Speculation, bubbles, yes, they have always been around. I entered the VC world in the late 90s. Now we are in the unicorns era. Or were we?
I did my 537th startup cap. table a few days ago (see below). I had hesitated a little as I was not sure a company selling mattresses, even online, could be classified in my list of tech companies. But with VCs like NEA, IVP, Norwest on board and leading banks such as Goldman Sachs and Morgan Stanley as underwriters, it had all the needed pedigree. Or at least it looked like it.
Then I read Casper’s IPO is officially a disaster on CNN and Here’s why Casper’s disappointing IPO could spell disaster for other unicorns on Business Insider Nordic
What happened? Well the initial IPO price on the table below should have been $18, then it was fixed at $12 for the first day of trading and this morning CSPR is at $10.26. The unicorn is now a $400M company. And you may want to have a look at the price of the B, C and D preferred rounds on the table below. Yes disasters happen from time to time.
As a quick remined my latest list to be updated when I will have reached 550 tables.
Following my recent post, The largest technology companies in Europe and the USA in the last 10 years, I needed to add a quick follow-on which comes from the fact that many people asked me two additional questions:
– but what about China?
– but what about biotech?
I am not a specialist of either dimension but I tried to do a similar exercice in the past and yesterday. Here are the results:
Top China 2020
Top China 2016
Top Biotech 2020
Top Biotech 2016
Top Biotech 2007
I have a small doubt about the year of that last table (best effort only…) and all the data in a single pdf here: Top China and Biotech
Also a short synthesis to be compared with the previous post:
It’s just after reading on Twitter that Google had just become a trillion dollar company (In honor of Google becoming a $1T company today), and also after reading Nicolas Colin’s concerns about European technology companies (Will Fragmentation Doom Europe to Another Lost Decade?) that I remembered I used to compare US and European tech former startups.
So here are my past tables and also a short synthesis in the end. The full data in pdf in the end too.
USA vs. Europe in 2020
USA vs. Europe in 2018
USA vs. Europe in 2016
USA vs. Europe in 2014
USA vs. Europe in 2012
USA vs. Europe in 2010
USA vs. Europe: the Synthesis over the decade
If you prefer to download it all and a little more: Top US Europe (in pdf)
It’s by reading Nicolas Colin’s always interesting newsletter, European Straits #149, 10 Tech Giants That Are (Almost All) in Bad Shape that I decided to revisit quickly the growth of 3 tech giants that I have been following for many years now: Google, Facebook and Tesla. And here are their numbers in terms of thousands of employees, revenue and profit in $M.
If you really love numbers, here is a little more: their average growth of 5 years is about 20% for Google, 40% for Facebook and about the same for Tesla (except that they never made a profit). Google is older so it is not a fair comparison. here is a more precise analysis.
So are the three tech giants threatened? I am not sure given this steady growth.
Here is an updated version of my equity tables from startups which filed to go public at some point. There are about 525 individual companies as well as just below statistical synthesis relatively to fields, geography and periods of time about VC amounts, time to IPO, levels of sales and income at IPO (as well as PS and PE ratios), age of founders, number of founders, ownership in companies by catagories. I think ths may be of interest for some of you…
Following my traditional analysis of startups through their IPO filings documents (you can check my 2017 analysis on 400+ documents here or the tag #equity on this blog), here is an updated analysis with 500+ start-ups.
You can have a look at the full 500 cap. tables on scribd or look at a shorter synthesis which follows.I hope this is self-explanatory enough.
Uber’s S-1 has just been released. I jumped on the opportunity to analyze the shareholding of the startup, a thing I had tried to do in 2017 (with much less information – check here). Here are the figures that I found (subject to errors related to my possible too much eagerness…)
Uber cap. table – from the SEC S-1 published on April 12, 2019
And, if you do not have the courage to read my post What is the equity structure of Uber and Airbnb?, here is what I understood in March 2017:
Uber cap. table – A speculative exercise with very little information available
The age of founders of start-ups is a recurrent topic on this blog. You can just check it through hashtag #age. I have just updated my cap. table database with now 500 “famous-enough” companies for which I have compiled a lot of data. You can check here the most recent update with 450+ companies in mid 2018 – Some thoughts about European Tech. IPOs or a synthesis dated 2017 with 400 companies Equity in Startups.
I just looked at the age of 850 founders from these 500 companies. I think it is interesting. I hope you will agree… I am not even sure I need to comment much. Average age is 37 overall, 45 in biotech, 37 in hardware (electronics, telecom and computers, energy) and 32 in software/internet.
I just read about Sebastian Quintero’s data analyses on start-ups on his web site Towards Data Science. Thanks Martin H. 🙂 I was really fascinated about his original way of looking at them, their failure rate, the valuation prediction, their runway between rounds, and his Capital Concentration Index or Investor Cluster Score. You should read them.
Of course, it rang strong bells with all the data analyses I have done in the recent past 8see end of the post if you wish)
So as an appetizer to Quintero‘s work, here are a couple of figures taken from his site…
Dissecting startup failure rates by stage
Predicting a Startup Valuation with Data Science
How much runway should you target between financing rounds?
Introducing the Capital Concentration Index™
Where c is the percentage capital share held by the i-th startup, and N is the total number of startups in the defined set. In general, the CCI approaches zero when a sector consists of a large number of startups with relatively equal levels of capital, and reaches a maximum of 10,000 when a sector’s total invested capital is consolidated in a single company. The CCI increases both as the number of startups in the sector decreases and as the disparity in capital traction between those startups increases.
Introducing the Investor Cluster Score™ — a measure of the signal produced by a startup’s capitalization table
As of my own analysis, here are a couple of links…
My papers on arxiv:
– Are Biotechnology Startups Different? https://arxiv.org/abs/1805.12108
– Equity in Startups https://arxiv.org/abs/1711.00661
– Startups and Stanford University https://arxiv.org/abs/1711.00644
or on SSRN
– Age and Experience of High-tech Entrepreneurs http://dx.doi.org/10.2139/ssrn.2416888
– Serial Entrepreneurs: Are They Better? – A View from Stanford University Alumni http://dx.doi.org/10.2139/ssrn.2416888
– Start-Ups at EPFL. An Analysis of EPFL’s Spin-Offs and Its Entrepreneurial Ecosystems Over 30 Years https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3317131
Lyft is the first Unicorn which published its S-1 document, i.e. its IPO filing. Is this good news or bad news? Lyft is impressive, two founders who were 22 and 23 when they co-founded their start-up 12 years ago have reached more than $2B in sales with a little less than 5’000 employees in 2018. This is the good part. The less good piece is it took the company more than $5B in equity investment and the reason is simple: Lyft has lost $900M in 2018, and more than $600M in both 2017 and 2016. This is more than $2B cumulative loss. I assume losses were pretty high in the previous years too. YOu can have a look at the cap. table I built from the S-1:
I read recently an article by Tim O’Reilly: The fundamental problem with Silicon Valley’s favorite growth strategy. O’Reilly has doubts about Reid Hoffman and Chris Yeh’s claiming that Blitzscaling would be the secret of success for today’s technology businesses. “Imagine, for a moment, a world in which Uber and Lyft hadn’t been able to raise billions of dollars in a winner-takes-all race to dominate the online ride-hailing market. How might that market have developed differently?” I have the same doubts about this crazy strategy but who am I to say?…