Not a single thing can save us. But a mix of all things might.

There is a wide consensus on humanity facing, in the coming decades, its toughest existential challenge since it emerged from the rain forest as a relatively feeble species, whose chances of survival in the savannah were slim “in the eye of the tiger”. It is not the first time. During the neolithic agricultural revolution, human population went through a first exponential growth (from a few millions to a few hundreds of millions) coupled with a serious deterioration of its average health due to the close proximity with herds of domesticated animals. That deterioration culminated in the 14th century’s Black Plague, which mauled the world population from an estimated 450 million to 350 million. As bad as it was then, the challenge is even more daunting now: with a second exponential growth, kick-started by the industrial revolution 250 years ago or so, humanity is facing the prospect of earth resources being grossly insufficient to support the 10-12bn humans that should populate the planet by the end of the century. 

To address this much bigger challenge, I hear, unfortunately, too much strident advocacy of too many simplistic approaches.

Making choices can give the illusion that decisions are being made

“To choose is to rely on rational criteria as a springboard for action. To decide is to make up for the scantiness of those criteria by exercising one’s freedom. To choose is to know before acting. To decide is to act before knowing.” – Charles Pépin.

Big corporations are good at choosing. They have data, analysts and, to some extent, time. They can benchmark, rank and review before “making a decision”. But, using Charles Pepin’s distinction, it turns out that corporations, in most cases, don’t make a decision; they make a choice. Armed with Value Investment Ratios, cost/benefit and risk/reward analysis, they choose which innovation project to invest into, and which not. And how do they estimate the Value Investment Ratios, the cost/benefit and the risk/reward balance? By tapping into market, cost, sales, profitability data they extract from similar projects that they, or their competitors, have been been running. These prior projects are of course different, but not so different that meaningful assumptions cannot be inferred from them. By definition, this approach leaves the corporation squarely in the tactical innovation space. 

How Entrepreneurial is your Intrapreneurship Program?

Corporation are all for innovation, business development, staff engagement. When senior executives look outside their traditional ecosystem, they see entrepreneurs – tech or otherwise – who are threatening to disrupt the market. These entrepreneurs have often launched a seemingly simple innovation, developed their business at a rate that corporations can only dream of – unless they are being disrupted by it and the dream turns out to be a nightmare – and they deliver sleek TED-talks that are so refreshing and engaging compared with boardroom endless powerpoint meetings. When they listen inside their organisations, executives hear from energetic millennials – and some older but no less energetic employees – who are enjoying the security that the big corporation brings but cannot be content with their salami-slice jobs, dreaming instead of their own startup launch. Connecting the dots, it is no wonder that executives want to foster an entrepreneurship spirit in their own organisations.

Enters the intrapreneurship program.

We’ve only seen the Impressionist debuts of the Internet of Things

Visiting the post-impressionist gallery on the 2nd floor of Musée d’Orsay in Paris, I realized how rapidly painting in the late 19th century evolved. 

However revolutionary it may have been, Impressionism was superceded fairly quickly. It rocked the boat in the 1860s, gained prominence in the 1870s, exhibiting 12 times between 1874 and 1886 in the Salon des Refusés (literally, the Exhibition of the Rejected), but by the end of the 1880s radically new styles and techniques were already emerging:

Three innovation metaphors from Jardin des Plantes in Paris

On a quiet Sunday afternoon, I roam the gardens and exhibition halls of Jardin des Plantes in Paris. In the glasshouses, I stumble on three statements about the evolution of ancient forests and life in today’s ones, which instantly resound in my ears as three innovation metaphors.

1. As plants first emerged from the sea in the Silurian and Devonian periods (440 to 350 million years ago) and started to spread on land, which by definition was desert at the time, they had to develop a strategy to resist the over exposure to sun and heat, and avoid dessication. Such strategy consisted in the development of:

Nature v Norm – How language drives innovation culture

There are moments when you connect unexpected dots and some new level of understanding clicks. Last week I was enjoying the park at Vaux-le-Vicomte designed by 17th century master of gardens ‘à la française’ André Le Nôtre, who went on to design gardens at Versailles and many other places throughout France and Europe. Le Nôtre’s vision of nature is one that is domesticated, made to fit a pattern, where seasons and distance are mastered, the latter through the use of perspective tricks, the former through the use of evergreen plants. Today, listening to a Modern Language professor at the University of Southampton, I picked this insight that a good behaviour referred to as ‘natural’ in English will be called ‘normal’ in French, a language subtlety that underpins deeper differences in the English and French ways of thinking.

Science paradigm-shifts for dummies

In his landmark book The Structure of Scientific Revolutions, Thomas S. Kuhn describes how science progresses through phases of continuous improvement in-between paradigm shifts.

An emerging scientific paradigm (which can be referred to as a theory or a model) can be compared to a net which is just good enough to hold a few large pieces of evidence that have been observed – but so far not grasped – by the scientific community. At the risk of overworking the metaphor, picture a net-bag holding Newton’s apple: as a bag, it is rather unsophisticated, but it is good enough to catch the apple as it falls. If it also manages to catch a few other pieces of fruit, the bag becomes effective and consistent enough in the eyes of the scientific community, that everyone adopts it as THE bag that will enable them to grasp ANY piece of fruit. A paradigm is born and everyone believes in its abiliy to explain the whole world.

Measuring the ROI of R&D is illusory, but shortcutting Prototyping & Scaling-up will destroy it

What is the Return On Investment (ROI) of R&D? The question regularly resurfaces but never seems to get a satisfactory answer. Here are two insights, one which explains why we cannot get a proper answer, the other what we can do to avoid destroying the ROI.

Insight 1. Samsung’s rule of thumb for R&D investment is: when spending $1 on R&D, they spend $4 on prototyping & scaling-up. Since all that follows R&D is necessary for the output of R&D to get to market and start generating a return, it becomes clear that the $1 investment in R&D has to be seen in combination with the $4 investment in ‘the rest’. So, calculating a return on the $1+$4 investment makes sense, but calculating a return purely on the $1 investment doesn’t.