Friday, December 18, 2020

Index Companies

Sometimes there are markets that are clearly going to grow massively over time. For example, ecommerce, genomics, crypto are all markets which were clearly going to compound over time. It might have been tough to call the winners of each market early, but it was clear the markets themselves would grow a lot.

One lens through which to view companies is to ask "what companies are an index of their underlying market"? 

Index companies often take a cut of every transaction in their space, or are a piece of infrastructure everyone in the market needs. For example, it is a hard to launch something into space in the West without using SpaceX. These companies may be ways to participate in the market broadly without having to worry about how wins in it.

Some example index companies are:

Online Commerce & Stripe. 

For many years Stripe effectively acted as an index of startups in online commerce. One can argue Stripe is now a proxy for the underlying global online economy. Buying Stripe means buying an important subset of the internet.

Crypto & Coinbase. 

Crypto is a dynamic market with hundreds of tokens beyond BTC and ETH. As long as Coinbase lists it and takes a cut of transactions, Coinbase is a proxy index for all of crypto. With its pending IPO, Coinbase will effectively be an index for crypto writ large. Coinbase is also unique as a high quality company which institutional investors can use as a proxy to participate in the crypto world, even if they are not allowed to hold crypto directly themselves.

Genomics & Illumina. 

I would not be surprised if 90% of clinical genomics were run on Illumina machines. Illumina stock is a proxy for the clinical use of genomics.

Space Launch & SpaceX. 

Today a majority of commercial space launches for the western world are conducted on a small number of companies with SpaceX as the majority of that share. There is a reasonable scenario that in 5-10 years time most of space launches will consolidate to SpaceX and Relativity. Right now SpaceX is a proxy for the entire space launch market. Relativity seems like a strong #2 technologically, although yet to launch a commercial rocket.

AI & Chips Companies. 

The best way to index AI is likely through an underlying AI-chip company. Today that is NVIDIA but GPUs are not really optimized for ML applications. One could argue Google should have launched its TPUs for others to buy directly, versus as a cloud service. Since it has not, potential contenders include Groq and Cerebras.

Fragmented indices

Some markets have a few players that index them - or the revenue mix of the companies prevents a pure play view. For example, AWS, Azure, and GCP are an index of the cloud, but none are investable as stand-alones.

Future indices?

It is fun to speculate on what markets or companies may have index companies emerge. For example, is Substack an index of next-gen journalism?  Zoom an index for remote work? 

Or you can turn it around and ask "What trends are important? Are there companies that represent a proxy for all the activity in this trend?" For example, what is an index for 3D printing? Or DeFi (is it ETH?)? Or....?

What are other "index companies" for exciting markets? Let me know on Twitter.

Friday, October 23, 2020

Unicorn Market Cap & Industry Towns, 2020

In 2019 I wrote about how "industry towns" emerge in every market. These clusters of people, ideas, capital, service providers, and companies tend to have strong network effects that support startup formation and success in a given industry. 

For example, Silicon Valley, London, Beijing are global tech centers. New York, London, HK, Shanghai etc. are global finance centers. Hollywood, Lagos, Bombay are global movie centers.

Given all the IPOs in the last 16 months (including Snowflake, Unity, Asana, Palantir) and the sharp decrease in market cap in some companies (WeWork), I thought it would be interesting to update the view of where unicorn market cap currently resides. 

Some big caveats include (1) Unicorn market cap is a lagging indicator of ecosystem health since many companies take anywhere from 2-7 years to be worth their first billion (2) COVID and the move to more remote work or "remote first" startups may impact what this looks like in 4-5 years (3) San Francisco governance may decrease San Francisco's long term relevance, although the broader Bay Area should be strong longer term. A big thanks to the talented Shin Kim for pulling & structuring the data below (raw data here if you want it).

Unicorn Turnover
Since June 2019, 37 of the 361 Unicorns at the time went public, 14 were acquired, and 8 did down rounds or shuttered. 187 new unicorns emerged in the last 15 months (>3 a week!) which means 38% of total unicorns today are new ones (and the number of unicorns grew 58% in 15 months!).

Half of the 187 new unicorns since June 2019 are in 5 cities
88 of the 187 new unicorns since June 2019 are in Silicon Valley, New York, Los Angeles in the USA and Beijing and Shanghai in China. Roughly 25% of new unicorns globally were in Silicon Valley. This is inline with Silicon Valley's traditional share of the overall unicorn market.

There were new unicorns in 65 different cities.

Below is the distribution of # of new unicorns. Only 8 cities in the entire world added 5 or more unicorns since June 2019. Only 4 cities added 10 or more unicorns - add accounted for 43% of all the new unicorns in the world over the last 16 months.

Overall Unicorn Market Cap: US + China = 77% of Unicorn Market Cap
As anticipated by industry clusters and network effects, over 3/4 of all unicorn market cap is in 2 countries, with high regional concentration within countries.

The USA and China continue to lead in terms of both Unicorn market cap and number. Of China's $512 billion in Unicorn market cap, almost 40% of it is from two companies - ByteDance ($140 billion market cap) and Didi ($62 billion).

Decacorns, or companies with $10B or more in market cap, are similarly concentrated in the USA and China representing 19 out of 26 total global decacorns.

In-country concentration
Just as unicorn market cap and number are concentrated by country globally, each country also has its regional tech clusters or industry towns.

In every country surveyed almost half or more of all unicorn market cap, and number, resided in a single city or major metro area.

Unicorns in the USA

In the USA, Silicon Valley is roughly 5X the size of New York and Los Angeles by market cap (of which 2/3 of the market cap is Space). Boston Unicorn market cap is biotech driven. SV is 5X NY in terms of # of unicorns, and ~8X the size of Los Angeles.

Next tech cluster in the USA
Intriguingly, a number of the cities often spoken about as the "next tech cluster" have not added much by way of unicorns. Austin has 2 total and Portland has 1. One can argue that this is simply a time lag and in 3-4 years many unicorns will have sprouted locally. Anecdotally, the cities that seem have a number of high quality founders and new companies - and therefore may be on their way to growing more unicorns include Denver and Salt Lake City. While I see many investors move to Austin, I see more founders move to Denver. Time will tell.

China Unicorns
In China, Beijing is 7X the size of Shanghai by market cap but only 2X by unicorn number. This is driven largely by ByteDance and Didi. Subtracting these two companies off yields only a 3X in market cap difference between Shanghai and Beijing. It is notable that both Beijing and Shanghai added 11 unicorns in the last 15 months. So new Unicorn growth is more neck and neck more recently.

India Unicorns
India presents an interesting case study in a second cluster forming. When I visited India in 2007, Bangalore was the clear engineering center and tech startup leader. Hyderabad was a strong tech customer support center. Since that time New Delhi as emerged as a major tech cluster and startup unicorn hub. While Bangalore continues to thrive, some point to bad governance locally (traffic, high rents, passive government) as one of the reasons it is not the only center. There are undoubtedly other reasons, but it is worth thinking about relative to San Francisco longer term.

Other markets
The pattern of a primary tech and unicorn and tech cluster repeats itself for the other major markets including Israel (Tel Aviv), Germany (Berlin & Munich more neck-in-neck), UK (London) etc.

Outlier market cap domination
Startup market cap tends to follow a power law. In some markets, there is very high market cap concentration currently (this will of course change when the companies go public). For example, 58% of Beijing's market cap is in two companies - ByteDance ($140 billion) and Didi ($62 billion). Los Angeles unicorn market cap is largely a function of SpaceX (2/3 of the total!). Silicon Valley market cap is more distributed, perhaps suggested a broader tech ecosystem.

Why are all the unicorn "Remote First" companies since COVID in the Bay Area?
Out of the top 100 private tech unicorns, 11 have perpetual "remote first" or "remote equal" policies. 5 of these were added since COVID. Interestingly, 4 of 5 (AffirmBrexCoinbaseFigma) of the unicorns who announced moving to remote-first forever post-COVID are all based in San Francisco, with 1 (Quora) based elsewhere in the Bay Area. 

Given that roughly half the unicorns in the USA are based in the Bay Area, you would expect roughly half the unicorns going remote first to be based elsewhere. Instead all of them are in Silicon Valley (roughly a 1/32 chance if this were to happen randomly). Obviously, something else may be afoot.

San Francisco should be going through a golden era and boom. It could be one of the great cities of the world, with a large city budget to support it. Unfortunately, San Francisco's poor governance, high cost of living, lack of housing, failed homeless services, bad budget controls, and other issues were prominent before COVID. With a never-lifted lockdown the city has continued to degrade and this is reflected in both the homeless situation and dropping rent prices as people move out of the city.

The smoke and fires was a recent last straw that drove a set of young unmarried founders I know out of the Bay Area. Anecdotally these founders have largely temporarily relocated to New York and Los Angeles. The main reason people stay in SF is the social network and the serendipity of a cluster and network effect. Due to SIP, if you can not meet people in person there is no impetus to put up with poor living conditions and to stay put. Many have decided to go to cities that are more liveable, with less restrictive conditions.

In parallel, a number of later stage startup CEOs are interested in hiring more outside of the Bay Area, and especially outside of San Francisco. There is an increasing perception that San Francisco based hires are more expensive, self-entitled, and political-activism-at-work oriented (versus core company mission & performance focused) than employees elsewhere. Of course, not all late stage founders share this perspective but an accelerating number do. This impacts early stage companies less with their smaller employee bases, tightly defined missions, and existential need to ship. 

If the Bay Area does eventually decrease as a cluster, I am guessing it will be only a partial decline. The network effects and talent base in the Bay Area are incredibly high and if diminished I would guess would drop by 10-20% not 80%. That said, New York, Los Angeles, and to a lessor extent Denver, seem positioned to grow in importance over time if COVID SIP extends indefinitely or SF takes an aggressive tax stance or continues on its governance slide. While I am long term bullish on the Bay Area as an ongoing home for unicorns and major US cluster, it is worth watching how ongoing governance and policies will impact SF. Only time will tell. 


  • Unicorn list and valuation as of 10/7/20 from CB Insights
  • HQ location based on company websites and Crunchbase

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Tuesday, October 13, 2020

Silicon Valley & Defense Tech

Over the last few years there has been a lot of press coverage of Google canceling project Maven, a defense contract. This has led to claims Silicon Valley is no longer engaging in defense tech, despite tech's roots working with the Department of Defense and other government agencies. Things like the Internet, various semiconductor companies, and GPS/location services are all outgrowths of defense-related work.

It turns out that despite the popular narrative, companies both large and small have continued to work with the government. Indeed, Amazon and Microsoft are publicly fighting over a major contract with the DoD called JEDI. Other companies such as Intel, IBM, and Oracle have long standing defense relationships. Salesforce has long had a "Government Cloud" and DoD ATO approvals.

A few years ago, I thought new DefenseTech would largely consist of specialist companies like Anduril, whose primary focus is defense (Anduril recently landed a $250 million, 5 year contract with DHS as well as a $13.5 million Marine Corps contract). I have long thought there is room for an AI/ML-centric software only defense contractor. 

The reality is that, in addition to defense-first companies like Anduril or Shield.AI, many of the companies recently landing large government contracts are tech companies that do not have defense as their primary vertical. The current generation of new defense tech companies look similar to the prior generation of defense tech companies - they are simply the leading companies of their broader respective areas selling technology to multiple markets including defense. Despite all the punditry claiming the opposite, mainstream Silicon Valley remains quite active in serving the defense world. 

Specialist firms like Anduril will continue to thrive. However there turns out to be a lot of room for standard tech companies to add defense as an important vertical market. Some examples of private non-defense tech companies working with national defense:

  • Applied Intuition. Applied Intuition's core business is with autonomous vehicle companies. However its simulation infrastructure software is being used in multiple defense mobility applications.
  • Palantir. Palantir has won an $876 million deal with the DoD. Their business includes fintech, healthcare (NIH and CDC), and other applications. [Note: Palantir went public while I was writing this post].
  • Scale.AI. Scale provides labelled data sets for machine learning applications across multiple verticals and is used by Airbnb, SAP, Pinterest, DoorDash and others. They recently signed a $91 million Army contract.
  • Skydio. Skydio started off as a consumer drone company only to quickly find enterprise applications in public safety and inspection. More recently it has also added defense.
  • SpaceX. Elon Musk's SpaceX has signed a $145 million contract with the Pentagon to build missile tracking satellites. SpaceX has also signed contract with the DoD to develop rockets with different defense cargo payloads. Existing incumbent solutions (the C-17 rockets) cost $200M each.
  • Tons of SaaS companies. Most SaaS companies eventually end up with the government as customers. However, in these cases it is a standard few hundred thousand to few million SaaS purchase so not notable enough to mention.
The common themes for emerging defense work include space, drones and AI. There are also many SaaS companies that sell their standard software to the various military branches. Outside of Google, the large tech companies (Amazon, Cisco, IBM, Microsoft, Oracle, etc) continue to work with the defense world as well.  

You can order the High Growth Handbook here.


Monday, October 5, 2020

Jobs, Wozniak, Cook (Build, Sell, Scale)

Over the life of a startup, 3 archetypes are needed to found, build, and scale a company. It is rare to find someone who is a 10X version of one of these archetypes, so even rarer to find someone who captures 2 or 3 of them. As such, usually these characteristics are divided into 3 or more people who are uniquely good at their core function.

Archtype 1: Ability to Sell. Apple example: Steve Jobs.  

Every startup needs someone who is great at selling. This founder convinces people to join the company, gets the first few customers, and pulls off the impossible partnership or ridiculous fundraise. Without a great sales person founders may find it hard to hire people, close customers or raise money. 

Jobs was also great at product, which leads to Archetype 2....

Archetype 2: Ability to Build (a great product). Apple example: Steve Jobs & Steve Wozniak. 

Wozniak could build anything. He was known for his impossible designs that dramatically increased utilization of the hardware and enabled the early Macs to do things similar hardware could not.

Coupled with Jobs, who later emerged as a product visionary, they drove great product and technical excellence. In other words, the ability to build.

Archetype 3: Ability to Scale (and run a tight ship). Apple example: Tim Cook.

Later in the life of the company someone is need to scale the organization, tighten controls, add process, and scale a company from tens or hundreds to many thousands. While some founders end up as excellent operators, often they need to hire someone who is their complement to learn from or to drive much of the scaling. These professional executives tend to be great at people issues but bad at making bold or controversial decisions or iterating on the next wave of disruption. This is why they are able to climb the corporate ladder and work with stubborn decisive founders, but also is why they are not usually founders themselves.

Founders & Archetypes.

Many of the best founders are good at 1 & 2 (Sell & Build) but not great at 3 (Scale). This is often a mix of experience (if you are a founder you are unlikely to have run a multi-thousand person organization in the past) and personality (impatience or raw cussedness or other traits that may help with early success may not always lend themselves well to every managerial situation). Some founders do well out of raw product/market fit and may not actually be great at any of the archetypes - although often these companies never quite reach their real potential. The founders I have seen build companies that reach their biggest potential have a spike in at least one, or potentially 2, archetypes. Some founders also eventually learn to scale, or get smart enough about hiring great people who provide scaling that it is equivalent to the same thing.

Archetypes and CEO transitions.

Founders tend to appreciate people who are complementary to them and can help scale their company. The first time a capable, experienced executive is hired is a magical moment for a founder. It turns out you can delegate all sorts of things to people who are better at it then you!

This leads to many professional operators taking over as CEO when a founder steps down[1]. The operator had scaled the company, gets along well with the founder to whom they tend to defer, and are great at running a tight ship. Unfortunately, the professional operator CEO often tend to avoid controversy, disruption, bold new product moves, and the ability to do something high risk or contrarian. Often the company will coast on prior products and do well for many years, only to get hit and destroyed by a new disruption or company.

One of the big mistakes successful founders tend to make late in the life of a company is to promote to CEO someone who is a different archetype from themselves, instead of looking for someone just like them. When stepping down from a major company built over a lifetime, it might be wiser to look for a founder type with Sell and Build archetype characteristics over a Scale archetype executive. Or, to at least look for a Scale archetype who has had a strong Build experience and aptitude.


[1] It is important to differentiate between CEO transitions earlier in the life of a company versus later. For example, if a founder has a great 20-30 year run and built a tens of billions company, this is the exact moment they may want more of a "founder" than a "scaler" as CEO. If, instead, the company has built an initial product but needs help executing, building sales etc and the founder is not up for the journey, it might make sense to just hire a "scaler" to get the company back on track (so that it survives). Like all things startuo-related, there is a lot of room for context and nuance on this.

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Tuesday, September 29, 2020

Collaborative Enterprise (at last!)

During the first social era as Facebook, LinkedIn, Twitter, Instagram, Pinterest, and other products were first breaking out, there was a lot of talk of the "social enterprise" or "networked enterprise". The idea, circa 2010, was that all the collaborative features of Web 2.0 social products were going to be baked into SaaS leading to large scale transformation of software. This obviously did not happen 10 years ago.

More recently, the two big trends transforming the enterprise are (i) Nocode/Lowcode/RPA, and the (ii) Collaborative Enterprise[1]. Collaborative enterprise is an updated take on building collaboration and learnings from consumer products into SaaS. 

The emergence of collaborative products in the enterprise is being driven by a handful of trends:

A. User shift. Users (and founders) who grew up with social product, chat, cloud storage, and lots of cloud apps are comfortable with using similar products in the enterprise. Adoption of basic team communication and collaboration tools have now been massively accelerated with COVID. COVID is a new "why now" statement for many companies in this area.

B. Distribution shift. Bottoms-up adoption and in-product viral and growth distribution techniques have at last been integrated into SaaS products. In-product distribution techniques are inherently focused on collaboration, so some of the earliest features in many products are peer-to-peer or network driven. Box and Dropbox are examples of early pioneers of these techniques, with Slack similarly adopting early in product-distribution techniques.

In the past, many large enterprises were locked down by IT and legal in terms of what could be downloaded or used by an individual in the enterprise. Given the platform shift below, much more can be done in browser now than in the past, opening up broader opportunities.

C. Tech shift. WebRTC and WebGL are now baked properly into browsers - this creates a platform shift that is enabling applications rich in audio, video, and collaborative graphics. Browser based audio/video are finally crisp and products like Figma work seamlessly in real time in part due to WebGL. This tech stack also has implications to social products (discuss in another post).

The emergence of the collaborative enterprise is going to yield a number of companies across categories. Below is a list of potential categories in which large collaborative enterprise products may emerge:

1. Collaborative Enterprise: Function-Specific Tools

These are team-oriented tasks or products in which multiple people work together to product an end product like a user interface design, BI graph interpretation, FP&A planning, or other areas. Here are some example areas: (Lists below are non-comprehensive - apologies for any omissions this post was written quickly)

  • Design. Figma was a forerunner on the collaborative enterprise with its best-in-class cloud-based collaboration focused design tools and early adoption of WebGL. Invision's first products were similarly focused on team collaboration in the cloud. Zeplin was focused early on on design-to-engineering hand offs. Sketch and others are now scrambling to catch up. Figma has emerged as the leader in core design on the web.
  • Engineering. Gitlab and Github are the grandparent apps in this category. A number of engineering collaboration and productivity tools are also being built. For example, Fig for the terminal.
  • FP&A. A number of startups are emerging with a focus on collaborative financial planning, headcount planning, and other tasks that tend to be cross-functional, currently run in a spreadsheet, and highly inefficient otherwise. Companies include,, and Cube.
  • Business intelligence & Dashboards. Focused on sharable graphs, commenting, and interactions for BI applications, companies include, Mode, and Sigma.
  • Data science. A number of tools have emerged recently for collaborative data science. Jupyter Notebooks was an early pioneer in this area with Deepnote a more recent entrant and Streamlit taking a very different approach focused on creating data apps.
  • Other areas. Many other areas are finally allowing for in-browser collaboration and cloud hosted output.
2. Collaborative Enterprise: Remote Work, Events, & Distributed teams. 

In addition to vertical or task-specific tools, there is also emergence of better tools for remote work, collaboration, events, and networking including:
  • The basics. 
    • Communication. Besides some of the vertical/functional tooling mentioned above (e.g. Github/Gitlab, Figma etc.) Zoom, Google Meet, Slack/Microsoft Teams, form the basics of communication for remote work. Newer companies like TandemAround.coThreads and Quill are also working in this area.
    • Productivity & emergence of NoCode/LowCode
      • Cloud based versions of productivity suite tools are accelerating. This include Docs (Google, Notion, Coda, to a lesser extent Roam), Spreadsheet/Access (Google, Airtable) and slides (Pitch). The new entrants like Airtable and Notion are dramatically more interesting than their Google cloud based predecessors.
      • Unlike their productivity suite predecessors, the NoCode platforms are actually broader-based tools to allow any person at an organization to build an application or capture knowledge collaboratively. For example, Airtable allows people to build simple software applications, or to use templated applications for their own work flow or productivity. You can think of this as taking a SQL database or excel spreadsheet and turning it into an app platform. Airtable has templates for everything from Applicant Tracking Systems to Marketing Forms to CRM. Notion (which is more docs-based, knowledge capture, and productivity-centric) has templates for design systems, knowledge capture, note taking, and other areas. These companies are building a few of the key bases for the future of collaboration in the enterprise.
      • (Aside: there are obviously also vertical NoCode/LowCode apps outside of productivity (e.g. Retool et al), and RPA or automation products (Parabola et al) which will be covered in a separate post.)
  • Cloud storage. Box, Dropbox, and Google Drive are obvious early examples of early collaborative enterprise tools, that are now used ~ubiquitously.
  • Virtual office. A number of companies are experimenting with providing a virtual space for people to hang out and collaborate. This includes companies like, and,
  • Virtual conference room. I think a virtual conference room product is going to emerge and scale rapidly. One could argue products like Miro, which focus on virtual white boards, project planning, and kanban boards, are the early precursors for what will likely be video enabled, tightly integrated products. This may be solved by the virtual office products above, by products like Miro, by Zoom or others integrating collaboration tools, or an entirely new company.
  • Virtual events. 
    • Once COVID is over, many events will snap back to the real world. However, social distancing has also shown the value of remote events - more people will attend virtually (in some cases 10X-100X more), there is no need for travel and wasted time, and sometimes the format is more efficient. 
    • The downside is the loss of serendipity and side conversations. This leads to virtual networking products (including a side project I am experimenting with).
    • Companies for virtual events include Hopin.toWelcome, Gatherly, EventMobi, and others. I expect one or more of these to be worth many billions in the future.
  • Virtual networking. There are two types of virtual networking - networking at an event or a social hour, and meeting people 1:1 to expand your network. Companies have arisen for both purposes including Airmeet, Run The World (see also), for the former, and Lunchclub for the later.

While many of the areas above are speculative, the movement to truly collaborative tooling for the business world is one of the two new big paradigm shifts for enterprises after the cloud (the other being Nocode/Lowcode/RPA). The Collaborative Enterprise is finally coming, and it is coming fast due to shifts in technology, user behavior, and bottoms up distribution.


[1] To coin a term, badly.

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