Return on Investments – IRR & multiples

In venture capital, returns on investments is the ultimate metric and although it is not very difficult to understand, there are many little tricks worth knowing about!

The reason of this short post is a recent article my friend Fuad advised me to read from the Financial Times : The parallel universe of private equity returns by Jonathan Ford. If you are not a subsciber to the FT (and I am not), you may not be able to read the article so here are short extracts: “Ever wondered about the extraordinary performance figures that listed private equity firms trumpet in their official stock market filings? […] Not only do the firms generate stratospheric numbers — far higher than anything produced by the boring old stock market — but they can apparently do it year in, year out, with no decay in returns. […] The reality is that these consistent IRRs show nothing of the kind. What they actually demonstrate is a big flaw in the way the IRR itself is calculated.”

When I looked at venture capital (VC) returns in the past, I learned you must carefully look at what IRR means. It looks simple at first sight as the next table shows, just simple math:

So the first question you care about is what matters: IRRs or multiples? And my simple answer is “it depends”. Up to you!

Secondly, measuring returns makes a lot of sense when you have your money back. Of course! But IRR and multiples can also be measured while you are still invested and when your investment is not liquid, which is the case for private companies in which invests private equity (PE) – venture capital belongs to PE. You can have a look at a former post of mine, Is the Venture Capital model broken? and among other figures look at this:

VC2016-1-IRRs
The VC performance according to the Kauffman foundation

The peak IRR is measured when your assets are not liquid whereas the final IRR is when you have your money back… A fund as usually a 10-year life (or 120 months) and you can check the peak IRR month.

Even more tricky, the money is called by periods to make the holding as short as possible: basically, when the money is needed to invest, though you commit to it for the full life of the fund. Measuring the real IRR begins to be complicated but what matters to me is the multiple from the day of commitment to the finaldah when the money is back… And to you?

A final point I love to mention all the time is that VC is not so much about a portfolio of balanced investments. In the same post mentioned above, I added two links, and one of the best quote is “Venture capital is not even a home run business. It’s a grand slam business.”

Have a look at The Babe Ruth Effect in Venture Capital or In praise of failure. VC statistics are not gaussian, they follow a power law:

Grothendieck, a genius

I’ve written about Grothendieck here before, through two books about this mathematical genius published shortly after his death: Alexandre Grothendieck, 1928 – 2014. Summer is an opportunity for listening to radio broadcasts and I had the pleasure to rediscover this extraordinary character, first of all through Alexandre Grothendieck : un mathématicien qui prit la tangente initially broadcasted in La conversation scientifique in 2016 on French radio, France Culture,

and then by listening (while writing this post) to Alexandre Grothendieck ou le silence du génie first broadcasted in 2015 in Une vie, une œuvre, on the same radio.

From one thing to another, I downloaded Récoltes et semailles, a 929-page document written between 1983 and 1986 by the mathematician. You can download the pdf in French. Just as Perelman, Gödel or Erdős, for us, simple mortals, we can believe that genius rubs shoulders with madness and the journey, the life of these creators will undoubtedly remain mysteries forever.

I read a few dozen pages of this book and Chapter 2.20 fascinated me. I suggest you read it. I find this extract quite admirable and translated it with my limited means…

2.20 A shot look at the neighbors across the street

The situation seems to me very close to the one which arose at the beginning of this century, with the emergence of Einstein’s theory of relativity. There was a conceptual dead end, even more blatant, materializing in a sudden contradiction, which seemed irresolvable. Of course, the new idea that would bring order to the chaos was one of childish simplicity. The remarkable thing (and conforms to a most repetitive scenario…) is that among all these brilliant, eminent, prestigious people who were suddenly on their teeth, trying to “save what there was to be saved”, no one thought about this idea. It had to be an unknown young man, fresh from the benches of student lecture halls (maybe), who came (a little embarrassed perhaps at his own audacity…) to explain to his illustrious elders what had to be done to “save the phenomena”: one just had to separate space from time [68]! Technically, everything was gathered then for this idea to hatch and be welcomed. And it is to the honor of Einstein’s elders that they were indeed able to welcome the new idea, without resisting too much. This is a sign that these were still a great time…
From a mathematical point of view, Einstein’s new idea was trivial. From the point of view of our conception of physical space, however, it was a profound change, and a sudden “change of scenery”. The first mutation of its kind, since the mathematical model of physical space released by Euclid 2400 years ago, and taken up as is for the needs of mechanics by all physicists and astronomers since antiquity (including Newton), to describe terrestrial and stellar mechanical phenomena.
This initial idea of Einstein was subsequently much developed, embodied in a more subtle, richer and more flexible mathematical model, using the rich arsenal of already existing mathematical notions [69]. With the “generalized theory of relativity”, this idea broadened into a vast vision of the physical world, embracing in one look the subatomic world of the infinitely small, the solar system, the Milky Way and distant galaxies, and the path of electromagnetic waves in a space-time curved at each point by the matter which is there [70]. This is the second and last time in the history of cosmology and physics (following Newton’s first great synthesis three centuries ago) that a broad unifying vision has emerged, in the language of a mathematical model, of all the physical phenomena in the Universe.
This Einsteinian vision of the physical universe was in turn overwhelmed by events. The “set of physical phenomena” which it is a question of reporting has had time to expand since the beginning of the century! There have emerged a multitude of physical theories, each to account, with varying degrees of success, for a limited set of facts, in the immense mess of all “observed facts”. And we are still waiting for the daring kid, who will find by playing the new key (if there is one…), The dreamed “cake model”, who wants to “work” to save all phenomena at once… [71]
The comparison between my contribution to the mathematics of my time, and that of Einstein to physics, was imposed on me for two reasons: both work was accomplished through a mutation of our conception of “space” (in the mathematical sense in one case, in the physical sense in the other); and both take the form of a unifying vision, embracing a vast multitude of phenomena and situations which heretofore appeared to be separate from one another. I see there an obvious kinship between his work [72] and mine.
This relationship does not seem to me to be contradicted by an obvious difference in “substance”. As I hinted earlier, the Einsteinian mutation concerns the notion of physical space, while Einstein draws from the arsenal of already known mathematical notions, without ever needing to expand it, or even upset it. His contribution consisted in identifying, among the mathematical structures known of his time, those which were best suited to [73] serve as “models” for the world of physical phenomena, instead of the dying model bequeathed by his predecessors. In this sense, his work was indeed that of a physicist, and beyond that, that of a “philosophy of nature”, in the sense in which Newton and his contemporaries understood it. This “philosophical” dimension is absent from my mathematical work, where I have never been led to ask myself questions about the possible relations between the “ideal” conceptual constructions, taking place in the Universe of mathematical things, and phenomena that take place in the physical Universe (or even, lived events taking place in the psyche). My work has been that of a mathematician, deliberately turning away from the question of “applications” (to other sciences), or “motivations” and psychic roots of my work. Of a mathematician, moreover, driven by his very particular genius to constantly expand the arsenal of notions at the very basis of his art. This is how I was led, without even noticing it and as if playing, to upset the most fundamental notion of all for the surveyor: that of space (and that of “variety”), that is our conception of the very “place” where geometric beings live.
The new notion of space (like a kind of “generalized space”, but where the points which are supposed to form the “space” have more or less disappeared) does not resemble in any way, in its substance, the notion brought by Einstein in physics (not at all confusing for the mathematician). The comparison is necessary on the other hand with quantum mechanics discovered by Schrödinger [74]. In this new mechanism, the traditional “material point” disappears, to be replaced by a kind of “probabilistic cloud”, more or less dense from one region of ambient space to another, depending on the “probability” that the point is in this region. We feel, in this new perspective, a “mutation” even more profound in our ways of conceiving mechanical phenomena, than in that embodied by Einstein’s model – a mutation which does not consist in simply replacing a somewhat mathematical model, narrow at the armatures, by another similar one but cut wider or better adjusted. This time, the new model resembles so little the good old traditional models, that even the mathematician who is a great specialist in mechanics must have felt suddenly disoriented, even lost (or outraged…). Going from Newton’s mechanics to Einstein’s must be, for the mathematician, a bit like going from the good old Provencal dialect to the latest Parisian slang. On the other hand, to switch to quantum mechanics, I imagine, is to switch from French to Chinese. And these “probabilistic clouds”, replacing the reassuring material particles of yesteryear, strangely remind me of the elusive “open neighborhoods” that populate the topos, like evanescent ghosts, to surround imaginary “points”, which still continue to cling to and against all a recalcitrant imagination…

Notes :

[68] This is a bit short, of course, as a description of Einstein’s idea. At the technical level, it was necessary to highlight what structure to put on the new space-time (it was already “in the air”, with Maxwell’s theory and Lorenz’s ideas). The essential step here was not of a technical nature, but rather “philosophical”: to realize that the notion of simultaneity for distant events had no experimental reality. This is the “childish observation”, the “but the Emperor is naked!”, which made cross this famous “imperious and invisible circle which limits a Universe”…

[69] These are mainly the notion of “Riemannian manifold”, and the tensor calculus on such a manifold.

[70] One of the most striking features which distinguishes this model from the Euclidean (or Newtonian) model of space and time, and also from Einstein’s very first model (“special relativity”), is that the global topological form of space-time remains indeterminate, instead of being prescribed imperatively by the very nature of the model. The question of what this global form is strikes me (as a mathematician) as one of the most fascinating in cosmology.

[71] One called “unitary theory” such a hypothetical theory, which would manage to “unify” and to reconcile the multitude of partial theories of which it was question. I have the feeling that the fundamental thinking that awaits to be undertaken, will have to be placed on two different levels.
1_) A reflection of a “philosophical” nature, on the very notion of a “mathematical model” for a portion of reality. Since the successes of Newtonian theory, it has become an unspoken axiom of the physicist that there exists a mathematical model (or even a single model, or “the” model) to express physical reality perfectly, without “detachment” no burr. This consensus, which has been law for more than two centuries, is like a sort of fossil vestige of a living Pythagorean vision that “Everything is number”. Perhaps this is the new “invisible circle”, which replaced the old metaphysical circles to limit the Universe of the physicist (while the race of the “philosophers of nature” seems definitively extinct, supplanted handily by that of computers…). As long as one likes to dwell on it for a moment, it is quite clear, however, that the validity [of] this consensus is by no means obvious. There are even very serious philosophical reasons which lead to questioning it a priori, or at least to providing very strict limits to its validity. It would be the moment or never to submit this axiom to a tight criticism, and perhaps even, to “demonstrate”, beyond any possible doubt, that it is not founded: that there does not exist a unique rigorous mathematical model, accounting for all the so-called “physical” phenomena listed so far.
Once the very notion of “mathematical model” has been satisfactorily identified, and that of the “validity” of such a model (within the limits of such “margins of error” admitted in the measurements made), the question of a “unitary theory” or at least that of an “optimum model” (in a sense to be specified) will finally be clearly stated. At the same time, one will probably also have a clearer idea of the degree of arbitrariness which is attached (by necessity, perhaps) to the choice of such a model.
2_) It is only after such reflection, it seems to me, that the “technical” question of identifying an explicit model, more satisfactory than its predecessors, takes on its full meaning. It would then be the moment, perhaps, to break free from a second tacit axiom of the physicist, going back to antiquity, and deeply rooted in our very way of perceiving space: it is that of continuous nature of space and time (or space-time), of the “place” therefore where “physical phenomena” take place.
Fifteen or twenty years ago, leafing through the modest volume constituting Riemann’s complete work, I was struck by a remark from him “by the way”. He observes that it could well be that the ultimate structure of space is “discrete”, and that the “continuous” representations which we make of it perhaps constitute a simplification (excessive perhaps, in the long run…) of a more complex reality; that for the human mind, “the continuous” was easier to grasp than “the discontinuous”, and that it serves us, therefore, as an “approximation” for understanding the discontinuous. This is a remark surprisingly penetrating into the mouth of a mathematician, at a time when the Euclidean model of physical space had never before been questioned; in the strictly logical sense, it is rather the discontinuous which, traditionally, has served as a technical method of approach to the continuous.
Developments in mathematics in recent decades have, moreover, shown a much more intimate symbiosis between continuous and discontinuous structures than was previously imagined in the first half of this century. Still, to find a “satisfactory” model (or, if necessary, a set of such models, “connecting” as satisfactorily as possible..), that this one be “continuous”, “discrete” “or of a” mixed “nature – such work will undoubtedly involve a great conceptual imagination, and a consummate flair for apprehending and updating mathematical structures of a new type. This kind of imagination or “flair” seems rare to me, not only among physicists (where Einstein and Schrödinger seem to have been among the rare exceptions), but even among mathematicians (and here I speak with full knowledge of the facts).
To sum up, I predict that the expected renewal (if it has yet to come…) will come more from a mathematician at heart, knowledgeable about the great problems of physics, than from a physicist. But above all, it will take a man with “philosophical openness” to grasp the crux of the matter. This is by no means technical in nature, but a fundamental problem of “philosophy of nature”.

[72] I make no claim to be familiar with Einstein’s work. In fact, I haven’t read any of his work, and only know his ideas through hearsay and very roughly. Yet I feel like I can make out “the forest”, even though I’ve never had to make the effort to scrutinize any of its trees. . .

[73] For comments on the qualifier “moribund”, see a previous footnote (note page 55).

[74] I think I understand (by echoes that have come back to me from various sides) that we generally consider that in this century there have been three “revolutions” or great upheavals in physics: Einstein’s theory, the discovery of radioactivity by the Curies, and the introduction of quantum mechanics by Schrödinger.

A comparison of the Swiss and French innovation ecosystems

Here is ma latest contribution to Entreprise Romande, it dates back to february 2020, that is before the Covid19 lockdown…

A comparison of the Swiss and French innovation ecosystems.
Hervé Lebret, former head of the start-up unit, EPFL.

Having left Switzerland last August after more than twenty years at the service of high-tech innovation to come back to my beautiful native country, France, where I will continue to work with the founders of startup, I will try to make here a brief comparison of the two innovation systems, with the aim of giving some advice to my friends who stayed in Switzerland, assuming that it may not be necessary!

At the risk of disappointing the reader, it is at the margin that I see differences and this is undoubtedly good news. In the past twenty years, all European states have understood the importance of innovation for the future of the economy and jobs; one speaks about FrenchTech, SwissTech, but in reality one speaks all the more of the same thing as the mobility of ideas, people and companies attenuates the national characters.

However, there are still some differences. What strikes the most, at the risk of caricature, is that France remains the centralized state that Louis XIV then Napoleon sculpted while Switzerland is viscerally federal. For example BPIFrance, the National Public Investment Bank, is critical to innovation both in Paris and in the regions and I don’t think there is an equivalent in Switzerland. The CTI, which would be closest to a national innovation agency, manages a few hundred million Swiss Francs where BPI manages tens of billions of Euros. The ratio is out of proportion to the relative size of the economies of the two countries.

The two agencies have great similarities in the sense that they finance a number of programs from awareness-raising and training in entrepreneurship to funding innovation projects in research centers and personalized advice to entrepreneurs. There is, however, a significant nuance: the public authorities do not directly finance companies or investment funds in Switzerland and these activities are left to the private sector, while in France, BPI finances startups and venture capital funds. . This is a major difference which partly explains the weakness of venture capital in Switzerland. The impact remains difficult to measure, however, because Swiss startups find capital abroad.

The French system also remains more bureaucratic despite major changes in recent years. Switzerland remains more pragmatic: philosophically it seems to me that the law expresses what is allowed in France, what is prohibited in Switzerland, it is a nuance which makes Switzerland more flexible and let us not forget that smaller size has many advantages over complexity. However I have wondered in recent years if the Swiss system has not had a certain tendency to become more complex and even to become more rigid like the French system, but this is just a feeling; I do not have enough data. I am refering, for example, of all the national or international programs, the objective of which is to make the ecosystem more visible: Digital Switzerland on the one hand, Startup Nation on the other; Human brain on one side, quantum computer on the other. Woe to those who are not members of them…

So if I can allow some advice, innovation is not a big machine that we can plan. A multitude of initiatives is better than big programs. Faced with the France of the CAC40, Switzerland has always preferred its fabric of SMEs, at the risk for each country to forget the importance of startups. Both countries have positively evolved, but I have a little fear of convergence towards this complex and slightly bureaucratic planning that I briefly mentioned. In reality, innovation is a fragile object, it is necessary to deal with a good deal of benevolence and tact [1].

[1] https://www.startup-book.com/2015/10/19/what-makes-an-entrepreneurial-ecosystem-by-nicolas-colin/​​

Equity sharing in startups – a presentation

A few days ago, I had the opportunity to present a video conference on equity sharing in a startup, between founders, investors and employees. I’ve done it many times in the last few years like the one Slideshare here, but I had never recorded it. It’s now done:

As archive, the Slideshare presentation…

The other links

600 capitalisation tables: https://www.startup-book.com/2020/04/06/updated-data-in-equity-of-600-former-startups/

Universities and equity ownership in startups : https://www.startup-book.com/2013/11/05/how-much-equity-universities-take-in-start-ups-from-ip-licensing/

Startups and titles : https://www.startup-book.com/2019/12/11/titles-in-start-ups/

Penny Schiffer’s Tweet : https://twitter.com/PennySchiffer/status/718323492006076417

Slicing pie : https://slicingpie.com/

Pie calculator : https://www.andrew.cmu.edu/user/fd0n/35%20Founders%27%20Pie%20Calculator.htm

Two additional lists of references I just found thanks to Penny Schiffer: Useful resources for (present and future) investment analysts — Part 1 and Part 2

The amazing challenge of finding great startups

“Prediction is very difficult, especially about the future.” attributed to Niels Bohr.

I was asked yesterday which startups I knew were the most promising, not to say the greatest. So I prefer to refer you to the quote above as I did not understand the potential of Google and Skype when I first heard of them. I am less shy of my lack of talent as this difficulty in predicting has been acknowledged by others.

Already in 2011, I had posted on the topic in The Missed Deals of Venture Capitalists. You should read the examples of Amazon and Starbucks by OVP.

So I did a little search and found again some more examples from again the antiportfolio of BVP (Bessemer Venture Partners) as well as from the book The Business of Venture Capital by Mahendra Ramsinghani. Enjoy!

First from the book The Business of Venture Capital on page 207:

Legendary investor Warren Buffet admired Bob Noyce, cofounder of Fairchlid Semiconductor and Intel. Buffet and Noyce were fellow trustees at Grinnell College, but when presented, Buffet passed on Intel, one of the greatest investing opportunities of his life. Buffet seemed “comfortably antiquated” when it came to new technology companies and had a long-standing bias against technology investments.

Peter O. Crisp of Venrock adds his misses to the list: One “small company in Rochester, New York [came to us, and one of our junior guys] saw no future [for] this product… that company, Haloid, became Xerox.” They also passed on Tandem, Compaq and Amgen.

ARCH Venture Partners missed Netscape – that little project Marc Andreessen started at the University of Chicago. An opportunity that, according to Steven Lazarus, would have been worth billions! “We just never knocked at the right door,” he would say. Eventually, ARCH decided to hire full-time person to just keep tabs on technology coming out of the universities to “make certain we don’t miss that door next time.”

Deepak Kamra from Canaan Partners comments on his regrets: “Oh, God, I have too many … this gets me depressed. A friend of mine at Sun Microsystems called and asked me to meet with an engineer at Xerox PARC who had some ideas to design a chip and add some protocols to build what is now known as a router. The drivers of bandwidth and Web traffic were strong market indicators, and he was just looking for $100,000. I really don’t do deals that small and told him lo raise some money from friends and family and come back when he had something to show” That engineer was the founder of Juniper Networks. He got his $100,000 from Vinod Khosla. Khosla, then with KPCB, added an IPO to his long list of winners. Juniper slipped out of Kamra’s hands because it was too early.
And of course, those were frothy times when everyone was deluged with hundreds of opportunities each day.

KPCB missed an opportunity to invest in VMWare because the valuation was too high: a mistake, according to John Doerr.

Draper Fisher Jurvetson (DFJ) was initially willing but eventually passed on Facebook (ouch!), as the firm believed the valuation was too high at $100 million pre-money.

KPCB, not wanting to be left out of an opportunity like Facebook, invested $38 million alt a $52 billion valuation.

Tim Draper of DFJ, turned down Google “because we already had six search engines in our portfolio.”

K. Ram Shriram almost missed his opportunity to invest in Google when he turned the founders away. “I told Sergey and Larry that the time for search engines had come and gone but I am happy to introduce you to all the others, who may want to buy your technology. But six months later, Ram Shriram, who had once turned Google down, now invested $500,000 as one of the first angel investors.

By the way Tim Draper’s father Bill also missed Yahoo. You can check The Startup Game by Bill Draper.

Now some examples of the updated BVP antiportfolio:

AirBnB: Jeremy Levine met Brian Chesky in January 2010, the first $100K revenue month. Brian’s $40M valuation ask was “crazy,” but Jeremy was impressed and made a plan to reconnect in May. Unbeknownst to Jeremy, $100K in January became 200 in February and 300 in March. In April, Airbnb raised money at 1.5X the “crazy” price.

Facebook: Jeremy Levine spent a weekend at a corporate retreat in the summer of 2004 dodging persistent Harvard undergrad Eduardo Saverin’s rabid pitch. Finally, cornered in a lunch line, Jeremy delivered some sage advice, “Kid, haven’t you heard of Friendster? Move on. It’s over!”

Atlassian: Byron Deeter flew straight to Atlassian in 2006 when he caught wind of a developer tool from Australia (of all places!). Notes from the meeting included “totally self-financed, started with a credit card” and “great business, but Scott & Mike don’t ever want to be a public company.” Years and countless meetings later, the first opportunity to invest emerged in 2010, but the $400m company valuation was thought to be a tad “rich.” In 2015, Atlassian became the largest tech IPO in Australian history, and the shares we passed on are worth more than a billion dollars today.

Tesla: In 2006 Byron Deeter met the team and test-drove a roadster. He put a deposit on the car, but passed on the negative margin company telling his partners, “It’s a win-win. I get a great car and some other VC pays for it!” The company passed $30B in market cap in 2014. Byron paid full price for his Model X.

eBay: David Cowan passed on the Series A round. Rookie team, regulatory nightmare, and, 4 years later, a $1.5 billion acquisition by eBay.

But one of the nicest stories I had heard of is Nolan Bushnell, founder and CEO of Atari, declining Apple… I heard of it through (absolute must-watch) Something Ventured. More here How Atari’s Nolan Bushnell turned down Steve Jobs’ offer of a third of Apple at $50,000.

The dark and mysterious side of British unicorns : Darktrace Ltd

My naive and obsessive quest for startup cap. tables has led me today to a thriller-like research! First I will let you have a look at Darktrace cap. table which I decided to study as it belongs to the short list of UK unicorns together with Revolut and Graphcore.

Well the first surprising information is the founding structure, ICP London. Why a British Virgin Islands structure? To hide who the founders are? Then I discovered surprising board members, Michael Lynch, the founder of Autonomy and Sushovan Hussain, the former Autonomy CFO… Autonomy was always a puzzle to me before becoming a scandalous HP acquisition and then the cause of a huge trial, not decided yet… And in law, you are innocent unless proven guilty.

Another strange side of the company is its links to secret services, MI5, CIA, NSA. Probably not so surprising when your industry is cybersecurity… Being based in Cambridge, it is not surprising that many Darktrace employees were at Autonomy before. The board members I did not know, but the investors are famous: Summit, KKR, Insight. Less maybe is Invoke Capital board members Vanessa Colomar and Andrew Camper. Lynch and Hussain are not on the board anymore and this is probably linked to the HP Autonomy litigation.

Then I got it: Invoke Capital Partners… ICP! So Darktrace was indeed founded by the former Autonomy people and its new investment structure, Invoke. I had to do a little more search and found two quite fascinating articles:

Skeletons In The Closet: $2 Billion Cybersecurity Firm Darktrace Haunted By Characters From HP’s Failed Autonomy Deal, a remarkable enquiry published in Feb. 2020 by Forbes staff member, Thomas Brewster.

And 2019 Darktrace and Autonomy: tracking down all the money and CEOs published in Dec. 2018 by Luca Kosev is nearl as good!

Worth reading. Enjoy!

The lean startup – my skepticism

I read again today about the importance of the lean startup movement. I have never been a big fan. Of course you need to interact with customers (at least to sell something) but you should not become a slave of your customers and pivot as soon as you can not get validation from them.

Do not get me wrong, I am a big fan of Steve Blank and customer development, I use his work a lot. But there is so much uncertainty, the tool should not replace the vision and intuition of the entrepreneur. Let me quote again Horowitz for example: “Figuring out the right product is the innovator’s job, not the customer’s job. The customer only knows what she thinks she wants based on her experience with the current product. The innovator can take into account everything that’s possible, but often must go against what she knows to be true. As a result, innovation requires a combination of knowledge, skill, and courage. Sometimes only the founder has the courage to ignore the data.”

It reminded me I had read something about this from Peter Thiel. I found it again in a 2014 post: Should entrepreneurs have start-up skills? Two counterintuitive answers. Here is what Thiel had said: “What do I think about lean startups and iterative thinking where you get feedback from people versus complexity that may not work. I’m personally quite skeptical of all the lean startup methodology. I think the really great companies did something that was somewhat more of a quantum improvement that really differentiated them from everybody else. They typically did not do massive customer surveys, the people who ran these companies sometimes, not always, suffered from mild forms of Aspergers, so they were not actually that influenced, not that easily deterred, by what other people told them to do. I do think we’re way too focused on iteration as a modality and not enough on trying to have a virtual ESP link with the public and figuring it out ourselves.”

And this morning I found another 2015 contribution to the debate which is worth reading: Peter Thiel is right about Lean Startup.

In a nutshell, “Lean Startup is best used as a teaching tool for those who need a little help in learning how to use their mirror neurons to feel the real needs of the real people they are seeking to serve. It can help to reduce waste. It can help to slow the rate of decline of organizations that are being disrupted.”

Two new British startup cap. tables: Autonomy and Bicycle

I recently published an updated version of a database of capitalization tables of 600 (former) startups. I obtain the data most of the time from the IPO prospectus of the company (that is the document the company publishes when it is listed on a public stock exchange, and in general Nasdaq.

These documents are an amazing source of information of all the business components of the companies even if I focus only on the shareholding and funding history. They are sometimes a little frustrating though as they do not cover the full history of the company, but only 3 to 5 years in the past so it is not simple to get the founders’ data for example.
Some countries do however provide access to the full company data, often for a fee like in France. A few cantons in Switzerland (Basel, Zurich) and the United Kingdom provide it for free and this is just great.

I have done some research for Revolut and Graphcore recently. Today, I revisited the data I had built for two British companies: Autonomy founded in 1996 and had gone public on Easdaq in 1998 and Bicycle Therapeutics, a biotech company with links to EPFL (Lausanne, Switzerland) founded in 2009 and public since July 2019.

The IPO documents did not provide enough for me about the founders and early rounds. So here are my new tables:

Autonomy

Bicycle from the IPO data

Bicycle from the UK register data, the updated cap. table, the funding rounds and its growth over time:

The funding rounds


The growth of revenues and jobs

Data about equity of 600 startups – comments (7)

A final post (for now) about the data about 600 (former) startups. So what have they become today in April 2020?

First a quick point of caution: I counted some companies twice, because I had looked at their equity strutcure at different points in time: Alibaba had two IPOs in 2007 in HK and 2014 in the USA, Esperion had 2 filings in 2000 and 2013. This is not a big deal, except if you count Alibaba’s value twice!

So out of the about 600 former startups, I found that
– 20 were still private (they may have recently filed for IPOs though)
– 12 were private again after an IPO
– 13 had stopped their activity (often through bankruptcy)
– 225 had been acquired or merged with another company (Merger and acquisitions – M&As)
– 331 were still public.

So let us have a closer look at M&As and public companies:

On the M&A side, the main acquisition value comes from biotech, with a $5B average value whereas software or internet is a little les below $3B.

On the public side, I will let you discover depending on your interest about, given the field, the number of companies, employees, cumulative market capitalizations, sales, profits, then age of companies and current average price to sales (PS), price to earnings (PE) and an interesting personal metrics, price ot employees in $M (Pemp).

Graphcore shareholding is really strange!

Graphcore gave me concerns. How is it possible that the two founders, Simon Knowles (58) and Nigel Toon (56), two serial entrepreneurs, who founded Icera Semiconductor in the past (sold to Nvidia in 2011 for $435 million or $367 million depending the sources – after having raised $258 million) and Element14 (a 1999 spin-off of Acorn – or its new name – sold to Broadcom in 2000 for $640 million), each owns only 4 shares of the startup? Are they so rich that they don’t need more? !!

All this follows my recent discovery that the UK gave open access to all company and in particular startup data. I began with Revolut a few days ago and now Graphcore. There had to be something wrong. The startup could not have only investors as shareholders. And then of course, I had forgotten the ESOP, the employee stock-options. So my only explanation is that the founders are part of this too and have a minimal number of shares. Still intriguing!