to think.

It took me a long time to understand that. Not me, see, I don’t want to be told what to think. And so I figured nobody wants to be told what to think. But indeed, I think almost everybody wants to be told what to think. That creates a tremendous advantage in managing money. Because in that window of time between a fact and people being told what the fact means, you have a window if you’re capable of figuring out what it means – and don’t need to be told what it means – where you can actually act before other people and I found I’ve made a lot of money that way.

I remember when Ben Bernanke announced the Fed funds rate was going to stay at 0% for three years, and the markets didn’t move. And I had my traders look for this asset class in the bond market that would be the primary beneficiary of rate staying at zero for three years. And I said, “How much of the prices up?” And they said, “They’re not up at all.”

Assessing IBM’s $34 billion Red Hat acquisition

Dan Scholnick, general partner at Trinity Ventures, whose investments have included New Relic and Docker, was not terribly impressed with the deal, believing it smacked of desperation on IBM’s part. “IBM is a declining business that somehow needs to become relevant in the cloud era. Red Hat is not the answer. Red Hat’s business centers around an operating system, which is a layer of the technology stack that has been completely commoditized by cloud. (If you use AWS, you can get Amazon’s OS for free, so why would you pay Red Hat?) Red Hat has NO story for cloud,” he claimed in a statement.

Forrester analyst Dave Bartoletti sees the cloud native piece as being key here. “The combined company has a leading Kubernetes and container-based cloud-native development platform, and a much broader open source middleware and developer tools portfolio than either company separately. While any acquisition of this size will take time to play out, the combined company will be sure to reshape the open source and cloud platforms market for years to come,” he said.


IBM’s old playbook

The best thing going for this strategy is its pragmatism: IBM gave up its potential to compete in the public cloud a decade ago, faked it for the last five years, and now is finally admitting its best option is to build on top of everyone else’s clouds. That, though, gets at the strategy’s weakness: it seems more attuned to IBM’s needs than potential customers. After all, if an enterprise is concerned about lock-in, is IBM really a better option? And if the answer is that “Red Hat is open”, at what point do increasingly sophisticated businesses build it themselves?

The problem for IBM is that they are not building solutions for clueless IT departments bewildered by a dizzying array of open technologies: instead they are building on top of three cloud providers, one of which (Microsoft) is specializing in precisely the sort of hybrid solutions that IBM is targeting. The difference is that because Microsoft has actually spent the money on infrastructure their ability to extract money from the value chain is correspondingly higher; IBM has to pay rent:

The threat of Amazon’s content strategy

Even if content is created by a publisher and merely distributed through the tech platform, the tech company still captures its data; Netflix, for example, doesn’t share ratings data with TV producers, and Amazon doesn’t share Kindle readership data with the publishing industry. Meanwhile, Facebook actually shared false data with brands about their video’s viewership for years.

  • Anheuser-Busch InBev acquired a stake in RateBeer, a leading beer review platform, and October, a beer culture website.
  • Popular makeup startup Glossier initially launched as a content site; it then used insights gathered from users to develop its own line of cosmetics. Now, it aims to launch a new social commerce platform to encourage user reviews and feedback.
  • L’Oreal invested in Beautycon Media, which creates digital beauty content and hosts festivals for influencers
  • Mattress startup Casper even launched its own magazine; the current issue includes features like “A skeptic’s guide to crystals” and an adult coloring book.

Social Capital’s Chamath Palihapitiya says ‘we need to return to the roots of venture investing’

“The dynamics we’ve entered is, in many ways, creating a dangerous, high stakes Ponzi scheme. Highly marked up valuations, which should be a cost for VCs, have in fact become their key revenue driver. It lets them raise new funds and keep drawing fees.”

“VCs bid up and mark up each other’s portfolio company valuations today, justifying high prices by pointing to today’s user growth and tomorrow’s network effects. Those companies then go spend that money on even more user growth, often in zero-sum competition with one another. Today’s limited partners are fine with the exercise in the short run, as it gives them the markups and projected returns that they need to keep their own bosses happy.”

“Ultimately, the bill gets handed to current and future LPs (many years down the road), and startup employees (who lack the means to do anything about the problem other than leave for a new company, and acquire a ‘portfolio’ of options.)”

The coming storm for consumer staples dividends

AB InBev argued that by taking its leverage down to 2x net debt/EBITDA, it will reduce its cost of capital and “maximize total enterprise value.” All else equal, a lower cost of debt would in theory increase enterprise value, yet AB InBev already has solidly investment-grade credit ratings (e.g., A- from S&P). A ratings upgrade within the investment-grade space would likely only have a marginal impact on lowering cost of debt. Deleveraging could even increase its cost of capital, as more expensive equity takes a greater share of the capital structure.

Ultimately, a company’s dividend should be affordable, reflect the growth in shareholder value creation, and help management more prudently select high-return projects rather than pursue wasteful “empire building” deals. Dividends can be a problem, however, when they become too generous and handcuff management’s ability to invest in high-return projects and defend or widen the firm’s economic moat. When this happens, a dividend “rebasing” or “cut” would benefit long-term shareholders.


Uber-inequality

Uber received proposals from investment banks that pegged the ride-hailing firm’s IPO valuation at $120B. So, that posits Uber’s value is greater than the value of the US airline industry or the US auto industry (excluding Tesla). I love Uber and think the firm is genius. But that valuation is insane. Uber’s model doesn’t have the moats of an auto firm or even Airbnb, which must create global demand and supply (a local competitor to Airbnb doesn’t work, as visitors from other countries wouldn’t know about it). In contrast, local on-demand taxi services abound, even if without an app. The 120K readers of this newsletter could each put in $250, and boom — we have the number-three ride-hailing firm in Miami. Who’s with me?

In today’s economy, innovation means elegant theft: robbery of your data, privacy, health insurance, or minimum-wage protection. Uber has 16K employees and 3M driver partners. “Driver partner” means some great things. It means you don’t have to show up to an office. And it means you can work whenever you want — this is key. When I speak to Uber drivers, I always ask, “Do you like working for Uber?” The overwhelming majority say yes and reference the flexibility. I’ve been especially struck by how many need the flexibility, as they’re taking care of someone who’s sick. So many people taking care of others. So many people loving other people. And it comes at a huge cost. Many of them used to have jobs with benefits. Many had to move to a strange place to take care of their sister, mother, nephew.

The economic value of artificial intelligence

In the near term, around $6.6 trillion of the expected GDP growth will come from productivity gains, such as the continued automation of routine tasks. Over time, increased consumer demand for AI-enhanced offerings will overtake productivity gains and result in an additional $9.1 trillion of GDP growth by 2030.

China is expected to see the greatest economic gains from AI, a $7 trillion or 26% boost in GDP growth. One reason is the high proportion of China’s GDP that is based on manufacturing, where AI is expected to have a particularly big impact between now and 2030. Even more important over the longer term is China’s higher rate of AI investments compared to North America and Europe.

China is expected to see the greatest economic gains from AI, a $7 trillion or 26% boost in GDP growth. One reason is the high proportion of China’s GDP that is based on manufacturing, where AI is expected to have a particularly big impact between now and 2030. Even more important over the longer term is China’s higher rate of AI investments compared to North America and Europe.

In North America, the economic gains from AI are expected to reach $3.7 trillion or 14.5% of GDP growth by 2030. North America will see the fastest growth in the near term, given its current lead in AI technologies, applications, and market readiness. But China will likely begin to catch up by the middle 2020s given its accelerating AI investments.


A.I. is helping scientists predict when and where the next big earthquake will be

Some of the world’s most destructive earthquakes — China in 2008, Haiti in 2010 and Japan in 2011, among them — occurred in areas that seismic hazard maps had deemed relatively safe. The last large earthquake to strike Los Angeles, Northridge in 1994, occurred on a fault that did not appear on seismic maps.

Curated Insights 2018.09.21

Brent Beshore: Learning to pole vault

Marketing will only get you where you’re going faster. If your product isn’t valuable, marketing will help put you out of business, fast. The best way to build trust and generate attention is to be relatively excellent. I say “relatively” because some markets are more efficient/mature than others. The less developed a market, the less valuable you have to be in absolute terms. You just have to be better than everyone else. I don’t want to try to outcompete smart, well-read, and hard working people. I want to find the lowest bar to jump over and then get good at pole vaulting.

Picking your field is arguably more important to your success than your current skill and future capacity. In some segments of business, everyone makes lots of money and the very best do outrageously well. In other areas, even the very best often declare bankruptcy. It’s a base rate analysis. Assume you’re only going to be mediocre, then explore what business and life look like if that’s true. So choose your field wisely and get good at what you’re doing before trying to make noise.

AI has far-reaching consequences for emerging markets

Without a cost incentive to locate in the developing world, corporations will bring many of these functions back to the countries where they’re based. That will leave emerging economies, unable to grasp the bottom rungs of the development ladder, in a dangerous position: the large pool of young and relatively unskilled workers that once formed their greatest comparative advantage will become a liability – a potentially explosive one.

The result will be an unprecedented concentration of productive capacity and wealth in the hands of the elite AI companies, almost all of which are located in the US and China. Of the US$15.7 trillion in wealth that AI is forecast to generate globally by 2030, a full 70 per cent will accrue to those two countries alone, according to a study by consulting firm PwC.

Spotify will now let indie artists upload their own music

According to a recent report by The NYT, artists working with labels may see much smaller percentages. The report said that Spotify typically pays a record label around 52 percent of the revenue generated by each stream. The label, in turn, then pays the artist a royalty of anywhere from 15% to as high as 50%. If artists are dealing directly with Spotify, they could be making more money.

Labels suggested that they could retaliate against Spotify for overstepping. The NYT had also said. They may do things like withhold licenses Spotify needs for key international expansions, like India, or not agree to new terms after existing contracts expire. They could also offer more exclusives and promos to Spotify’s rivals, like Apple Music, which has surged ahead in the U.S. and is now neck-and-neck here with Spotify for paid subscribers.

A music upload feature also means artists who own their own rights could break out big on Spotify if they catch the attention of playlist editors – something that Spotify now makes it easier for them to do, as well. In addition, having indies upload music directly means Spotify could better compete against Apple Music by attracting more artists and their fans to its platform.


Apple’s neural engine = Pocket machine learning platform

If you have followed many of the posts I’ve written about the challenges facing the broader semiconductor industry, you know that competing with Apple’s silicon team is becoming increasingly difficult. Not just because it is becoming harder for traditional semiconductor companies to spend the kind of R&D budget they need to meaningfully advance their designs but also because most companies don’t have the luxury of designing a chip that only needs to satisfy the needs of Apple’s products. Apple has a luxury as a semiconductor engineering team to develop, tune, and innovate specialized chips that exist solely to bring new experiences to iPhone customers. This is exceptionally difficult to compete with.

However, the area companies can try with cloud software. Good cloud computing companies, like Google, can conceivably keep some pace with Apple as they move more of their processing power to the cloud and off the device. No company will be able to keep up with Apple in client/device side computing but they can if they can utilize the monster computing power in the cloud. This to me is one of the more interesting battles that will come over the next decade. Apple’s client-side computing prowess vs. the cloud computing software prowess of those looking to compete.


Tim Cook reveals in interview that the Chinese consumer is different because they don’t carry the burden of the desktop era

China has not experienced the so-called stage of the desktop Internet, but directly embraced the mobile Internet. Therefore, Chinese consumers do not have the burden of the desktop Internet era. This explains to some extent why China’s mobile payment share is so high. In other countries, the mobile payment process is much slower. In fact, they just have no more attempts.”

Perhaps Apple’s delay in advancing Macs and angering the pro community comes from this deep seated attitude that it’s a “burden” holding back the advancement of their iOS agenda.

The best company you’ve never heard of

With no true competitive threats, wide-moat commercial real estate data provider CoStar Group is a borderline monopoly. The other companies in the space are predominately small startups focused on crowdsourcing data. These companies can’t replicate the intangible assets from the vast cost and effort associated with compiling the data the company offers to its customer base.

Given the importance customers place on the underlying data, CoStar also keeps competitors at bay with a switching cost moat source. It’s just too risky to switch sources. Strong platform effects found throughout CoStar’s product offerings earn the company a network effect moat source, too.

The company continues to increase its coverage and boasts that it covers every building in the country, widening the gap between itself and its fragmented competition. The firm recently established itself as a leading provider of rental data with its acquisitions of Apartment Finder and Apartments.com. CoStar is only 30% penetrated in its target market for apartments, so we see room for growth in this area.

Moreover, CoStar is only 15% penetrated in the broker community and 7% penetrated with institutional investors, two groups we can see the firm going after. As several investments are integrated and benefits are realized, we project CoStar’s economic profit to steadily increase over the next several years, reflecting our positive moat trend rating.

Here’s why Yelp and Grubhub could keep rising

“Grubhub is in the early stages of enabling the shift to online of the still offline dominant restaurant takeout businesses and driving the improved consumer experience that comes with it,” they wrote. About “90% of delivery and pickup orders still come from offline, making the phone book, print out menus and walk-ins the number one competitor to Grubhub and its peers.”

How early is the shift? “We estimate Grubhub has about 40% market share of the third-party online delivery/pickup industry which itself we estimate has a 4% penetration of the $250 billion restaurant takeout industry,” they wrote. “Its early mover and scale advantage—about 85,000 restaurants on its platform in 1,600 cities—has allowed Grubhub to offer, in our view, the best consumer value across its competitors.”


Why Yelp could rise 200%

If we can introduce ourselves to those advertisers with a good ‘til canceled $300, $400 a month, $10, $20 a day kind of service proposition, what we’re finding is it really opens up our sales funnel. It makes our product more competitive in the marketplace. It allows us to get into third-party sales channels that we haven’t been in before. And we’re now kind of one quarter into it and we had this quarter, the first quarter, about 140% as many new or net customer additions in this quarter as we’ve had in any prior quarter and kind of 2x the run rate that we’ve normally seen when we were selling the term contract. And, now, we move to the non-term contract.

In the long-term, our tests and our analysis all show that the LTV of a cohort of advertisers that we bring in today will be quite a bit higher. And what we’ve seen in our tests is that we continue to sell the sort of long and strong loyal long-term advertisers under the new pricing model just as we always have, but on top of that we’re introducing ourselves to a lot more new customers along the way

Yelp is in the early days of elevating the consumer experience by expanding the number of transactional features such as Request-A-Quote from a home service professional or book a restaurant reservation or spa appointment. Request-A-Quote lead volume grew 27% from the first to the second quarter of 2018 and topped 5.5 million delivered requests in the second quarter. During that same short timeframe, revenue attributable to Request-A-Quote increased by more than 50%, surpassing a $35 million annual run rate at the end of the second quarter. The company is not yet fully monetizing Request-A-Quote, which we believe could accelerate free cash growth even further. We like finding misunderstood, yet promising, and free embedded call options within the companies we invest in and hope Request-A-Quote proves to a second material avenue for free cash per share growth.


GGV Capital: Unpacking Xiaomi’s IPO

Instead of paying for users, Xiaomi actually gets paid at least 5% gross margin through hardware to get users…it’s a very different model from almost any other internet services model out there. So if this is sustainable, and to make sure this is sustainable is to have a lot more hardware products out there that the middle class can buy, and use that portfolio of hardware devices to get paid for acquiring users, so that internet services can scale thereafter…There’s definitely elements of Muji and Uniqlo in a different field for Xiaomi, there’s definitely elements of a Costco model of subscription plus very low cost to make sure more products are affordable by the rising consumer class, there’s definitely elements of Amazon in there as a platform to sell many products and being very focused at delivering a superior experience…

If we look at the number of internet users coming online, the next 1.5bn internet users coming online between now and 2030, most of that growth will come from the 74 countries that Xiaomi is in already. So when people ask me if Xiaomi is coming to the US or not, they completely miss the point, the growth is coming from the existing countries that Xiaomi’s already in…

Xiaomi has over 18 apps, each with monthly active users of over 50mn. It also has 38 apps, each with over 10mn MAUs. In aggregate, it did over 1.5bn RMB in internet services revenue in 2017, which already puts them as a top 25 internet services only company in the world. The most popular [app] that people know is probably Xiaomi Video, which has an interesting way of becoming aggregation services. It doesn’t license content from anyone, what it does is it aggregates content from all the top Chinese video apps, each of which have already licensed the content and whenever a user clicks on a video, it takes you to the content from its partners but within the app itself, so you can have a more integrated experience. It charges advertising revenue and also subscription from the users…and they share that revenue with its partners that provide the original video content. So, it can focus on providing the most comprehensive collection of content to the user, at the same time, so far, they don’t have to spend much money on acquiring the content itself.”


Tesla, software and disruption

It’s pretty clear that electric disrupts the internal combustion engine, and everything associated with it. It’s not just that you replace the internal combustion engine with electric motors and the fuel tank with batteries – rather, you remove the whole drive train and replace it with sometime with 5 to 10 times fewer moving or breakable parts. You rip the spine out of the car. This is very disruptive to anyone in the engine business – it disrupts machine tools, and many of the suppliers of these components to the OEMs. A lot of the supplier base will change.

We will go from complex cars with simple software to simple cars with complex software. Instead of many stand-alone embedded systems each doing one thing, we’ll have cheap dumb sensors and actuators controlled by software on a single central control board, running some sort of operating system, with many different threads (there are a few candidates). This is partly driven by electric, but becomes essential for autonomy.

Tesla’s first bet is that it will solve the vision-only problem before the other sensors get small and cheap, and that it will solve all the rest of the autonomy problems by then as well. This is strongly counter-consensus. It hopes to do it the harder way before anyone else does it the easier way. That is, it’s entirely possible that Waymo, or someone else, gets autonomy to work in 202x with a $1000 or $2000 LIDAR and vision sensor suite and Tesla still doesn’t have it working with vision alone.

‘Flash Boys’ exchange IEX wins first listing

The U.S. corporate-listings business, in which companies pay fees to an exchange for services tied to being the primary venue for the company’s stock trading, has for years been an effective duopoly of the NYSE and Nasdaq. A third big exchange group, Cboe Global Markets Inc., lists exchange-traded funds and its own shares, but hasn’t made a bid to attract other companies. NYSE parent Intercontinental Exchange Inc. and Nasdaq earned a combined $684 million from listings last year, according to the two exchange groups.

“We at Interactive Brokers understand that being the first listing on a new exchange may entail certain risk, but we think that individual and institutional customers who own and trade our stock will receive better execution prices and that advantage will outweigh the risk,” Mr. Peterffy said in a press release announcing the move.

Because of China’s outsized workforce, the density of automation usage lags other countries: 68 robots per 10,000 industrial workers, compared with 631 bots for every 10,000 manufacturing staff in South Korea, the global leader in automation. Singapore, Germany and Japan all have higher densities of automation than China. China wants to more than double that usage density to 150 for every 10,000 workers by 2020. To do so would require massive amounts of government help.

‘Made In China 2025’: a peek at the robot revolution under way in the hub of the ‘world’s factory’

A skilled factory worker earns about 36,000 yuan a year in wages and benefits in China’s poorer provinces and second-tier cities, away from the coast. Total remuneration can exceed 60,000 yuan in cities nearer the coast and along the eastern seaboard, like in the Pearl River and Yangtze River deltas. A 200,000 yuan robot that can do the job of three humans can recoup its capital cost in 22 months in central provinces, or in a little over a year in coastal cities. In the face of rising prices pressures for labour, energy and rents, such a cost advantage would be attractive to many manufacturers.

China’s total spending on research and development is estimated to have risen 14 per cent last year to 1.76 trillion yuan, according to the Ministry of Science and Technology.

“Among the thousands of so-called Chinese robotics companies – including robot and automated equipment producers as well as those who only provide automation integration solutions – only about 100 firms could mass produce the main body and core components of high-end and middle-market industrial robots, such as servo motors, robot controllers and speed reducers,” he said. “We lack original research and have already tried to catch up by copying advanced technology. But neither technology-related mergers and acquisitions nor copycat [production] can close the gap in the short term.”

He said many domestic robotics manufacturers were still developing the traditional core parts of robots, like servo motors, robot controllers and speed reducers. But these parts would not be the core components of the future, he said.

Don’t take asset allocation advice from billionaires

One of the best ways to stay out of trouble with your finances is to focus all of your energy on your own circumstances and ignore what other people say or do with their money. Not only will it likely save you from making a grievous financial error but it will also make you happier. Constantly comparing yourself or your portfolio to others can be exhausting.

This is how to raise emotionally intelligent kids: 5 secrets from research

Don’t argue the facts. Feelings aren’t logical. You wouldn’t expect the new employee to know how to find the bathroom and you shouldn’t expect a child to know how to handle emotions that, frankly, you still have problems dealing with after decades of experience. Don’t immediately try to fix things. You need to establish you’re a safe ally before you can solve anything. Understanding must precede advice, and, just as with adults, they decide when you understand.

The critical distinction Gottman realized is that it’s important to accept all feelings — but not all behavior. If you skip immediately to problem-solving, the kid never learns the skill of how to deal with those uncomfortable emotions. You want to use “empathetic listening.” Get them to talk. Help them clarify. Validate their feelings (but, again, not necessarily their behavior). They need to feel you really understand and are on their side.

Providing words in this way can help children transform an amorphous, scary, uncomfortable feeling into something definable, something that has boundaries and is a normal part of everyday life. Anger, sadness, and fear become experiences everybody has and everybody can handle. Labeling emotions goes hand in hand with empathy. A parent sees his child in tears and says, “You feel very sad, don’t you?” Now, not only is the child understood, he has a word to describe this intense feeling. Studies indicate that the act of labeling emotions can have a soothing effect on the nervous system, helping children to recover more quickly from upsetting incidents.

As we have discussed earlier, the implications of teaching a child to self-soothe are enormous. Kids who can calm themselves from an early age show several signs of emotional intelligence: They are more likely to concentrate better, have better peer relationships, higher academic achievement, and good health. My advice to parents, then, is to help your kids find words to describe what they are feeling. This doesn’t mean telling kids how they ought to feel. It simply means helping them develop a vocabulary with which to express their emotions.

In an ideal world, we’d always have time to sit and talk with our kids as feelings come up. But for most parents, that’s not always an option. It’s important, therefore, to designate a time—preferably at the same period each day—when you can talk to your child without time pressures or interruptions.

Curated Insights 2018.09.14

Risk, uncertainty and ignorance in investing and business – Lessons from Richard Zeckhauser

People feel that 50% is magical and they don’t like to do things where they don’t have 50% odds. I know that is not a good idea, so I am willing to make some bets where you say it is 20% likely to work but you get a big pay-off if it works, and only has a small cost if it does not. I will take that gamble. Most successful investments in new companies are where the odds are against you but, if you succeed, you will succeed in a big way.” “David Ricardo made a fortune buying bonds from the British government four days in advance of the Battle of Waterloo. He was not a military analyst, and even if he were, he had no basis to compute the odds of Napoleon’s defeat or victory, or hard-to-identify ambiguous outcomes. Thus, he was investing in the unknown and the unknowable. Still, he knew that competition was thin, that the seller was eager, and that his windfall pounds should Napoleon lose would be worth much more than the pounds he’d lose should Napoleon win. Ricardo knew a good bet when he saw it.

…in any probabilistic exercise: the frequency of correctness does not matter; it is the magnitude of correctness that matters…. even though Ruth struck out a lot, he was one of baseball’s greatest hitters…. Internalizing this lesson, on the other hand, is difficult because it runs against human nature in a very fundamental way… The Babe Ruth effect is hard to internalize because people are generally predisposed to avoid losses. …What is interesting and perhaps surprising is that the great funds lose money more often than good funds do. The best VCs funds truly do exemplify the Babe Ruth effect: they swing hard, and either hit big or miss big. You can’t have grand slams without a lot of strikeouts.

Risk, which is a situation where probabilities are well defined, is much less important than uncertainty. Casinos, which rely on dice, cards and mechanical devices, and insurance companies, blessed with vast stockpiles of data, have good reason to think about risk. But most of us have to worry about risk only if we are foolish enough to dally at those casinos or to buy lottery cards….” “Uncertainty, not risk, is the difficulty regularly before us. That is, we can identify the states of the world, but not their probabilities.” “We should now understand that many phenomena that were often defined as involving risk – notably those in the financial sphere before 2008 – actually involve uncertainty.” “Ignorance arises in a situation where some potential states of the world cannot be identified. Ignorance is an important phenomenon, I would argue, ranking alongside uncertainty and above risk. Ignorance achieves its importance, not only by being widespread, but also by involving outcomes of great consequence.” “There is no way that one can sensibly assign probabilities to the unknown states of the world. Just as traditional finance theory hits the wall when it encounters uncertainty, modern decision theory hits the wall when addressing the world of ignorance.


Hank Paulson says the financial crisis could have been ‘much worse’

While Bear Stearns’ failure in normal markets would not hurt the U.S. economy, we believed that the system was too fragile and fear-driven to take a Bear Stearns bankruptcy. To those who argue that Bear Stearns created moral hazard and contributed to the Lehman failure, I believe just the opposite—that it allowed us to dodge a bullet and avoid a devastating chain reaction.

If Bear had failed, the hedge funds would have turned on Lehman with a vengeance. Lehman would have failed almost immediately and the result would have been much worse than Lehman’s September failure, which occurred after we had stabilized Fannie Mae and Freddie Mac and Bank of Americaacquired Merrill Lynch. I would hate to imagine what would have happened if this whole thing started before we’d stabilized Fannie and Freddie.

An interview with Tim Geithner on this topic was done recently at the Yale School of Management and he speaks much more authoritatively on the limits of the Fed powers than I, but here goes. While our responses may have looked inconsistent, Ben, Tim, and I were united in our commitment to prevent the failure of any systemically important financial institution. But we had a balkanized, outdated regulatory system without sufficient oversight or visibility into a large part of the modern financial system and without the necessary emergency powers to inject capital, guarantee liabilities, or wind down a non-banking institution. So we did whatever we could on a case-by-case basis.

For Lehman, we had no buyer and we needed one with the willingness and capacity to guarantee its liabilities. Without one, a permissible Fed loan would not have been sufficient or effective to stop a run. To do that, the Fed would have had to inject capital or guarantee liabilities and they had no power to do so. Now, here’s the point that I think a lot of people miss: In the midst of a panic, market participants make their own judgments and a Fed loan to meet a liquidity shortfall wouldn’t prevent a failure if they believed Lehman wasn’t viable or solvent. And no one believed they were.

AIG is a cautionary tale. We should not have let our financial regulatory system fail to keep up with modern financial markets. No single regulator had oversight visibility or adequate powers to deal with AIG. Its insurance companies were regulated at the state level, its holding company was like a giant hedge fund sitting on top of the insurance companies, and it was regulated by the ineffective Office of Thrift Supervision, which also regulated—get this—Countrywide, WaMu, IndyMac, GE Capital. They all selected their regulator. So you get the picture, it’s regulatory arbitrage.

And I’m concerned that some of the tools we effectively used to stave off disaster have now been eliminated by Congress. These include the ability of Treasury to use its exchange stabilization fund to guarantee the money market funds, the emergency lending authority the Fed used to avoid the failure of Bear and AIG, and the FDIC’s guarantee of bank liabilities on a systemwide basis, which was critical.

The global smartphone supply chain needs an upgrade

At the peak in October 2017, smartphone components accounted for over 33% of exports from Taiwan, 17% of those from Malaysia and 16% from Singapore. Smartphones comprise 6% of Chinese exports. Memory chips flow from South Korea and Vietnam; system chips from Malaysia, Taiwan and elsewhere; and displays from Japan and South Korea. Rich-world firms, such as Qualcomm, sell licences to use their intellectual property (IP). The parts are then assembled, mainly by armies of Chinese workers.

Apple and 13 of its chip suppliers earn over 90% of the total pool of profits from the Apple system. Meanwhile the tail of other firms doing more basic activities must pay for most workers, inventories and fixed assets (see chart). So they have in aggregate a weak return on equity, of 9%, and a net profit margin of just 2%. Their earnings have not risen for five years. They include assemblers such as Taiwan’s Hon Hai and niche component makers, some of which are visibly struggling. On August 22nd AAC Technologies, a specialist in making phones vibrate, said its second-quarter profits fell by 39% compared with the previous year.

Apple, Samsung and most semiconductor makers could ride out such tensions, with their high margins and cash-laden balance-sheets. But the long chain of other suppliers could not, given their razor-thin margins, big working-capital balances and fixed costs. Tariffs could push them into the red. Of the 132 firms, 52% would be loss-making if costs rose by just 5%. And a ZTE-style cessation of trade would be disastrous. If revenues dried up and the 132 firms continued to pay their own suppliers, short-term debts and wages, 28% of them would run out of cash within 100 days.

If you are running a big firm in the smartphone complex, you should be reimagining things in preparation for a less open world. In a decade, on its current trajectory, the industry will be smaller, with suppliers forced to consolidate and to automate production. It may also be organised in national silos, with production, IP, profits and jobs distributed more evenly around the world. Firms will need to adapt—or be swiped away.

The story of Box: A unicorn’s journey to public success

The early days of Box’s selling file sharing and collaboration have largely been replaced by big corporate wins. One measure of Box’s success is its penetration of the Fortune 500—from 52% in the second quarter of 2016 to 69% in the same quarter of fiscal 2019. About 58% of Box’s total revenue comes from enterprises of 2,000 employees or more.

In Box’s recently completed fiscal quarter, it closed 50 deals of more than $100,000, compared with 40 a year ago; 11 deals of more than $500,000, versus eight a year ago; and two deals of more than $1 million, compared with four a year ago. It expects a strong pipeline of seven-figure deals in the back half of this year.

But in encouraging its salespeople to pursue bigger deals, Box increasingly faces competition from deeper-pocketed competitors in a total addressable market pegged at $45 billion, based on market research by Gartner and IDC.

Soccer fans, your team is coming after you

At the time of its 2012 initial public offering, Man United counted 659 million fans worldwide. Analysts estimate the team’s revenue this year will be about 587 million pounds ($763 million) — just $1.16 per supporter. Twitter Inc. has just 338 million active monthly users, yet enjoys revenue of $2.4 billion and a market value of $27 billion.

Digital marketing provides the opportunity for teams to put themselves in the middle of the sale of a service or product. It’s not simply about using a website or an app to sell fans more jerseys or baseball caps. It’s about turning the team into a platform, a way of connecting brands to customers, in the same way as Facebook Inc. and Alphabet Inc. already do.

Much in the way that price-comparison websites charge insurers or credit card companies for connecting them to customers, a sports team could, for example, offer its own exclusive video content with another provider’s mobile phone contract and take a cut of the proceeds. If that meant each fan were to spend just one more dollar a year with the club, it would provide a significant boost to sales.


Alibaba-backed apparel-sharing company YCloset brings sharing economy to a new level

Founded in December 2015, YCloset charges a monthly membership fee of 499 yuan and allows female users to rent unlimited clothes and accessories country-wide. Furthermore, users can choose to buy the apparel if they like to and prices fluctuate according to the rent count. Thus far, 75% of the income comes from membership fees and the remaining comes from sales of clothing. YCloset positions itself as a company that offers affordable luxury, professional and designer brand clothing. The company hopes to have the top famous brand to drive the long-tail brands.

In terms of business model, YCloset gradually shifted from one-time supplier purchase to brand partnerships with clothing companies. Brand partnerships allow revenue sharing between YCloset and their partners. To these clothing companies, YCloset gave them a new revenue, at the same time, they may get consumer insights from the data YCloset collects. In the future, YCloset will have joint marketing campaigns with the brands and assist in incubating new brands.

Autonomous delivery robots could lower the cost of last mile delivery by 20-fold

Last mile delivery – the delivery of goods from distribution hubs to the consumer – is the most expensive leg of logistics because it does not submit to economies of scale. The cost per last mile delivery today is $1.60 via human drivers but could drop precipitously to $0.06 as autonomous delivery robots proliferate.

Autonomous delivery robots are roughly seven times more efficient than electric vehicles on a mile per kilowatt basis. The major costs for autonomous delivery robots are hardware, electricity, and remote operators. Unlike in electric vehicles, the battery is not the largest cost component in slow moving robots. Air resistance is a function of velocity squared, suggesting that a robot traveling at four miles per hour loses much less energy than a car traveling at highway speeds to air resistance. As a result, rolling robots do not require large batteries, lowering both hardware and electricity costs relative to more traditional electric vehicles.

If rolling robots enable last mile delivery for $0.06 per mile, artificial intelligence could be advanced enough to improve their unit economics. A remote operator responsible for controlling robots in difficult or confusing situations probably will oversee roughly 100 robots, accounting for more than half of the cost per mile, as shown below. As autonomous capability improves, remote operators should be able to manage larger fleets of robots, bringing down the costs per robot.


Hospitals are fed up with drug companies, so they’re starting their own

A group of major American hospitals, battered by price spikes on old drugs and long-lasting shortages of critical medicines, has launched a mission-driven, not-for-profit generic drug company, Civica Rx, to take some control over the drug supply. Backed by seven large health systems and three philanthropic groups, the new venture will be led by an industry insider who refuses to draw a salary. The company will focus initially on establishing price transparency and stable supplies for 14 generic drugs used in hospitals, without pressure from shareholders to issue dividends or push a stock price higher.


Harvard Business School professor: Half of American colleges will be bankrupt in 10 to 15 years

There are over 4,000 colleges and universities in the United States, but Harvard Business School professor Clayton Christensen says that half are bound for bankruptcy in the next few decades. Christensen and co-author Henry Eyring analyze the future of traditional universities, and conclude that online education will become a more cost-effective way for students to receive an education, effectively undermining the business models of traditional institutions and running them out of business.

Christensen is not alone in thinking that online educational resources will cause traditional colleges and universities to close. The U.S. Department of Education and Moody’s Investors Service project that in the coming years, closure rates of small colleges and universities will triple, and mergers will double.

More than 90 per cent of Chinese teens access the internet through mobile phones, says report

The proportion of Chinese children under 10 years old who use the internet – which was only 56 per cent in 2010 – reached 68 per cent last year. More than 90 per cent of Chinese minors, those aged up to 18, can now access the internet through mobile phone and over 64 per cent of primary school kids have their own smartphones. Nearly 85 per cent of Chinese minors use WeChat, compared to only 48 per cent five years ago, but Chinese juveniles are still more fond of QQ, while Chinese adults prefer WeChat as a social app.

Curated Insights 2018.08.17

Not enough people are paying attention to this economic trend

Haskel and Westlake outline four reasons why intangible investment behaves differently:

  • It’s a sunk cost. If your investment doesn’t pan out, you don’t have physical assets like machinery that you can sell off to recoup some of your money.
  • It tends to create spillovers that can be taken advantage of by rival companies. Uber’s biggest strength is its network of drivers, but it’s not uncommon to meet an Uber driver who also picks up rides for Lyft.
  • It’s more scalable than a physical asset. After the initial expense of the first unit, products can be replicated ad infinitum for next to nothing.
  • It’s more likely to have valuable synergies with other intangible assets. Haskel and Westlake use the iPod as an example: it combined Apple’s MP3 protocol, miniaturized hard disk design, design skills, and licensing agreements with record labels.

For example, the tools many countries use to measure intangible assets are behind the times, so they’re getting an incomplete picture of the economy. The U.S. didn’t include software in GDP calculations until 1999. Even today, GDP doesn’t count investment in things like market research, branding, and training—intangible assets that companies are spending huge amounts of money on.


How Box conquered the enterprise and became a $1.7 billion company in a decade

However, what most people failed to understand—and continue to misunderstand to this day—is that Dropbox was never launched as a competitor to Box. The use cases were completely different. Box.net and Dropbox may have shared some similar underlying technologies (and an uncomfortably similar name), but the focus of Dropbox was cloud-based file management for the consumer market. Box was focused on file sharing. By the time Dropbox launched in 2007, Box.net had already largely abandoned the consumer market in favor of the enterprise. There were other key differences between the two products, such as the necessity of installing a dedicated Dropbox directory on a user’s local machine versus Box.net’s entirely cloud-based interface. Additionally, the two companies’ target markets and business models couldn’t have been more different.

Levie knew SharePoint was Box’s biggest competitor, so he did what any inventive, irreverent entrepreneur would do—he took out a billboard advertisement on a stretch of highway on Route 101 between San Francisco and Silicon Valley. The ad promised SharePoint users that Box would pay for three months of SharePoint access if they didn’t prefer Box. In February 2009, Box went one step further in its media assault on Microsoft by erecting another billboard, this one highlighting the many aspects of SharePoint that were most unpopular among its user base.

While the enterprise market represented a unique chance for Box to pivot away from the increasingly competitive consumer market, essentially shifting the focus of the entire company was no small undertaking. Until that point, Box had used a freemium business model. This worked fine for the consumer market, but it was completely unsuitable for the enterprise. This meant Box would not only have to radically redesign its product from the ground up but also restructure its entire business model.

By acquiring Increo, Box immediately gained access to Increo’s innovative document collaboration tools. This was crucial. It wasn’t enough for Box to offer cloud-based storage or integrations with Salesforce and Office. It had to offer additional value as competing tools vied for dominance.

The consumerization of enterprise IT driven by Box and other forward-thinking companies wasn’t merely an attempt to cultivate a unique value proposition or drive adoption. It reflected much broader shifts in computing in general. The advent of Web 2.0 apps created a new design paradigm that placed emphasis on ease of use and accessibility across multiple devices over complex file management tools. Smartphones fundamentally changed the way we think of computing. For an enterprise software company like Box to be at the forefront of trends in usability was impressive.

OneCloud was an excellent example of how consumer-focused design informed Box’s broader strategy. The company had built a platform for developers in 2011 known as the Box Innovation Network, which functioned similarly to an app marketplace. OneCloud was an extension of this idea, only it was intended exclusively for mobile devices. This would later become a predictable cycle in Box’s development. New features were added to the product to meet emerging needs, and those features were presented to users in ways that directly mirrored those of consumer apps and sites.

What’s more important, however, is how well Box converted its free users to paid subscribers. Consumer apps like Evernote convert free users to paid plans at a rate of approximately 3%. Box was converting free users to paid plans at a rate closer to 8%, including major corporate customers such as Bank of New York and ambient advertising powerhouse Clear Channel. As a result, Box achieved revenues of more than $11M in 2011.

Because most of Box’s sales calls came from companies that had already been using the product, Box’s sales teams were typically able to close 60% of those deals within two weeks—an impressive figure, especially considering the often months-long sales cycles typically associated with the enterprise market.

Box has done an excellent job of not only carving out its own niche in an increasingly competitive space but also by applying design and UX principles of consumer-focused SaaS products to redefine how enterprise software looks, feels, and works. With its keen focus on usability, ease, and simplicity, Box has become a leading force in the consumerization of the enterprise and has shaped how other enterprise software companies approach their products.

Ad tech firm poised to surge 50%

Bid factoring is essentially a linear equation that enables marketers to apply multipliers to different targeting parameters. This approach makes it easier to value each user individually and dynamically, allowing marketers to more easily reach their target users. Bid factoring saved time for marketers through automation and removed the need to store tons of line item permutations, therefore lowering data storage costs.

When Green started The Trade Desk, his goal was to “build a company for the next 100 years.” He did not want to follow the same mistakes that other companies in the space made such as having a conflict of interest by being on both the buy and sell side. Green decided to build a demand side platform because he believed the demand side of the advertising transaction will always have the advantage. In advertising it will always be a buyer’s market because it is easy to add supply by having an extra impression on a web page or additional 30-second spot to a commercial break to meet increased demand. This basic economic reality means advertising supply is more elastic than demand and will forever put the buy side in the power position.

The Trade Desk would also be transparent and not charge unsustainable take rates. Green believed once the digital advertising industry matures, total transaction costs to purchase a digital ad would be $0.20-$0.30 for every $1.00 spent, with roughly $0.15-$0.20 going to the DSP and $0.05-$0.10 being split between the SSP and the ad exchange. The Trade Desk could have charged much higher take rates but decided to charge customers what it believed would be the fair end-state price for their services. While take rates could become lower as competition potentially increases, similar to what happened with discount stock brokerages, barriers to entry and the DSP’s ability to provide increasing value to advertisers overtime should preserve prices.

As the ad market has grown, the number of auctions has increased exponentially. In order for a DSP to win an auction, it now takes many more looks. For each ad campaign, costs have increased while revenues remained fairly flat, increasing operating leverage. DSPs that have half the ad spend as The Trade Desk will struggle because they will incur the same amount of expense per ad campaign but monetize less, making it much more difficult to be profitable if you are a smaller player and don’t have the scale.

Every day The Trade Desk’s customers log into their platform to use the data and analysis to value ad inventory and run marketing campaigns. Advertisers provide their customer data and publishers provide their user data, which The Trade Desk uses to help advertisers value media for their specific needs. As The Trade Desk accumulates more data over time, its insight and analysis add more value to its customers, creating a self-reinforcing virtuous cycle.


Nvidia’s new Turing architecture is all about real-time ray tracing and AI

Nvidia describes the new Turing architecture as “the greatest leap since the invention of the CUDA GPU in 2006.”

“Hybrid rendering will change the industry, opening up amazing possibilities that enhance our lives with more beautiful designs, richer entertainment and more interactive experiences,” said Nvidia CEO Jensen Huang. “The arrival of real-time ray tracing is the Holy Grail of our industry.”

The new RT cores can accelerate ray tracing by up to 25 times compared to Nvidia’s Pascal architecture, and Nvidia claims 10 GigaRays a second for the maximum performance.

With NGX, Nvidia today also launched a new platform that aims to bring AI into the graphics pipelines. “NGX technology brings capabilities such as taking a standard camera feed and creating super slow motion like you’d get from a $100,000+ specialized camera,” the company explains, and also notes that filmmakers could use this technology to easily remove wires from photographs or replace missing pixels with the right background.


Tesla’s autonomous opportunity is severely underappreciated

We estimate that net revenue for autonomous platform providers – those companies that own the software technology stack for autonomous ride-hailing services – should exceed $2 trillion by 2030, roughly equal to our expectations for automaker revenue at that time. Unlike their auto-manufacturing peers, however, autonomous platform providers should see software-like margins, be less capital-intensive, and enjoy network-effect-driven regional competitive dominance. So, while autonomous platform providers may generate the same revenue as automotive manufacturers, ARK believes these providers will generate six times the operating earnings and consequently will prove to be substantially more valuable. In fact, ARK estimates autonomous platforms will be worth more than the entire $4 trillion global energy sector.

An enhanced Autopilot package with the ability to self-drive costs $5,000 upfront or $6,000 for customers who choose to wait and buy later. Payment for this feature alone can be thought of as nearly pure profit on every Tesla sold. In addition, once Tesla launches the Tesla Network, its autonomous ride-hailing network, it could collect platform fees, similar to Uber’s model today, from every autonomous ride charged to the consumer. Given a rate of $1 per mile to the end consumer and over 100,000 miles per year per vehicle, Tesla could benefit from $20,000 in high-margin platform fees per car per year. Over a five-year lifetime, a single Model 3 could generate $40,000 in net cash flow. Even investors optimistic about Tesla’s prospects project the Model 3 cash flow at $4,000 and one-time in nature. In effect, each Model 3 sale could generate 10 times more cash flow than investors currently understand.

Google’s targeted ads are coming to a billboard near you

Digital outdoor ad spending is growing at 15 percent annually, and will overtake traditional outdoor outlays by 2020, according to PwC. But Google is the 800-pound gorilla that’s not yet in the room. It would give the company another major edge over Facebook, which doesn’t have the same access to location-based mobile data.


Alibaba tweaks a controversial legal structure

There are three problems with VIEs. First, key-man risk. If the people with nominal title die, divorce or disappear, it is not certain that their heirs and successors can be bound to follow the same contracts. Second, it is not clear if the structure is even legal. China’s courts have set few reliable precedents on VIEs and the official position is one of toleration rather than approval. Third, VIEs allow China’s leading tech firms to be listed abroad, preventing mainlanders from easily owning their shares and participating in their success.

Alibaba’s proposed change is aimed at tackling the first problem, key-man risk. At the moment four of its five VIEs are nominally owned by Jack Ma, the firm’s leader, and Simon Xie, a co-founder and former employee. After the restructuring, the two men will no longer be the dominant counterparties. Instead the VIEs will be owned by two layers of holding companies, which will sign contracts with Alibaba. These holding companies will ultimately be nominally owned by a broader group of Alibaba’s senior Chinese staff. The idea is that if anyone gets run over by a bus, then the scheme will not be disrupted, because nominal control is spread among a wider group of people. The new approach is far from perfect but it is an improvement. If all goes to plan it will be completed by 2019. Other tech firms may feel pressure to follow.

$1b+ market map: The world’s 260 unicorn companies in one infographic
60+ startups disrupting IKEA in one market map

SoftBank’s Son says WeWork is his ‘next Alibaba’

It is rare for Son, who casts a wide net with his startup investments, to commit so much resources to a single company. But he said WeWork is more than just a renter of office space: it is “something completely new that uses technology to build and network communities.”

The use of shared space to forge connections is not unique to WeWork. The company’s edge lies in the steady flow of data it collects on members, which is shared with other locations and can be accessed by users of the WeWork app around the world. The idea is that more data means more innovation — a model that underlies Son’s excitement about the company.

What MoviePass can teach us about the future of subscription businesses

Pricing is so powerful that playing with it requires great skill and precision. MoviePass should have done its price experimentation at the outset and on a local basis. It could have optimized the price points and tested alternative pricing models quietly, instead of jerking millions of customers around. Even a slight tweak — such as moving to a club pricing model like Costco’s — might have solved its cash-flow problems.

These kinds of tweaks could also have enabled the company to consider regional pricing strategies, given that its cost of goods (the full price of movie tickets, which it pays theater operators) varies from $8 in Nebraska to over $15 in New York. This case is also a good reminder that the United States has local profit pools. It is silly to think that a one-size-fits-all national strategy is the right approach for a market as ethnically and economically diverse as the United States.

MoviePass failed to recognize how the behavior of superconsumers, customers who are highly engaged with a category and a brand, differs from that of average consumers — and how, if not anticipated, this difference can create problems for a company’s cost model. It can especially be a problem if the company uses a “buffet” model of fixed price and unlimited quantities, as MoviePass did.

Quantum computers today aren’t very useful. That could change

Quantum computers are, however, far more prone to errors than binary machines. Instead of using electric signals to generate a series of zeros and ones like a conventional computer, quantum computers rely on the real-world, mechanical behavior of photons, which are packets of microwave energy. The machines require a complex, multi-layered refrigeration process that brings quantum chips to a temperature just above absolute zero. By eliminating certain particles and other potential interference, the remaining photons are used to solve computational problems. The true magic of this system is how photons can become entangled and produce different but related results. Scientists only partially understand why it works the way it does.

A quantum chip doesn’t look like much with the naked eye. Through an optical microscope, though, you can see the quantum logic gate that makes everything possible. The team here is working on a process of stringing together 16-qubit chips to execute on the 128-qubit design. Essential to this is a new kind of quantum chip that communicates results in three dimensions instead of the current two, which allows Rigetti to fit the chips together like puzzle pieces and turn them into a single, more powerful computer. “What we’re working on next is something that can be scaled and tiled indefinitely,” Bestwick said.

Why the future belongs to ‘challenge-driven leaders’

The consensus view of Mr. Marchionne, relayed by hundreds of tributes, is that he possessed an unusual blend of vision, technical expertise, analytical rigor, open-mindedness and candor. The remembrances also agreed on something else: he was a bona fide eccentric. “God bless you, Sergio,” Morgan Stanley analyst Adam Jonas told Mr. Marchionne during a January conference call. “We’re never going to see anyone like you again.”

The trajectory of great ideas

“Being right is the enemy of staying right because it leads you to forget the way the world works.” – Jason Zweig. Buddhism has a concept called beginner’s mind, which is an active openness to trying new things and studying new ideas, unburdened by past preconceptions, like a beginner would. Knowing you have a competitive advantage is often the enemy of beginner’s mind, because doing well reduces the incentive to explore other ideas, especially when those ideas conflict with your proven strategy. Which is dangerous. Being locked into a single view is fatal in an economy where reversion to the mean and competition constantly dismantles old strategies.

Survivorship bias on wheels

One last thing: When it was introduced as new in 1984, the 1985 Testarossa listed for $90,000 (but dealers charged huge premiums over list due to “Ferrari fever.”) You can still find Testarossas for that original list price — meaning the net returns over 43 years has been precisely zero — before maintenance, storage and repair costs.

As a comparison, in 1985, the benchmark S&P500 was about 200, and it closed yesterday at 2,821.93. That generated an average annual return of about 8.5%, returning 1,400% price appreciation since then, and, with dividends reinvested, over 3,000% total return (in nominal terms, like the chart above, neither is adjusted for inflation).

Selecting investments after the fact is easy; ask yourself this question: What car do you want to buy as an investment for the next 34 years to be sold in 2052?


Curated Insights 2018.07.06

What would happen if China started selling off its Treasury portfolio?

And the perennial threat that China would sell its Treasuries. That could happen as a byproduct of a decision by China to push its currency down—if China signals that it wants a weaker currency, the market would sell yuan for dollars, and controlling the pace of depreciation would require that China sell reserves. Or could happen even if China maintained its current basket peg and shifted its portfolio around—selling Treasury notes for bills, or selling Treasuries and buying (gulp) Bunds (if it can find them—it might end up buying French bonds instead) or JGBs.

If Treasury sales came in the context of a decision by China that it wanted a weaker currency to offset the economic impact of Trump’s tariffs (or simply a decision by the PBOC that it needed to loosen monetary policy in response to a slowing Chinese economy, and thus to no longer follow the Fed), the disinflationary impulse from a weaker yuan (and a broader fall in most Asian currencies and a rise in the dollar) would likely be more powerful than the mechanical impact of Treasury sales. That is the lesson of 2015-16.

Treasuries sales in a sense are easy to counter, as the Fed is very comfortable buying and selling Treasuries for its own account. I have often said that the U.S. ultimately holds the high cards here: the Fed is the one actor in the world that can buy more than China can ever sell.

Who has the best business model (and it’s not Google or Facebook)

Staying on the topic of streaming video, this is a relevant example of how shared-value transactions gives Amazon a potential structural advantage over the leader in the space: Netflix. Success in streaming video requires great video content, and Netflix will spend $8 billion this year buying video rights. The way Netflix funds this hefty content bill is that they have 120 million customers who pay them $10 each month directly, and then they take half of that fee collected from every subscriber and spend it on content. So every subscriber pays for content equally (about $5 per user per month) as Netflix earns the exact same amount from their best users as their worst users.

Amazon too will spend a significant sum buying video content (about $5 billion this year). But their content bill is paid entirely differently. Instead of only depending on a percentage of Prime membership fees (which are the same for every user) to fund their content budget, Amazon can pay for content using revenue from purchases of books, diapers, toilet paper, laundry detergent, and more (and this spend is most definitely not the same for every user). As Bezos has said: “When we win a Golden Globe, it helps us sell more shoes”. Amazon’s best users are able to purchase significantly more goods than their average user, and these funds can be indirectly applied to fund video content that everyone shares value from.


Dropbox vs. Box: The story of enterprise SaaS multiples

By digging deeper into the operating margins, we find that the difference between the two companies seems to come down to the approaches of their growth strategies. Dropbox has grown primarily through a highly efficient marketing function and self-serve model, while Box has grown through a traditional, and more expensive, enterprise sales model.

This story hides some major issues with Dropbox. Their strategy for years has been to go after the consumer cloud storage market, which never made sense, as that market is highly competitive and has limited revenue potential. Box decided long ago to pivot to the enterprise, while Dropbox went through numerous failed acquisitions and internal initiatives, attempting to build products in everything from email to payments. They built a strong consumer brand in the process but ultimately decided to double down on enterprise. We think it’s too late.

The cloud storage and file hosting industry, including all the related services, doesn’t seem to be protected by a particularly wide moat. All of the major technology names are active in this field as well, including Amazon, Google, Microsoft, and Apple. All of these companies have the added advantage of pre-existing customer relationships. The main advantage Dropbox would need is the ability to provide differentiated services to enterprises. However, we haven’t seen evidence of Dropbox’s ability to effectively build differentiated enterprise products. As they are forced to expand their market, we believe they will face stiff competition that will make it more difficult to grow. On the other hand, the 500 million users may be the key to unlocking growth within enterprises that enterprise sales teams couldn’t effectively crack.

The Airbnb challenger you’ve never heard of (by name)

Airbnb has reportedly spent only $300 million on marketing since its inception in 2008. “We don’t acquire customers by buying them. We acquire customers by providing a superior experience and having offerings around the world,” a spokesperson emailed.

Booking spent $4.5 billion on marketing last year alone. Yet Fogel admits that it still lags in consumer awareness. The brand is much better known in Europe, where it was founded. “The product is just as good here as anywhere else … and therefore we should have much more [awareness],” he says, noting that Booking.com only came to the US in 2013. Booking Holdings’ other brands, like Priceline and Kayak, have loyal bases of users, Fogel says. But Booking.com makes up the vast majority of the company’s revenue, and the name change from Priceline to Booking Holdings shows what executives consider their crown jewel.

Airbnb is fighting back with two high-end tiers of hotel-like offerings and luxury accommodations, Airbnb Plus and Beyond by Airbnb. The company emphasizes that 3.5 million of its listings are exclusive and that business travel now makes up 15 percent of its bookings. Beyond that, Airbnb has been selling tourist activities to its customers through its Experiences product for two years.


A $6 billion China startup wants to be the Amazon of health care

WeDoctor’s data comes from several sources, but one of the most important is the hundreds of hospitals in its network whose doctors plug information into a central database — with consent from patients who may want to switch care-givers. They could also upload their own records. The company then profiles users, classifying them in buckets based on age, gender, region or symptoms. That’s a potent advertising aid to drugmakers and insurers, Chen says. That leeway to commercialize patient information comes with caveats: WeDoctor stresses data is anonymous and it doesn’t share it with third parties.

That’s just one piece of the money-making puzzle. WeDoctor also takes a cut on consultation fees via its app or smart speaker. The 4,000 yuan box has a screen in the front and comes with a year’s access to doctors online.

Those clinics complement “online hospitals.” WeDoctor’s won licenses to operate 10 such platforms that offer real-time chats with doctors. This also lets the best clinicians, usually working out of big hospitals that keep fees artificially low, to earn more on the side. Top doctors can demand 3,000 yuan per session, WeDoctor says.

WeChat Impact Report 2018 shows impressive social impact

WeChat-driven information consumption reached RMB 209. 7 billion
WeChat accounted for 34% of the total data traffic of users
WeChat drove RMB 333.9 billion traditional consumption, covering travel, food, shopping, tourism, etc.
WeChat contributed the employment of 20.3 million persons in 2017, more than twice the 2014 figure
The number of stores accepting WeChat Payment in Japan was multiplied by 35 in 2017

China isn’t playing tech catch up – it’s leapfrog and it may get dirty

According to business managers, many of those three million annual science and technology graduates lack crucial analytical and communication skills, and are barely employable. Similarly, a large proportion of those 430,000 research papers have little or no scientific value. And many of China’s 1.4 million yearly patent applications are destined to prove worthless. In fact, fewer than 20 per cent of China’s applications even claim to be for new inventions; the vast majority are for lower-tier design or utility model patents, which typically cover minor incremental changes to existing products.

Inventive economies generate handsome international income streams by licensing their technologies to foreign companies, which then pay them intellectual property royalties. In 2016, China earned just US$1 billion from the rest of the world in intellectual property payments. In contrast it paid out US$24 billion (and according to many critics, it should have paid a great deal more). Now compare those numbers with the equivalent figures for the US, which last year earned US$128 billion from licensing its intellectual property to other countries, while paying out US$48 billion. Meanwhile, Japan earned US$35 billion, and paid out US$18 billion.

The thought father: Nobel Prize-winning psychologist Daniel Kahneman on luck

One of the most amusing episodes in the book comes when Kahneman visits a Wall Street investment firm. After analysing their reports, he calculated that the traders, who were highly prized for their ability to “read” the markets, performed no better than they would have done if they made their decisions at random. The bonuses that they received were, therefore, rewards for luck, even though they found ways of interpreting it as skill. “They were really quite angry when I told them that,” he laughs. “But the evidence is unequivocal — there is a great deal more luck than skill involved in the achievements of people getting very rich.”


Better ways to learn

“When you are cramming for a test, you are holding that information in your head for a limited amount of time,” Mr. Carey says. “But you haven’t signaled to the brain in a strong way that’s it’s really valuable.”

One way to signal to the brain that information is important is to talk about it. Ask a young student to play “teacher” based on the information they have studied. Self-testing and writing down information on flashcards also reinforces learning.

“Sleep is the finisher on learning,” Mr. Carey says. “The brain is ready to process and categorize and solidify what you’ve been studying. Once you get tired, your brain is saying it’s had enough.”

Curated Insights 2018.05.20

The spectacular power of Big Lens

There is a good chance, meanwhile, that your frames are made by Luxottica, an Italian company with an unparalleled combination of factories, designer labels and retail outlets. Luxottica pioneered the use of luxury brands in the optical business, and one of the many powerful functions of names such as Ray-Ban (which is owned by Luxottica) or Vogue (which is owned by Luxottica) or Prada (whose glasses are made by Luxottica) or Oliver Peoples (which is owned by Luxottica) or high-street outlets such as LensCrafters, the largest optical retailer in the US (which is owned by Luxottica), or John Lewis Opticians in the UK (which is run by Luxottica), or Sunglass Hut (which is owned by Luxottica) is to make the marketplace feel more varied than it actually is.

Now they are becoming one. On 1 March, regulators in the EU and the US gave permission for the world’s largest optical companies to form a single corporation, which will be known as EssilorLuxottica. The new firm will not technically be a monopoly: Essilor currently has around 45% of the prescription lenses market, and Luxottica 25% of the frames. But in seven centuries of spectacles, there has never been anything like it. The new entity will be worth around $50bn (£37bn), sell close to a billion pairs of lenses and frames every year, and have a workforce of more than 140,000 people. EssilorLuxottica intends to dominate what its executives call “the visual experience” for decades to come.

For a long time, scientists thought myopia was primarily determined by our genes. But about 10 years ago, it became clear that the way children were growing up was harming their eyesight, too. The effect is starkest in east Asia, where myopia has always been more common, but the rate of increase has been uniform, more or less, across the world. In the 1950s, between 10% and 20% of Chinese people were shortsighted. Now, among teenagers and young adults, the proportion is more like 90%. In Seoul, 95% of 19-year-old men are myopic, many of them severely, and at risk of blindness later in life.

Del Vecchio paid $645m (£476m) for Ray-Ban. During the negotiations, he promised to protect thousands of jobs at four factories in the US and Ireland. Three months later, he closed the plants and shifted production to China and Italy. Over the next year and a half, Luxottica withdrew Ray-Ban from 13,000 retail outlets, hiked their prices and radically improved the quality: increasing the layers of lacquer on a pair of Wayfarers from two to 31. In 2004, to the disbelief of many of his subordinates, del Vecchio decided that Ray-Ban, which had been invented for American pilots in the 1930s, should branch out from sunglasses into optical lenses, too. “A lot of us were sceptical. Really? Ray. Ban. Banning rays from the sun?” the former manager said. “But he was right.” Ray-Ban is now the most valuable optical brand in the world. It generates more than $2bn (£1.5bn) in sales for Luxottica each year, and is thought to account for as much as 40% of its profits.

The Moat Map

Facebook has completely internalized its network and commoditized its content supplier base, and has no motivation to, for example, share its advertising proceeds. Google similarly has internalized its network effects and commoditized its supplier base; however, given that its supply is from 3rd parties, the company does have more of a motivation to sustain those third parties (this helps explain, for example, why Google’s off-sites advertising products have always been far superior to Facebook’s).

Netflix and Amazon’s network effects are partially internalized and partially externalized, and similarly, both have differentiated suppliers that remain very much subordinate to the Amazon and Netflix customer relationship.

Apple and Microsoft, meanwhile, have the most differentiated suppliers on their platform, which makes sense given that both depend on largely externalized network effects. “Must-have” apps ultimately accrue to the platform’s benefit.

Apple’s developer ecosystem is plenty strong enough to allow the company’s product chops to come to the fore. I continue to believe, though, that Apple’s moat could be even deeper had the company considered the above Moat Map: the network effects of a platform like iOS are mostly externalized, which means that highly differentiated suppliers are the best means to deepen the moat; unfortunately Apple for too long didn’t allow for suitable business models.

Uber’s suppliers are completely commoditized. This might seem like a good thing! The problem, though, is that Uber’s network effects are completely externalized: drivers come on to the platform to serve riders, which in turn makes the network more attractive to riders. This leaves Uber outside the Moat Map. The result is that Uber’s position is very difficult to defend; it is easier to imagine a successful company that has internalized large parts of its network (by owning its own fleet, for example), or done more to differentiate its suppliers. The company may very well succeed thanks to the power from owning the customer relationship, but it will be a slog.

How much would you pay to keep using Google?

Part of the problem is that GDP as a measure only takes into account goods and services that people pay money for. Internet firms like Google and Facebook do not charge consumers for access, which means that national-income statistics will underestimate how much consumers have benefitted from their rise.

Survey respondents said that they would have to be paid $3,600 to give up internet maps for a year, and $8,400 to give up e-mail. Search engines appear to be especially valuable: consumers surveyed said that they would have to be paid $17,500 to forgo their use for a year.


There is another

Spotify has better technology, merchandising (like discovery playlists), and brand. Unlike Apple Music, being a pure-play (as opposed to being owned by a tech giant) gives Spotify more cred among purists, young people, and influencers. The instinct / T Algorithm cocktail has resulted in a firm with 170M users, 75M of whom are premium subscribers. The firm registered €1B this quarter, representing 37% growth. Spotify accounted for 36% of premium music subscribers globally.

What takes Spotify to $300B, and true horseman status? They launch video, and become the most successful streaming entertainment firm, full stop. Netflix’s legacy is on the second most important screen, TV. Spotify was raised on the most important – mobile. Netflix needs to become Spotify before Spotify becomes Netflix. Nobody has cracked social and TV, and as half of young people no longer watch cable TV, if Spotify were to launch video and captured any reasonable share and engagement via unique playlists, then cable and Netflix would begin ceding market cap to Spotify.


Subscriptions for the 1%

The problem with these minuscule conversion rates is that it dramatically raises the cost of acquiring a customer (CAC). When only 1% of people convert, it concentrates all of that sales and marketing spend on a very small sliver of customers. That forces subscription prices to rise so that the CAC:LTV ratios make rational sense. Before you know it, what once might have been $1 a month by 20% of a site’s audience is now $20 a month for the 1%.

There is a class of exceptions around Netflix, Spotify, and Amazon Prime. Spotify, for instance, had 170 million monthly actives in the first quarter this year, and 75 million of those are paid, for an implied conversion of 44%. What’s unique about these products — and why they shouldn’t be used as an example — is that they own the entirety of a content domain. Netflix owns video and Spotify owns music in a way that the New York Times can never hope to own news or your podcast app developer can never hope to own the audio content market.

The Apple Services machine

It is this hardware dependency that makes it impossible to look at Apple Services as a stand-alone business. The Services narrative isn’t compelling if it excludes Apple hardware from the equation. Apple’s future isn’t about selling services. Rather, it’s about developing tools for people. These tools will consist of a combination of hardware, software, and services.

Apple currently has more than 270 million paid subscriptions across its services, up over 100 million year-over-year. Apple is in a good position to benefit from growing momentum for video streaming services including Netflix, HBO, and Hulu. It is not a stretch to claim that Apple will one day have 500 million paid subscriptions across its services. Apple isn’t becoming a services company. Instead, Apple is building a leading paid content distribution platform.

Tencent Holdings Ltd. delivered two major milestones when it reported its earnings Wednesday: record quarterly profits and more than one billion monthly active users on its WeChat platform. The social media and gaming giant, which has been leery of barraging its users with ads, also declared it had raised the maximum number of ads that customers see on WeChat Moments from one a day to two. The app has become China’s most popular messaging service and is integral to driving everything from gaming and payments to advertising for Tencent.

MoviePass: the unicorn that jumped into Wall Street too soon

“The growth-at-all-costs strategy is being funded these days by the venture community, not the public market. The last time we saw the public markets fund a growth-at-all-costs strategy was the 1999 internet bubble, and we all know how that ended.”

The prospect of steep declines in a company’s valuations once it hits the public markets is one reason why U.S. companies are waiting longer to go public. Overall, U.S. companies that have gone public this year have done so at an average market capitalization of $1.1 billion, according to Thomson Reuters data, a 44 percent increase from the average market cap during the height of the dot com craze in 1999. At the same time, companies are now going public 6.5 years after receiving their first venture capital backing on average, more than double the three years between initial funding and going public in 1999.

Cerebras: The AI of cheetahs and hyenas

The specialist starts out with a technology optimized for one specific task. Take the graphics-processing unit. As its name denotes, this was a specialist technology focused on a single task–processing graphics for display. And for the task of graphics, graphics-processing units are phenomenal. Nvidia built a great company on graphics-processing. But over time, the makers of graphics-processing units, AMD and Nvidia, have tried to bring their graphics devices to markets with different requirements, to continue the analogy to hunt things that aren’t gazelle. In these markets, what was once a benefit, finely tuned technology for graphics (or gazelle-hunting), is now a burden. If you hunt up close like a leopard and never have to run fast, having your nose smooshed into your face is not an advantage and may well be a disadvantage. When you hunt things you were no longer designed to hunt, the very things that made you optimized and specialized are no longer assets.

Intel is the classic example of a generalist. For more than 30 years the x86 CPU they pioneered was the answer to every compute problem. And they gobbled up everything and built an amazing company. But then there emerged compute problems that specialists were better at, and were big enough to support specialist companies—such as cell phones, graphics and we believe AI. In each of these domains specialist architectures dominate.

We are specialists, designing technology for a much more focused purpose than the big companies burdened with multiple markets to serve and legacy architectures to carry forward. Specialists are always better at their target task. They do not carry the burden of trying to do many different things well, nor the architectural deadweight of optimizations for other markets. We focus and are dedicated to a single purpose. The question of whether we—and every other specialist– will be successful rests on whether the market is large enough to support that specialist approach. Whether, in other words, there are enough gazelle to pursue. In every market large enough, specialists win. It is in collections of many modest markets, that the generalist wins. We believe that the AI compute market will be one of the largest markets in all of infrastructure. It will be the domain of specialists.


This $2 billion AI startup aims to teach factory robots to think

What sets Preferred Networks apart from the hundreds of other AI startups is its ties to Japan’s manufacturing might. Deep learning algorithms depend on data and the startup is plugging into some of the rarest anywhere. Its deals with Toyota and Fanuc Corp., the world’s biggest maker of industrial robots, give it access to the world’s top factories. While Google used its search engine to become an AI superpower, and Facebook Inc. mined its social network, Preferred Networks has an opportunity to analyze and potentially improve how just about everything is made.

At an expo in Japan a few months later, another demo showed how the tech might one day be used to turn factory robots into something closer to skilled craftsmen. Programming a Fanuc bin-picking robot to grab items out of a tangled mass might take a human engineer several days. Nishikawa and Okanohara showed that machines could teach themselves overnight. Working together, a team of eight could master the task in an hour. If thousands — or millions — were linked together, the learning would be exponentially faster. “It takes 10 years to train a skilled machinist, and that knowledge can’t just be downloaded to another person” Fanuc’s Inaba explained. “But once you have a robot expert, you can multiply it infinitely.”

China buys up flying schools as pilot demand rises

In September Ryanair axed 20,000 flights due to a rostering mess-up made worse by pilot shortages. This forced the low-cost carrier to reverse a longstanding policy and recognise trade unions and agree new pay deals — a move that it said would cost it €100m ($120m) a year from 2019.

China is on course to overtake the US as the world’s largest air travel market by 2022, according to the International Air Transport Association.

US aircraft maker Boeing predicts China will need 110,000 new pilots in the years through to 2035, and its airlines are expected to purchase 7,000 commercial aircraft over the next two decades.

China’s aviation market grew by 13 per cent last year, with 549m passengers taking to the skies, double the number who flew in 2010. Growth is being driven by the rising middle class, an expansion of routes by Chinese airlines and the easing of visa restrictions by foreign governments keen to attract Chinese tourists.

California will require solar power for new homes

Long a leader and trendsetter in its clean-energy goals, California took a giant step on Wednesday, becoming the first state to require all new homes to have solar power.

The new requirement, to take effect in two years, brings solar power into the mainstream in a way it has never been until now. It will add thousands of dollars to the cost of home when a shortage of affordable housing is one of California’s most pressing issues.

Just half a percent

If you save $5,000 a year for 40 years and make only 8% (the “small” mistake), you’ll retire with about $1.46 million. But if you earn 8.5% instead, you’ll retire with nearly $1.7 million. The additional $230,000 or so may not seem like enough to change your life, but that additional portfolio value is worth more than all of the money you invested over the years. Result: You retire with 16% more.

Your gains don’t stop there. Assume you continue earning either 8% or 8.5% while you withdraw 4% of your portfolio each year and that you live for 25 years after retirement. If your lifetime return is 8%, your total retirement withdrawals are just shy of $2.5 million. If your lifetime return is 8.5% instead, you withdraw about $3.1 million. That’s an extra $600,000 for your “golden years,” a bonus of three times the total dollars you originally saved.

Your heirs will also have plenty of reasons to be grateful for your 0.5% boost in return. If your lifetime return was 8%, your estate will be worth about $3.9 million. If you earned 8.5% instead, your estate is worth more than $5.1 million.

Keep your investment costs low.
Slowly increasing your savings rate over time.
Consistently saving while treating investment contributions like a periodic bill payment.
Bettering your career prospects to increase your income over time.
Avoiding behavioral investment mistakes which can act as a counterweight to the benefits of compounding.