Tag Archives: Uncertainty

When Peter Thiel talks about Start-ups – Final Thoughts: Human After All

As you noticed if you read my previous posts, I’ve been quite impressed by Peter Thiel’s notes about start-ups. I’ve written 7 long parts. I had been similarly impressed by Mariana Mazzucato’s The Entrepreneurial State even if with only 5 posts!

Thiel-Mazzucato

I said it already, I would have loved to attend their debate in a few days at the conference Human After All, Toronto 2014. But apparently they do not participate to the same roundtable anymore… (After reading what follows, I see that Taleb would have been a great addition).

– He will discuss “The Economics of Radical Uncertainty.”
How do human beings truly react when confronted with conditions of genuine “unknown unknowns”? According to Frank Knight, “Uncertainty must be taken in a sense radically distinct from the familiar notion of risk, from which it has never been properly separated…The essential fact is that ‘risk’ means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far – reaching and crucial differences in the bearings of the phenomena depending on which of the two is really present and operating… It will appear that a measurable uncertainty, or ‘risk’ proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all.” The economics literature from Knight onward is very good at laying out the propensity of markets to greatly overshoot and undershoot the fundamentals. However, economics does not adequately address the implications of “Knightean” uncertainty, because the discipline finds it hard to model this phenomenon. To get a full measure of this, one has to enter into the realm of psychology and neuroscience. That’s where the definition lies. Radical uncertainty, like so much else, is too important to be left to the realm of economics alone.

– She will be part of “Innovation: Do Private Returns Produce the Social Returns We Need?”
The machines of the first age replaced and multiplied the physical labour of humans and animals. The machines of the second age will replace and multiply our intelligence. The driving force behind this revolution will, argue the “techno-positivists,” exponentially increase the power (or exponentially reduce the cost) of computing. The celebrated example is Moore’s Law, named after Gordon Moore, a founder of Intel. For half a century, the number of transistors on a semiconductor chip has doubled at least every two years. But the information age has coincided with – and must, to some extent, have caused – adverse economic trends: stagnation of median real incomes; rising inequality of labour income and of the distribution of income between labour and capital; and growing long – term unemployment. Are the great gains in
wealth and material prosperity created by our entrepreneurs in and of themselves sufficient to produce desired social returns demanded in today’s world?

Start-ups are a great area to study the tension between individuals and society. A kind of chicken and egg situation… Indeed they might explain the growing gap between the USA and Europe in many dimensions. Mazzucato would be on the social side, Thiel closer to the individual. But do not see any provocative statement here. The thoughts of Thiel and Mazzucato are profound. I agree with most of what they say, disagree with smaller pieces, though most people could think their thinking can not be reconciled. I really think that combining their point of views is an interesting approach to what innovtaion really is…

PS (May 8, 2014): I just found that video of Thiel at SXSW.

What’s a start-up? (part 3)

My colleague Jean-Philippe Solvay recently asked me to a react to a Facebook post asking what is exactly a start-up. And as you may read there, it is not so easy to answer. One of the best references given in the post is swombat.com rather exhaustive analysis.

In the past, I wrote two posts: “part 1” was in 2011, where I had given my definition: “A start-up is a company which is born out of an idea and has the potential to become a large company” as well as the very good definition by Steve Blank: “startups are temporary organizations designed to search for a scalable and repeatable business model.” (There is something I am not comfortable with Steve Blank’s: I would delete “model”, as a start-up may know what it wants to do, but has not validated it yet. And start-ups copying existing business models would not be ones…)

Then in “part 2” in early 2013, I added the following: “A start-up is a corporation which explores, which is looking for a business model, a market, customers and is trying to innovate. It usually looks for a big market (“scalable”) and therefore service businesses do not qualify (except on the web) as they do not often scale. It is also a matter of strong and rapid growth in emerging markets because the competition is tough and there will be few winners. It often go fast. That is why it is more about a mindset: you are curious, in an uncertain world, trying to bring new things to the world. Because you are looking for a business, you do not have enough paying customers, and you will most likely need external capital (business angels, venture capital) except if your future customers accept to pay a lot in advance. This is why there is a strong correlation between being a start-up and having investors.”

I agree with most features given in the facebook or swombat contributions: “start-ups are new firms focusing on innovation and growth in situations of high uncertainty (or risk)”. They do not have to be about technology and if so, they are called high-tech start-ups. Maybe innovation is not so important, as many just copy others, but growth (through scalability) is critical. Consulting or service firms usually do not qualify because the growth is linear, not exponential (with the number of jobs).

Let me add another point: if the start-up term, was created, there has to be a good reason! When was it created? Wikipedia claims it became popular with the dot.com bubble of the late nineties. However, I found the term in Saxenian’s Regional Advantage (1994) and even in Silicon Valley Fever (1984). There is no doubt the term emerged with the technology clusters Route 128 and Silicon valley, the reason why it is associated with high-tech as well as venture capital. But not all start-ups belong to these geographic clusters. Microsoft and Amazon are based in Seattle, which is (at least was) not really a cluster. When they do not belong to a geographic cluster, they belong to a technology cluster, mostly IT (electronics, software, internet) or biotech/medtech. Tesla Motors is considered a start-up because it belongs to the Silicon Valley ecosystem though it is in an industry where very few start-ups exist. I do not think EasyJet was ever called a start-up because it belongs to no (technology or geographic) clsuter. So I would finally define a start-up as “a new firm focusing on growth in situations of high uncertainty, and belonging to a technology or geographic cluster”.

PS: while looking into the topic again, I found a debate on how to spell the word… In 2007, I had decided for “start-up”, but “start up” and “startup” also existed. It seems “startup” is now more and more popular. I stick to “start-up” for the time being, just to be consistent with what I always did.

Proven Tools for Converting Your Projects into Success (without a Business Plan)

Winning Opportunities is not just another book about business planning. Indeed Raphael Cohen’s new book is subtitled Proven Tools for Converting Your Projects into Success (without a Business Plan).

This 200-page, 18-(short)-chapter book is a very interesting way to analyze your project opportunity (maybe more in a corporate than in a start-up set-up). “Designed for doers, it provides a structured model of the entrepreneurial/intrapreneurial process. […], it is about discipline and process. […]. In other words, creativity is not enough. Framework and discipline are essential companions.” [Page 3] Cohen is therefore a disciple of Peter Drucker who believes entrepreneurs can be tought. But he adds on page 15, that “Observation is a state of mind. To understand your customers, you need to spend time observing them in their own environment. […]. There is no way engineers ensconced in their cubicle offices could observe (and so identify) such a “Pain”. Many real opportunities can only be identified outside of your office.” He is also close to Steve Blank and his customer development framework and here I should remind the reader with Blank’s comment on creativity.” But it’s more likely that until we truly understand how to teach creativity, [entrepreneurs] numbers are limited. Not everyone is an artist, after all.” And we should be all aware that though tools and states of mind are critical, success can not be guaranteed, its odds can increased however.

Cohen has a great framework that is summarized in the next figure but you should read his book and see how he builds the full IpOp (Innovation by Opportunity) model, step by step.

Again he is close to Blank when he explains that assumptions will be checked via practice, not via theory: “Selecting a Business Model usually requires making a number of assumptions. In many cases, it is impossible to verify these assumptions before implementing the Business Model in real time or at least in a pilot study. You should test a Business Model whenever possible, and must always be prepared to revise it or explore alternatives.” [Page 73]

One critical factor that may not be enough emphasized in business planning is the energy required to sell. “To be successful, it is not enough to have written up the perfect Business Model, you still need to persuade customers to buy. And for this, you must convince them that what you offer has an outstanding superior perceived value”. [Page 80]. You need to desire and be able to sell!

Cohen mentions metrics as a way to measure success. His KISS are Key Indicators of Success and these may be subjective. He is right. But once you decide about how you define success, measure it. “The Definition of Success determines a project’s sex appeal. […] While other factors such as preventing the competition from entering the market, testing new markets or distracting stakeholders from other issues may play a role in the decision process, it is the Definition of Success that is the bottom line. Whatever is measurable will always be very much at the heart of the decision process, because it is an output that can be monitored.” [Page 91] “Defining failure will provide stop/no stop criteria” [Page 92]. My personal experience is that it is one of the toughest decisions to admit one’s own failure. “If the opportunity is worth it, you will find the necessary resources when the time comes.” [Page 99].

Cohen introduces the concept of Unknowns as a separate chapter, showing again that entrepreneurship is not easy. They should be catalogued, characterized, prioritized. “Be humble enough to recognize what you do not know” [page 109] and “testing assumptions is often the key to reducing the level of uncertainty” [page 110]. One of the best examples of reducing unknowns is Arnaud Bertrand’s amazing testing with Housetrip.

Again entrepreneurship is about selling, making money, it is about action. “The fun part is in the action. This is why people excel at thinking of Tactical Moves. In fact, most people jump straight from identification of the Opportunity into planning Tactical Moves. Some even jump into the action without any planning at all. Because most creative people are action-oriented, their natural inclination is to skip the strategic analysis presented in the previous chapters. […] And these people like action” [Page 113] and again: “Finding Tactical Moves is a highly creative process” [Page 115].

At the same time, action can be scary, because of the possible collateral effects: “damaging the company’s reputation; altering the essence or image of an existing brand; upsetting distributors or other partners; reducing the market share of other company products (this is known as cannibalization); irritating management; disclosing critical information; making colleagues jealous” [Page 118]. I remember an entrepreneur from my Index days telling me, “each day, you take 10 decisions, 5 might be good, 5 might be bad; just hope the bad ones will not be deadly”. Action, Action!

“Contrary to common belief, entrepreneurs do not like to take risks” [Page 126] “What they like is success and they are willing to take risks to achieve it.” {…] “Managing risks means not only identifying them and anticipating their impact but also preparing contingency plans.” (cf Plan B by Mullins and Komisar, next blog paper or the famous Pivot by Blank / Ries). “The contingency plan sometimes turns out to be the main plan”. And it may mean rethink the Definition of Success and revisit the stop / no stop criteria. Once again uncertainty is highly present and decisions never black and white.

Lack of money is often presented as the main obstacle to start-ups and intraprises. While this may sometimes be the case, the truth generally is that really attractive projects get the necessary funding. Of course, some people are more skilled than others in obtaining the Resources they need. Necessary qualities of an attractive entrepreneurial or intrapreneurial project are:
• The ability to deliver a convincing Definition of Success (plus possible additional Benefits) as against the Resources required (Return on Investment)
• A reasonable chance of success, given the team behind the project and other critical success Factors and Unknowns.
Many entrepreneurs are not lucid enough to make a realistic assessment of the attractiveness of their project, having a tendency to believe that what is attractive to them is automatically attractive to others. It is important that entrepreneurs seek resources from the right people. To do so, they will need a sufficiently large network to turn to.” [Pages 135-136]
“Fund-raising exacts an enormous collateral cost. The whole time spent on looking for money and convincing fund providers is unavailable to promoting delivery of the Definition of Success. The milestone-based is much healthier than putting a lot of energy into multiple rounds of financing, but is only possible with a very well-thought-out pre-project.” [Page 138]

Business plans are in fact more trouble than they are worth [page 151], because:
• They do not increase the probability of success of a new venture, […]
• Less than 10% of business plans actually get read. […]
• Production of the plan delays presentation of the project to Decision-makers
• Apart from people who make a living producing, teaching or selling business plans, almost everybody else in the business community agrees that they are useless for start-ups and new initiatives. The business plan does however remain relevant as the output of a strategic analysis for coordinating the functions of an existing organization (marketing, production, HR, finance, etc.)
• So … writing them is a waste of time and energy

Cohen finishes his book by explaining how important is an ecosystem friendly to entrepreneurs. “The simple Five P’s formula for emPowerment is a recipe that works wonders to promote innovation within organizations:
+ A Passionate leader
+ Permission (to do)
+ Protection (in the event of failure)
+ a Process
= Powerful Performance (by emPowered People)” [Page 185]

The book is extremely well-written and this is not so common in the business litterature. Another original feature is that Cohen does not use quotes (mea culpa!) at the beginning of each chapter but jokes. And because he authorizes the use of them, here is one I liked:

Making a compelling proposition pays
A guy with a severe stutter applied for a job selling Bibles. The interviewer believed he’d never make it as a salesman, and was about to tell the guy to look elsewhere for work. The stutterer begged for the job, “P-p-p-p-p-le-ease g-gg-g-ive m-m-m-mee a ch-ch-cha-a-ance. I-i-ic-c-can d-d-d-o i-i-tt.”
The manager said, “Okay”, and gave him a few Bibles and the rest of the day to see if he could sell one or two. By lunchtime, the stutterer was back, having sold all the Bibles. The manager was impressed, and asked if he could accompany the stutterer after lunch. “S-s-sure,” said the guy, and later they went out to the streets.
They approached a house, and the stutterer went up and knocked on the door. When the homeowner answered, he said, “G-g-g-g-good a-a-a-ftern-n-n-noon, M-m-ma’am. I-i-i’m s-s-s-selling B-b-b-bibles. W-w-w-w-would y-y-y-you l-l-l-l-l-like to b-b-b-buy a B-b-b-b-bible, or sh-sh-sh-ould I j-j-j-j-ust r-r-read it t-t-t-to you?”

A non-negligeable advantage of Cohen’s book is that it is freely downloadable and the author is just aksing you to pay what you think is fair once you’ve read it. I have not paid anything yet but my contribution has been to write this blog article and I would certainly recommend interested people to read and pay! Is this enough Raphael? 🙂

The Black Swan again

If you understand French, you might be interested in how I explained the Black Swan on French-speaking radio broadcast Babylon on Espace 2. You just have to click on the picture. Many thanks to Jean-Marc Falcombello for the time he gave me to describe Taleb’s ideas. It is 19 minutes long – between 23:15 and 42:00.

I am less sure this works: http://www.rts.ch/espace-2/programmes/babylone/4203353-moi-je-ne-bluffe-pas-l-insoutenable-legerete-de-l-incertitude-30-08-2012.html?f=player/popup

The Black Swan and the danger of statistics

“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. [http://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

Carol Bartz and Yahoo

Carol Bartz is an exceptional woman. The new Yahoo CEO had given an interview in 2002 that you can read in the book Betting It All. Author Michael Malone described her two passions: Fight Cancer and Girls and Math: “Girls in general have no interest for math. I think that in fact they are dissuaded.” On the more general topic of women and technology/business, she added: “I left 3M because I could not evolve just because I was a woman. […] You are a woman, what are you doing here?” and she also said: “But being a woman in Silicon Valley is to be part of a minority”. The topic of woman in technology is seldom and clearly not enough developed.

Carol Bartz is also amazingly energetic : “I was still running my company while I was having my chemotherapy”.

Finally among the ingredients required for entrepreneurs, she quotes uncertainty that you have to be ready to accept. “Facing the many jobs I took, I was not comfortable because I was wondeing if I was the best for it.” But she also added: “if you cannot make it, you just have to go across the street and try with someone else… which is always possible in Silicon Valley.”

In the company of Giants

I had read In the Company of Giants in 1997 just before becoming a venture capitalist. Then when I began to read again about entrepreneurs, I just could not find it anymore and had to buy it through the reseller network of Amazon. It is as interesting as my previous posts (Once You’re Lucky, Betting it All, Founders at Work).

I will let you link the names and quotes with the pictures if you have time!

Steve Jobs: “In the early days, we were just trying to hire people that knew more than we did about anything and that wasn’t hard because we didn’t know a lot. Then your perspectives are changing monthly as you learn more. People have to be able to change.”

T. J. Rodgers (Cypress Semiconductor): “the standard entrepreneurial answer is frustration. You see a company running poorly, you see that it could be a whole better. Intel and AMD were arrogant. If you think about it, any billion dollar company, that has so much money to spend on R&D should be unassailable. But the large companies routinely cannot crunch little companies so something’s got to be wrong.”

Gordon Eubanks (Symantec): “What makes a company successful is people, process, product, and passion. You must have great people and product and passion balanced by process.”

Steve Case (AOL): “Do something you really love, you are passionate about. Take a long-term view, be really patient. There are going to be bumps on the road.”

Scott Cook (Intuit): “People [customers] won’t tell you what they want. Often they can’t verbalize it because they don’t understand things they’ve not seen. You must understand fundamental motivations and attitudes.”

Sandy Kurtzig (ASK): “I did not see it as incredible risk. Many entrepreneurs would tell you why it was obvious to do what they did. When you have nothing, you have nothing to lose. That’s why so few entrepreneurs can do it a second time. Even Jim Clark did not really start Netscape or Jobs did not really start Pixar. They funded it. You need other people to be hungry… Believe in yourself, surround yourself with good people, be willing to make mistakes, don’t get wrapped up in your success. You are still the same person you were when you started.”

John Warnock and Charles Geschke (Adobe): “Actually there was the very first business plan, then there was the second business plan, and then the third business plan; we never actually wrote the third business plan.”

Michael Dell: “It did not seem risky to leave school because I was already earning obscene amounts. The worst thing that could happen is I would return to school. The greater risk was to stay at school.”

Charles Wang (Computer Associates): “Managing is not just telling people what to do, but it is leading by doing. Know your strengths and weaknesses and complement yourself. Be realistic and objective. Surround yourself with great people.”

Bill Gates: “It’s mostly about hiring great people. We are [in 1997] 18,000 people and still the key constraint is bringing in great people. We naively thought there were guys who could tell us we weren’t doing things the best way.”

Andy Grove: “I can’t look at a startup as an end result. A startup to me is a means to achieve an end.”

Trip Hawkins (Electronic Arts): “You don’t have an objective, rational process. You need a certain amount of confidence. There are many things that you don’t know will go wrong. If you knew in advance all the things that could go wrong, as a rational person, you wouldn’t go into business in the first place.”

Ed McCracken (Silicon Graphics): “My venture capital friends tell me that many of the ideas they’re seeing for new businesses are coming from people under 26 years old.”

Ken Olsen: “Business school’s goal today is to teach people to become entrepreneurs. I think it’s a serious mistake. You learn first how to be a team member, then a leader.”

Bill Hewlett: “It was 1939 and it was no time to start a company. It was probably the supreme optimism of youth.” and “It’s not all due to luck, but certainly a large percentage of success is. We were in the right place at the right time. We were lucky and we had wonderful teachers and mentors. HP didn’t start in a vacuum.”

An Ode to Disorder

Too much organization harms Innovation

nouveleco.jpg

These are the title and subtitle of a brilliant paper (inFrench only) by Julien Tarby in the Nouvel Economiste dated June 5, 2008. His article echoes my worries about innovation in Europe. His analysis is really interesting. Among other examples, he quotes:

Samuel Kortum et Josh Lerner: 1 euro invested in venture capital has a 10x return over 1 euro spent in the traditional R&D of companies

Pascal Picq, a paleo-anthropologue, who develops the evolution theory applied to the enterprise: start-ups which adapt to survive are Darwinian. “Unfortunately the French education system remains Lamarckian, and considers that organizations improve in a development scheme (administration, big companies). It is the country of the planned projects (planes, trains) and not of disuptions. This culture of the norm does not tolerate variability, trial and error and it induces the development of the [existing] fields of excellence and not the creation of new fields.”

If you read French, and because it is free, you shoud run and download it!

About Peter Druker

Drucker

Far from my previous post about Perkins, Peter Drucker’s book Innovation and Entrepreneurship was a paradoxical reading. The first chapters were painful even if brilliant. I understood there that innovation is a process which will be successful if carefully planned and managed. Fortunately, chapter 9 completely changed my perception when the author dealt with knowledge-based innovation, which includes innovations based on science and technology. So let me summarize the main points of this chapter:

1- the characteristics of knowledge-based innovation:

a. the time span between the emergence of the technology and its application is long, 20 to 30 years,

b. it is a convergence of several knowledge and until all the needed ones are available, this innovation can not succeed,

2- the requirements:

a. a careful analysis of the required factors, i.e. the available knowledge and the missing ones,

b. a clear focus on the strategic position, i.e. you have to be right the first time or others will take your place,

c. learn and practice entrepreneurial management, because most tech. innovators lack management skills ,

3- the risks:

a. first, even after a careful analysis, knowledge-based innovation remain unpredictable and turbulent (see also Moore’s books about the chasm and the tornado), and this is linked to its characteristics above; this has two important implication:

i. time plays against innovators,

ii. survival rate is low,

b. there is a limited window where new ventures start, and when it closes, there is a general shakeout, where few survive; who survives is also unpredictable. The only chance of surviving is to have a strong management and resources,… and luck;

c. there is also a receptivity gamble. Even market research does not work with these innovations and the reason why an innovation is accepted or not is also unpredictable.

I have to admit this confirms an intuition I had since my VC years: you have to make a bet and then work hard. But there is no way, you can really plan the success of knowledge-based innovations.

The end of the book is quite good, in particular its conclusion: “The first priority in talking about public policies is to define what will not work: Planning is actually incompatible with an entrepreneurial society and economy. Innovation has to be decentralized, ad hoc, autonomous, specific. It had better start small, tentative, flexible. […] It is popular today [1983!], especially in Europe, to believe that a country can have “high-tech entrepreneurship” by itself. But it is a delusion. In fact a policy which promotes high-tech and high-tech alone will not even produce high tech. All it can come with is another expensive flop, another Concorde. […] The French are right, economic and political strength requires high tech but there must be an economy full of innovators with vision and entrepreneurial values, with access to venture capital, and full of economic vigour.”