I tend to agree 100% but I may have an idealized view of my own experience! It also reminded me another quote from the same period (2011 vs. 2010) by Steve Blank: Over the last decade we assumed that once we found repeatable methodologies (Agile and Customer Development, [Lean Startup], Business Model Design) to build early stage ventures, entrepreneurship would become a “science”, and anyone could do it. I’m beginning to suspect this assumption may be wrong. It’s not that the tools are wrong. Where I think we have gone wrong is the belief that anyone can use these tools equally well. In the same way that word processing has never replaced a writer, a thoughtful innovation process will not guarantee success.” Blank added that “until we truly understand how to teach creativity, their numbers are limited. Not everyone is an artist, after all. The full interview can be found on archive.org.
and also Komisar: “I think there’s stuff you can’t possibly learn in school and I’m not even sure you can learn that on the job. There’s an entrepreneurial character. Some people have it and some people don’t. Some people may not think they have it, and they may have it. A lot of people they think they have it, and many don’t.”
I was lucky to present some ideas around entrepreneurship at a Startup event of Institut Pasteur. I did not reinvent the wheel but used quotes of people I have a lot of respect for. Here they are again:
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 .
“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.
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.
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.
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.”
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.”
I had to wait many years to discover there was a book written about science and innovation which convincingly shows there is not such thing as a linear model of innovation described usually as Basic research → Applied research → Development → (Production and) Diffusion
Pasteur himself apparently said: “There is not pure science and applied science but only science and the applications of science”. More precisely he seems to have said according to Wikipedia again: « Souvenez-vous qu’il n’existe pas de sciences appliquées, mais seulement des applications de la science ».
(Remember that there are no applied sciences, but only applications of science)
and « Non, mille fois non, il n’existe pas une catégorie de sciences auxquelles on puisse donner le nom de sciences appliquées. Il y a la science et les applications de la science, liées entre elles comme le fruit à l’arbre qui l’a porté »
(No, a thousand times no, there is not a category of sciences to which we can give the name of applied sciences. There is science and the applications of science, linked together like the fruit to the tree that carried it.)
I have agreed with this for so many years and for the same reasons I never really understood the concept of R&D, I mean why the concepts of research and development would be associated in the same unit, but that is a slightly different topic!
Here is a long extract from Stokes (taken from a pdf found here) worth reading I think:
The examples from the history of science that contradict the static form of the postwar paradigm call into question the dynamic form as well. If applied goals can directly influence fundamental research, basic science can no longer be seen only as a remote, curiosity-powered generator of scientific discoveries that are then converted into new products and processes by applied research and development in the subsequent stages of technology transfer. This observation, however, only sets the stage for a more realistic account of the relationship between basic science and technological innovation.
Three questions of increasing importance arise about the dynamic form of the postwar paradigm. The least important is whether the neatly linear model gives too simple an account of the flows from science to technology. An irony of Bush’s legacy is that this one-dimensional graphic image is one he himself almost certainly never entertained. An engineer with unparalleled experience in the applications of science, he was keenly aware of the complex and multiple pathways that lead from scientific discoveries to technological advances-and of the widely varied lags associated with these paths. The technological breakthroughs he helped foster during the war typically depended on knowledge from several, disparate branches of science. Nothing in Bush’s report suggests that he endorsed the linear model as his own.
The spokesmen of the scientific community who lent themselves to this oversimplification in the early postwar years may have felt that this was a small price to pay for being able to communicate these ideas to a policy community and broader public for whom science was always a remote and recondite world of affairs. This calculation may well have guided the draftsmen of the second annual report of the National Science Foundation as they stated the linear model in the simplistic language quoted earlier in this chapter. In any case, these spokesmen did their work well enough that the idea of an arrow running from basic to applied research and on to development and production or operations is still often thought to summarize the relationship of basic science to new technology. But it so evidently oversimplifies and distorts the underlying realities that it began to draw fire almost as soon as it was widely accepted.
Indeed, the linear model has been such an easy target that it has tended to draw fire away from two other, less simplistic misconceptions imbedded in the dynamic form of the postwar model. One of these was the assumption that most or all technological innovation is ultimately rooted in science. If Bush did not subscribe to a linear image of the relationship between science and technology, he did assert that scientific discoveries are the source of technological progress, however multiple and unevenly paced the pathways between the two may be. In his words,
new products and new processes do not appear full-grown. They are founded on new principles and new conceptions, which in turn are painstakingly developed by research in the purest realms of science.
Even if we allow for considerable time lags in the influence of “imbedded science” on technology, this view greatly overstates the role that science has played in technological change in any age. In every preceding century the idea that technology is science based would have been false. For most of human history, the practical arts have been perfected by “‘improvers’ of technology,” in Robert P. Multhauf’s phrase, who knew no science and would not have been much helped by it if they had.
But the deepest flaw in the dynamic form of the postwar paradigm is the premise that such flows as there may be between science and technology are uniformly one way, from scientific discovery to technological innovation; that is, that science is exogenous to technology, however multiple and indirect the connecting pathways may be. The annals of science suggest that this premise has always been false to the history of science and technology. There was indeed a notable reverse flow, from technology to science, from the time of Bacon to the second industrial revolution, with scientists modeling successful technology but doing little to improve it. Multhauf notes that the eighteenth-century physicists were “more often found endeavoring to explain the workings of some existing machine than suggesting improvements in it.”
Tinkerings is not a word, I think, that is easily or commonly associated with innovation. And yet! It appears several times on this blog as indicated by the #tinkering tag. And here is the reference to a nice article by Paul Millier entitled The engineer, the tinkerer and the innovator (L’ingénieur, le bricoleur et l’innovateur). I’m not sure if you can have free access so here is a brief excerpt:
The other way of innovating is that of the “Tinkerer” , who, on the contrary, collects pieces to get an idea of the whole. He collects disparate elements from the left and the right which he preserves “in case it could be useful”. He brings them together, he assembles them, he organizes and reorganizes until suddenly – almost surprisingly – it makes sense and the innovator can say “eureka”. Damn, but it’s obvious! How had we not thought about it before? The suitcase and the wheel existed separately from each other until the day when someone brought them together to make the suitcase on wheels. How could we imagine traveling without a suitcase on wheels today? This is a radical innovation.
 The term “Tinkering” used here has no derogatory character, quite the contrary. It corresponds to a profound distinction proposed by Claude Lévi Strauss in “La pense sauvage” (1962) between two approaches (both valid) that of the “scientist”, of the “engineer” who defines himself by a project, and that of the “Tinkerer” who deals with the “means at hand” (and therefore with the client in the case of innovation). This term is quite positive for this author as for all those who, in strategic analysis, semiotics or sociology, have appropriated this notion.
The word “Tinkering” in innovation, I discovered it with a magnificent text by Tom Wolfe, The Tinkerings of Robert Noyce, which I strongly encourage you to (re)read!
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]
I had a few days ago a conversation about why I thought titles such as CEO or CTO were not such a good idea in start-ups. I thought this was a close debate and apparently not. So let me try to elaborate.
A good quote – I just found trying to structure my thinking – is “CEO means in a startup Chief Everything Officer”! CTO means someone who does not want to interact with customers while Business Development means the opposite. But you would not use VP of Sales in a small team…
In the book Startup Nation, there is something similar: “The multitasking mentality produces an environment in which job titles — and the compartmentalization that goes along with them — don’t mean much.”
Steve Blank explains titles are for established companies with knwon business models and known processes: Companies Have Titles to Execute a Known Business Model. […] Therefore the job title “Sales” in an existing company is all about execution around a series of “knowns.” [For example] Did he have a repeatable and scalable business model? Did he have a well understood group of customers? […] Startups Need Different Titles to Search For an Unknown Business Model. You didn’t need a VP of Sales, you needed something very different. Searching around a series of unknowns. You needed a VP of Customer Development
I am not sure I am allowed to do the following but here is a long extract from Bussgang: “Job titles make sense for mature companies, not for start-ups. […] At business school, I learned all about titles and hierarchies and the importance of organizational structure. When I joined my first start-up after graduation, e-commerce leader Open Market, I found the operating philosophy of the founder jarring: He declared no one would have titles in the first few years. If you needed a title for external reasons, our founder told us, we should feel free to make one up. But we would avoid using labels internally. In other words, there would be no “vice-president” or “director” or other such hierarchical denominations.
Why? Because a start-up is so fluid, roles changes, responsibilities evolve and reporting structures move around fluidly. Titles represent friction, pure and simple, and the one thing you want to reduce in a start-up is friction. By avoiding titles, you avoid early employees getting fixated on their role, who they report to, and what their scope of responsibility is – all things that rapidly change in a company’s first year or two.
So when I co-founded Upromise, I instituted a similar policy. We had an open office structure and functional teams, but a fluid organizational environment and rapid growth. One of our young team members changed jobs four times in her first year. Only after the first year, as we settled into a more stable organizational structure and I recruited senior executives who were more obviously going to serve as my direct reports on the executive team did I begin to give out titles (CTO, CMO, CFO, etc.). But you can establish role and process clarity without having to depend on titles.
Here is Steve Blank visual summary of all this:
In his four steps to the epiphany, he adds a quick check list about this: Goal of phase O-b: Set up the Customer Development Team. Agree on Customer Development team methodology and goals.
Author: Whoever is acting as CEO
Approval: Entire Founding Team/Board
Time/Effort: 1/2-l day meeting of entire founding team
A- Review the organizational differences between Product and Customer Development – Traditional titles versus functional ones.
1. No VP of Sales
2. No VP of Marketing
3. No VP of Business Development
B-Identify the four key functional roles for the first four phases of a startup
1. Who is the Business Visionary
2. Who is the Business Execution
3. Who is the Technical Visionary
4. Who is the Technical Execution
C-Review the goals of each of the roles for each of the four Customer Development phases
D-Enumerate 3 to 5 Core Values of the Founding Team
1. Not a mission statement
2. Not about profit or products
3. Core ideology is about what the company believes in
Phase O-b Exit Criteria: Buy-in of the team and board for functional job descriptions, right people in those jobs, core values