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Talent vs Luck: the role of randomness in success and failure

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I must thank my friend and colleague Fuad for pointing to me a remarkable research article entitled Talent vs Luck: the role of randomness in success and failure. You can find the paper on Arxiv in pdf format.

I must say this resonates with research I did in the past on serial entrepreneurs, where I discovered there was no real correlation between experience and success in high-tech entrepreneurship. Here is a link to this work: Serial entrepreneurs: are they better?

If you are interested, just download and read the paper. Here are some short teasers from their paper:

It is very well known that intelligence (or, more in general, talent and personal qualities) exhibits a Gaussian distribution among the population, whereas the distribution of wealth – often considered a proxy of success – follows typically a power law (Pareto law), with a large majority of poor people and a very small number of billionaires. Such a discrepancy between a Normal distribution of inputs, with a typical scale (the average talent or intelligence), and the scale invariant distribution of outputs, suggests that some hidden ingredient is at work behind the scenes. In this paper, with the help of a very simple agent-based toy model, we suggest that such an ingredient is just randomness. [Page 1]

There is nowadays an ever greater evidence about the fundamental role of chance, luck or, more in general, random factors, in determining successes or failures in our personal and professional lives. In particular, it has been shown that scientists have the same chance along their career of publishing their biggest hit; that those with earlier surname initials are significantly more likely to receive tenure at top departments; that the distributions of bibliometric indicators collected by a scholar might be the result of chance and noise related to multiplicative phenomena connected to a publish or perish inflationary mechanism; that one’s position in an alphabetically sorted list may be important in determining access to over-subscribed public services; that middle name initials enhance evaluations of intellectual performance; that people with easy-to-pronounce names are judged more positively than those with difficult-to-pronounce names; that individuals with noble-sounding surnames are found to work more often as managers than as employees; that females with masculine monikers are more successful in legal careers; that roughly half of the variance in incomes across persons worldwide is explained only by their country of residence and by the income distribution within that country; that the probability of becoming a CEO is strongly influenced by your name or by your month of birth; that the innovative ideas are the results of a random walk in our brain network; and that even the probability of developing a cancer, maybe cutting a brilliant career, is mainly due to simple bad luck. Recent studies on lifetime reproductive success further corroborate these statements showing that, if trait variation may influence the fate of populations, luck often governs the lives of individuals. [Page 2]

So here are some striking results:

But to understand the real meaning of [these] findings it is important to distinguish the macro from the micro point of view. In fact, from the micro point of view, following the dynamical rules of the model, a talented individual has a greater a priori probability to reach a high level of success than a moderately gifted one, since she has a greater ability to grasp any opportunity that will come. Of course, luck has to help her in yielding those opportunities. Therefore, from the point of view of a single individual, we should therefore conclude that, being impossible (by definition) to control the occurrence of lucky events, the best strategy to increase the probability of success (at any talent level) is to broaden the personal activity, the production of ideas, the communication with other people, seeking for diversity and mutual enrichment. In other words, to be an open- minded person, ready to be in contact with others, exposes to the highest probability of lucky events (to be exploited by means of the personal talent). On the other hand, from the macro point of view of the entire society, the probability to find moderately gifted individuals at the top levels of success is greater than that of finding there very talented ones, because moderately gifted people are much more numerous and, with the help of luck, have – globally – a statistical advantage to reach a great success, in spite of their lower individual a priori probability. [Page 14]

The authors draw some practical recommendations: for example, for strategies about funding research among a diversity of talented people looking at the table [below], it is evident that, if the goal is to reward the most talented persons (thus increasing their final level of success [C]), it is much more convenient to distribute periodically (even small) equal amounts of capital to all individuals rather than to give a greater capital only to a small percentage of them, selected through their level of success – already reached – at the moment of the distribution. The histogram shows that the “egalitarian” criterion, which assigns 1 unit of capital every 5 years to all the individuals is the most effcient way to distribute funds. [Pages 17-18]

Finally, the environment may have a role, such as improbing education, hence talent: Strengthening the training of the most gifted people or increasing the average level of education produce, as one could expect, some beneficial effects on the social system, since both these policies raise the probability, for talented individuals, to grasp the opportunities that luck presents to them. On the other hand, the enhancement in the average percentage of highly talented people who are able to reach a good level of success, seems to be not particularly remarkable in both the cases analyzed, therefore the result of the corresponding educational policies appears mainly restricted to the emergence of isolated extreme successful cases. […] Also, it results that increasing the variance without changing the average, enhances the chances for more talented people to get a very high success. This, on one hand, could be considered positive but, on the other hand, it is an isolated case and it has, as a counterpart, an increase in the gap between unsuccessful and successful people. Increasing the average without changing the variance induces that also in this case the chances for more talented people to get a very high success are enhanced, while the gap between unsuccessful and successful people is lower than before. [Pages 20-21]

As a stimulating conclusion, the authors write: Our results highlight the risks of the paradigm that we call “naive meritocracy”, which fails to give honors and rewards to the most competent people, because it underestimates the role of randomness among the determinants of success. In this respect, several dfferent scenarios have been investigated in order to discuss more effcient strategies, which are able to counterbalance the unpredictable role of luck and give more opportunities and resources to the most talented ones – a purpose that should be the main aim of a truly meritocratic approach. Such strategies have also been shown to be the most beneficial for the entire society, since they tend to increase the diversity of ideas and perspectives in research, thus fostering also innovation. [Page 23]

The Black Swan and the danger of statistics

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“Thought is only a flash in the middle of a long night. But this flash means everything.”
Henri Poincaré*

When I talked to friends and colleagues about The Black Swan (“BS”), they were surprised about my interest in the movie with Natalie Portman. I cannot say, I have not watched it. I was talking about Nassem Nicholas Taleb’s book and theory. Some other friends classified at it as American b… s…, these superficial books that give advice on anything and that seem to always become bestsellers; my colleagues would classify it as airport literature, not to be read in academic circles.

I read it and enjoyed it, but I have to admit Taleb is sometimes painful. Is it because he was so much frustrated by I do not know whom or what or is it because he is so proud of his certainties? I am not sure. But his ideas are certainly worth thinking about more than a minute. (Whereas you forget about airport American b… s… after 30 seconds). So back to the BS.

You’ll find great accounts of his book or of his theory, e.g.
– Nassim Taleb’s “The Black Swan” by Andrew Gelman,
– The Wikipedia page on the Black Swan theory
– or even another essay by Taleb, the Fourth Quadrant,
so I will not try to do the same.

However defining the Black Swan might be useful! In the Fourth Quadrant, Taleb writes the following:

There are two classes of probability domains—very distinct qualitatively and quantitatively. The first, thin-tailed: Mediocristan”, the second, thick tailed Extremistan. Before I get into the details, take the literary distinction as follows: In Mediocristan, exceptions occur but don’t carry large consequences. Add the heaviest person on the planet to a sample of 1000. The total weight would barely change. In Extremistan, exceptions can be everything (they will eventually, in time, represent everything). Add Bill Gates to your sample: the wealth will jump by a factor of >100,000. So, in Mediocristan, large deviations occur but they are not consequential—unlike Extremistan. Mediocristan corresponds to “random walk” style randomness that you tend to find in regular textbooks (and in popular books on randomness). Extremistan corresponds to a “random jump” one. The first kind I can call “Gaussian-Poisson”, the second “fractal” or Mandelbrotian (after the works of the great Benoit Mandelbrot linking it to the geometry of nature). But note here an epistemological question: there is a category of “I don’t know” that I also bundle in Extremistan for the sake of decision making—simply because I don’t know much about the probabilistic structure or the role of large events. Black Swans are the unknown deviations in Extremistan.

Here are more notes taken while reading.

[Page xxii] The black swan is characterized by “rarity, extreme impact and retrospective (though not prospective) predictability” (with additional footnote: the occurrence of a highly improbably event is the equivalent of the nonoccurrence of a highly probably one.

[Page 8] The human mind suffers from 3 aliments:
-The illusions of understanding, or how everyone thinks he knows what is going on in a world that is more complicated (or random) than they realize;
-the retrospective distortion, or how we can assess matters only after the fact, as if they were in a rearview mirror; and
-the overvaluation of factual information and the handicap of authoritative and learned people – when they platonify.

[Page 15] While in the past a distinction had been between drawn Mediterranean and non- Mediterranean (i.e., between the olive oil and the butter), in the 1970s, the distinction suddenly became between Europe and non-Europe.

[Page 54] There is a major difference and often-made mistake between no evidence of something and the evidence of its non-occurence (mental bias.)

[Page 77] The answer is that there are two varieties of rare events: a) the narrated Black Swans, those that are present in the current discourse and that you are likely to hear about on television, and b) those nobody talks about, since they escape models – those that you would feel ashamed discussing in public because they do not seem plausible. I can safely say that it is entirely compatible with human nature that the incidences of Black Swans would be overestimated in the first case, but severely underestimated in the second one.

[Page 80] One death is a tragedy; a million is a statistic. […] We have two systems of thinking. System 1 is experiential, effortless, automatic, fast, and opaque. System 2 is thinking, reasoned, local, slow, serial, progressive. Most mistakes come from using system 1 when we think we use system 2.

[Page 140] We overestimate what we know and underestimate uncertainty. Another bias, ”think about how many people divorce. Almost all of them are acquainted with the statistic that between one-third and one-half of all marriages fail, something the parties involved did not forecast while tying the know. Of course, “not us” because “we get along so well” (as if others tying the know got along poorly.)”

[Page 174-179] Poincaré is a central personality of Taleb’s theory, in particular through the 3-body problem. According to Taleb, “Poincaré angrily disparages the use of the bell curve.” Now the next figure simply illustrates the concept of sensitivity to initial conditions.

Predicting

Operation 1: imagine an ice cube and consider how it may melt.
Operation 2: consider a puddle of water. Try to reconstruct the shape of the ice-cube.
The forward process is generally used in physics and engineering, the backward process in nonrepeatable, nonexperimental historical approaches. And the backward is much more complex to analyze.

[Page 198] While in theory it is an intrinsic property. In practice, randomness is incomplete information. Nonpractitioners do not understand the subtlety. A true random process does not have predictable properties. A chaotic system has entirely predictable properties, but they are hard to know.
a) There are no functional differences in practice between the two since we will never get to make the distinction.
b) The mere fact that a person is talking about the difference implies he has never made a meaningful decision under uncertainty – which is why he does not realize that they are indistinguishable in practice.
Randomness in practice, in the end, is just unknowledge. The world is opaque and appearances fool us.

[Page 204] Trial and error means trying a lot. In the Blind Watchmaker, Richard Dawkins brilliantly illustrates this notion of the world without grand design, moving by small incremental random changes. Note a slight disagreement on my part that does not change the story by much: the world, rather moves by large incremental random changes. Indeed, we have psychological and intellectual difficulties with trial and error and with accepting that series of small failures are necessary in life. “You need to love to lose”. In fact the reason I felt immediately at home in America is precisely because American culture encourages the process of failure, unlike the cultures of Europe and Asia where failure is met with stigma and embarrassment.
[It’s really Taleb writing and not the blog’s author, but I fully agree !]

[Page 207] When you have a very limited loss, you need to be as aggressive as speculative and sometimes as unreasonable as you can be. Middlebrow thinkers sometimes make the analogy with lottery tickets. It is plain wrong. First lottery tickets do not have a scalable payoff. Second, lottery tickets have known rules.

The economics of superstars

[Page 24] Who is this book written for? You need to understand who your audience is and amateurs write for themselves, professionals write for others. [This irony of the author’s is stimulating. I experienced it, I’m an amateur. But are the masterpieces not then written by amateurs? The Black Swans (The Lord of the Rings, Harry Potter) look often like a work of amateurs. The Yevgenia Krasnova example provided by Taleb is also stimulating]

[Page 214] Someone who is marginally better can easily win the entire pot. The problem is the notion of “better.” People take from the poor to give to the rich. An initial advantage follows someone through life and keep getting cumulative advantages. Failure is also cumulative. The advent of modern media has accelerated these cumulative advantages. The sociologist Pierre Bourdieu noted a link between the increased concentration of success and the globalization of culture and economic life.

[Page 221] Taleb claims new comers mitigate the cumulative advantages. “of the five hundred largest US companies in 1957, only seventy-four were still part of that select group, the S&P 500, forty year later. Only a few hundred had disappeared in mergers; the rest either shrank or went bust.

Actors who win an Oscar tend to live on average five years longer than their peers who don’t. People live longer in societies that have flatter social gradients.

[Page 277] What is poorly understood is the absence of a role for the average in intellectual production. The disproportionate share of the very few in intellectual influence is even more unsettling than the unequal distribution of wealth- unsettling because, unlike the income gap, no social policy can eliminate it. Communism could conceal or compress income discrepancies, but it could not eliminate the superstar system in intellectual life. [I am not sure]

Skepticism

Taleb defines himself as a skeptic and his mentor are Hayek and Popper. He links it with humility in the following: [Page 190] Someone with a low degree of epistemic arrogance is not too visible, like a shy person at a cocktail party. We are not predisposed to respect humble people, those who try to suspend judgment. Now contemplate epistemic humility. Think of someone heavily introspective, tortured by the awareness of his own ignorance. He lacks the courage of the idiot, yet has the rare gust to say “I don’t know”. He does not mind looking like a fool or, worse, an ignoramus. He hesitates, he will not commit, and he agonizes over the consequences of being wrong. He introspects, introspects, and introspects until he reaches physical and nervous exhaustion.

Experts

[Page 146] We know the difference between know-how and know-what. The Greeks made a distinction between techne and episteme, craft and knowledge. We have experts who tend to be experts: astronomers, pilots, physicists, mathematicians, accountants and experts who tend to be… note experts: stockbrokers, psychologists, councilors… Simply things that move and therefore require knowledge do not usually have experts and are often Black-Swan-prone. The negative effect of prediction is that those who have a big reputation are worse predictors than those who had none.

[Page 166] The classical model of discovery is as follows: you search for what you know (say, a new way to reach India) and find something you didn’t know was there (America). It’s called serendipity. A term coined in a letter by the writer Hugh Walpole who derived it form a fairy tale, “The Three Princes of Serendip” who “were always making discoveries by accident or sagacity, of things they were not in quest of.“ […] Sir Francis Bacon commented that the most important advances are the least predictable ones.

[Page 169] Engineers tend to develop tools for the pleasure of developing tools. Tools lead to unexpected discoveries. So I disagree with Taleb’s definition: A nerd is simply someone who thinks exceedingly inside the box. It may not be contradictory but I prefer the engineer-like one: “I think a nerd is a person who uses the telephone to talk to other people about telephones. And a computer nerd therefore is somebody who uses a computer in order to use a computer. [https://www.startup-book.com/2012/02/03/triumph-of-the-nerds/]
And [Page 170] Pasteur claims “Luck favors the prepared”

[Page 170] On the difficulty of predicting, just look at the failure of the Segway which “it was prophesized, would change the morphology of cities.”

[Page 184] Another example of Taleb’s target: optimization… Optimization consists in finding the mathematically optimal policy that an economic agent could pursue. Optimization is a case of sterile modeling [discussed also in Chpater 17].

Politics

[Page 16] Categorization always produces a reduction in true complexity. Try to explain why those who favor allowing the elimination of a fetus in the mother’s womb also oppose capital punishment. [Which reminds me of André Frossard : “The unfortunate thing is that the left does not believe much in original sin and that the right has not much faith in redemption.”]

[Page 52] “I never meant that the Conservatives are generally stupid. I meant to say that stupid people are generally conservative” John Stuart Mill once complained. The problem is chronic: if you tell people that the key to success is not always skills, they think that you are telling them that it is never skills always luck.”

[Page 227] Which may explain “we live in a society of one person, one vote, where progressive taxes have been enacted precisely to weaken the winners”. I am not sure if Taleb does not prefer the aristocratic world. At least he seems to favor his friends from that world.

[Page 255] True, intellectually sophisticated characters were exactly what I looked for in life. My erudite and polymathic father – who, were he still alive, would have only been two weeks older than Benoît Mandelbrot [his mentor on non-linear fractals] – liked the company of extremely cultured Jesuit priests. I remember these Jesuit visitors […] I recall that one has a medical degree and a PhD in physics, yet taught Aramaic to locals in Beirut’s Institute of Eastern Languages. […] This kind of erudition impressed my father far more than scientific assembly-line work. I may have something in my genes dirving me away from bildungsphilisters.

Globalization/Scalability

[Page 28] a scalable profession is good only if you are successful; they are more competitive, produce monstrous inequalities and are far more random. Consider the example of the first music recording, of the alphabet, of the printing press. Today a few take almost everything; the rest, next to nothing [page 30].

[Page 32] In Mediocristan,” when your sample is large, no single instance will significantly change the aggregate or the total”. In Extremistan, Bill Gates in wealth or J. K. Rowling in book selling totally change the average of a crowd. “Almost all social matters are from Extremistan.” [When giving a talk on high-tech serial entrepreneurs at BCERC last month, I was slightly criticized with a “but you are only looking at 2% of the entrepreneurs! And I replied, yes but look at the impact…”]

[Page 85] Intellectual, scientific, and artistic activities belong to the province of Extremistan. I am still looking for a single counter-example, a non-dull activity that belongs to Mediocristan.

[Page 90] You not only see that venture capitalists do better than entrepreneurs, but publishers do better than authors, dealers do better than artists, and science does better than scientists.” (I can add that gold seekers made less money than the people who sold them picks and shovels.)

[Page 102] The consequence of the superstar dynamic is that what we call “literary heritage” or “literary treasures” is a minute proportion of what has been produced cumulatively. Balzac was just the beneficiary of disproportionate luck compared to his peers.

[Page 118] The problem here with the universe and the human race is that we are the surviving Casanovas (who should not have survived and had his life without luck – no destiny].

Statistics

Taleb is not against statistics, but against Gaussian law, averages, etc. [Page 37] “The near-Black Swan are somewhat tractable. These are phenomena commonly known by terms such as scalable, scale-invariant, power laws, Pareto-Zipf laws, Yule’s law, Paretian-stable processes, Levy-stable and fractal laws.”

One thousand and one days or the story of the turkey confirms to me that an individual may not owe to the society that fed them initially!

[Page 239] Standard deviations do not exist outside the Gaussian, or if they do exist, they do not matter and do not explain much. But it gets worse. The Gaussian family (which includes various friends and relatives, such as the Poisson law) are the only class of distributions that the standard deviation (and the average) is sufficient to describe. You need nothing else. The bell curve satisfies the reductionism of the deluded. There are other notions that have little or no significance outside of the Gaussian: correlation and worse, regression. Yet they are deeply ingrained in our methods: it is hard to have a business conversation without hearing the word correlation.

[Page 240] Taleb has nothing against mathematicians, but he refers to Hardy’s views: The “real” mathematics of the “real” mathematicians, the mathematics of Fermat end Euler and Gauss and Abel and Riemann, is almost wholly “useless” (and this is as true of “applied” as of “pure” mathematics).

[Page 252] A critical feature of Gaussian statistics is the inclusion of two assumptions: First central assumption: the flips are independent of one another. The coin has no memory. The fact that you got heads or tails on the previous flip does not change the odds of your getting heads or tails on the next one. You do not become a “better” coin flipper over time. If you introduce memory, or skills in flipping, the entire Gaussian business becomes shaky. (Whereas there is preferential attachment and cumulative advantage in non-Gaussian events.) Second central assumption: no “wild” jump. The step size in the building block of the basic random walk is always known, namely one step. There is no uncertainty as to the size of the step.
[…] I have not for the life of me been able to find anyone around me in the business and statistical world who was intellectually consistent in that he both accepted the Black Swan and rejected the Gaussian and Gaussian tools. Many people accepted my Black Swan idea but could not take its logical conclusion, which is that you cannot use one single measure for randomness called standard deviation (and call it “risk”), you cannot expect a simple answer to characterize uncertainty.

But Taleb goes one step further. [Page 272] “But fractal randomness does not yield precise answer. […] Mandelbrot’s fractals allow us to account for a few Black Swans but not all. […] A gray swan concerns modelable extreme events, a black swan is about unknown unknowns. […] I repeat: Mandelbrot deals with gray swans; I deal with the Black Swan. So Mandelbrot domesticated many of my Black Swans, but not all of them, not completely.

Finance

Taleb shows that the stock crashes are sometimes linked to bad modeling and is particularly critical of the Black-Scholes options. He is very much critical of the stock portfolio theories and related Nobel prizes (Markowitz, Samuelson, Hicks or Debreu, “wrecking the ideas of Keynes”. The story of the LTCM hedge fund is an illustration of Taleb’s points.

Business and technology

[Page xxv] Almost no discovery, no technologies of note came from design and planning – they were just Black swans. […] So I disagree with the followers of Marx and those of Adam Smith: the reason free markets work is because they allow people to be lucky thanks to aggressive trial and error, not by giving rewards or “incentives” for skill.

[Page 17] The business world – inelegant, dull, pompous, greedy, unintellectual, selfish and boring.
[…] What I saw was that in some of the most prestigious business schools in the world, the executives of the most powerful corporations were coming to describe what they did for a living and it was possible that they too did not know what was going on.

[Page 135] When I ask people to name three recently implemented technologies that most impact our world today, they usually propose the computer, the Internet and the laser. All three were unplanned, unpredicted and unappreciated upon their discovery, and remained unappreciated well after their initial use. They were consequential. They were Black Swans.

Against averages

[Page 295] Half of the time I am a hyperskeptic; the other half I hold certainties. […] Half of the time I hate Black Swans, the other half I love them. […] Half of the time I am hyperconservative; the other half I am hyperaggressive”. I could delete the quotes!

I am not fully finished with the Black Swan, I am now reading the 70-page postcript essay which Taleb added to the latest paperback edition. There might be more to say (and read if you followed me until now…)

* Poincaré is quoted in Le Monde on July 7, 2012, by Cedric Villani, who by the way also mentions Black Swans in Dans les entrailles des cygnes noirs

Serial entrepreneurs: are they better?

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Are serial entrepreneurs better than novices? This is a classical topic in entrepreneurship and it seems to me that urban legend says yes! There has been academic research going that way, with one major argument being that experience matters. However, I just finished my own analysis which I presented at the BCERC conference in Fort Worth (Texas). It is based on my previous work related to Stanford related start-ups: Stanford University and High-Tech Entrepreneurship: An Empirical Study (you can have a look here at the presentation and the article). The article on serial is available on the SSRN network and you can have a look at the presentation in pdf below.


click on picture to view the pdf slides

And the conclusion? I do not find evidence that novice entrepreneurs would be less performant. It is a “work in progress” but if you have a look at the slides, you might see it in particular on slides 7, 9 or even 20. Slide 7 shows average performances according to experience. Slide 9 (q-q graphs) sshows something else: serial founders would do worse with time. Finally slide 20 that serial successful in the past have a new success rate of about 28-29 % which is similar to novices (the novice figure is not on the slide), whereas serial who failed before have a lower success rate. As if talent mattered more than experience…

European Founders at Work

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European Founders at Work is a very interesting book. It is the perfect complement to Founders at Work, particularly for the European dimension.

One comment though, I noticed 8 UK projects out of a little more than 20 and these 20 are mostly Software or Internet. More diversity may have been great. This being said, the lessons are great! Here are some… (and you will learn much more by reading the book entirely!)

About the US Market (for Europeans)

“I think that Europe has a lot of credibility in certain sectors, particularly media and the creative industry, but I think that in technology, generally, most of the world’s biggest companies were founded in the US and, therefore, the expectation in the US market is that in technology, they are going to be talking and buying from US companies. […] it’s important to become a US team in the US market. […] I think you need to be prepared to make a pretty big investment in the US and you need to be prepared to build up the business for several years,” Jos White – MessageLabs

“I would say that the IT sector, and especially enterprise software, is extremely global but remains dominated by US companies. There are very, very few examples of European IT and software companies that have managed to go global. I believe, the only way to make that happen is to go global very, very quickly, as we did from the outset.” Bernard Liautaud – Business Objects

“In my experience, if you come from a smaller European market, like Hungary or Sweden, you tend to think that it’s a nice next step to go to UK or Germany. The issue is that if you become successful there, it is still only a sixth of that of the US market. So, if you get a US competitor, you immediately become a regional player instead of a global player. So, very early on, I said we shouldn’t even be thinking about opening up offices in Frankfurt or in London because the way to make it globally was to first prove that we can make it on the world’s biggest market, which is the US. That’s going to be the truth at least for the next ten to fifteen years.” Peter Arvai – Prezi

“I think the reality is that it’s not about Europe vs. Silicon Valley. The best entrepreneurs in Europe understand Silicon Valley very well. They have spent time in Silicon Valley and developed relationships in Silicon Valley. Take all of that and all of the value that comes from that because you’re a fool if you think that Silicon Valley isn’t the most sophisticated, vibrant place for technology start-ups on the planet. It probably will continue to be so for the next twenty-five to fifty years because of the network. And the ecosystem is so profound there and keeps on getting stronger with Zynga, with Twitter, with Facebook, etc. I think any European entrepreneur or any entrepreneur in this space that doesn’t want to spend time or learn from Silicon Valley is foolish. But I think there’s a lot of things that you can learn and be aware of as an entrepreneur if you’re not in Silicon Valley, that you can use to your advantage.” Saul Klein – LoveFilm


The interviewed entrepreneurs

About success and failure

“Any successful entrepreneur knows that it was a combination of skill and attitude, with luck, that really leads to success. And there are very fine lines between success and failure” Jos White – MessageLabs

“I learned that the game is never over: you should never give up, stubbornness is somehow a requirement to lead a company to success, and the road to success is inevitably paved with failures. When things start to go wrong, the worst thing to do is panic and change everything.” Olivier Poitrey – DailyMotion

“I think as an entrepreneur you fail all the time. You’ve got failure built into your business. Right? So you don’t really keep track of failure. You never really fail. I think that’s essential when you’re an entrepreneur, that you’re not afraid of failure. You embrace failure. Your whole business is based on trying out stuff, being ready for stuff to fail and just taking the next step as soon as you fail.” Boris Veldhuijzen van Zanten – The Next Web

About ambition

“Come up with an idea which is impossible then try to find somebody who can make it un-impossible and then do deals which have never been done before.” from the Shazam founders

“[A new trend is] You definitely see entrepreneurs being extremely ambitious.” Reshma Sohoni – Seedcamp

“I guess one advice is it’s more exciting if you feel like you’re changing the world in a positive and innovative way. So we’d love to see more of those out of Europe.” Brent Hoberman – lastminute.com

“But it is probably harder in Europe in that it innovates less, because you have less-crazy investors financing crazy entrepreneurs. [Advice:] One, international. Two, innovation and no copycat. And then, three, big ambition.” Loic Le Meur – Le Web

About the team

“There are very few founders that stay with their businesses beyond five years and quite often, in my opinion, it’s because they didn’t manage to surround themselves with the right team.” Bernard Liautaud – Business Objects

“But also obviously you hire people that are better than you” Ian Dodsworth – TweetDeck

“I also learned how hiring the right people from the start is key: the very first people to join will shape the company’s personality. And finding talented people you are pleased to work with is very important to generate emulation from new hires. Olivier Poitrey – DailyMotion

“A common mistake is building the team. If they’re quite scared to part with something … Like when they’re quite scared to part with equity or bringing on mentors. “Do you want to be a big fish in a small pond or a big fish in a big pond?” They’re too closed with their equity and they try to do everything.” Reshma Sohoni – Seedcamp

“Another common mistake is like a cliché now, but it’s just the classic: “I’ll just build another feature and I’ll focus on my product.” Alex Farcet – Startupbootcamp

About entrepreneurship

“The main advice is just start. Many people have hundreds of ideas, but they never really start their own project. And if you fail, start again. Entrepreneurship is, in my point of view, the best and the only way to personal development” Lars Hinrichs – Xing

“There are a lot of moments like that where you don’t know what you’re doing, but this was the whole point.” Giacomo Peldi Guilizzoni – Balsamiq

“ “Do it.” It’s the best decision I’ve ever done in my whole life. […] And I was studying engineering as well, and I had one hundred classmates. And I know that almost zero of them actually went on to start a company, which is kind of crazy because I know a lot of them have good ideas. But none of them quite felt that they were able to pull it off.” Eric Wahlforss – Soundcloud

“I have been lucky enough to be born with optimism.” Richard Moss – moo.com

“Hang in there. Don’t give up. I heard that most start-ups fail because the founders stop working on them.” Richard Jones – last.fm

“I would be realistic and I would say, “Look, if you think you are the lucky sperm that’s going to get the ovule, go ahead and start the business.” It’s a very difficult thing to do with a very high probability of failure. But it is essential for society and even those who try and fail are also helping society. So I encourage people to try, but at the same time warning them how difficult it is. I am tenacious and I am sometimes lucky and I’m good at spotting trends. But I was also lucky. Most people who try businesses fail. That’s the truth and people should be warned about that.” Martin Varsavsky – FON

As a conclusion let me quote Saul Klein in his foreword… “Right now, Silicon Valley is peerless at both supporting innovation and creating serious scale. There’s been no master plan, but the 60-year interplay of government as an early catalyst; academia and established companies as early customers and sources of talent; and of course, investors willing to take risks and a long term view, have given entrepreneurs fertile ground to sow seeds and try to grow monsters with dragon’s teeth ready to conquer the world.You need every element of this ecosystem working perfectly to create monsters. This is serious progress. But the straight facts are that while we are unquestionably masters of invention in Europe, we don’t yet have the ecosystem— or perhaps the attitude. […] For me, the big question is if we are truly able to do this.”

Post Scriptum: I am not finished yet. I love to add cap. tables and not so many of these entrepreneurs are running a publicly quoted company. Strangely enough, one is Russian, Yandex. Its foudner and CTO says something great about sales: “I think one of them is when you create a software product, you have to learn how to sell it, you have to learn how to make it a product. It’s a very basic skill. I think every engineer has to try that at least once, to sell the software he created, regardless of how bad it is. No matter how unpolished your product is, you have to try to explain why it is good for someone else.”

Here is Yandex amazing cap. table…

Click on picture to enlarge

After the lean startup, the anorexic startup

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You must read The Anorexic Startup. Just because it is a funny tale about start-ups. More precisley author Mike Frankel claims it is a “A Tale of Sex, Drugs, and C++”. You will follow entrepreneur and hero, Dale Schmidt, from Day 37 to Day 155 of his great adventure!! You can either download the 15-page pdf on the author’s site or please him by buying it on Amazon for $1.20!

Following my review of The Lean Startup, the author of The Anorexic Startup contacted me and asked what I thought of his work. I read it, smiled first and then laughed. I love this short story and the 10-20 minutes it takes to read is worth your time. Realistic I am not sure, but certainly close to many true stories. The shortest and probably among the best stories I read on the (high-tech) start-up and entrepreneurship words. Enjoy!

During The Bubble, 77% Entrepreneurs Failed. Now, It’s Around 40%

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My colleague and entrepreneur David Portabella just mentioned to me Conway’s views on his investments. Conway is a famous business angel who invested in AskJeeves, Google and Paypal.

In a nutshell:

– In the 1997-2001 period, 77% of his investments failed. Since 2002, it’s down to 40%.
– Entrepreneurs have a 66 percent chance of being successful on a startup if it’s their second one.
– There is a misconception that “every 10 years we get a Google.” “That’s not true,” he claims it is at a much faster rate.

If I agree that failure is common and success is not so rare, I am less sure about serial entrepreneurs being better. I have hard data from Stanford entrepreneurs and serial entrepreneurs are not any better. I will share these data in the future…

Survival or failure – which success?

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Failure and success are keywords in the world of start-ups. They even generate some heated debate, at least in Europe, when it is a question of surviving as long as possible until customers materialize or failing fast so that one avoids wasting precious time. The debate is difficult because all entrepreneurs deserve respect (yes, it is a tough job) and because slow and controlled growths (including survival modes) vs. fast and risky growths (with the risk of failing fast) may apply to totally different ventures. Here are therefore some figures that may contribute to the debate.

I must add that my motivation comes from a report published by ETHZ (the Swiss Federal Institute of technology in Zurich) about its start-ups, The performance of Spin-off companies at the Swiss Federal Institute of Technology Zurich. A 90% survival rate after 5 years was shown. But what are the typical survivate rates of firms? I searched the web sites of the US and Swiss institutes of statistics and the following chart illustrates the rates of the two countries for their entreprises overall.

In high-tech, the survival rates seem to be even higher. The authors of the report I mention above give figures as high as 70% to 90% for 5 years. Zunfu Zhang in his excellent “High-Tech Start-Ups and Industry Dynamics in Silicon Valley” (dated 2003 ) published the following curves:

The survival rates after 5 years are 76% for “non-service firms” and 72% for “service firms”. The authors of the ETHZ report added: “The low survival rate in the US – where some of the most successful University spin-offs have been created – raises, however, the question whether a high survival rate is actually desirable or whether too strong a focus on creating ‘surviving’ spin-offs does not eliminate some of the potentially very successful ventures that may not look so promising or too risky.”

As a conclusion to this post, I’d like to extract the following from my book!

As a footnote, I had added, the saying is pronounced “Shi Bai Nai Cheng Gong Zhi Mu” and means “failure is the mother of success”. There is a very similar quote by T. J. Rogers, founder of Cypress and another Silicon Valley icon: “failure is a prerequisite to success”. A Chinese student, Jie Wu, noticed the similarity. I would like to thank him for this. It might be encouraging to end this [post] with a quote, which shows that Silicon Valley mentality can be developed elsewhere. What we need to digest is that failure is not negative, but trying is what counts.