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Dear avid readers,

We're flying to Romania this morning, where we'll stay at an Airbnb. I also published a rather-long article recently which I hope you'll enjoy, about Airbnb's premature abandonment of its initial mission statement: serve customers that were otherwise un-served. Tech-enabled platforms are best positioned to enable an alliance between the amateurs and the professionals to satisfy peak demands, benefiting all stakeholders, and there is still plenty of wind ahead, if only Brian Chesky would pay more attention to politics as a leverage for further legitimising his business.

One question that I sometimes get asked is if I think this digest is too long for people to have the time to read it. The same critique goes nowadays, it seems, towards most economic papers (not that I`m comparing this digest with economic research!) that are being published, as they seem to be getting longer and longer, making peer-review and assessment process more demanding. 

One aspect that we must keep in mind, and one that this newsletter tries to help us achieve is that, in the age of abundant (and duplicated) information, being distracted is a norm. Hence, it is the skill to stay focused for longer periods of time that will be an individual's competitive advantage in the new economy, as opposed to the stroll through out-of-context, randomly sorted titles, in the hope to know-it-all, which is both impossible and damn unsatisfying.

A second aspect is that this digest is not necessarily intended for being read in one go! The content does not expire - as it does not contain breaking news. Most readers come back to it numerous times to pick up from where they were left, since it is organised by topics and sub-sections.

A third aspect would be that it is counter-intuitive to think that it consumes readers time, when in fact the feedback I receive is that it actually saves them time. By entrusting in this email to deliver them all the quality content produced in the past 2-3 weeks, narrated and contextualised, they are able to break the habit of addiction to feeds, recovering their sanity and improving relationship with family and friends. When a reading is long and satisfying, it removes the instinct of scrolling through the online algorithmic feeds for shallow, random content. 


So I was inspired to do a quick word-count analysis on how this digest evolved over time, from back in September 2017 when I started it. As imagined, as knowledge compounds, the reading community of this digest is able to stay focused through an increasing number of ideas from both-sides of the coin on multiple topics. Think of how valuable this is, relative to the person next to you that swipes through knowledge almost tinder-style, as we speak. Here's how Strategy, digested evolved:
With this being said, this newsletter will intend to keep the same structure, allowing you to disconnect from daily twitter vortex without the fear of missing out. 

As Dave Pell wrote recently, newsletters are immortal, since they are personal, persistent, personalized, permanent, performant and perpetual

On to the Digest!

By the way - I fixed the problem with the horizontal scrolling on mobile. 

Strategy and Business Models in the Digital Age


Consumers startups are dead. Long live consumer startups.

🔑 Eric Feng again with a great article exploring if there are any fruits left in the economy for any new consumer startup, since the golden age of direct-to-consumer (D2C) unicorns seems to consist mainly of startups created between 2009 and 2012, with volumes declining afterwards, as the past 5 years, despite producing some great consumer startups, were not able to keep pace. One way to look at it it’s that it has become incredibly hard, with the FAANGs increasing market power (80% of the value of the FAANG was generated after 2013). This implies in a way that whereas 2009-2013 created new market leaders, 2013-2018 only reinforced established market leaders and their competitive advantage (network effects, unparalleled distribution advantages, tech talent absorption). But Eric argues that there is still room for new players, since today’s average mobile users are savvy enough and product-fluent to comfortably use multiple services simultaneously. Which implies that with the right value proposition, a startup can co-exist alongside incumbents. The door is still open, just not as wide as before, and there are reasons to believe that a second rebellion of new startups can happen again (customers’ multi-product savviness, examples of apps still becoming overnight-hits in app-stores, technology becoming more accessible to builders).


🚪 Christopher Mims argues that the most important competitive advantage for today’s established market leaders (either the tech giants like FAANGs or more traditional companies like Walmart, CVS, UPS, Nissan, Pfizer, Roche), is the huge amount of money they are able to invest in their own tech. He believes that one of the biggest competitive advantages that these firms have is the IT spending that goes into hiring developers and creating proprietary software (and even hardware) owned and used exclusively internally, by the firm for its operations (vs. using external firms). This is contrary to Eric’s point above, as Christopher is arguing that technology diffusion is slowing down, because of increased complexity, it is becoming harder to separate technology from systems and processes (i.e. Facebook’s artificial intelligence cannot be simply replicated), meaning it’s becoming harder, if not impossible, for newer, smaller companies to build enough meaningful threat.  

🤝 There is increasing talk about the potential to unbundle Procter & Gamble, since, within the consumer packaged goods space, the digital economy makes 'small' to be 'superior', primarily as growth has shifted to brands that have cultivated direct relationship with consumers, argues Sunny Dhillon. He explores the two areas in which the direct-to-consumer (D2C) disruption is happening, which aren’t exclusive to each other: a) supply-chain disruption which provides a fast and effective way to gain traction and steal market share from incumbents (new business models that greatly simplify the front-end, remove intermediaries and reduce or eliminate friction); and b) brand disruptions which builds a competitive moat, reduces CAC and increases LTV (startups that are able to create super-engaged customers and a devoted digital community, as opposed to traditional advertising).
 

🎇 More on this, Li Jin of a16z posted a great thread about the imperative of consumer startups, especially the ones that are created to leverage the brand of an influencer, to evolve and become “purpose brands” (inextricably linked with specific jobs). Think of Kylie Jenner's cosmetics business (person-centric) versus Gwyneth Paltrow's Goop (which evolved beyond her brand - but this beautifully written essay will underline some of its ridiculousness, and further contributes to the idea that "lifestyle brands" are the new marketing BS). Li writes that in today's digital world, with compressed hype cycles and without the benefit of multi-year retail or broadcasting contracts, celeb-underpinned brands can fade even faster, because individual popularity inevitably wanes - which in turn creates an opportunity for new startups that can align themselves with broader movements and communities, but also deliver superior products at scale.

💤 These days, consumers are less likely to have favourite brands, writes Ian Leslie in this article titled ‘The death of Don Draper’ (he is the embodiment of the advertising industry in the 60s), since most interaction is now handled by Google, Facebook, Amazon, so they are orchestrating what is the right product served at the right time to consumers (commoditizing brands in the meantime). Shopping is now an engineering problem, not a creative process. In the same time, Ian makes the point that some of the adtech efficiency rates are overrated, and it is superficial to believe that storytelling is dead, since micro-targeting has a major lacuna: aligning a brand with broader movements and communities implies ads must be visible to broader audiences in the same time, rather than one-on-one. So maybe Don Draper is not dead, but merely a sleeping giant?

🎇 The brand vs. brandless game is definitely on. This startup aims to go all-in on the engineering story: that is, Brandless is the future of online e-commerce.

On metrics and what happens after product/market fit

🎤 Excellent interview of Marc Andreessen, taken by Elan Gid, where Marc argues there are three important steps after a company achieves product/market fit: 1/ taking the market, meaning achieving dominant market share. This requires a well tuned distribution machine, as successful tech companies arguably become distribution-centric rather than product-centric in time; then 2/ get to the next product (as every product in tech becomes obsolete), by leveraging the distribution-channel (which acts as a moat against better new-products from other startups); to expand total addressable market; and 3/ getting the painful org structure in place, HR, legal, marketing, IR etc. To complement this article, I recommend also Suhail's tweetstorm.
 

👩‍🔬 Shifting the balance back to product-centricity, Tom Tunguz segments any tech product features-roadmap into three layers: 1/ minimum market requirements; 2/ neutralizers that mitigate competitive advantage; 3/ differentiators, or the reason the customers prefer the solution to alternatives, and they become clearer after product/market fit. The danger, therefore, of relying too much on customer feedback with no understanding of the strategic positioning is that customers will provide more feedback related to points 1/ and 2/, but customers rarely push tech vendors to further their differentiation (since the differentiating features might not even be obvious to customers). So what Tom argues that sometimes, premature or excessive distribution focus would direct engineering efforts mainly to MMRs and competitive neutralizers, and less on differentiators, and this can leave a company exposed to having its product replicated. But then again, does simply having a superior product means one can win market share?
 

📐 Andrew Chen on the fallacy of being overly focused on the DAU/MAU metric (that is, the total daily active users divided to the total monthly active users, a metric which was popularized by Facebook) to assess product/market fit. That is because there are still highly-valuable products (either consumer, either SaaS - LinkedIn, Airbnb, Dropbox, and of course, e-commerce) where usage is not necessarily required to be daily, but rather episodic, and more important could be lifetime value, or the quality of data generated, or the value generated by the most active user-cohort, or simply total sales volumes.

📐 Another important metric, per Benjamin Brandall, is freemium-to-paid conversion rate (that is, of the total monthly users, what percentage are paying customers). Especially if the business model is monetization through subscription rather than ads, then yes, DAU/MAU makes less sense vs. freemium conversion rate. Benjamin flags Spotify as incredibly healthy, and analyses how the platform’s user journey is well designed to lead to Premium: with 80% of all users (free and paid) using Spotify multiple times per week, and 27% of all users being paying customers (vs. 4% Dropbox, and 1% average).

🎼 Spotify is also an interesting case as it actively contributed to the expansion of its total addressable market, by reverting the downward revenue trend which the music industry was experiencing. Spotify’s Director of Economics, Will Page, publishes every year, an analysis that adds together the revenues of the whole music copyright industry, and in 2016 (last year where full data is available), the global value of music copyright in revenue terms increased by 6.1% vs. 2015 (with the biggest growth percentage taken by the collecting society network for publishers and songwriters, which dispels the myth that streaming services are paying labels too much relative to publishers and songwriters). This analysis allows Spotify to understand where and how it creates value in the chain, and probably where to invest next.
 

🔁 When choosing metrics-frameworks, the AARRR funnel (Acquisition, Activation, Retention, Referral and Revenue) was good for early stages of startup growth, but for today’s fastest growing products, a new framework is required: a Growth-Loop, writes Brian Balfour. The reasons are that funnels create strategic silos (product strategy separated from acquisition strategy, when the acquisition channels should mould the product), functional silos (with teams optimizing against each other), they operate in one direction (lacks compounding effects). Shifting to a loop mindset, strategy can be adapted to closed systems where the inputs through some process generates more of an output that can be reinvested in the input.

Where is the value in crypto?

🔀 Fred Wilson wrote again about the crypto space going through Carlota Perez’s installation phase (frenzy of innovation and capital), and it is still early days of putting the pieces in place for a completely new technology architecture. And from this architecture, of tokenized networks, the new Google, Amazon, Facebook, Airbnb will arise.

🖧 Tokenized networks represent the end of corporate rent-seeking and economic extraction, writes KJ Erickson, building on Chris’ Dixon work, as distributed, token based ecosystems will radically transform the current network-effects driven market power of tech giants: since the ability to exert market power rests on two factors: 1) that network owners and network participants have different incentives; and 2) that network participants don’t have quality, realistic alternatives. Tokenized ecosystems align incentives and ensure competitive pressure (by doubling the network effects, since all the value accrues to the participants themselves)

 

🖧 As crypto moves into the mainstream, understanding in which layer will the most value accrue is the next big challenge, argues Jeremy Liew. There are mainly three thesis of where the most value will be created: 1/ protocol layers, like Ethereum (If drawing parallels to the early days of the internet, the protocol layer produced huge value initially, but it was captured eventually by the app layer. But in decentralized networks, the reverse will be true. The challenge: fragmentation and forks); 2/ decentralized apps (dapps) as they capture people’s attention (as of today, dapps still only have a few thousand users, but can create a lot of value since they offer the potential to codify incentive structures that drive usage and reward those who contribute to the creation and development) ; 3/ access points, or wallets, as they hold the keys to interact to multiple protocols and dapps (acting therefore as the gate of access to the network, by making usage both simple and safe, aggregating therefore communities which can generate advantage). On the third layer, Albert Wenger has more angles: agent, proxy, and authenticator. A piece of software that the enduser controls and that represents him vis-a-vis the decentralized infrastructure (granting/revoking access to his data, storing and managing access to private keys).

 

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Policy, Techies and Misdemeanours


Data, responsibilities and regulation

🖧 Last month, Facebook, Google, Twitter, and Microsoft announced a data-portability project called “Data transfer project” which is a platform that aims to enable users to move their content, contacts, and more (?) across apps. This is basically platforms moving ahead of regulators and trying to create a space where “switching” is as nimble as possible, to avoid anti-trust. A few comments, though: moving all your data from facebook to twitter doesn’t mean you move all the insights about you to twitter. It is up to twitter what insights will (and is able) to draw from that data. Also, surely this could have been preceded, at least between facebook and twitter, by an agreement to properly display links shared between the platforms, with nice thumbnails (currently, when you share a facebook link on twitter, or viceversa, there is so much intentional visual friction there). This is not data portability, but it’s more similar to what would happen if telecoms would deliberately add noise to when you call from Orange to Vodafone.

📃 Separately, quoting Alex Stamos, Facebook’s departing Chief Security Officer:

🏞️ These initiatives come on the back of a growing narrative that data is a common good, and tech platforms should not be entitled to extract so much profits out of it (and for free, since basically data-labour is not paid, and even more important, taxes are not being paid, considering the massive corporate profit shifting that leads to tax avoidance, therefore leading to a missing profit of nations, as per this paper from Thomas Tørsløv, Ludvig Wier, Gabriel Zucman). So the data-commons is a topic this year, which I also touched upon in the previous digest. This time, John Battelle covers the data commons in health insurance (or the lack of). Mainly, the risk that, in a data-driven world, the things we buy, the food we eat, the time we spend watching TV or other idle activities we do like internet browsing, one’s race, education level, marital status may end up determining the price we pay for health insurance. Insurance has always been a data-driven business, but the kind of data it used in its risk assessment, argues John, were high-level data points like age and location, meaning that we were essentially being judged on a simple shared commons sharing the load of public health in common — evening out the societal costs in the process. But once the system can discriminate on a multitude of data points, the commons collapses, devolving into a system rewarding whoever has the most profitable profile - destroys the fabric of the commons. The imperative action is not neo-luddism, but to re-architect the core framework of how data flows through society.

🇨🇭 Excellent summary from Marija Gavrilov of Exponential View of a new paper titled “Digital Switzerlands” of UCLA School of Law’s Kristen Eichensehr. The context is that there is a three-player game (tech platforms, state, users) which evolved in three phases: 1/ early-days, power with users, state was to keep away; 2/ then territorial governments took control to deal with various threats; 3/ third phase is the one where tech platforms are so powerful, they are challenging the state and touting the idea that they should be responsible for laws and policy making - since they are global by nature, with a global-user base and are attractive, not extractive (debatable as well pointed out by Marija), but most importantly since they could be granted a status of neutral players (relative to nation-states). This would mean an additional layer of power over users, which without the important mechanisms of democracy such as voting and representation, can be (and has been) misused.

👨‍⚖️ Harold Feld goes deep on the other side (which is exploring how exactly should governments regulate today’s platforms). He dismisses the superficial idea of “breaking them up”, since it won’t solve privacy issues, it won’t guarantee smaller pieces won’t become dominant again, and, to quote also Benedict Evans, break them into what?. Harold also points to the fact that defining a platform is hard. What’s the scope of the regulation - will it target specific names or all platforms (is “YO” a platform?). Even more challenging is obtaining consensus on what should be the goals of public policy that must be achieved (i.e. if platforms are somewhat between telecommunication companies, for which we don’t ask them to monitor phone calls and ban hate-speech, and mass media broadcasters - which have more strict rules -, plus other characteristics, then what do we want to achieve? And what trade-offs are we prepared to make?

 

Uber narratives

✊ This research paper from Alex Wood, Vili Lehdonvirta and Mark Graham looks into the collective organisation in the gig economy and freelancing through online labour platforms (particularly in Africa and Asia) and argues that as the gig economy grows in importance, so too will the microworkers self-organisation. Currently, microworkers face significant barriers to collective organisation (physical barriers, fragmentation of platforms), and thus action.Therefore, Internet‐based communities (such as Facebook groups, forums) enable micro-workers to support each other and share information (e.g. identify fair and unfair clients, attempt to unilaterally regulate labour conditions through negatively highlighting tasks which are seen as too low-paying and admonishing each other against accepting tasks that would result in hourly earnings below some given minimum wage). This, in turn, increases their security and protection. However, these online communities are fragmented by nationality, occupation, by seniority and by platform (i.e. Indian Uber Drivers with 3+ years of experience). This can limit the scalability of action, resulting in relatively small numbers engaging in collective action.

🚘 Olivia van Nieuwenhuizen, Data Scientist, Policy Research & Economics @ Uber writes about the intangible impact Uber has on the economy. That is, there are a lot of positive externalities that aren’t measured (e.g. relief of being able to tap into transportation on an urgent matter, safety mechanisms of ride-sharing). However, citing a recent study, Olivia quantifies some of the value-add to the lives of riders and drivers. For example, in the United States, Uber’s platform supports $17 billion dollars of GDP per year over the study period, with the the net economic value-add to drivers being at $5.7 billion annually (with schedule flexibility being the most favoured amenity drivers cite - n.b. the positive impact of this is compounded when you think that U.S. does not have proper paid maternal leave, so flexibility of schedule there is much more important than what we in Europe imagine). An even more important figure is that almost a quarter of the drivers were previously unemployed before joining the platform. Which means Uber should be acknowledged as a safety layer for people who are in-between jobs. Do not underestimate the positive impact of this. Only 10% of rides are connecting to public transportation, which implies that Uber is mostly an end-to-end service, replacing public transportation.
 

👍🏿 Also, let’s not forget, that, as someone on Twitter was mentioning, now infamous Uber’s Travis Kalanick might have done more against black and poor neighbourhood discrimination than our favourite activists. This groundbreaking dissertation paper from Anne E. Brown (which I found through Benedict Evans’ newsletter), finds that, in contrast with the taxi-industry, Uber and Lyft nearly eliminate the racial differences in the taxi service, as well as improving auto-mobility for residents of lower-income, underserved neighbourhoods.

🚇 Now, if on the positive side Uber (and by extension Lyft and the others) are attracting a good part of drivers that were unemployed, on the negative side, these ride-sharing platforms are also attracting riders who otherwise have taken public transit, walked, biked, or simply avoided the trip, a new study from Bruce Schaller says. This increases the congestion problems that cities like New York have (since ride-sharing has added 5.7 billion vehicle miles to nine major urban areas over six years), and curbing this growth is necessary, if city-cores are to maintain any desirability at all, is the report’s recommendation. Now, it's easy to do Uber-backlash, but if you read this New Yorker’s essay about how bad the city’s subway system is, you can see the dilemma: do people really want to return to these poor services? The easy route of banning/curbing Uber (which as per Liya Palagashvili won't solve the traffic problem), or the complex route of re-thinking urban planning?

🇸🇬 One of Uber’s biggest threats (besides regulation like the one upcoming in New York that is looking to cap the maximum number of drivers and aggregators that aim to disintermediate it at the front-end, like CityMapper) is the sort of driver-owned ride-sharing platforms, built as tokenized networks. Apparently, there’s one that gets closer to that model, and it just launched in Singapore, called Tada, built on a dedicated distributed ledger and which will not charge any commission from its driver-partners. Apparently, it already signed up more than 2,000 driver-partners, and expects to onboard between 100 and 200 a day going forward. It will offer tokens to both drivers and riders based on their engagement, etc. Will be interesting to follow the economics of it all.
 

Housing, education, skills and wages. Economic narratives

🏡 Alex Tabarrok writes about the extreme supply restrictions in a small number of concentrated places (San Francisco, San Jose, LA, New York, Boston etc.) that decouple the housing prices from the construction costs. The results of this geographical concentration means that a substantial share of the productivity gains from technology, bio-tech and finance have gone not to producers, but to non-productive landowners (high returns to land have meant lower returns to other factors of production). Even more, the housing costs are absorbing the return on education: in the U.S., circa 25% of the increase in the wage premium that comes with college between 1980 and 2000 was absorbed by higher housing costs. Considering housing prices explored *after* 2000, that percentage is certainly must higher now. This diminishes the incentive to invest in education, which further reduces human capital and skills.

🤹 There is a narrative constructed by some companies that it is this reduced human capital and the skills shortage that is the reason for the flat wage growth over the past decades. But Heidi Shierholz and Elise Gould argue that this has backwards logic: when employers can’t find workers with the skills they need at the wages they are offering, they will raise wages in order to attract qualified workers from competition (which will counter-offer, so further increasing the wages). More realistically, the reason is the companies’ monopsony power (reduced number of buyers of labour in a certain industry or geography), so employers are stuck in their own paradox: monopsony power enables them to offer and maintain wages low, but when they would like to hire more workers, the low wages they offer mean they can’t attract more workers unless they pay more. So it’s their own choice that renders them unable to attract more workers as they expand.
 

📈 A more likely culprit for stagnating wages is the fact that companies spent roughly $7 trillion on their own shares buybacks from 2004 to 2014, and have spent hundreds of billions of dollars on buybacks in the past six months alone, writes Annie Lowrey, citing a a new report by Irene Tung of the NELP and Katy Milani of the Roosevelt Institute. For example, the restaurant industry spent 140% of its profits on buybacks from 2015 to 2017, retail industry 80%, and food-manufacturing firms nearly 60%  (surely that’s not sustainable, right?). Now, if all those money were to be diverted into higher wages, which in turn powers more consumption etc. This is the equivalent of not having a proper social insurance for the many, with the argument that “we can’t afford it”.

 

⛓️ Another issue is the ever-growing intermediary chains that stand between employers and workers. For example, about half of Google’s workers are contractors, and obviously they don’t receive the same benefits as direct employees, write Mark Bergen and Josh Eidelson. Hiring contractors keeps the official headcount low, and frees up millions of dollars to retain superstars in fields like artificial intelligence - while contributing to flattening of wages for the rest which have their voice lost in the chain, otherwise called the invisible workforce. Now, some of these contractors are also paid well, especially the ones working for established service providers, but most hiring agencies don’t offer the same luxury. The safety net must be adapted to this new reality.

📊 Excellent textual analysis from Henrik Jacobsen Kleven, looking to identify ‘new directions in economic research’ based on wording and language trends from public economic papers since 1975. Selecting a few graphs below.

📊 If I may, I’d like to complement this series of charts with Nic Carter’s illustration of changing narratives around Bitcoin:

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(Healthy) Entrepreneurial Ecosystems


We will talk less over Silicon Valley (and U.S.) over time

🇺🇸 This section is filled with beautiful essays, from which I will quote at large. I just recently discovered Dan Wang (not sure why so late), and his long-writings are incredibly satisfying. He has recently wrote this great piece in which he argues that technology should be classified under three forms: 1/ processes embedded into tools; 2/ explicit instructions (recipes); 3/ process knowledge, which is mainly hard to write-down, as it is not the type of outsourcing standard-operating-procedure stuff (but tacit knowledge, know-how, and technical experience).

He is arguing that most people, especially in the U.S. and the Valley, focus too much on first two points, but also when referring to technology, they focus too much on the digital world and not enough on the industrial world (too much online, too little offline). And the reason why the future looks like a cyberpunk dystopia is because there is too little focus on the advances in the industry. One example is that the U.S. has many decades of experience in designing and fabricating semiconductors, and it has developed the talent ecosystem that allows the country to maintain its lead on a critically-important technology. This ecosystem (successful industries tend to cluster into tight-knit production networks) gives it a competitive advantage that is hard to replicate (no matter how many spies are deployed), but only in this space, while other industrial areas are suffering (mainly due to outsourcing, like splitting design from manufacturing), and with it, the process knowledge disappears and the expertise decays.

He gives Germany as a counter example of a country that succeeded in maintaining the process knowledge in the industry (but he trade-off is lagging in the digital world - I`m thinking of the recent Lidl-SAP fiasco which shows how reluctant to change are German companies). So why can’t a country excel in both areas: digital and industries? Dan argues that it is possible. And it is an imperative, since the decline of industrial work makes it harder to accumulate process knowledge (or maintain since it generates a vicious loop), and also the future should be more than services (a lot of it services are winner-take-all, and much of the rest is zero-sum, like cancel out the efforts of other service jobs), since there is so much left to be built outside the internet/digital world (cheap materials, better logistics and public transport, faster airplanes, better and cheaper energy, medical devices, Are we sure Silicon Valley, and by extent the world, is not pushing a premature deindustrialization? Are we following the right priorities? Excellent essay!


🇩🇪 Also, more proof about Germany's struggle with transitioning to a digital mindset:

🇺🇸 The second great essay comes from Edward Tenner, which beautifully illustrates a case that today’s Silicon Valley, and by extent all global tech companies are growing at the expense of undercapitalised market-creating innovations. More exactly, 21st century Silicon Valley innovation is very different from the physical, chemical, industrial champions of earlier centuries which all took painstaking, risky, indirect routes to fruition, and yet they overcame many setbacks to make a successful prototype (innovation was harder and slow).

Software-based ventures are far, far easier to scale up than hardware pioneers. And from the perspective of technology and social progress, the problem with Silicon Valley is that the opportunity costs of its start-up mentality makes it to divert investments from the hard innovations that the Valley and the world also needs. Silicon Valley prides itself on innovation, because of software’s capacity increase the scope of operations rapidly, but isn’t an increased scope of operations in itself a modest innovation?

🇺🇸 Ending this with John Battelle’s recent decision to leave Silicon Valley, moving to New York. To quote:

“Truth be told, the place is starting to annoy me a bit more than I’m comfortable with. I can rationalize San Francisco’s adolescent fits – it’s trying to grow up, and it’s terrible at it – and it seems our industry is trying to press past its bro culture and blinkered focus on tech for tech’s sake. But to be honest, it’s the lack of networked, lateral thinking that’s left me wanting. It feels like nearly everyone in the Bay area is so busy making companies (guilty), they don’t have time to have conversations about much more than … making companies.”

We're talking more about Asia, particularly China

🇨🇳 China's booming innovation economy has transformed Shenzhen from a small fishing village into a global tech powerhouse. More on the Chinese tech sector in Silicon Valley’s Bank State of the Markets report.

🇨🇳 But if one truly wants to understand more on China, one should definitely take the journey that Saku Panditharatne took. Excellent essay, here’s what I highlighted. China understands, unlike the U.S., the importance of export-driven manufacturing: “export the surplus from farming, and use the new capital to buy industrial technology from rich countries. After establishing an industrial base, keep the economy export-driven — the global market provides greater incentives to get to the technological frontier than the domestic market”. China has made massive advances in recent years, however it is still dependent on other countries for key technologies such as airplanes and semiconductors. Producing them has also geopolitical implications (or is hard, if we think of the talent ecosystem that Dan Wang mentioned which takes time to be nurture). Chinese tech companies are also strong at rapidly iterating and discovering new business models, but face numerous challenges (domestic market saturation, limited appeal outside China), but probably most important, the geopolitical one: it is very difficult for a rising power to peacefully supplant an existing power. There is only one such transition in history — the USA replacing Britain as the leading power in the 19th century. Nice read!

Ending China section with a really great article, this time why a U.S. professor is leaving China (which I discovered through Matt Cliffords' great newsletter):

"China is a rising power but probably more importantly is a deeply illiberal, expansionist, authoritarian, police state opposed to human rights, democracy, free trade, and rule of law.  Just as we need to consider the state, speed, and direction of change in the United States, China has been deeply illiberal authoritarian for many years, is becoming increasingly illiberal, and is accelerating the pace of change towards greater control. [...] The concern is not over Chinese access to technology to facilitate economic development for a liberal open state. The concern is over the use of technology to facilitate human rights violations and further cement closed markets."

🇭🇰 Also, a look at Honk Kong’s startup ecosystem from Romain Aubert.

🇮🇳 And India just reinforced its net neutrality rules, ensuring online access will remain unrestricted and non-discriminatory (with some predefined exceptions which might require faster speed lanes, like driverless cars, telemedicine).

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Fintech Snippets

Right, I`m just going to show a few diagrams which aim to explore fintech business models in the digital age.

Dave Birch predicts a middle-layer will appear between manufacturing and distribution in financial services, where some of the value will shift. He calls it a packaging layer, others like to call it systems of intelligence.

📊 Accenture views 4 platform banking models:

📊 Alessandro Hatami of Peacemakers Ltd sees the following banking and fintech collaboration models:

📊  But if there’s one I truly recommend, is this one - which I shared in a previous digest. Do read it (again) - I do promise it will be a very good use of your time. It will enable you to better understand the recent article written by Stella Yifan Xie on how Jack Ma’s giant financial startup (Ant Financial) is shaking the Chinese banking system.

Share your thoughts

I would love to hear from you, on Twitter @DanColceriu

Thank you for reading. Regards from Bucharest!

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One more essay for the long commute

Alexis Madrigal's history of modern capitalism from the perspective of the plastic straw. Plastics have both improved human life and eroded the earth’s ecosystems. 
 

Below the patent design for the original bendy straw. Joseph B. Friedman Papers, Archives Center, National Museum of American History, Smithsonian Institution

Top 10 articles I recommend which were featured in this digest:

1. Eric Feng - Consumer startups are dead. Long live consumer startups. - July 2018
2. Marc Andreessen and Elad Gil - Where to Go After Product-Market Fit - July 2018
3. KJ Erickson - The Future Of Network Effects: Tokenization and the End of Extraction - July 2018
4. Marija Gavrilov - Short Guide to Digital Switzerlands—When Companies Act as Countries - July 2018
5. Anne E. Brown - Ridehail Revolution: Groundbreaking ITS dissertation examines discrimination and travel patterns for Lyft, Uber, and taxis - June 2018
6. Alex Tabarrok - Housing Costs Reduce the Return to Education - July 2018
7. Dan Wang - How Technology Grows (a restatement of definite optimism) - July 2018
8. Edward Tenner What Silicon Valley Won’t Admit About Technology and Progress July 2018
9. Saku Panditharatne - China economy FAQ - July 2018
10. Christopher Balding - Balding out - July 2018

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     My name is Dan Colceriu and I hope this reading was rewarding. Any opinions expressed here do not represent financial or investment advice. Also, they represent my personal view, and not my employer's, which is in no way associated with this email. 
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