Enterprise tech, platforms, marketplaces, networks, a new web
archived [a p e r t u r e newsletter #19 ] — Oct 2018
Strategy and Business Models in the Digital Age
Enterprise software, sales and M&A. Large orgs and startups
🏦 I’ve been saving this post from Sarah Guo of Greylock VC since July, but it’s great because it shows how C-level executives from large enterprises think about emerging tech and B2B startups, and also it speaks about what enterprise-tech startups must understand in order to effectively work with big, incumbent companies (= read largest budgets in the world). Despite all corporations wanting to “innovate and open up”, and despite all enterprise-tech startups wanting to work with “slow, incumbent organizations”, things are always much more complicated.
Some tips extracted from the article: corporate execs pay more attention to startups that are introduced to them by a trusted third-party (a marketplace, a thought-partner); new tech from a new vendor triggers an immune system inside the large organisation (perceived as risks that must be neutralized), but also a whole bucket of hidden costs (vendor management, training, change management, integration, implementation); hence explaining the value proposition of the new solution is overly underestimated by startups — corporates don’t buy tech for tech’s sake (pricing should be tied to the value creation); also, mapping the existing tech ecosystem of a large organization is a critical skill startups should acquire, because executives want to understand the integration costs and efforts — so a primarily product-focused startup must develop a strong services partner-network from Day 1 (or be brave enough to charge for services, writes Martin Casado, since so much heavy lifting is involved in the sales and implementation process through founders’ and engineering time).
Also this one I really liked, from a banking exec: enterprise-tech startups should spend less time belittle large orgs for having legacy technology, and instead more time explaining how easy it would be for their solution to integrate into the existing IT spaghetti. At the end of the day, these startups target a market made up of institutions where their newest systems are more than 10 years old. A common pitfall for startups to avoid, though, is falling prey to the plethora of customisation requests, which before they know it, will transform their business from a repeatable, scalable model of selling software, into an unscalable bespoke dev shop.
🤝 A natural path for most tech partnerships leads to M&A (the large org acquiring the smaller company once it deems it a strategic asset). I have very much enjoyed this thread from Steven Sinofsky built on his own tech-M&A “integration expectations” matrix. Tech M&A follows two dimensions, one of operations (how do things work) and one of product (what gets done). Based on these two dimensions, the next question is around M&A-strategy and negotiations: are they pushed by the acquirer or pulled by the acquired, or a mix of both? Interesting to read this on the back of recent news that founders of WhatsApp, Instagram, Oculus have all left Facebook in the past two months.
👨💼 Staying in the realm of big companies, Morgan Housel’s short article on how dysfunctional they can become is a good read. Some downsides of large organizations: 1/ Best ideas from employees die through the various committees labyrinth because of poorly articulated internal marketing (the ignored truth that flashing out value proposition is a serious game); 2/ people inside big orgs act for receiving credit (which helps them moving up in hierarchy), and not for what they believe in (hence execution is given less importance over time, relative to presentation); 3/ employees are hard to please, because in time they lose sight of what they want from their career, and spend more time focused on frustrations from dynamics between colleagues, their boss, other departments. Probably why after a point, a freelancer based corporate strategy makes sense.
🐌 Also on big companies, Steven Sinofsky’s great thread on why sometimes, especially during crisis periods, large orgs are perceived as being slow. It is because responding to a crisis is fundamentally about *breaking* your customer promises in order to make a new customer promise. In other words, about employees obtaining the permission and capability to essentially break what was built (and when you have a lot of customers, vs. startups that don’t have, it is harder than most think).
Funding secured. The demise of the public company
📈 A notable event that happened in the past few months was Elon Musk’s announcement that he plans to take Tesla private (in order to innovate faster, away from the short-sellers and the short-termism of the public market). This has fuelled again the narrative that he US public market is a dying breed. Unrelated, but timely enough, Brian Cheffin’s research paper tries to put this idea to bed: Rumours of the Death of the American Public Company are Greatly Exaggerated. The stock market is as large relative to the American economy as it ever has been. The public-to-private buyout trend remains relevant, but not strong enough to imperil the public market status. Also, fast-growing business enterprises are not going public as frequently as they used to — true — nevertheless, the point has not been reached where successful sizeable American firms consistently stay private permanently. See Uber 2019.
🖧 I guess what Brian’s paper doesn’t cover is the development of token fundraising as an alternative to issuing shares. Gigi Levy-Weiss draws a few lessons from the recent frenzy of token investments, and despite uncertainty and scepticism, he believes they are an important part in the future of fundraising. He focuses this article on security tokens (digital objects on blockchain infrastructure that represents ownership of some real-world asset which, after removing a few barriers, can become a better alternative to traditional equity — reasons in the article) and utility tokens (digital object that represents credit to use a product or participate in the activity of a decentralized-app — ideal for incentive alignment for kickstarting network effects during platform creation, while also enabling lower transaction costs). Barriers mentioned are regulations; separating the models that require utility tokens (and differentiating from the ones when tokens are completely unnecessary); and the early liquidity provided by these networks, which can mean the discount from liquidity that usually benefits early investors no longer makes sense — same liquidity provides volatility since startups (in search of a product market/fit) are unstable by design.
Designing platforms, marketplaces, networks
⚙️ Back in August, I enjoyed reading Simone Cicero’s post on the 7 key principles on how to design platform companies: 1/ recognize the edge (small entities now have the power); 2/ design from an existing ecosystem’s needs (not from an inside-out analysis of own core assets); 3/ use self-organizationto provide mass-customization (reduce transaction costs for peers to connect in interaction); 4/ enable continuous learning; 5/ design for disobedience(remember that the power has shifted from one organization to the outside ecosystem — hence if new behaviours from the multitude appear as recurrent, then the platform design must be able to turn it into a feature); 6/ design for interconnectedness; 7/ let go of corporate brand identity in the platform design, and identify with the ecosystem itself.
🖧 Mike Maples writes about how “networks are eating the world” (n.b. he seems to dislike the actual eating metaphor). More specifically, software-defined networks (leveraging mass computation, mass connectivity, and network effects) will be the most valuable businesses, displacing traditional corporations as central actors (characterized by mass production, mass distribution, and economies of scale). Important to understand the difference between companies using networks to enhance their business model, and companies that are defined by networks. And of course, like with any shift in power, networks will encounter fierce resistance from traditional businesses, governments, and other parts of society. Just like the rise of large corporations was messy and faced backlash, so is today’s rise of networks. The startup culture needs to change, mature and speak more about policy than it does now.
🖧 Companies that start out with core network effects — network effects that are integral to a company’s core business, not arising from features added later — are the easiest to reinforce, writes James Currier (by reinforcement meaning whenever a company adds a new defensibility, its existing defensibilities become even more powerful). And because defensibilities in networks compound, the earlier they are built, the better.
🧠 Bart Dessaint sees the next-gen of winning two-sided (or multi-sided) marketplace businesses as the ones that are enabled by sensor technologies and AI. Hence why, when analysing future smart-marketplaces, one angle to look at is if AI a core competency baked into the platform, or is AI an additional technology layer that is brought in at a later stage (and if this the case, what does this imply for defensibility?). Bart’s view is that “the current crop of marketplaces are likely to layer AI on top of their current offerings to reduce friction and increase efficiencies, but the truly smart marketplaces will be those reliant on AI to broker previously impossible transactions.”
🇨🇳 Ming Zeng makes the case that Alibaba is such a networked-business of the future: ecosystem players coordinated in an online network and use machine-learning technology to efficiently leverage data in real time. Detailed case-study.
🇨🇳 Also a fascinating deep-dive from Jeffrey Ding into Tencent’s re-thinking of its strategy and the steps it takes to become a data company (and the challenges it now faces since data was not baked into its model from early on).
Policy, Techies and Misdemeanours
A new web, data self-sovereignty, a new platform economy
🕸️ At the end of September, Tim Berners-Lee, the creator of the web, published his manifesto for the next step in the history of the internet: a platform called Solid, an open-source project to restore the power and agency of individuals on the web. To quote, “Solid changes the current model where users have to hand over personal data to digital giants in exchange for perceived value. As we’ve all discovered, this hasn’t been in our best interests. Solid is how we evolve the web in order to restore balance — by giving every one of us complete control over data, personal or not, in a revolutionary way (gives every user a choice about where data is stored, which specific people and groups can access select elements, and which apps you use. It allows you, your family and colleagues, to link and share data with anyone. It allows people to look at the same data with different apps at the same time)”. He calls it the personal empowerment through data.
💻 Nare Vardanyan makes the case on why the importance of self-sovereign data goes beyond the philosophical and political spectrum: it is an economic enabler. She writes that data self-sovereignty is going to be a shift equal to and potentially bigger than the move to the cloud (as it affects income and profit distribution, gig economies, automation and jobs, spawning ways of scalable, connected and intelligent collaboration unseen before). Platforms enabling user data self-sovereignty are more efficient (and allow startups to obtain access to data from Day 1), since fragmented data pieces come together inside a user owned data vault and can be scaled across verticals and jurisdictions (new forms of businesses and capabilities that are impossible within the current paradigm). They are safer and more intelligent.
👨⚖️ Viktor Mayer-Schönberger and Thomas Ramge also write in favour of a progressive data-sharing mandate from policymakers, instead of backward looking solutions like breaking giants up. Such a mandate would decentralize digital markets and spur innovation as companies competed to extract the best insights from the same data. Viktor and Thomas argue that if such a mandate is not enforced, the risk is an economy that gets closer to centrally planned systems and more far away from the resilient and decentralized traditional marketplaces, since in data-rich markets run by digital superstars, these companies control all the information about customer preferences and transactions, and despite buyers still theoretically making individual decisions, they are greatly influenced both by explicit recommendations and by the ways in which options are filtered and presented. As per their recommendation: the role of regulators in such a mandate would be limitedto assessing market share (to determine the amount of data a company should share based on market share), and if necessary, regulators would also enforce access to data, but they would not actively organize or operate the sharing system or the platform. What about a view where it is worth exploring if the government could have a bigger role? To be seen, especially since democratic socialism is catching steam in the U.S. as well.
Future of work, slacking, welfare state and universal basic income
🔃 Louis Coppey does a great job illustrating some of the concepts around market equilibrium in the 1/ traditional economy, 2/ in the platform economy without regulations and 3/ then in the platform economy with progressive regulations, painting the picture on why platforms should ultimately welcome regulations on many levels, be it at data-sharing level or at forcing social insurance in the gig-economy, since it leads to both highly paid (and better protected) workers, happier consumers and higher profits for them.
I will take the liberty to include Louis’ graphs below because they are great, but please do read his thinking as well.
👩💻 Excellent article from Marco Torregrossa on the continuous rise of freelancing and gig-work driven by platforms. He delves into the different kinds of platform models: 1/ Pipe Model = linear, value-extracting model previously proposed by intermediary contractor firms (no network effects, no contact between customer and freelancer, no value add hence easily avoidable); 2/ Transitional model = where firms facilitate direct interaction between freelancer and customer, acting as a concierge and payments facilitator (limited network effects); 3/ Commission model = or 1st stage platform model where the platform is the enabler (and owner of the rules and governance of the platform; decentralised value creation, more network effects); 4/ Subscription/membership model = 2nd platform model (The firm gives a menu for customers to choose from and charges them per month or year according to a subscription plan based on frequency, specific services or number of freelancers needed).
📺 Andrew Kortina and Namrata Patel argue in a research paper that labour force participation in the US declined sharply for men aged 20–34 and it has little to do with wages (but more to do with the decreasing cost, increasing availability and quality of media entertainment), hence stimulus in the wage-levels would do little to increase the overall economic productivity. Therefore, they discuss the radical idea of introducing a tax on human attention or time spent consuming entertainment media as a way to stimulate productivity. Because the demand for labour exceeds what workers are willing to supply, production and overall economic output are lower when workers prefer media entertainment leisure over wages. In short, Netflix and EA Games are creating slacking young boys. Andrew and Namrata’s idea rests on these arguments: tax the unproductive leisure activities which people prefer over work because, to quote, “(i) the true cost of these activities is already distorted from a consumer perspective by the advertisers who subsidize media consumption,and (ii) we already tax income and productivity — if time and money are fungible, you might just pull the idea of income tax ‘above’ the decision of how to spend time, and say that each person is responsible for investing some amount of sweat (in the form of time or money) into the public good. Therefore, since media companies are capitalizing and profiting on a huge amount of attention that might otherwise be spent productively, however, taxing them for the share of the citizenry’s time that they consume could be more sensible and more practical than taxing citizens themselves.”
A few positives worth noting:
🎓 More than a dozen companies, including Google, Apple and IBM, are no longer requiring applicants to have college degrees (acknowledging in a way that today’s education system is not necessarily fit for purpose, while being inexplicable expensive)
👵🏻 Airbnb is now proving to be a good alternative for retired seniors to monetize their real-estate asset: hence enabling them to continue to afford to keep it, while also solving a a big problem of people of age: loneliness
👨💼 Massachusetts seems to finally understand how its enforcement of noncompete clauses led to it losing competitive advantage versus Silicon Valley, in the race to develop healthy entrepreneurial tech ecosystems in the 80s and 90s. Now it’s trying to fix it — allowing therefore for more workers’ mobility. One thing to consider: there is also the narrative pushed by others that Silicon Valley won because of its non-supportive position towards workers-unions during those years, but now this position is facing its own threat.
🌐 Chris Ferguson, director at the UK’s Government Digital Service, put together with public servants from over 140 countries a single repository for civil servants and government employees to find all the cool, freely available tools for digital government.
💬 Facebook hires former UK Lib Dem leader Nick Clegg, in a move that (hopefully) shows that the company is prepared to embrace regulations and in general its role in understanding global policy for the greater good. Also, it is a good sign that they selected an European liberal to drive this mission.
🎭 Ending this section, I would like to take a moment to praise the legacy of Paul Allen, co-founder of Microsoft, who died recently. “His energetic curiosity lingered in the corporate culture, which welcomed rather than dismissed interests beyond technology. Unlike the millennial billionaires who condescend to non-technical pursuits, Allen attributed his entrepreneurial ambition and imagination to a wide-ranging autodidacticism and a natural passion for art and literature”, writes Eren Orbey.
(Healthy) Entrepreneurial Ecosystems
🇪🇺 Why can’t Europe do Tech?, asked Jeremy Kahn a while ago. In summary, he sees some of the problems being: entrepreneurs think too small (create regional market leaders or at least something that global giants will buy), lack of VC funding (which has been addressed in the past years), unforced errors (Brexit).
🇪🇺 Nicolas Colin’s take on the Europe’s problem is that it is a lack of a proper Safety Net 2.0 that is creating a risk-averse culture — Europeans, being accustomed with a strong social protection mechanism, cling to current jobs since embarking on the entrepreneurial wagon creates new risks for which today’s institutions are not designed to protect against.
🇪🇺 The Economist’s recent take on it is that it is inherent to Europe’s own history to not ever produce a Google. Europe’s patchwork of rules and markets is a disadvantage. New technologies require vast lakes of data, skilled labour and capital, and despite the EU’s single market, in Europe these often remain in national ponds. Another argument is that the collective experience of Nazi and Soviet surveillance and dictatorship makes many Europeans protective of their data (which if it is not harnessed, it cannot lead to great tech companies and services). Also, its lack of mission-driven government programs, which are to invest massively in programs such as military research or climate change, which in turn create the technological infrastructure for further tech private developments.
Many should exercise more caution in predicting China’s future
🇨🇳 Excellent thread from Kyle Yuan!
💳 Excellent speech from US Fed Governor Lael Brainard, about FinTech and the Search for Full Stack Financial Inclusion.
Top 10 articles I recommend which were featured in this digest:
1. Sarah Guo — Startups serving the enterprise — July 2018
2. Martin Casado — Why direct sales always matters in the enterprise — September 2018
3. Gigi Levy-Weiss — The Future of Fundraising? What We Need to Fix About Token Investing — September 2018
4. Simone Cicero — The 7 Key Principles of Platform Design — August 2018
5. James Currier — Reinforcement: The Hidden Key to Building Iconic Tech Companies — September 2018
6. Nare Vardanyan — 3 why-s of self-sovereign data — August 2018
7. Louis Coppey — Why Platforms might want to welcome Regulators — August 2018
8. Marco Torregrossa — How the Platform Economy Gives Superpowers to Freelancers- August 2018
9. Andrew Kortina and Namrata Patel — Kinky Labor Supply and the Attention Tax — October 2018
10. Lael Brainard — FinTech and the Search for Full Stack Financial Inclusion — October 2018