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.
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.
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
This is a research work I did recently and after trying very shortly to publish it in academic papers, I stopped trying. Maybe it is not good enough. Maybe the research world and I do not fit! It is the result of two series of research I have done for years, one about Stanford-related spin-offs and another about equity in start-ups.
I encourage you to read it if the field is of interest for you or just have a look at the tables below which I extracted from this 5-page short document.
In the recent years, there had been regular filings in the biotech field, but IT had suffered. then Dropbox and Spotify filed and successfully went public. This probably gave confidence to “unicorns” and many have filed recently such as Smartsheet, DocuSign, Zuora. Carbon Black is the latest one with an interesting history. here is its S-1 filing and below my computed cap. table.
Carbon Black was founded in 2002, has raised close to $200M since inception (not counting the money raised by 4 startups is has acquired, Confer Technologies, Objective Logistics & VisiTrend). It has a royal list of VCs, including Kleiner Perkins, Sequoia, Highland, Atlas or lesser know funds such as .406 or Accomplice. I do not know who the founders were, but I could get the name of Todd Brennan who has left in 2008. Who else, help me! Finally the company is based close to Boston, not in Silicon Valley… This is just the latest of my compilations, that you may find in a previous post Equity in Startups.
Yesterday, in Do Ex-Startup Founders Make The Best Venture Capitalists? I mentioned CB Insights analysis about the background of the top VCs, and expressed my doubts about comparing founders vs. non founders. So I used the Top100 list and had a different look: what about the background in high-tech or not? Here are some charts. Quick and dirty so do not take it as a scientific analysis. Still…
First a point of caution. This list is a little strange and the authors know better than me, but I am sure this list is not highly subjective… Now it seems founders were never a majority and VCs with no high-tech experience always a majority. Now what is puzzling is that these VCs are rather young and that a high majority of them having been in the business for less the 20 years… interesting. What would have been the results of the VCs active in the 70s and 80s? Not sure…
Also the change in the last 15 years is not the ratio with a tech background, but the ones who are founders has increased and the ones with no tech background has decreased…
Interesting question as I have often claimed that there was a difference between US and European venture capitalist (VC), which had been also illustrated in the past by Tim Cruttenden (see below).
CB Insights, a leading firm analyzing data about start-ups, looked at the experience of VCs: Do Ex-Startup Founders Make The Best Venture Capitalists? The next figure illustrates their results and they additionally claim: “Of the 100 VCs, 38 founded or co-founded a company before becoming venture investors, while 62 did not. Six of CB Insights’ top 10 investors haven’t founded a company. That includes the top two: Benchmark’s Bill Gurley and the recently retired Chris Sacca.”
However interesting, I would have preferred a different analysis: how many had a direct experience in technology firms, whether in product / technology development or on the business sides such as sales or marketing compared to teh ones who were “only” consultants or bankers. This would be highly important as the value you bring t the board level may be entirely different. Look at what Tim Cruttenden explained in 2006.
Indeed Cruttenden says “entrepreneurs” too, but if we remember that Kleiner Perkins and Sequoia had a lot of managers more than entrepreneurs then, we might have obtained another measure of what makes a good VC…
This is the third short report I publish this summer about startups. After Startups at EPFL and Stanford and Startups, here is (I hope) an interesting analysis about how equity was allocated in 400 startups, entitled Equity in Startups (in pdf). Here is the description of the report on its back page: Startups have become in less than 50 years a major component of innovation and economic growth. An important feature of the startup phenomenon has been the wealth created through equity in startups to all stakeholders. These include the startup founders, the investors, and also the employees through the stock-option mechanism and universities through licenses of intellectual property. In the employee group, the allocation to important managers like the chief executive, vice-presidents and other officers, and independent board members is also analyzed. This report analyzes how equity was allocated in more than 400 startups, most of which had filed for an initial public offering. The author has the ambition of informing a general audience about best practice in equity split, in particular in Silicon Valley, the central place for startup innovation.
I will let you (hopefully) discover this rather short report which could have been much longer if I had decided to analyze the data in detail. I will just right here my main results. A simple look at data shows that at IPO (or exit) founders keep around 10% of their company whereas investors own 50% and employees 20%. The remaining 20% goes to the general public at IPO . Of course, this is a little too simplistic. For examples founders keep more in Software and Internet startups and less in Biotech and Medtech. There could be a lot more to add but I let the reader focus on what possibly interests her.
Additional interesting points are:
– The average age of founders is 38 but higher in Biotech and Medtech and lower in Software and Internet.
– It takes on average 8 years to go public after raising a total of $138M, including a first round of $8M in VC money.
– On average, companies have about $110M in sales and are slightly profitable, with 500 employees at IPO time. But again there are differences between Software and Internet startups which have more sales and employees and positive income and Biotech and Medtech startups which have much lower revenue and headcount and negative profit.
– The CEO owns about 3% of the startup at exit. This is 4x less the founding group and depending when she (although it is too often a “he”) joined it would mean up to 20% close to foundation (assuming the founders would keep 80% and allocate the delta to the CEO)
– CEOs are non-founders in about 36% of the cases, more in biotech (42%) and Medtech (35%) than Internet (31%) and Software (25%), more in Boston (48%) than Silicon Valley (43%) .
– The Vice-Presidents and Chief Officers own about 1% and the Chief Financial around 0.6%.
– Finally, an independent director gets about 0.3% of the equity at IPO. If we consider again that the founders are diluted by a factor 8x from their initial 100% to about 12%, it means a director should have about 2-3% if he joins at inception.
– In the past universities owned about 10% of a startup at creation in exchange for an exclusive license on IP. More recently, this has been more 5% non-diluted until significant funding (Series A round).
Stanford is in the top2 universities with MIT for high-tech entrepreneurship. There is not much doubt about such statement. For the last ten years, I have been studying the impact of this university which has grown in the middle of Silicon Valley. After one book and a few research papers, here is a kind of concluding work.
A little less than 10 years ago, I discovered the Wellspring of Innovation, a website from Stanford University listing about 6’000 companies and founders. I used that list in addition from data I had obtained from OTL, the Stanford office of technology licensing as well as some personal data I had compiled over years. The report Startups and Stanford University with subtitle “an analysis of the entrepreneurial activity of the Stanford community over 50 years”, is the result of about 10 years of research. Of course, I did not work on it every day, but it has been a patient work which helped me analyze more than 5’000 start-ups and entrepreneurs. There is nearly not storytelling but a lot of tables and figures. I deliberately decided not to draw many conclusions as each reader might prefer one piece to another. The few people I contacted before publishing it here twitted about it with different reactions. For example:
Katharine Ku, head of OTL has mentioned another report when I mentioned mine to her: Stanford’s Univenture Secret Sauce – Embracing Risk, Ambiguity and Collaboration. Another evidence of the entrepreneurial culture of that unique place! I must thank Ms Ku here again for the data I could access thanks to her!
This report is not a real conclusion. There is still a lot to study about high-tech entrepreneurship around Stanford. With this data only. And with more recent one probably too. And I will conclude here with the last sentence of the report: “How will it develop in the future is obviously impossible to predict Therefore a revisited analysis of the situation in a decade or so should be very intersting.”