Category Archives: Innovation

Andrew S. Grove 1936 – 2016

Andrew Grove died a few days ago. I remember reading is “Only The Paranoid Survive”. I remember that he had an amazing life, at least his first years from his native Hungary until he reached New York.

Andrew S. Grove was chairman of the board of Intel Corporation from May 1997 to May 2005. He was the company’s chief executive officer from 1987 to 1998 and its president from 1979 to 1997. Ref: Andrew S. Grove 1936 – 2016 (Intel web site)

I also remember he wrote in 1010 an analysis about start-ups which is very profound. So I will quote him again.

It’s our own misplaced faith in the power of startups to create U.S. jobs. Americans love the idea of the guys in the garage inventing something that changes the world. New York Times columnist Thomas L. Friedman recently encapsulated this view in a piece called Start-Ups, Not Bailouts. His argument: Let tired old companies that do commodity manufacturing die if they have to. If Washington really wants to create jobs, he wrote, it should back startups.

Mythical Moment.

Friedman is wrong. Startups are a wonderful thing, but they cannot by themselves increase tech employment. Equally important is what comes after that mythical moment of creation in the garage, as technology goes from prototype to mass production. This is the phase where companies scale up. They work out design details, figure out how to make things affordably, build factories, and hire people by the thousands. Scaling is hard work but necessary to make innovation matter. The scaling process is no longer happening in the U.S. And as long as that’s the case, plowing capital into young companies that build their factories elsewhere will continue to yield a bad return in terms of American jobs. Scaling used to work well in Silicon Valley. Entrepreneurs came up with an invention. Investors gave them money to build their business. If the founders and their investors were lucky, the company grew and had an initial public offering, which brought in money that financed further growth.

Intel Startup

I am fortunate to have lived through one such example. In 1968, two well-known technologists and their investor friends anted up $3 million to start Intel Corp., making memory chips for the computer industry. From the beginning, we had to figure out how to make our chips in volume. We had to build factories; hire, train and retain employees; establish relationships with suppliers; and sort out a million other things before Intel could become a billion-dollar company. Three years later, it went public and grew to be one of the biggest technology companies in the world. By 1980, which was 10 years after our IPO, about 13,000 people worked for Intel in the U.S. Not far from Intel’s headquarters in Santa Clara, California, other companies developed. Tandem Computers Inc. went through a similar process, then Sun Microsystems Inc., Cisco Systems Inc., Netscape Communications Corp., and on and on. Some companies died along the way or were absorbed by others, but each survivor added to the complex technological ecosystem that came to be called Silicon Valley. As time passed, wages and health-care costs rose in the U.S., and China opened up. American companies discovered they could have their manufacturing and even their engineering done cheaper overseas. When they did so, margins improved. Management was happy, and so were stockholders. Growth continued, even more profitably. But the job machine began sputtering.

U.S. Versus China

Today, manufacturing employment in the U.S. computer industry is about 166,000 — lower than it was before the first personal computer, the MITS Altair 2800, was assembled in 1975. Meanwhile, a very effective computer-manufacturing industry has emerged in Asia, employing about 1.5 million workers — factory employees, engineers and managers. The largest of these companies is Hon Hai Precision Industry Co., also known as Foxconn. The company has grown at an astounding rate, first in Taiwan and later in China. Its revenue last year was $62 billion, larger than Apple Inc., Microsoft Corp., Dell Inc. or Intel. Foxconn employs more than 800,000 people, more than the combined worldwide head count of Apple, Dell, Microsoft, Hewlett-Packard Co., Intel and Sony Corp.

10-to-1 Ratio

Until a recent spate of suicides at Foxconn’s giant factory complex in Shenzhen, China, few Americans had heard of the company. But most know the products it makes: computers for Dell and HP, Nokia Oyj cell phones, Microsoft Xbox 360 consoles, Intel motherboards, and countless other familiar gadgets. Some 250,000 Foxconn employees in southern China produce Apple’s products. Apple, meanwhile, has about 25,000 employees in the U.S. — that means for every Apple worker in the U.S. there are 10 people in China working on iMacs, iPods and iPhones. The same roughly 10-to-1 relationship holds for Dell, disk-drive maker Seagate Technology, and other U.S. tech companies… (more on the Bloomberg article)

A great man has just disappeared.

Two Challenges of Technology Transfer – Part 2, Get to Know Your TTO.

My second post about Technology Transfer (following the one about National Systems) is about the micro-economics of the activity. This is motivated by the very good Keys to the kingdom – subtitled What you need to know about your technology transfer office.

Before summarizing its content, let me remind you about the posts which already cover the topic so you will agree it’s not a new topic for me and I consider it as important:
– University licensing to start-ups in May 2010 ( followed by
– University licensing to start-ups (Part 2) in June 2010 (
– How much Equity Universities take in Start-ups from IP Licensing? in November 2013 (
– Should universities get rich with their spin-offs? in June 205 (


Co-authored by 18 people from Stanford, Oxford, Harvard, the University of California in San Francisco and the University College London, the article describes what should know people interested in getting a license on intellectual property to create a start-up. The paper begins with “As an academic […]entrepreneur, you will face many challenges” and the second paragraph follows with “In addition, you will most likely have to negotiate with your university’s technology transfer office (TTO) to license the intellectual property (IP) related to your research”.

What are these challenges related to TTO? they are written in the article in bold fonts as follows: Overcoming information asymmetries – Long negotiations – Inexperience – Lack of funding – Conflict of interest rules – Experienced legal counsel. This means that as a future entrepreneur, you should be prepared and ideally be knowledgeable about these.

The challenges

The main challenge seems to be the administrative complexity and opacity (page 1), including confidentiality of contracts, which makes it difficult for outside observers to understand fair market terms (page 1 again). In the end, they nearly conclude with: “Indeed, even for the universities for whom we have data regarding equity policies, it was often hidden deep within a jumble of legalese. To that end we encourage universities and research institutes receiving public monies to be fully transparent in their equity and royalty policies, and not use these information asymmetries as a bargaining advantage against fledgling […]entrepreneurs.”

On page 2, I note:
– A negotiation may be long (6-12 months, even 18 months) and one way to make it short is to take the proposed terms.
– A way to mitigate inexperience is by “preparing an adequate business plan or strategy for your IP before approaching your TTO” or by “bringing aboard team members with prior experience in […] commercialization to improve your team’s credibility”.
Lack of funding can be partially solved by signing “license option agreements”.
Conflict of interest rules “exist to prevent academics from playing both sides of a technology licensing deal or devoting too much time to nonacademic obligations”. Furthermore, “TTOs represent the interests of the university (not the academic), yet the academic is technically an employee of the university. “Our policy is to never negotiate directly with the faculty,” says a US-based TTO representative”.
– Experienced legal counsel is advised for assessing the quality of the IP but also because “[…]entrepreneurs often fail to appreciate the opportunity cost to the TTO in outlicensing. If a technology is licensed to an ineffective team (particularly with an exclusive license), the university forgoes any success or revenue it may have received from licensing the technology to a better organized industry partner. Moreover, universities have limited resources and manpower to protect IP, and, for this reason, prefer to license technology to teams they believe are well prepared to commercialize it.”

The equity deal terms

“Perhaps the most striking difference between the United States and United Kingdom is seen with equity deal terms. In the United Kingdom, a typical licensing deal is a rarely negotiable 50:50 split between the university and the academic […]entrepreneur, whereas US interviewees often reported universities taking a 5–10% negotiable equity share.”

You now understand why I said I was not convinced in my previous post about taking the UK as a reference. The US practice shows space for debate. You may check again my article from November 2013, where you will see that a typical deal is either 10% at creation or 5% after significant funding. Very rarely more.

Again the authors mention “US founders often do not realize that some deal terms are negotiable, including upfront fees, option payments, equity, royalty payments, milestone payments, territories covered, field of use and exclusivity versus nonexclusivity” and “In the UK, licensing deal equity terms are often perceived as being non-negotiable, though this is not always the case. In fact, many institute policies explicitly state that equity terms are negotiable.” This may however make the process lengthier.

On page 4, the authors add: “It is difficult to understand the justification of UK TTOs, such as Oxford’s Isis Innovation, taking 50% of a company’s equity at formation — which after investment can leave the academic entrepreneur with an extremely low stake from the get-go, for what was likely years of work, and will require many years and millions more to develop.” and indeed “The data would suggest that TTOs taking less upfront and leaving more to the academic and investors who will actually carry the idea forward pays off in the long term. Simply put: holding a smaller piece of something is still more valuable than a large piece of nothing.”

The mystery of royalties

“It is also worth noting that while a discussion on royalties was outside the scope of this study, it was clear from our research that many university TTOs “double dip” and take significant equity and royalty.” but again “Perhaps more disquieting than the out-sized equity and royalty stakes that universities are claiming is the lack of transparency from many universities on this critical issue.”

My conclusion: any wannabe entrepreneur should read this short 5-page paper and be prepared to negotiate. I would love as much as the authors that universities and research institutes be fully transparent in their equity and royalty policies, though I am also aware of the possibly weakened position of universities which would do so.

Two Challenges of Technology Transfer – Part 1, the National Systems.

Two documents have led me to describe two types of challenges facing the technology transfer of academic institutions.
– First, at a macro-economic level, the challenge comes from the various possible administrative structures, but also the complexity of the operations. The report Transfert et Valorisation dans le PIA (in French) by Bruno Rostand compares the national policies of Germany and the United Kingdom to that of France.
– Secondly, at the micro-economic level, the journal Nature published the article Keys to the kingdom with the subtitle, What you should know about your technology transfer office. I will come back to this in my next post.

Mise en page 1

The report of Bruno Rostand addresses the challenges that France meets after having established regional structures for technology transfer, the “SATT”. He notes that Germany has built a similar system with its “PVA” in the Länder. In both cases, there is a goal of financial independence which seems difficult to achieve if not unrealistic, despite the existence of public subsidies. In Germany, two of these companies have even filed for bankruptcy in Lower Saxony in 2006 and Berlin in 2013.

Why such difficulties? Because the returns on investment have not been up to the expectations. For example, approximately €10M euros have been invested each year in the form of public funds in Germany, but revenues remained much lower. In addition the regional structure has its limitations, as it is difficult to gain expertise in all areas of technology.

The United Kingdom has a different situation. The state has been a marginal actor and technology transfer was organized either by universities (Cambridge, Oxford, Imperial College) or by private structures close to venture capital (IP group) which organically helped in structuring technology transfer. Through externalization, these organizations have become private organizations, which have become rich in financial and human resources. At Oxford, ISIS employs 80 people for £14.5m in revenue in 2014. Imperial innovation has been publicly traded since 2006, employs 45 people and generated a profit of £27M in 2014. Imperial innovation has expanded its initial base in collaborating with other universities. Finally, the IP Group has agreements with over 15 universities for a profit of £9.5M in 2014. The report shows very different philosophies, whether public or private, with profitability as an end or not, with an obvious entrepreneurial dimension in the UK. if the focus on start-ups is important, this will lead to different structures, including maturation funds and incubators.

The report also shows that a licensing policy and a policy to support the creation of start-ups are very different. Finally, the new TT structures often have the sole responsibility of the development and maturation of IP, while research collaborations with industry remain the responsibility of universities. This separation could be a weakness when the two topics are linked.

A sensitive issue is that of exclusivity that can create tension when TT management is pooled over many universities. Some universities want to maintain some autonomy, especially in areas where the technical competence of the TT structure seems weak to them. Another sensitive issue is that of the structure by region while a transregional structure by field of expertise might be more appropriate. (The report also addresses research partnerships and international cooperation that I will not discuss here.)

In the final part, Rostand shows the complexity of the challenges. One must first define the mission of technology transfer which can be for profit or not. Externalization seems to be a trend in the three countries, but it has its advantages and disadvantages. It also seems that there is a lot of instability and fluctuations in funding cycles, which does not help to make an analysis of the transfer tools. The report also addresses the issue of human resources (types of skills and experience), another subject which may be related to the available resources of these organizations.

The only personal comment I make here is about my slight frustration at not having found in the report (which is extremely informative) an analysis of the US situation. The country of liberalism and private universities have very few external technology transfer structures, let alone for-profit. I have in mind WARF at University of Wisconsin-Madison – while revenues of TT in the USA are significantly higher than in Europe. The explanation could simply come from a far more dynamic private innovation, regardless of all the systems in place.

Emerging Science and Technologies, why so many promises? (Part 4)

This is my final post about what I have learned from Sciences et technologies émergentes, pourquoi tant de promesses? (For the record here are the links to part 1, part 2 and part 3).


The last chapters of this excellent book try to explore ways to solve the problem of excessive promises that have become a system. In Chapter IV.2, it is question of “désorcèlement” (the closest term I found would be “disenchanted”); I read it as a critical analysis of the vocabulary used by those who promise. The chapter speaks at length of the transhumanist movement, the promise of promises! “[…] Describe how these actors certainly produce, but especially divert away, reconfigure and amplify these promises […] in front of passive and naive consumers.” [Page 261] and later “[but] transhumanists are first activists, mostly neither engineers nor practitioners […] attempting answers to questions not asked or badly expressed, […] hence a really caricatural corpus,” to the point of talking about a “cult” (quoting Jean-Pierre Dupuy), “a muddled, often questionable thinking.” [Page 262]

In Chapter IV.3, the authors explore unconventional approaches, a possible sign of disarray to “scientifically” react to the promises. For example, they have contributed to the creation of a comic book to answer another comic which wanted to popularize and promote synthetic biology.


The final chapter explores scenarios that may follow the explosion of promises, like the idea of ​​increasing the number of Nobel Prize. New promises?!! More concretely, the author shows that the initial promises are not followed in practice: “The wait & see phenomenon in investment, or lack of innovation, is less known, though widespread: the effect of general and diffuse promises maintains the interest of players but too much uncertainty holds back investment in cycles of concrete promises-requirements.” [Page 297] “A game is at work which continues as long as the players follow the rules, […] they are prisoners of the game. […] They may also leave it if the right circumstances occur and then the game collapses.” [Page 298]

In conclusion, beyond a very rich description of many examples of scientific and technical promises, the authors have shown how a system of promises was built through interactions between the various stakeholders (the researchers themselves, the (political, social and economic) decision makers who fund them, and the general public which hopes and feels anxiety). The relationship to time, not only the future but also the present and the past, is beautifully described, in addition to a desire for eternity. And finally, we mostly discover that the promises have led to numerous debates that were perhaps, if not entirely, useless, as we could have known that the promises can not be kept, even from the moment they were created…

Emerging Science and Technologies, why so many promises? (Part 3)

This is my third article about the book Sciences et technologies émergentes, pourquoi tant de promesses? After the general considerations on the system of promises, the book presents contributions describing specific areas:

I.3: nanotechnologies
II.1: semiconductors through Moore’s Law
II.2: big ata
II.3: digital Humanities
III.1: neurosciences and psychiatry
III.2: The Human Brain Project (HBP)
III.3: personalized medicine
III.4: biodiversity and nanomedicine
IV.1: assisted reproduction
IV.2: regenerative medicine


Each chapter is interesting for the curious reader as it shows the dynamics between promises and expectations of stakeholders (researchers, politicy makers, general public). The chapter about the HBP is particularly interesting in the description of the disconnection between content and form. “How was it possible that the HBP “won the competition” despite the lack of evidence to establish pragmatically the scientific relevance and the legitimacy of its ambitious organizational goals? We develop the hypothesis that this deficit, criticized afterwards, was both hidden and compensated by the production of promises shaped to anticipate and / or respond effectively to the political, economic, social and health-realted stakes on the agenda of the “challenges to come”. [Page 166] The credibility of the HBP sealed by this decision has been built […] following an adaptation process and reciprocal validations in the double register of the politicization of science and the scientification of politics. In other words, we show that one of the important conditions of this credibility was the successful co-production of a strategic congruence between [scientific] promises and the agenda of policy issues. [Page 171] The connection between knowledge of the brain and forms of social life took place mainly in the domain of discourse. […] In this contrasting situation, discursive inflation around the brain and neuroscience seems to be the consequence of a lack of evidence, as if it had overcome, positively or negatively, the differences between the present and the future, the proven and the possible, the absence and the desire. This regular feature of big science projects has resulted in the development and implementation of a prophetic rhetoric that seeks to anticipate the possibility of a better future by borrowing to the notions of hope and promise.” [Page 176-77]

I come back to a quote from chapter 3 that is essential to me as a conclusion to this new post: The real progress of techno-science will less come from their ability to keep promises than from their ability to do without them, to inherit critically from the era of great technological promise. This is not to break an idol, but to learn how to inherit. [Page 111]

Emerging Science and Technologies, why so many promises? (Part 2)

(A word of caution: my English is reaching its limits in trying to analyze a demanding book, written in French. I apologize in advance for the very awkward wording…)

So just one day after my article describing Chapter 1 of Emerging Science and Technologies, why so many promises?, here comes an analysis of the second chapter, where the relation to time is analyzed, as well as presentism, futurism and the role of time in the promise system. There is the nice following passage:


Since The New Atlantis, futuristic speculations have accompanied the development of modern science. And in the twentieth century, Jean Perrin has sealed a new alliance between science and hope. But for him, it is science that preceded and provoked hope while now, it is rather hope that drives research. Technosciences reverse, in fact, the order of the questions that was following the three critiques of Kant: “What can I know?” – the issue addressed in Critique of Pure Reason – then the question “What can I do?” – treated in the Critique of Practical Reason – finally the question “What can I expect?” – discussed in the Critique of Judgment. In contrast, in the current scientific policies, one determines what to do and what we can possibly acquire as knowledge by identifying the hopes and promises. (Page 50)

Yet there is a paradox already expressed in the first chapter between futurism with the terms of promise, foresight and prophecy that project us and presentism particularly marked by the memory that freezes the past and transforms the future as a threat that no longer enlightens neither the past nor the present. To the point of talking about a future presentification…

The chapter also deals with the question of the future as a shock, a time “crisis” due to the acceleration. To the feeling of the misunderstanding and helplessness, is added the experience of frustration and stress caused by the accelerated pace of life, the disappointment of a promise related to modernity, where techniques were supposed to save time, to emancipate.

Another confusion: the features of planning and roadmap which are typical of technology projects slipped into research projects where is used the term of production of knowledge, while in research, it is impossible to guarantee a result. But the author shows through two examples, that this development is complex.

In the case of nanotechnology, there has been roadmap with the first two relatively predictable stages of component production followed by a third stage on more speculative systems crowned by a fourth stage which speaks of emergence, and all this by also “neglecting contingency, serendipity and possible bifurcations,” not to predict, but to “linearize the knowledge production”. The roadmap predicts the unexpected by announcing an emergence, combining a reassuring scenario of control which helps in inspiring confidence and with at the same time an emerging scenario, to create dreams. (Pages 55-56)

In the case of synthetic biology “despite a clear convergence with nanotechnology,” the rapid development occurs without any roadmap. “A common intention – the design of the living – gathers these research paths.” And it is more to redo the past (“3.6 billion years of genetic code”) than to imagine the future. The future becomes abstract and it comes as proofs of concept. And the author adds that in normal science in the sense of Kuhn, these proofs of concepts would have fallen into oblivion. The paradox is that there is no question of right or wrong, but of designing without any needed functionality.

In the first case, “prediction or forecasting are convened as the indispensable basis for a strategy based on rational choice”, “the future looks to the present. “In the second case, there is the question of “towing the present” and “fleeing out of time.” We unite and mobilize without any necessary aim. The future is virtual, abstract, and devoid of culture and humanity; the life of the augmented human looks more like eternal rest …

Ultimately, the economy of promises remains riveted on the present either by making the future a reference point to guide action in the present, or it is seeking to perpetuate the present.

Chapters three and four are less theoretical, describing on one hand new examples in the field of nanotechnology and on the other, how Moore’s Law became a law when it was initially a prospective vision of progress in semiconductor. Perhaps soon a follow-up about the next chapters…

Emerging Science and Technologies, why so many promises? (Part 1)

Sciences et technologies émergentes, pourquoi tant de promesses? (Emerging Science and Technologies, why so many promises?) is the title of a book (in French only) from a group of authors under the direction of Marc Audétat, a political scientist and researcher at the Sciences -Society Interface of the University of Lausanne. This is not an easy reading book, it is quite demanding, but it raises important questions.

I have already reported on this blog about books that speak of a certain crisis of science, for example in The Crisis and the American model (in French), about the books “La Science à bout de Souffle” or “The University bubble. Should we pursue the American dream?” or in The Trouble With…, a book by Lee Smolin, not to mention the most violent criticism of the promises of technology by Peter Thiel in Technology = Salvation.


This new book explores the promises related to science and technology to the point of talking about an economy of promises. This is a collective work which does not make it an easy reading, but the diversity of points of views is certainly an asset. I have not finished reading it and I will certainly come back to it. In the first chapter, P.-B. Joly describes the system of techno-scientific promises. He begins by introducing the concepts of Imaginary and Vision [Page 33] This “couple of concepts takes into account how various sources of inspiration are involved in the technical creation. […] The Imaginary gives an almost tangible appearance to concepts and ideals that are a priori devoid of it … [and becomes] a common sense that founds the action into society. […] The concept of Vision is close to that of Imaginary, but on a smaller scale. It is akin to that of “rational myth” used to analyze the dynamics of collective action in changing contexts. […] Coalitions of actors form around these visions of a prospective order and contribute to their dynamics. […] If we accept this conceptual distinction between Imaginaries (at large scales – the Nation – and in the long term) and Visions (at a level of coalitions of actors and active over periods of medium length) then comes the question of the interaction between the two.”

“Unlike Visions and Imaginaries, for which the content of technical arrangements is essential, what is essential for the techno-scientific promises is the creation of a relation, as well as a time horizon of expectations. […] Promises are essential in technology creation, because they enable innovators to legitimize their projects, to mobilize resources and to stabilize their environment. […] Any techno-scientific promise must convince a large audience that it determines a better future than the alternatives, even if the realization of the promise requires major, sometimes painful changes.” (The author mentions the history of electricity or the green revolution as the solution to world hunger)

“Our concept of techno-scientific promises has been systematized and became in the last forty years the governance of the new techno-sciences (biotechnology and genomics, nanotechnology, neuroscience, synthetic biology, geo -engineering, etc.) The construction of a techno-scientific promise meets two conflicting constraints: the constraint Radical Novelty and that of Credibility. […] (And I interpret that) for this request to be credible, one must disqualify alternatives. [Furthermore] For a scientific theory to be credible, its validity is neither necessary nor sufficient. […] The techno-scientific promises must have the support of a circle of specialists. Otherwise, they cannot resist the opposition manifested either in scientific arenas, or in public arenas. An extreme version is observed when the specialists refer to natural laws to justify the inevitability of technological change. (Examples are Moore’s Law and Gabor’s Law.) Thus, in principle, generic promises are not subject to validity tests.”

Finally, this intensification is reinforced by three complementary elements [page 39]:
– the future is more a threat than a source of hope;
– research and innovation are often presented as the only way to solve problems;
– the research stakeholders should demonstrate their societal impacts.

This leads to pathologies [pages 40-43]:
– the myth of a public victim of irrational fears and to be educated becomes an intangible scheme;
– the promises turn into bubbles;
– the radical novelty and uncertainty create conflicting discourses, sources of mistrust because the effects of such radicalism is not predictable so that through experimentation, the technologists become sorcerer’s apprentices and society, a laboratory;
– finally promises lead to endless discussions on fictions, on issues that may have nothing to do with the reality of research.

In conclusion Joly thinks this promises system is one of the enemies of the future because of the clear separation it creates between those who make the promise and those who are supposed to accept it. The recognition of this regime and therefore these problems is a prerequisite imperative.

After reading the first chapter, I remembered the societal concerns of Cynthia Fleury, about whom I have already said a few things in a digression in the article On France Culture, Transhumanism is Science Fiction. Our democratic societies are in crisis, and the distrust of politics as well as of experts has never been stronger. The issue of research and innovation is a component of this crisis. I am eager to discover the rest of this very interesting (and important) work …

Global Entrepreneurship 2016 – Part 2: the microeconomic analysis of the Startup Playbook by Sam Altman

After Part1 about the global vision of Entrepreneurship in 2016, here is a “micro” analysis of what entrepreneurship is. I finished reading this report while on a transcontinental flight, where I watched recent movie The Martian with Matt Damon.

Not only is The Martian describing a story very similar to what being a CEO might be – lonely with a life and death situation (at least for the start-up) after each major decision, but that day, I also learnt the death of David Bowie. In that movie, you can listen to Starman… my humble tribute to a great artist.

Again Ycombinator produces an efficient and compelling document about start-ups and entrepreneurship. After Paul Graham’s blog and Sam Altman’s class at Stanford in 2014, here is his Startup Playbook. A short document “for people new to the world of startups. Most of this will not be new to people who have read a lot of what YC partners have written—the goal is to get it into one place.” Altman explains “So all you need is a great idea, a great team, a great product, and great execution. So easy! 😉 A must read which I summarize my way through shorter extracts:


Friendly advice first
– Make something users love.
– A word of warning about choosing to start a startup: It sucks!
– On the other hand, starting a startup is not in fact very risky to your career.

A great idea (including a great market)
– Something explained clearly and concisely with a fast-growing potential.
– It’s easier to do something new and hard than something derivative and easy.
– The best ideas sound bad but are in fact good.

A great team
– Mediocre teams do not build great companies.
– A great founder characteristics include unstoppability, determination, formidability, and resourcefulness; intelligence and passion.
– Good founders have a number of seemingly contradictory traits such as rigidity and flexibility.

A great product
– A great product is the only way to grow long-term.
– “Do things that don’t scale” has rightfully become a mantra for startups.
– Iterate and adapt as you go.
PS: By the way, “product” includes all interactions a user has with the company. You need to offer great support, great sales interactions, etc.

A great execution
– You have to do it yourself — the fantasy of hiring an “experienced manager” to do all this work is both extremely prevalent and a graveyard for failed companies. You cannot outsource the work to someone else for a long time.
– Growth (as long as it is not “sell dollar bills for 90 cents” growth) solves all problems, and lack of growth is not solvable by anything but growth.
– Extreme internal transparency around metrics (and financials) is a good thing to do.

Focus and intensity
– The best founders are relentlessly focused on their product and growth. They don’t try to do everything—in fact, they say no a lot.
– While great founders don’t do many big projects, they do whatever they do very intensely. Great founders listen to all of the advice and then quickly make their own decisions.

Being a founder & CEO
– The CEO jobs: 1) set the vision and strategy for the company, 2) evangelize the company to everyone, 3) hire and manage the team, especially in areas where you yourself have gaps 4) raise money and make sure the company does not run out of money, and 5) set the execution quality bar.
– As I mentioned at the beginning, it’s an intense job. If you are successful, it will take over your life to a degree you cannot imagine—the company will be on your mind all the time. Extreme focus and extreme intensity means it’s not the best choice for work-life balance. You can have one other big thing—your family, doing lots of triathlons, whatever—but probably not much more than that.
– No first-time founder knows what he or she is doing. To the degree you understand that, and ask for help, you’ll be better off. It’s worth the time investment to learn to become a good leader and manager. The best way to do this is to find a mentor—reading books doesn’t seem to work as well.
Be persistent. A successful startup CEO is not giving up (although you don’t want to be obstinate beyond all reason either—this is another apparent contradiction, and a hard judgment call to make.)
Be optimistic. Although it’s possible that there is a great pessimistic CEO somewhere out in the world, I haven’t met him or her yet.

Additional advice

– Hiring: Don’t do it. Wait!
– Competition: 99% of startups die from suicide, not murder.
– Fundraising: Investors are looking for companies that are going to be really successful. The “really successful” part is important. If an investor believes you have a 100% chance of creating a $10 million company but almost no chance of building a larger company, he/she will still probably not invest. Always explain why you could be a huge success. . Many of the best companies have struggled with this, because the best companies so often look bad at the beginning (and they nearly always look unfashionable.) And remember that anything but “yes” is a “no”.
– Investors: Good investors really do add a lot of value. Bad investors detract a lot. Most investors fall in the middle and neither add nor detract. Great board members are one of the best outside forcing functions for a company.

All this again was extracted from Sam Altman’s Startup Playbook. Thanks to him for a great job! I must also thank one of my students (he will recognize himself) for mentioning that document to me…

Global Entrepreneurship 2016 – Part 1: the Macroeconomics

I just read two great reports about entrepreneurship. The first one is the Global Entrepreneurship Index 2016 (GEI). The second one is the Startup Playbook by Sam Altman (Ycombinator). Whereas the second one is about the micro features of entrepreneurship, the GEI is a worldwide macro-economic analysis. I will cover the Startup Playbook in the part 2 of these series of posts, so let me focus here in the GEI.


What I found really interesting is that compared to the Global Innovation Index (GII) about which I always have doubts – I think it measures more the inputs necessary for innovation than the outputs – I feel much more comfortable with the criteria and results of the GEI. For example, the USA is number one which makes a lot of sense and Switzerland is #8. Switzerland is #1 in the GII which is some kind of a mystery to me. France and Israel are #10 and #21 in the GEI but #20 and #21 in the GII.


The 3 As of Entrepreneurship

So how is this measured? The authors define 3 framework conditions entrepreneurship: attitudes, abilities and aspirations.[Pages 26-27 of the document or 49-50 of the pdf]. They also define 14 related pillars [Pages 19-22 of the document or 42-45 of the pdf]

Entrepreneurial attitudes are societies’ attitudes toward entrepreneurship, which we define as a population’s general feelings about recognizing opportunities, knowing entrepreneurs personally, endowing entrepreneurs with high status, accepting the risks associated with business startups, and having the skills to launch a business successfully. The benchmark individuals are those who can recognize valuable business opportunities and have the skills to exploit them; who attach high status to entrepreneurs; who can bear and handle startup risks; who know other entrepreneurs personally (i.e., have a network or role models); and who can generate future entrepreneurial activities.

Moreover, these people can provide the cultural support, financial resources, and networking potential to those who are already entrepreneurs or want to start a business. Entrepreneurial attitudes are important because they express the general feeling of the population toward entrepreneurs and entrepreneurship. Countries need people who can recognize valuable business opportunities, and who perceive that they have the required skills to exploit these opportunities. Moreover, if national attitudes toward entrepreneurship are positive, it will generate cultural support, financial support, and networking benefits for those who want to start businesses.

Entrepreneurial abilities refer to the entrepreneurs’ characteristics and those of their businesses. Different types of entrepreneurial abilities can be distinguished within the realm of new business efforts. Creating businesses may vary by industry sector, the legal form of organization, and demographics—age, education, etc. We define entrepreneurial abilities as startups in the medium- or high-technology sectors that are initiated by educated entrepreneurs, and launched because of someone being motivated by an opportunity in an environment that is not overly competitive. In order to calculate the opportunity startup rate, we use the GEM TEA Opportunity Index. TEA captures new startups not only as the creation of new ventures but also as startups within existing businesses, such as a spinoff or other entrepreneurial effort. Differences in the quality of startups are quantified by the entrepreneur’s education level—that is, if they have a postsecondary education—and the uniqueness of the product or service as measured by the level of competition. Moreover, it is generally maintained that opportunity motivation is a sign of better planning, a more sophisticated strategy, and higher growth expectations than “necessity” motivation in startups.

Entrepreneurial aspiration reflects the quality aspects of startups and new businesses. Some people just hate their employer and want to be their own boss, while others want to create the next Microsoft. Entrepreneurial aspiration is defined as the early-stage entrepreneur’s effort to introduce new products and/or services, develop new production processes, penetrate foreign markets, substantially increase their company’s staff, and finance their business with formal and/or informal venture capital. Product and process innovation, internationalization, and high growth are considered the key characteristics of entrepreneurship. Here we added a finance variable to capture the informal and formal venture capital potential that is vital for innovative startups and high-growth firms.

Each of these three building blocks of entrepreneurship influences the other two. For example, entrepreneurial attitudes influence entrepreneurial abilities and entrepreneurial aspirations, while entrepreneurial aspirations and abilities also influence entrepreneurial attitudes.


The 14 Pillars of Entrepreneurship

The pillars of entrepreneurship are many and complex. While a widely accepted definition of
entrepreneurship is lacking, there is general agreement that the concept has numerous dimensions. […] Considering all of these possibilities and limitations, we define entrepreneurship as “the dynamic, institutionally embedded interaction between entrepreneurial attitudes, entrepreneurial abilities, and entrepreneurial aspirations by individuals, which drives the allocation of resources through the creation and operation of new ventures.”

Entrepreneurial Attitudes Pillars

Pillar 1: Opportunity Perception. This pillar captures the potential “opportunity perception” of a population by considering the size of its country’s domestic market and level of urbanization. Within this pillar is the individual variable, Opportunity Recognition, which measures the percentage of the population that can identify good opportunities to start a business in the area where they live. However, the value of these opportunities also depends on the size of the market. The institutional variable Market Agglomeration consists of two smaller variables: the size of the domestic market (Domestic Market) and urbanization (Urbanization). The Urbanization variable is intended to capture which opportunities have better prospects in developed urban areas than they do in poorer rural areas.

Pillar 2: Startup Skills
. Launching a successful venture requires the potential entrepreneur to have the necessary startup skills. Skill Perception measures the percentage of the population who believe they have adequate startup skills. Most people in developing countries think they have the skills needed to start a business, but their skills usually were acquired through workplace trial and error in relatively simple business activities. In developed countries, business formation, operation, management, etc., requires skills that are acquired through formal education and training. Hence education, especially postsecondary education, plays a vital role in teaching and developing entrepreneurial skills.

Pillar 3: Risk Acceptance. Of the personal entrepreneurial traits, fear of failure is one of the most important obstacles to a startup.

Pillar 4: Networking. Networking combines an entrepreneur’s personal knowledge with their ability to use the Internet for business purposes. This combination serves as a proxy for networking, which is also an important ingredient of successful venture creation and entrepreneurship.

Pillar 5: Cultural Support. This pillar is a combined measure of how a country’s inhabitants view entrepreneurs in terms of status and career choice, and how the level of corruption in that country affects this view.

Entrepreneurial Abilities Pillars

Pillar 6: Opportunity Startup. This is a measure of startups by people who are motivated by opportunity but face regulatory constraints. An entrepreneur’s motivation for starting a business is an important signal of quality. Opportunity entrepreneurs are believed to be better prepared, to have superior skills, and to earn more than what we call necessity entrepreneurs.

Pillar 7: Technology Absorption. In the modern knowledge economy, information and communication technologies (ICT) play a crucial role in economic development. Not all sectors provide the same chances for businesses to survive and or their potential for growth. The Technology Level variable is a measure of the businesses that are in technology sectors.

Pillar 8: Human Capital. The prevalence of high-quality human capital is vitally important for ventures that are highly innovative and require an educated, experienced, and healthy workforce to continue to grow.

Pillar 9: Competition. Competition is a measure of a business’s product or market uniqueness, combined with the market power of existing businesses and business groups.

Entrepreneurial Aspirations Pillars

Pillar 10: Product Innovation. New products play a crucial role in the economy of all countries. New Product is a measure of a country’s potential to generate new products and to adopt or imitate existing products.

Pillar 11: Process Innovation. Applying and/or creating new technology is another important feature of businesses with high growth potential. New Tech is defined as the percentage of businesses whose principal underlying technology is less than five years old.

Pillar 12: High Growth. This is a combined measure of the percentage of high-growth businesses that intend to employ at least ten people and plan to grow more than 50 percent in five years (Gazelle variable) with business strategy sophistication (Business Strategy variable).

Pillar 13: Internationalization. Internationalization is believed to be a major determinant of growth. A widely applied proxy for internationalization is exporting.

Pillar 14: Risk Capital. The availability of risk finance, particularly equity rather than debt, is an essential precondition for fulfilling entrepreneurial aspirations that are beyond an individual entrepreneur’s personal financial resources.

The reason I really felt synchronized with the authors (congrats to Zoltán J. Ács, László Szerb, Erkko Autio for the great work!) is a final extract from pages 63-64 (86-87 of the pdf): they explain the challenges and related mistakes and describe better approaches.

Unfortunately, although high-growth entrepreneurship and entrepreneurial ecosystems are high on many policy agendas, there is fairly little understanding of how policy can foster them most effectively. Most entrepreneurship policy playbooks remain stuck with old world policy approaches, which focus on identifying and fixing “market failures” and “structural failures.” Such approaches, while effective in addressing well-specified market and structural failures, are hopelessly inadequate to deal with the complexities of entrepreneurial ecosystems.
A classic example of a market failure is the failure of businesses to invest in R&D. Because R&D is a risky and uncertain activity, many firms are tempted to wait, to let others to take the risk, and then quickly copy successful projects. But if everyone thought this way, no one would invest in R&D, and innovative activities would stagnate. Therefore, governments address this market failure by providing subsidies for R&D—in effect, participating in the downside risk while allowing firms to keep the upside returns.
In contrast to subsidizing specific activities, a structural failure policy would seek to build support services and structures that support new firm creation and growth. Examples of structural failure policies include, for example, the creation of science parks and business incubators to shelter and support startup ventures.
Both of these approaches fail to address the complexities of entrepreneurial ecosystems, which are too complex to allow easy identification of specific clean-cut market failures, such as insufficient investment in R&D. The “product” entrepreneurial ecosystems produce is innovative and high-growth new ventures. Creating high-growth new ventures is a far more complex undertaking than starting an R&D project. If we do not see a sufficient number of high-growth new ventures, where exactly is the market failure supposed to reside? The standard approach by governments, which is consistent with market failure thinking, is that there perhaps is not sufficient support funding available to start new, high-growth firms. However, as much as governments have provided subsidies to support new firm creation, the results have not been very encouraging.
Another major problem with both market failure and structural failure approaches is that they are top-down, where the policy maker analyzes, designs, and implements entrepreneurship policy. Top-down, however, is not a feasible approach in entrepreneurial ecosystems that consist of multiple independent stakeholders. In such situations, a policymaker cannot simply command and control, as you have no formal authority over ecosystem stakeholders. Instead, policymakers need to engage the various stakeholders and co-opt them as active participants and contributors to the policy intervention.
Entrepreneurial ecosystems are fundamentally interaction systems consisting of multiple, co-specialized, yet hierarchically independent stakeholders, many of which may not even know one another. Here, co-specialization means that different stakeholders play different roles—venture capitalists, research institutions, different supporting institutions, new ventures, established businesses, and so on. They offer complementary skills and services, and normally depend on others to accomplish their goals, which implies that team play is needed.
In the above, hierarchical independence means that there are no formal lines of command, unlike, say, within government agencies or industrial corporations. Everyone makes their own independent decisions and optimizes their own performance. Combined with co-specialization, this creates a mutual dependency dilemma: to accomplish your goals you must depend on others, yet you cannot tell others what to do. Cooperation is therefore required. This limits the usability of traditional top-down policies, which are usually implemented through formal chains of command (e.g., a government department designing a policy, which is then implemented by a government agency overseen by the department).
Also of relevance is the notion of interaction systems, which means that the stakeholders of entrepreneurial ecosystems “co-produce” their outputs, such as innovative high-growth new ventures. These outputs are coproduced through a myriad of usually uncoordinated interactions between hierarchically independent yet interdependent stakeholders. This combination of independence and interdependence makes coordination challenging.
In the GEI model, it is the entrepreneurs who drive the entrepreneurial trial-and-error dynamic. This means that entrepreneurs start new businesses to pursue opportunities that they themselves perceive. An entrepreneurial opportunity is simply a chance to make money through a new venture, such as producing and selling goods and services for profit. However, entrepreneurs can never tell in advance whether a given opportunity is real or not: the only way to validate an opportunity is to pursue it. In other words, entrepreneurs need to take risks: they need to access and mobilize resources (human, financial, physical, technological) before they can verify whether or not a profit can be made. This means, then, that not all entrepreneurial efforts will be successful, as some opportunities turn out to be mere mirages. In such cases, the budding entrepreneur will realize sooner or later that they are never going to make a profit, or that they could make more money doing something else. In such cases, the entrepreneur will abandon the current pursuit and do something else instead.
If, however, an entrepreneurial opportunity turns out to be real, the entrepreneurs will make more money pursuing that opportunity than doing something else, and they will continue to exploit it. The net outcome of this entrepreneurial trial-and-error dynamic, therefore, is the allocation of resources to productive uses. In other words, a healthy entrepreneurial dynamic within a given economy will drive total factor productivity, or the difference between inputs and outputs. The greater the total factor productivity, the greater the economy’s capacity to create new wealth.

The Challenges of Creating a Start-up

January is the month where we publish our start-up statistics at EPFL and when the media contact us to discuss the matter. I had the opportunity to share my views with Danny Baumann, from the AGEFI, and I have the feeling he gave a very good account of our exchange. Here it is:


The EPF Lausanne has been creating, during the last ten years, on average fifteen start-ups per year. Hervé Lebret lists a few leads to follow.


The numbers fell the day before yesterday (L’Agefi, January 6): Researchers at the Federal Institutes of Technology in Lausanne and Zurich have created 43 companies in 2015, including 18 in Lausanne. The Innovation Park of EPFL is growing year after year, with as a proof the 700 jobs created since its launch in 1991. Fintech, biotech, medtech are in the mouth of everyone, but how to successfully create and above all to perpetuate a start -up in the world in constant evolution that we know? There is obviously no quick fix, as explained by Hervé Lebret, innovation specialist and teacher at the EPFL.

The success of a start-up depends on countless parameters. These elements must be as the perfect alignment of planets for that success to occur. Random factors, such as chance, are part of this process. The EPFL provides financial support, eight and ten grants per year, the Innogrants. Launched in 2005 with the support of Lombard Odier, these Innogrants consist of a maximum of 100,000 francs in salary. This does not in any way guarantee the success of a start-up but is a great launching pad.

Hervé Lebret lists a few leads to follow. For starters, the overall vision is essential. Having an international goal rather than local. The future of a start-up must immediately be anticipated: it indeed reaches its maturity after five to seven years. “From that moment, either it is acquired by giants such as Google or Apple or it continues to develop via the equity markets. It rarely stays at the stage of SMEs with 20-30 employees”, adds Hervé Lebret. According to him, 90% to 99% of these young companies disappear within ten years.

Another major aspect: not being cautious about the market. “An entrepreneur with a start-up should keep in mind that his company should be constantly growing,” he continues. Being ambitious and trust your potential investors, in order to raise funds, even at the cost of losing some of her company’s control. A must for growth. On average, 100 million Swiss francs are invested annually from private funds in EPFL start-ups. But how to find investors? The award race is a great way to advertise its product. The first two years are rather of survival; it is at this point that the various awards are essential. “The prize is good, but after two years or so, do not forget to pass in growth mode,” he expressed. Many make the mistake of losing sight of the overall objective and thus remain too small in the market while the company development is vital.

A good recruitment is a major asset in the success. Then comes the question of wages to be paid. The newly recruited employees must be aware that the remuneration will be lower than in a large company. The stock options can be a good alternative to compensate for the difference in pay. Still remains the problem of the taxation of stock options which are still seen as an income even if they are paper only. It should be possible to find an agreement on a special status of “start-up” in the law. The issue has been debated for several years.

Other elements are still important for an entrepreneur such as flexibility, creating a dense network, or having mentors, and, this sounds obvious, have a passion for his product.

Macroeconomic factors also make their entrance. To name one, but essential, mainly in Switzerland, migration. Out of the 90 Innogrants distributed by EPFL since 2005, 75% of them have ended up in the hands of foreign entrepreneurs. And it’s not a matter of discrimination. Switzerland needs foreign brains. A long political debate.

For EPFL, creating start-ups, and related jobs, is a major asset. Not so much from a financial standpoint but rather for the image. Economically, revenues come from licenses granted (they receive dividends or royalties in exchange) to the various entities or from the sale of the start-ups, about 1% of the transaction value. [You may check again How much Equity Universities take in Start-ups from IP Licensing?] The image is much more noticeable. Getting the message of constant innovation, to the eyes of the world, is a vital point for EPFL and the country.

The case study of an ambitious start-up at EPFL.

L.E.S.S. Founders - Tissot and Rivier
Yann Tissot and Simon Rivier, co-fouders of L.E.S.S.

The young company L.E.S.S. (Light Efficient Systems) is the perfect example of a fast growing EPFL start-up. The optical fiber of the company helps in generating a new light system that does not leave indifferent the automotive or computer manufacturers. Yann Tissot, co-founder and CEO, received an EPFL Innogrant in 2011. With this investment, the start-up was founded in June 2012. From that time, ambition and passion of the young entrepreneur made the difference. Travelling around the world to make his product known and running the award race such as the Entrepreneurship Prize of the WA de Vigier Foundation, the Strategis Prize competition or the prize for second best Swiss start-up in 2014 [then the best one in 2015!]. Awards that enabled it to survive and to find investors. In April 2015, it raised a vital three million concluded with VI Partners, supervised by Alain Nicod, as well as from various business angels.
Today L.E.S.S. has nine employees and was close to reach one million in sales last year. The estimated income for 2016 will be of the order of several million francs. – (DB)