Category Archives: Innovation

The Nobel Prize for Thomas Piketty?

I have already said here how much I liked Thomas Piketty’s Capital in the Twenty-First Century (see Has the world gone crazy? Maybe…). In finally ending my reading of the French edition of this 970-page book, I could not help thinking that the author would soon have the Nobel Prize in Economics, even though I have no competence to judge.


When reading his conclusion, I found in the author’s words one of the reasons for my respect regarding this work: “Let us repeat it: the sources gathered in this book are more extensive than those of the previous authors, but they are imperfect and incomplete. All the conclusions I have reached are inherently fragile and deserve to be challenged and debated. Research in social science is not intended to produce ready-made mathematical certainties and to substitute for public, democratic and contradictory debate” [Page 941].

He adds further on: “I see no other place for the economy but as a sub-discipline of the social sciences. […] I do not much like the expression “economic science”, which seems to me to be terribly arrogant and which could lead one to believe that the economy would have reached a higher scientific specificity, distinct from other social sciences. […] One can, for example, spend a great deal of time demonstrating the indisputable existence of a pure and true causality, by forgetting in passing that the question treated is sometimes of limited interest.” [Page 945-7].

Piketty also summarizes his work in a few lines [Page 942]:

“The general lesson of my inquiry is that the dynamic evolution of a market economy and of private property, left to itself, contains within it important convergent forces, linked in particular to the dissemination of knowledge and qualifications, but also powerful forces of divergence, potentially threatening for our democratic societies and the values ​​of social justice on which they are based.

The main destabilizing force is related to the fact that the private rate of return on capital r can be strongly and permanently higher than the growth rate of income and output. The inequality r > g implies that the heritages of the past recapitalize faster than the rate of increase of production and wages. […] The entrepreneur tends inevitably to become an annuitant. […] The past devours the future.”

And the solution is clear: “The right solution is the progressive annual tax on capital. […] The difficulty is that this solution requires a very high degree of international cooperation and regional political integration” [Pages 943-44].

All is said.

I can not help ending this brief article by recalling a striking example among the multitude of data analyzed:


The digital revolution: stakes and challenges (for Switzerland).

My latest contribution to Enterprise Romande, this time about the digital revolution. Below is my “quick and dirty” translation.


I have always been suspicious of fashionable expressions and buzzwords (nanotechnologies, Health Valley, etc.) that are often meaningless and refer to societal or political issues without inducing the slightest change. “Digital Revolution” should not have been an exception to my rule. But the stakes ahead are of a completely different nature and a few salutary readings quickly made me change my mind.

Far from home, President Barack Obama has just published in The Economist a text, which must be read absolutely, the Way Ahead [1] and a series of interviews in Wired [2] calling for confidence in technological progress and for supporting the development of artificial intelligence. His optimism and enthusiasm for the future, even moderated by the challenges and stakes ahead, are impressive and his only vision of the world makes him undoubtedly one of the greatest leaders in history.

Closer to us, Angela Merkel and Johann Schneider-Ammann also took the measure of a revolution which Germany and Switzerland will have to take into account despite the solidity of their economy (see [3] for example). The article “Smart Industry 4.0 in Switzerland” by Matthias Kaiserswerth [4] brilliantly describes the Swiss digital landscape, the stakes and the challenges.

The stakes are simple: there is no doubt that all sectors of the economy, from industry to services, will be affected, not to say “disrupted” by the acceleration of digital transformations. So far, only information and communication technologies (ICT) have been impacted. But today all services can be threatened by the “uberization”. And tomorrow the German automotive industry will be challenged by the Googles, Apples and other Teslas of the world, the Swiss watch industry by the connected watch. And the day after tomorrow, perhaps, bank services by blockchain, health services by personalized medicine and even more seriously the world of labor by robotics, automation and artificial intelligence. Without any reaction from us, Europeans, we will become consumers only, then unable to consume due to lack of resources.

The challenges are up to what is at stake. They start with education and I fear that the actors and decision-makers in primary and secondary education have not understood that Word and Excel are not enough to raise awareness about the algorithmic culture. In terms of vocational training, Kaiserswerth estimates that there will be a shortage of over 30,000 digital experts in Switzerland in 2022. Yet ICT represents more than 20,000 jobs in French-speaking Switzerland alone (in fact about as much as Medtech and Biotech together). But except some great success stories (Temenos, Logitech, Swissquote), most jobs are created by large foreign companies (IBM, HP) or service companies. In Zurich, the leader is called Google. For more than 20 years I have been trying, often unsuccessfully, to describe Europe’s innovation gaps by shaking the banner of a shortage of start-ups that have become such giants as the GAFAs.

An awareness of the challenges ahead is welcome as the country has time to adapt. At least if we react now. Much more needs to be done to integrate digital technologies in education and training and to increase the research effort in these new fields, at the risk of lagging behind. But even this will not be enough. The Americans have sufficiently shown that the first digital revolution, far from being solely technological, was also cultural. We must stimulate the desire. Why are there so few computer science students in our universities? Innovation itself has drastically changed. Innovation has deserted the laboratories of large groups to find refuge in the start-up garages. I dream that our alarmed decision makers do not remain as too often attached to short-term messages and invest in education, research and innovation by start-ups to enable the Swiss economy with its large corporations and many SMEs to adapt to a revolution rich in opportunities. Switzerland has the means. Does it have the will?


The Innovation Illusion by Fredrik Erixon and Bjorn Weigel

The Innovation Illusion: How So Little is Created by So Many Working So Hard by Fredrik Erixon, Bjorn Weigel is a rather strange book but very interesting. I fully agree with most of the authors’ analyses about the illusions we have created around innovation. Less sure I agree with some of their important claims. Their “very liberal” point of view, not to say libertarian, makes their claims sometimes extreme, but in the end, I am not even sure my own claim…


But before beginning, let me mention another interesting piece of analysis from Steve Blank about the innovators. In a recent article in the Harvard Business Review, (The Fatal Flaw That Steve Jobs and Bill Gates Shared), an article that he developed further on his blog, Why Tim Cook is Steve Ballmer and Why He Still Has His Job at Apple, Blank explains how difficult it is to replace a visionary entrepreneur and how they are mostly replaced by executors. I don’t disagree with an answer / analysis on Forbes, Why Apple CEO Tim Cook Is Doing Fine: A Response To Steve Blank’s Critique Of Execution . In a way nobody knows how to innovate in a disruptive manner so the rational decision is to focus on execution.

Which brings me back to the Innovation Illusion. My main concern is that the authors claim capitalism has lost its soul, and they explain how, but I am not sure we have answers, in the same way nobody knew how to replace Steve Jobs so that Apple would still innovate… Below, I will quote the authors a lot. I begin first with a brief synthesis of which you will find the elements again later. Basically, the authors could have titled their book Innovation in the XXIst Century (by reference to Piketty’s extraordinary work on capital). Their work probably has the same ambition but may not have had the same means.
– Chapters 3 to 6 describe the reasons why innovation has slowed down, dedicated to capital, managerialism, globalization and regulation respectively.
– Chapter 8 – Capitalism and Robots – is one of the most interesting and I feel much closer to the authors here: “Should we prepare for a technological blitz? The troubling reality is that we should fear an innovation famine rather than an innovation feast.”
– Chapter 9 – The Future and How to Prevent It – is a convincing conclusion, although it is slightly disappointing. Analysis is one thing. The recommendations are much more difficult. I cannot help but feel embarrassed about the main argument that more liberalism will improve the situation. But the richness of the analysis makes this book an unavoidable reading (even if it is demanding …)
Their final recommendation summarize in: “To spark new life in capitalism, attention must be given to, first, severing the link between gray capital and corporate ownership; second, giving competition a real boost; and third, nurturing a culture of dissent and eccentricity.”

Now my usual way of commenting, i.e. by quoting:

[Pages 10-11] In Germany’s DAX30 index of leading companies, only two were founded after 1970. In France’s CAC40 there is only one. In Sweden, 30 of the 50 biggest companies were created before the start of World War I in 1914 and the remaining 20 were founded prior to 1970. If you compile a list of Europe’s 100 most valuable companies, none were actually created in the past 40 years. America is different, but less different from Europe than it used to be.

Their initial analysis [page 16]: The four factors that have made Western capitalism dull and hidebound are gray capital, corporate managerialism, globalization, and complex regulation.

Chapter 2 – When Capitalism became Middle-aged – describes the lack of investment (in innovation) and the slowing GDP growth. The authors show they are different reasons if you look at Italy, France, Germany or the USA.

[Page 29] Take the example of telecommunications. The telecom sector has expanded fast in the past three decades. But for that expansion to happen, companies and governments needed to invest in network infrastructure and other fixed capital – and that is exactly what they did. Likewise, to use these networks, companies and households had to lay out capital expenditures in buying telecommunications equipment like mobile phones and broadband routers. And that is exactly what they did. The telecom example, however, is not representative for entire Western economies. Business investment growth in Western economies is declining and does not follow the pattern you would expect from an economy moving in the direction of rapid innovation fast [productivity] growth.

[Page 33] Moreover, like the rest of society, the concept of “research” in the corporate sector has changed. While the image of corporate research still evokes places like AT&T’s Bell Labs (whose scholars have received eight Nobel Prizes) and Xerox’s Palo Alto research center (PARC), the reality is that a declining share of R&D budgets is spent on research.

[Page 34] Many companies have reacted to problems with their R&D strategy (some of which relate to increasing regulatory costs) by “outsourcing” their R&D to smaller firms that can take bigger risks. Once the R&D investments have begun to mature into innovative products, large companies have acquired them and integrated them into their sales and marketing infrastructure. Pharmaceuticals is one such sector. Time will tell if this strategy works or not. Perhaps it is efficient at the corporate level; perhaps it will destroy the innovation ethos.

[Page 38] Indeed, Studying 15 years of delistings, a group of economists showed that from 1997 to 2012, the US had 8327 delists, of which 4957 were due to mergers. (Cf my own post Cisco’s A&D)

I will not enter into much detail about Chapters 3-6 which describes the reasons why innovation has slowed, chapters dedicated respectively to gray capital, corporate managerialism, globalization, and regulation. Here are some interesting extracts though:

[Page 43] “Capitalists should not be the targets of the angry left or right. People with money and capitalists are not the same thing. […] The tenor of ownership in the capitalist system has changed profoundly, and not for the better. Big capitalists still exist, and some new ones have been minted too, especially in the digital sector. Yet the color of capitalism has turned gray.”

[Page 45] Where market and regulatory trends lead to far greater homogenization of investor behavior, the general profile of corporate ownership gradually comes to reflect broad macro trends and issues around systemic risks rather than the actual merits of a company and its future.

[Page 86] The authors criticize the common negative view about entrepreneurship, i.e. “today we talk about entrepreneurship versus bureaucracy. The entrepreneur represents all beauty in life. It represents progress, optimism and eternal success. The entrepreneur does not need to care about the rest of society. This constant talk about entrepreneurs is dangerous. We can’t afford many of them… The main part of industrial activity and societal maintenance is not built on so-called entrepreneurship.” Or is it?

[Page 89-90] The authors remind us of the difference between risk and uncertainty. Risks can be priced, for instance, just as is done in an insurance contract. […] Uncertainty however is different, in the sense that it cannot be contracted out, neither internally within a firm nor to the market. […] While companies have grown skilled at measuring and handling risks, they have crippled their ability to deal with uncertainty.

[Page 93] Performance tools are great for augmenting operational performance. There is nothing wrong with that aspiration or the tools themselves; all companies can perpetually need to improve, and using best practice is indisputably efficient. But apart from connecting measurements with actual improvements, the platoon of executives graduating from business schools came to believe that the tools were the answer to everything, including how a company should strategize for something new to make money in the future. While the recipe for corporate success cannot be found in a text-book, and not everyone is an entrepreneur just because they have read a book on entrepreneurship, the dominating notion was that strategizing for something new was almost equal to finessing costs by a few percent every year, gradually improving sales tactics, analyzing a key performance ratio here and adding another staffer there, and generally being opportunistic.

(I must quote Blank here again: Over the last decade we assumed that once we found repeatable methodologies 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. When page-layout programs came out with the Macintosh in 1984, everyone thought it was going to be the end of graphic artists and designers. “Now everyone can do design,” was the mantra. Users quickly learned how hard it was do design well and again hired professionals. The same thing happened with the first bit-mapped word processors. We didn’t get more or better authors. Instead we ended up with poorly written documents that looked like ransom notes. It may be we can increase the number of founders and entrepreneurial employees, with better tools, more money, and greater education. But it’s more likely that until we truly understand how to teach creativity, their numbers are limited. Not everyone is an artist, after all.”)

[Page 95] To look beyond what is quantifiable from current markets and aim for something new is pretty much the whole idea behind innovation. […] Before penicillin was invented, the market for it did not exist. Before the internet, the market for domain names or web designers was unknown. Before the automobile, who could calculate the return on investment in the car market?

[Page 105] Executive recruiters were not scouting for entrepreneurial people like Elon Musk or Mark Zuckerberg to take up key positions in multinationals. They wanted executives with specialisms in optimization, management, logistics, capital markets, and other key operative functions of a firm. […] And these partners were planners, not entrepreneurs.

[Page 107] Clearly, the era of globalization deserves a central place in future history textbooks. Markets were liberalized. Inflation was brought under control. New forces of productivity were unleashed, lowering the price of goods and raising real income.

[Page 110] Standing behind the fast growth had been, first and foremost, the expansion of emerging markets as sources and destinations of trade, especially China’s move into the global economy. The country’s share of global exports doubled between 1990 and 1996. And then it doubled again between 1996 and 2001, and doubled yet again between in 2001 and 2006. Since 2006, it has grown by just 50 percent. For China and other countries the development was extraordinary. In 2014, China’s GDP per capita was 13 times higher than in 1990, when measured in purchasing power.

[Page 119-121] Second-generation globalization could spur efficiency rather than contestable innovation. […] The patterns of competition emerging under the second-generation globalization period increasingly resembled so-called oligopolistic and monopolistic competition. In a nutshell, globalization enabled concentration and slowed innovation…

[Page 125] A start-up based on a new drug, chemical, battery, turbine technology, or toothbrush for that matter, will have to invest far more today than 20 years ago in order to get into the market and reach scale. It is not just that the price of entry has gone up, but that production is so tightly knitted and efficient that it is difficult to contest the market without stepping into one of the production networks. The more firms have tightened their boundaries, the more they have had to focus on repelling boarders and preventing intruders.

[Page 128-130] Specialized organizations are often better than less specialized organizations at accommodating incremental technological change and the results of investment in research and development with that profile. However, when inventions and discoveries challenge the profile of specialization and the boundaries of the prevailing economic organization, specialization often turns out into a cost. When that happens – as in the case of Nokia and Microsoft – specialization can actually become a factor of resistance to any innovation that disrupts and charts a different future than the one a firm has invested in. […] The high degree of specialization in today’s economy both spurs incremental innovation and slows down radical innovation. […] Technical complexity, social risk management (including lower tolerance for unintended consequences), diminishing returns, and talent challenges have all combined to raise the cost threshold of breakthrough innovation, even as downstream the costs of proliferation – reproducing, replicating, diffusing, disseminating, and indeed hacking innovation – have decreased. Big companies know this by heart. They learnt to navigate this landscape of innovation a long time ago – and thus lost their “Schumpetarian” dispositions.

[Page 146] The flip side of the coin is that the rate of knowledge obsolescence has increased. […] Economist Edwin Mansfield, a scholar of knowledge diffusion, found in a 1985 study of industrial technology that 70 percent of product innovations were known and understood by competitors 12 months after the innovation. That process now works much faster. In later studies, several economists have found the economic lifetime of patents to be much shorter than their duration. [For example…] half of the computer patents are worthless within ten years of their application date.

[Page 149] While there is much that speaks for the narrative of accelerating diffusion, […] the bigger the economic effect of an innovation, the more old capital needs to be retired to make space for the new technology and new capital. With declining levels of investment, the diffusion of new innovation has no necessarily accelerated in the past decade or had a greater economic impact than in the past.

Chapter 7 – Killing Frontier Innovation – claims that the precautionary principle is also killing innovation. The authors give examples about the use of Cadmium & Quantum Dots, about Genetically Modified organisms (GMOs) and their impact on BASF and Monsanto’s strategy, and about coolants in Mercedes Benz cars. It is also true that emerging self-driving cars have created new philosophical debates about “assignments of liability in the events of accidents” [Page 167].

I have to admit that it is a topic where I am not fully convinced by the authors. They give the feeling that innovators and experts should not be blocked by policy makers. With the risk of alienation from society and people… a tough topic. It is true that “uncertainty changes the composition of business investments and expenditure to the disadvantage of R&D and innovation.” [Page169]

But they also acknowledge that “in fact, sometimes innovation can be encouraged by regulation. [..] Take the example of US regulations enacted in the 1970s to lift the environmental standard of automobiles. Several scholars have found that these regulations prompted greater innovation activity among American automobile firms and that they had to shift the allocation of the R&D budget from D to R. […] However [they claim], there are limits to what regulation can achieve. […] Regulation that deters innovation tends to be more frequent in sectors that are important for pushing the technological frontier and that could lift productivity and economic growth” [Pages 170-72].

Chapter 8- Capitalism and Robots – is one of the most interesting one and I feel much closer to the authors here: “Should we prepare for a technological blitz? The troubling reality is that we should fear an innovation famine rather than an innovation feast. The thesis of a New Machine Age radically contradicts our view of stagnating economies, increasingly incapable of catering for their own future. Perhaps we are the old men out, but for us the thesis is a utopian rather than a dystopian vision of the future” [Page 179]. “Undoubtedly, many of the coming innovations in big data, the Internet of Things, machine intelligence, robotics, and more should be commended, yet they fail to impress, at least our technology-frustrated generation. […] We do not get around in flying cars. Nor do we have home fusion reactors. […] New knowledge does not automatically translate into innovation.” [Page 180]

Automation, like previous technological shifts, destroyed jobs, but it also created new ones, and much safer and better-paid jobs at that. […] Contemporary prophets of the New Machine Age make the same mistake. They judge the speed and quality of future innovation on the technological creation they see today, not on how the economy works. […] Intriguingly, they also seem to share the key economic gospels of previous eras of technology: fascination and fear. […] Finally they worry that employment opportunities will be destroyed in the wake of new innovations. […] they ignore two key features about radical innovation. For new technology to power fast-and-furious innovation there has to be, first, entrepreneurship, and second, a general economic dynamism that promotes the contestability of markets. [Page 184]

Innovation comes mainly from its adoption, not from its creation. […] In the example of the global warming, reductions of carbon emissions take longer because of costs and limits in quickly substituting new capital for old. […] Entrepreneurs control their own performance, but they cannot control unpredictable markets; if they could, business failures would be a matter of choice. Innovation based only on its own technological or corporate merits does not have the power to break intro markets. Markets are far too complex for that to happen. [Page 185]

The authors remind us of the recent failure of the Google Glass and also that Ericsson had presented a tablet (the Cordless Web Screen) in 2000. Or the slow evolution of electronic payments since the first plastic cards in 1959. “Tech failures are just one of the problems faced by new innovations. New technologies have to fight for a place in the market. […] The reason is market complexity. […] Think about the infrastructure and how long it took to create that. It is very difficult to change merchant behavior. No one knows how this market will evolve, but markets, competition and consumer behavior – not only the technology itself – will determine its future success. The same is true for another promising technology that can be applied to the payment markets: blockchain. […] Some have billed it as a greater technological leap than the internet for capital markets. Perhaps it will be, but the hype around the technology is premature and the expectation of big market changes is an aspiration.” [Page 187]

Markets are becoming increasingly complex because of vertical and horizontal specialization and a confluence of perpetual trial-and-error processes and generations of technologies, traditions, and customer values. [Page 188]

Don’t get us wrong: the passion of entrepreneurs is exactly why societies should appreciate and encourage them. If they were not, few new companies would make it past their first birthday. Passion is why they sacrifice time with family and friends or neglect private interests and put their money and reputation on the line. […] But the “hockey-stick world” is a fantasy. […] George Foster has analyzed 158,000 early companies and almost two thirds of them experienced one or more consecutive years of decline in the third to fifth year of existence. (Cf “Are Startups Really Jobs Engines?”) […] Markets are difficult to read, let alone manoeuver, even for skilled entrepreneurs. [Pages 189-90]

The proportion of firms less than a year old as a share of all firms in the American economy has steadily abated, from a level of approximately 16 percent, to slightly over 10 percent today. […] Only one-third of all firms were 11 or older in 1987, compared to nearly half of all firms in 2012. […] Entrepreneurship is also on an aging trend. […] In 1996, people aged between 20 and 30launched approximately 35 percent of all start-ups in America; in 2014, they only launched 18 percent of them. […] Around 3 percent of all firms qualified as high-growth companies in 1994-97, but in 2008-11 that share had been cut by half. True the latter period came amid a crisis-recovery cycle and it may be that declining business dynamism followed on the heels of the general downturn. However, that is not the lesson from history: crises, for sure tend to hit output and corporate size, but they also create good opportunities for new firms with the capacity to grow. [Pages 191-2]


And the authors go much further [Pages 195-6]: There is even more conclusive evidence against the hypothesis of discriminate dynamism. Investment in ICT equipment when measured as a share of GDP has been on the decline since the beginning of the millennium. […] Big claims require big evidence. And should make people doubt rather than accept the promise of fast-and-furious innovation is that it is thin in actual confirmation. […] The argument comes in three different instalments. First […] cyclical effects have hidden the structural shifts taking place in the Western economy. Second, there is a growing disconnect between recorded data and the real improvements. […] Third the decoupling of productivity and labor incomes prove the transformational change of technology.

But the authors dismiss the arguments. [Page 196-8] The cyclical effects have substantially weakened over time to become acyclical. Technology optimists like Brynjolfsson and McAfee would disagree, but [their] propositions do not stand up scrutiny. The second argument is more intriguing. But the problem of measuring innovation was settled a long time ago. The real debate should be about whether the problem has increased or decreased over time. […] Unfortunately, those who make the claim about the growing mismeasurement of innovation do not have much conclusive evidence supporting their thesis. […] The productivity slowdown has been universal for Western economies and it shows next to no variation when compared to ICT intensity in the economy. […] Moreover, if it were true that recorded economic output was significantly below the actual value, there would be at least one sector where that relationship did not hold – the sector that produces and services all the digital hardware and software. It is difficult to find evidence supporting that view. The growth in revenues and productivity is simply too small to account even a fraction of the mismeasurement.

[Page 201] Like so much else in the gospel of the New Machine Age, the criticism about productivity, real GDP and consumer surplus fails to appreciate other periods in history than our current time. It is as if the period of innovation is a recent phenomenon, something that merged via the internet.

Here a side comment, of interest only for those interested in start-up valuation, [page 200]: Such valuations rather reflect smart structures of financing. Equity investors are in the business of buying and selling company shares. And the price of a share is the result of both internal and external factors – such as capital market trends, regulatory frameworks, and substitute goods. To safeguard investments from the changing dynamics of markets, investors naturally protect themselves. Later investors (referring to investment stages) routinely use liquidation preferences to guarantee returns even if future liquidation valuations disappoint. Layers upon layers of liquidation preferences are virtually the norm and it helps drive private company valuation by allowing for investors to accept higher valuations. If expectations are not met, investors are still protected and get their money back before founders and employers. And it all looks good from the outside; it shows business strength and attracts employees, customers, partners and new investors. But many times it is a house of cards.

Technology and income – are they decoupling? Even there, the authors disagree with authors such as William Galston, Martin Ford or Brynjolfsson and McAfee again [page 202] adding there seems to be growing support for the proposition that productivity growth destroys jobs. [But] the thrust of serious analysis suggests that productivity growth does not decrease demand for labor and that the relationship between productivity and unemployment is trivial. Productivity growth, however, changes the composition of labor. Naturally, productivity growth and innovation can lead to capital substituting for labor, and it is generally acknowledged that economies have technological unemployment. […] but about the decoupling story: is that thesis more convincing? No, is the simple answer.

“Harvard economist Robert Lawrence has measured net output per hour and adjusted compensation with the same deflator, to allow for comparison over time, and comes to a sobering conclusion for the United States. All things taken together, the gap between productivity and compensation growth between 1970 and 2000 generally does support the thesis of a dramatic decoupling”. [Page 205]


But the authors again show the complexity of the causes, in Germany, in the USA, in the UK, in Sweden. “Three sectors explain about two-thirds of the falling share of labor income in the US manufacturing sector, and in all three sectors new technology tends to augment labor rather than capital. In other words, the marginal output of labor has gone up faster than the marginal product of capital.” [Page 206] In Sweden, “While income inequality has accelerated rapidly, the real cost of labor closely follows productivity.” [Page 207]

What is dramatic however is the long-term effect of lower productivity growth. White House economists, comparing various effects on pay from different sources of growth, suggest that if productivity growth between 1973 and 2013 had been the same as productivity growth prior to 1973, incomes would have been 58 percent (or 30,000) higher in the United States. By contrast, if income equality has stayed the same, incomes today would “only” be 18 percent (or $9,000) higher. [Page 207]

And what about the Foxconn legend! “In 2011 its Chief Executive Officer, Terry Gou, announced it was aiming for 1 million robots. […] Its 1.2 million workers assemble products for Apple, Sony, Nokia, Motorola, and others. The example of Foxconn became the smoking gun for believers in the New Machine Age. […] In early 2015, Gou was still on the offensive, claiming that 70 percent of assembly-line work would be automated within three years. […] later Gou’s story changed. In fact, after his bold announcement, Foxconn had not installed more than 50,000 “automated employees” well into 2015. That summer, Gou suddenly retracted his claim and blamed the media for having misunderstood the original announcement. Robots, he now claimed, would substitute for only 30 percent of Foxconn’s manpower – and it would happen in five, not three years. […] the jury is still out on Foxconn, but the chronicle of its robotization is revealing. [Pages 209-10]

And the authors add, “it is not technology we should worry about, but economic behavior determined or aided by regulatory uncertainty and corporate leaders whose lives are too focused on rentier returns.” [Page 214]

Chapter 9 – the Future and How to Prevent It – is a convincing even if slightly disappointing conclusion. Analysis is one thing. Recommendations are much more challenging. They convincingly use the BRIC acronym for a Bloody Ridiculous Investment Concept. They focus a lot on regulations as a critical blocking point. Regulatory uncertainty has three main sources: political leaders have become a very anxious species, occupied as much with the Twitter reaction to policy as with the quality of the policy itself. Second. Regulation has become much more prescriptive and less proscriptive.

As of their final recommendations:

– Severing the link between gray capital and corporate ownership
First action is needed to prevent investment institutions from draining companies of capital. […] One way to sever the link is to grant companies greater freedom to discriminate between owners by expanding the usage of dual class stock. […] Both google and Facebook have dual share structures, something that arguably helped to maintain a culture of innovation in those firms. A few days after Facebook’s initial public offering, founder mark Zuckerberg owned 18 percent of Facebook, but controlled 57 percent of the share-votes. The reason is obvious: maintaining entrepreneurial spirit. [Page 233]

– Boosting the contestability of markets
Greater competition should also help to speed up the exit of low productivity firms. […] In the US, for instance, there is greater variation in pay between firms than within firms. […] Related to that, market regulation has generally skewed the market, favoring older firms over new, leading to more consolidation of markets and higher entry barriers. [Page 235]

Take the example of Europe’s digital economy. Its size, growth, and contribution to GDP have been far less impressive than in other comparable economic regions like the United States. While Europe has a problem with fragmented markets in the field of digital services, a far bigger hindrance to growth is the highly regulated services sector that inhibits the diffusion of new digital technology from rippling through economies. […However ] past lessons of dynamics competition, especially in sectors where technology has driven competition, suggest that temporarily high market shares for some companies are beneficial. [Page 236] [Again a complex situation]

– Nurturing a culture of dissent and eccentricity
There is a final point to be made. Because it is more about culture than policy, it does not lend itself to a program of reforms. It concerns eccentricity, or the leeway given to these innovators and entrepreneurs who do not conform to the norm. And it is about dissent, and the freedom people enjoy to articulate and pursue their ideas. A culture of dissent and eccentricity is of great importance to innovation – and not just to invention or technology creation. For economies to be innovative, there has to be tolerance of the unknown and acceptance of experimentation. [Page 237]

After this too long presentation, I must end with two quotes, one famous and the other almost unknown. If you have arrived here, you have the right to ask me who are the authors…

Here’s to the crazy ones. The misfits. The rebels. The troublemakers. The round pegs in the square holes. The ones who see things differently. They’re not fond of rules. And they have no respect for the status quo. You can quote them, disagree with them, glorify or vilify them. About the only thing you can’t do is ignore them. Because they change things. They push the human race forward. While some may see them as the crazy ones, we see genius. Because the people who are crazy enough to think they can change the world, are the ones who do.

“Entrepreneurs are the revolutionaries of our time. Democracy works best when there is this kind of turbulence in the society, when those not well-off have a chance to climb the economic ladder by using brains, energy and skills to create new markets or serve existing markets better then their old competitors”

Obama and Silicon Valley, a common vision of the future?

Rarely have I read two articles giving a vision as close apparently of the challenges and issues of the future of the planet as I’ll mention in a moment. I say apparently, because behind some consistencies about a confident vision of the future, lie fairly fundamental differences about the challenges.

But I will allow myself a digression before commenting these tow articles. A third article was published on a very different subject in the paper edition the New Yorker dated Oct. 10, 2016 – again apparently as it deals about the past and the present! It is entitled He’s Back. This article reminded me that my two most important readings in 2016 (and perhaps in the 21st century) are those that I mentioned in the post Has the world gone crazy? Maybe…, namely the tremendous Capital in the 21st Century by Thomas Piketty and the no less remarkable In the disruption – How not to go crazy? by Bernard Stiegler. I need to give the title of the digital edition that might hopefully inspire you to discover Karl Marx, Yesterday and Today – The nineteenth-century philosopher’s ideas may help us to understand the economic and political inequality of our time.

Back to the point that motivates this post. Barack Obama has just published in The Economist a short text in which he describes the challenges ahead. This is a brilliant article. It also creates a certain mystery for me around the American president. Is he very well surrounded by knowledgeable advisors and / or has he become interested so deeply in topics to the point of finding the time to write (I should say to describe) himself the world’s complexity. An absolute must-read: The Way Ahead.


In comparison, Adding a Zero in the same Oct. 10 New Yorker – entitled in the electronic version Sam Altman’s Manifest Destiny with however an identical subtitle Is the head of Y Combinator fixing the world, or try trying to take over Silicon Valley? This very long article describes perfectly the reasons why we can equally love and hate Silicon Valley. It is a Pharmakon (both a remedy and a poison according Stiegler’s words). I encourage you to read it too, but your priority should go to reading Barack Obama.

I’ll try to explain myself. Obama has tried a lot and has not been so successful, but there has a consistency in his acts, I think. In The Economist, he wrote: “Fully restoring faith in an economy where hardworking Americans can get ahead requires addressing four major structural challenges: boosting productivity growth, combating rising inequality, ensuring that everyone who wants a job can get one and building a resilient economy that’s primed for future growth.” Obama is an optimist and a moderate. All but a revolutionary. There is a beautiful sentence in the middle of the article: “The presidency is a relay race, requiring each of us to do our part to bring the country closer to its highest aspirations.” The highest aspirations. I sincerely believe that is why Obama deserved the Nobel Peace Prize despite all the difficulties of his task.

Silicon Valley has the same optimism and the same belief in technological progress and well-being that it brings (or may bring). Growth is a mantra. Sam Altman is no exception to the rule. Here are some examples: “We had limited our projected revenue to thirty million dollars,” Chesky [the founder and CEO of Airbnb] said. “Sam said, ‘Take all the “M”s and make them “B”s.’ ” Altman recalls telling them, “Either you don’t believe everything you said in the rest of the deck, or you’re ashamed, or I can’t do math.” [Page 71] then a little further “It is one of the rarer mistakes to make, trying to be too lean,” Altman said, “Don’t worry about a competitor until they’re beating you in the market,” … “Competitors are one of the last monsters that haunt your dreams.”… “Always think about adding one more zero to whatever you’re doing, but never think beyond that.” [Page 75]

161010_r28829-863x1200-1475089022 Illustration by R. Kikuo Johnson

Clearly risk taking steps accordingly: In a class that Altman taught at Stanford in 2014, he remarked that the formula for estimating a startup’s chance of success is “something like Idea times Product times Execution times Team times Luck, where Luck is a random number between zero and ten thousand.” [Page 70] The strategy of accelerators such as Y Combinator looks pretty simple: “What we ask of startups is very simple but very hard to do. One, make something people want”—a phrase of Graham’s, which is emblazoned on gray T-shirts for the founders—“and, two, all you should be doing is talking to your customers and building stuff.” [Page 73] The result of this strategy lies in the performance of these acceleration mechanisms: A 2012 study of North American accelerators found that almost half of them had failed to produce a single startup that went on to raise venture funding. While a few accelerators, such as Tech Stars and 500 Startups, have a handful of alumni worth hundreds of millions of dollars, Y Combinator has graduates worth at least a billion—and it has eleven of them. [Page 71] but Altman is dissatisfied: Venture capitalists believe that their returns follow a “power law,” by which ninety per cent of their profits come from one or two companies. This means that they secretly hope the other startups in their portfolio fail fast, rather than staggering onward as resource-consuming “zombies.” Altman pointed out that only a fifth of YC companies have failed, and said, “We should be taking crazier risks, so that our failure rate would be as high as ninety per cent. [Page 83]

“Under Sam, the level of YC’s ambition has gone up 10x.” Paul Graham, who was leaving soon after the dinner for a sabbatical year in England, told me that Altman, by precipitating progress in “curing cancer, fusion, supersonic airliners, A.I.,” was trying to comprehensively revise the way we live: “I think his goal is to make the whole future.” [Page 70] Recently, YC began planning a pilot project to test the feasibility of building its own experimental city. It would lie somewhere in America, or perhaps abroad, and would be optimized for technological solutions: it might, for instance, permit only self-driving cars. “It could be a college town built out of YC, the university of the future,” Altman said. “A hundred thousand acres, fifty to a hundred thousand residents. We crowdfund the infrastructure and establish a new and affordable way of living around concepts like ‘No one can ever make money off of real estate.’ ” He emphasized that it was just an idea—but he was already looking at potential sites. You could imagine this metropolis as an exemplary post-human city-state, run on A.I. — a twenty-first-century Athens — or as a gated community for the élite, a fortress against the coming chaos. [Page 83] YC’s optimism goes very far: “We’re good at screening out assholes,” Graham told me. “In fact, we’re better at screening out assholes than losers. […] Graham wrote an essay, “Mean People Fail,” in which—ignoring such possible counterexamples as Jeff Bezos and Larry Ellison—he declared that “being mean makes you stupid” and discourages good people from working for you. Thus, in startups, “people with a desire to improve the world have a natural advantage.” Win-win. [Page 73]

Altman is not devoid of social conscience, well not quite. “If you believe that all human lives are equally valuable, and you also believe that 99.5 per cent of lives will take place in the future, we should spend all our time thinking about the future.” [He looks at] the consequences of innovation as a systems question. The immediate challenge is that computers could put most of us out of work. Altman’s fix is YC Research’s Basic Income project, a five-year study, scheduled to begin in 2017, of an old idea that’s suddenly in vogue: giving everyone enough money to live on. … YC will give as many as a thousand people in Oakland an annual sum, probably between twelve thousand and twenty-four thousand dollars. [Page 81] But the conclusion of the article is perhaps the most important sentence of the whole article, which brings us back to Obama’s moderation. Comparing himself to another wildly ambitious project creator, Altman says, “At the end of his life, he did also say that it should all be sunk to the bottom of the ocean. There’s something worth thinking about in there.”

Ultimately, Obama, Altman, Marx, Piketty and Stiegler all have the same faith in the future and progress and the same concern about the growing inequalities. Altman seems to be the only one (together with many people in Silicon Valley) to believe that disruptions and revolutions will solve everything, while the others see their destructive features and prefer a moderate and progressive evolution. Over the years, I tend to prefer moderation too…

PS: if you would not have enough reading, then continue with the series of interviews President Obama gave to Wired: Now Is the Greatest Time to Be Alive.

Discovering bitcoin and Blockchain

I do not remember when I heard of bitcoin for the first time. Blockchain (see the wikipedia page on the subject), the technology that has allowed the bitcoin “currency”, is something I did not know in 2015. I just remember discussions a few months ago with a colleague from INRIA who had explained the main lines of this innovation. As I wanted to know more I bought recently three books about this, including two that I just finished.

Bitcoin et Blockchain. Vers un nouveau paradigme de la confiance numérique ? (Bitcoin and Blockchain. Towards a new paradigm in digital trust?)

This short book (in French) of 126 pages is an excellent introduction to the subject (a little expensive though). I especially noticed the functions of money, namely: a medium of exchange, a store of value and a measure of value. And everyone knows that “a currency is characterized by the confidence of its users in its enduring value and its ability to serve as means of exchange” (wikipedia). But beyond the bitcoin, the Blockchain is a pretty exciting technology that has the potential to revolutionize the way we achieve a large number of transactions. The main idea is that a trusted third party can be replaced by the Blockchain for all types of contracts such as deeds, land registry, copyright management or simple rentals with Airbnb.Now, when I look at the volatility of bitcoin, I am not sure it is a currency yet…

Digital Gold – The Untold Story of Bitcoin
The book by Nathaniel Popper is a real thriller. It is your choice about how to approach this new thing! I would advise the curious reader a dual approach. A serious book to understand the issues and a more entertaining book for the history. Certainly I’m sure Wikipedia provides everything you need but Popper has a real writing talent. A real page-turner.

Here are some photographs of characters behind this story (because I have the impression that the story is just beginning).

A few pioneers, from left to right: Hal Finney, Gavin Andresen, Martti Malmi, no picture of the mysterious Satoshi Nakamoto, some have suspected that it was Craig Wright and others Nick Szabo.
A few entrepreneurs: Jed McCaleb, Mark Karpelès, Erik Voorhees, Charlie Shrem,
Ross Ulbricht, Wences Casares.

A few investors: Roger Ver, Tyler & Cameron Winklevoss, David Marcus, Reid Hoffman, Marc Andreessen.

At the trivia question of who invented Bitcoin, the author quotes Erik Voorhees: Erik’s pet theory was that Satoshi was actually a small circle of programmers at some major tech firm, who had been assigned by their company to come up with a new form of online money. When the project had come back and was deemed too dangerous by the higher-ups the creators decided to put it out anonymously – they “felt really strongly that this was something important they discovered and went rogue with it,” Erik explained, even while noting, with a laugh, that he had no actual evidence to back up his hypothesis.

What is more amazing with the short history of bitcoin is the rather incongruous combination of personalities gathered here. Some will end their lives in prison, others were stars of Silicon Valley long before the emergence of this technology. I think no one today can say whether bitcoin will end up in the dustbin of history or whether it will have the same impact as the Internet. And I’ll bet neither to one nor the other …

The 3rd book I bought is The Age of Crytocurrency. But this might be for another post.

Has the world gone crazy? Maybe…

I wanted to write this article the day after July 14 and the tragic events in Nice. But it took me a little longer. Start-ups, Innovation are above all a passion for me, a topic that fascinates me. I see many reasons for optimism and hope for humankind and for the planet as a whole. But for any positive pole, there is a negative one. And any optimistic analysis of a complex topic always induces its pessimistic viewpoints. The point is not to provide a “simplistic” opposition to innovation and entrepreneurial creativity, but to mention here some works which demonstrate, by their depth, the complexity of the subject.

The simplest, and probably the least interesting of the three controversial analyses I will present here comes from the United States. Two MIT researchers, Erik Brynjolfsson and Andrew McAfee, explain the risk of automation that are created by science and information and communication technologies (ICT). In Race Against The Machine followed by The Second Machine Age, they show that many jobs will necessarily disappear with the development of ICT. All technological advances have created such risks (printing, the steam engine, electricity) but it seems that ICT is of much higher dimension, with the “fantasy” of transhumanism, which suggests that humans could be totally replaced by the machine.


The book is an excellent introduction to the challenges the world will meet and let me quote. The chapter Beyond GDP begins with a quote of Robert Kennedy: “The Gross National Product does not include the beauty of our poetry or the intelligence of our public debate. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion. It measures everything, in short, except that which makes life worthwhile.” I know that these books were best-sellers in the US, probably because they ask interesting questions. But I must say that I found the analysis a little light with nor facts and figures compared to the two books that I will write about now.


Capital in the 21st Century by Thomas Piketty is one of the most impressive books I have ever read. I will not give my summary here, and I encourage you to read the wikipedia page or slides from its website, if you do not have the courage to read some 900 pages! But again this is an absolutely remarkable book which the following 4 figures will further encourage you in trying…


Piketty shows that capitalism has reached its limits probably due to unregulated globalization but more importantly because the growth of the planet will probably not be anymore what it was during the post-war boom. Piketty is quite close to the theses of Erik Brynjolfsson and Andrew McAfee, but he seems to me much more convincing about the causes, effects and remedies. Bernard Stiegler wrote a strange book, In the disruption – How not to go crazy? (In French only so far, but many of his books have been translated) This is a very difficult book to read, closer to philosophy and psychology, but behind the difficulty, what a fascinating analysis, rich and also taking into account the complexity of the world. If you fear the demanding reading, you can listen Stiegler (in French only )in a series of 15 one-hour epiosed produced by Radio Suisse Romande in June 2016: see the web site of Histoire Vivante that is devoted to the work of Ars Industrialis. The main thesis of Stiegler is that capitalism has gone crazy and that the absence of regulation can lead you to madness. The “disruption” can be good when it is followed by a stabilization phase. And as serious as the economic analysis of Piketty, Stiegler undoubtedly explains why people become crazy to the point of causing events like in Nice.


Challenges and Opportunities of Industry 4.0

I must say that last week I did not understand very well the “Industry 4.0” concept. And after a brief stay in Munich this week – where I had an explanation by E&Y – see below – but especially after reading the text of a speech entitled “Smart Industry 4.0 in Switzerland” (see pdf) given by Matthias Kaiserswerth, the “Business and Innovation Forum Slovakia – Switzerland” in Bratislava on June 20, I fully understood the importance of the subject. I also found out this morning two excellent reports: “Industry 4.0 – The role of Switzerland Within a European manufacturing revolution” (see pdf) by the firm Roland Berger and the “Digital Vortex – How Digital Disruption Is Redefining Industries’ (see pdf) published by Cisco and IMD. I got permission from Matthias Kaiserswerth to publish his speech here (I thank him for this) and this speech is an excellent introduction to the subject with many interesting ideas to solve the challenges ahead…

Smart Industry 4.0 in Switzerland

Matthias Kaiserswerth, Business and Innovation Forum Slovakia – Switzerland, 20.06.2016, Bratislava

In this brief input speech, I want to talk about some of the challenges and opportunities that the on-going digitalization has for the Swiss economy, our labor force and the education system.

Current State and Challenges

Unfortunately, Switzerland is not yet a leader in digitalization. When we compare ourselves with other OECD countries, we play at best in the middle field. From a policy point of view, we are behind the European Union. This month, June 7, our Ständerat, the smaller parliamentary chamber representing the cantons, has asked our government to analyze what economic effect the emerging EU single digital market will have on our country. Our current president, the minister for economy, education, and research in his response admitted that until the beginning of this year Switzerland had underestimated the 4th industrial revolution and now is trying to catch up with various measures[1].

ICTSwitzerland, the association of the Swiss ICT industry, earlier this year launched a scorecard [2] in which they rate Switzerland’s state of digitalization in 15 dimensions. While we have excellent basic infrastructure and rank highly on a generic international competitive index, we don’t yet sufficiently leverage digital technologies in the various sectors of our economy.


The scorecard reflects a classic Swiss paradox. Because of our very direct democratic system, built on subsidiarity, we provide good infrastructure and general economic framework. When it comes to leveraging these foundations, we leave it to private initiative as we don’t pursue an active industrial policy – certainly not at the federal level. So far our companies – mostly SMBs, 99.96% of our companies have less than 250 employees – have excelled at incremental innovation. Incremental innovation can be good for a long time, but it impedes dealing with major technology shifts that can disrupt an entire industry.

This happened in the 70s and early 80s when the “Quartz Revolution” almost extinguished Swiss watchmaking. Now again history may repeat itself as the watch industry missed or were too slow to embrace the trend towards smartwatches. Apple within the course of only one year managed to surpass with their watch-related revenues all Swiss watch companies even Rolex [3].

With the digital revolution, driven out of Silicon Valley, we compete with an entirely different innovation model, namely disruptive innovation.

Just look at examples from the sharing economy such as Airbnb and Uber.

But it doesn’t stop there. Consider computer companies now building the future self-driving electric car – Google being a prime example. While European OEMs had experimented for a long time with self-driving cars putting all the intelligence into the car, Google took an entirely different approach. Because of their maps, their work with Streetview, they already have very precise information about where the car is going and thus can leverage the power of connectivity and the cloud as well.

While we would strive to build the perfect battery for an electric car, Tesla took what we would consider inferior laptop batteries and leveraged IT to make them useful in their cars.


With the long Swiss tradition of bringing foreign talents into the country and allowing them to succeed, we have an outstanding opportunity not to miss out on the current industrial revolution. Many of our successful international companies got started by foreigners – just think of Nestle, ABB, or Swatch.

Businesses have now realized that meeting the pressures of the strong Swiss Franc with only cutting costs is insufficient. They are looking for different forms of innovation leveraging IT. About a year ago, various Swiss industry associations launched an initiative “Industry 2025” to change the mindset in our machine industry and alert them to the new opportunities [4].

Some companies though have seen these chances already long before our national bank stopped pegging the Swiss Franc to the Euro.

For example in 2012, Belimo a company producing actuator solutions to control heating, ventilation and air conditioning systems launched their “Energy Valve”. It consists of a 2-way characterized control valve, volumetric flow meter, temperature sensors and an actuator with integrated logic, that combines the five functions of measuring, controlling, balancing, shutting and monitoring energy into a single unit with its own web server as IT interface. The intelligent valve can be used to optimize water flow in heating and cooling systems and yields significant energy savings for its customers [5].

Other companies in the Swiss machine industry have started to think about how they can leverage Internet of Things (IoT) to create new businesses based on the data that their machines generate. A good example is LCA Automation, a company in the business of building factory automation solutions. They want to offer predictive maintenance based on dynamic condition monitoring of their installed factories. Leveraging existing information like current and position from frequency converters in their drives help understand how the machines are used. In select cases they install additional sensors to measure vibration, acoustic noise to allow their clients to schedule maintenance instead of running their installations to failure [6].

In my opinion, the challenges in addressing more of these opportunities are (1) cultural, (2) an IT skills gap, (3) finding and realizing new business models that best exploit the digital opportunity and finally (4) creating an environment where collaboration with external partners can let you innovate with speed.

Contrary to software, industrial products cannot be easily updated in the field, they are engineered to last 10 to 20 years. The mindset of the computer scientist: “we can fix it remotely with an update,” requires the mechanical and electrical engineers to rethink how they construct their systems. When Tesla had issues in 2013 with one of their cars catching fire because its suspension at high speeds lowered the car too close to the road, they did not issue a massive recall but instead remotely overnight changed the software in the cars to guarantee a higher distance between car and road.

Getting these diverse cultures to collaborate requires respect among the different professional disciplines and would call for the occasional computer scientist to serve on the board of industrial companies to challenge their established way of thinking.

The skills gap, finding enough software engineers interested to work in industrial companies is significant. Current predictions are that by 2022 Switzerland will lack 30’000 IT experts. Considering that industrial companies compete with the better paying finance industry for the same talents, means that industrial companies need to become very creative to address this shortage.

Implementing new business models that exploit the digital opportunities is a significant challenge for established industrial companies. If a company whose core business is selling industrial machines, wants to start offering value added subscription based services to optimize the industrial process realized by their products, they get into an entirely new business. They will need to decide whether these services are only available for a process realized by only their machines or whether they want to offer it also on competitors’ installations. They need to devise a new sales incentive scheme based on a recurring revenue stream. They need to build a support infrastructure that matches the optimized process and no longer consists of experts that only know about their own machine. In short, they need to build an entirely new business. Doing so inside an established large company is extremely hard maybe even more so than doing it in an external startup.

Finally, creating a collaborative environment with external partners to innovate with speed is not something unique to the age of digitalization, however it will be key for industrial companies to capture the opportunity. In spite of the good examples from large industrial companies like Procter and Gamble around Open Innovation, a concept coined 13 years ago, many firms still have a strong sentiment of doing everything themselves or with their established supply chain partners. In the case of digitalization, however, new partners from outside the traditional industry need to be involved and made part of the solution. “Rather than using their own R&D budget, enterprises can leverage venture capitalist investments and integrate a technology solution in an accelerated timeframe” [7].


Before I close, let me get back to education, a topic of particular importance in this new era. Switzerland has an excellent education system. However, we have a significant shortage of students that pursue a career in the Science Technology Engineering and Mathematics field (in short STEM) in addition to a skills gap in STEM for all the other students.

In 2014, the German speaking cantons launched a new common competence oriented curriculum “Lehrplan 21” (LP21) to address the skills gap by putting more focus on STEM subjects. For example, by introducing a new subject called Media and Informatics, the cantonal education ministers have accepted the notion that all students need basic skills in computer science to succeed in the professional or academic education system. As we speak, this LP21 is being implemented in the German speaking part of Switzerland, albeit not fast enough for my taste.

To succeed with LP21 we also need to qualify the teachers to competently teach these subjects in a way that keeps all students motivated. Specifically female students have a significantly lower self-perception in how they master technology and what they can use technology for [8]. The consequence is that we lose the female talent also in our workforce. So for example, in IT there are only 13% women in the Swiss workforce.

Promoting women in technology as role models and broadening specific programs to get girls interested in technology at a primary school age will hopefully help to bridge the gender gap in the long run.


When we look at the system of the Federal Polytechnic Schools (ETH Zurich and EPF Lausanne), the universities and specifically also the universities of applied science, government funding for research then we have an outstanding foundation upon which we can build to effectively compete in this 4th Industrial Revolution. It now requires a new mind set for our industrial companies to embrace the emerging IoT, Big Data, and artificial intelligence trends and the courage to experiment with the new business models that they enable.

You don’t get disrupted because you don’t see the technological shift and opportunity, you get disrupted because you chose to ignore it.


Postscript: I mentioned above the presentation by E&Y, here is the slide that struck me…

The crazy ones. The misfits. The rebels. The troublemakers.

How is possible I never used this great quote when I talk about what is needed in innovation and entrepreneurship. What a moron, I am (sometimes…)

Here’s to the crazy ones. The misfits. The rebels. The troublemakers. The round pegs in the square holes. The ones who see things differently. They’re not fond of rules. And they have no respect for the status quo. You can quote them, disagree with them, glorify or vilify them. About the only thing you can’t do is ignore them. Because they change things. They push the human race forward. While some may see them as the crazy ones, we see genius. Because the people who are crazy enough to think they can change the world, are the ones who do.

Of course it’s very likely that you know what this is. And if not, no worry either. Here is the video:

And if you want to know more, check Think_different on Wikipedia.

Listen to the other voice too:

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.