Paul Saffo’s talk at the Long Now Foundation (MP3 here) is a very good overview of foresight research heuristics/rules of thumbs/methods. Some notes:

• “Hunt of Bin Laden, experts agree, Al Qaeda leader is dead or alive” is a great forecast because it accurately captures the uncertainty of the moment. The biggest mistake is to be more certain than what the fact suggest, especially today, at this very uncertain moment in time (where indicators are going in different directions). As Peter Schwarz says: “The difference between a good forecast and reality is…a good forecast has to be believable and internally consistent”
• The job is not about predicting but rather mapping the “cone of uncertainty” on a subject. And, uncertainty means opportunity. It’s a cone shape for commonsensical reasons and because uncertainty expands as you project further into the future. The important thing is to find edges: Where might they happen? There you should look for wild-cards to define the boundaries and science-fiction can be a good candidate for that matter (as well as bad press about the future).
• Change is not linear and very slow and most big technological changes take 20 years to develop (”new technologies take 20 years to have an overnight success”). This means that you need good backsight, BUT because evolution is slow, you still have time even if you miss an early indicator.
• Look then for early indicators (”prodromes” or “prodroma”: an early symptom or leading indicator) as claimed by William Gibson’s observation that the “future is already here, it’s just not unevenly distributed”. Look for indicators and things that don’t fit.
• We tend to over-estimate the speed of short-term adoption and under-estimate the diffusion of the technology (”Never mistake a clear view for a short distance”). In addition, things aren’t accelerating and every society has always complained that things were getting faster, even in the 16th century (”every generation thinks things are accelerating”).
• Look at failures and cherish them (Preferably other people’s). Silicon Valley has been built on the ashes of failure. Look also for people who failed in a company and went starting their own.
• Prove yourself wrong: look for indicators that proves what you say BUT also weak signals that prove it wrong
• “Be indifferent. Don’t confuse the desired with the likely”
• Know when not to make a forecast
• The problem for forecasters is not of being wrong, it about persuading people to act on forecasts.

It’s often when reading obscure and never translated european writers that I find the most intriguing ideas, especially when it comes to foresight and innovation. The book “Les sens de la Technique” by Victor Scardigli is no exception to this; the title is a sort of pun since “sens” in french means both “meaning” and “direction”. Thus you can read the title as “The Meaning of Technique” or “Where Technique is heading”, which reveals the ambivalence of technical innovation. What’s intriguing here is that the author, for once, do not distinguish “techniques” and “technologies”, rather taking techniques as a whole that encompass vaccines or ICTs.

Above all, the book is above the gap between the expectations our societies put into innovation AND the weak consequences of the first change we can notice. After inventions and R&D processes, innovation is expected by some (especially the inventors) to diffuse in society and “impact it” (for best or for worse). Different rationales are at stake here since engineers or biologists expect Sciences to serve Progress, the reciprocal adaption of human beings and techniques and hence measure the “social impact” of their invention. On the other hands, social scientists often more convinced by the prominence of human causalities are more skeptical and think that new techniques are only tools to modify the course of time based on their own objectives.

The author then addresses how techniques and their usage evolve over time, for which he describes 3 phases in his “diffusion model” using a raft of interesting examples that I won’t describe here:

1. Phase 1: The “time of prophecy and fantasy” (enthusiastic or terrifying) where revolutions are predicted and technique is “inserted socially” (right after invention and R&D). It’s mostly the time of positivists and the moment where imaginary symbols are constituted. The less objective fact you have, the more imaginary you get, so irrational thoughts are important here. Prophecies (or social actors who promote them) attempt to create a connection between 3 elements: the new technical object, human desire and expectations/fear of the time being. This leads to imaginary representations that you can find in the discourse of companies promoting the innovation, surveys or advertising/media messages. For Scardigli, there are of course constant imaginary issues: power on constraints (liberty of slavery), knowledge, fear of death, social justice, social bounds, economical wealth and global solidarity. There is therefore a discourse around the hopes and fears linked to these issues which are recurring in history. What happen is that fantasy, scientific knowledge and actions are intertwined and even the weakest signal is turned into an excessive hope or fear. Prophecies become necessities and then self-justificated.
2. Phase 2: The “delusion phase” that suggest how the expected technological revolution does not lead to a social revolution. Positivists’ prominence is obscured by skeptical voices who raise the gap between forecasts and realizations/effects. They also reveal how “techniques” themselves are not sufficient to change “society”. To some extent, observers realize that science only make progress… in science. It’s of course the time where “users/people” enter the scene and begin employing the technique. These small actors transform, invent new uses, hack or tweak the innovation. This appropriation and reinvention of daily life leads to a third phase.
3. Phase 3: “the side-effect phase”: 30 or 40 years after, the real diffusion of the technique is effective and some social and more long term consequences appear but often different from the one expected at first (new social form, new forms of cultures or human activities). He cites an example of a sort of bulletin-board system in the 80s in French that was expected to revive surburbian communities. What happened is that technology vanished (the state program was stopped) but it allowed people to gather, meet and create “mediating” organizations that survived. In the end, the collective imaginary of progress from the 1st phase is articulated with the strategy of actors who promote the innovation. Social change appear as a side-effect of the technical innovation, not because of it. The introduction of the innovation acts as a “analyser” revealing problems, social dynamic, aspirations, needs and above all as an alibi for new forms of sociality. And at the end of the road, it’s end-users themselves who give sense to techniques by integrating to their daily life/culture.

Also Scardigli raises the importance of the socio-cultural context of innovation, who often fail without it. He exemplify this with a description of “mediating” persons who are social actors who can promote technologies and make people understand how it will be of interest for their purposes/life. In addition, there is of course a compromise between the Ideal of the project and the economic/user realism. If what happen in the 3rd phase is different than what was expected in the first one, it’s because big actors (States, companies) are struggling with each others with different visions BUT also because small actors (users!) modify, change, tweak or slow down the unfolding of these innovation.

Finally, in his conclusion, he discusses some lessons about progress and innovation:

• Human beings build their own history, sometimes by designing new techniques but often with other means (e.g. organizational). And it’s not these techniques that will change or social and daily life.
• These innovation effort are always carried out over and over, as a sort of Sisyphean curse because new techniques have to articulate both Science (who likes to “discover”) and social demand for a better world. Unfortunately, harmonious encounters between both is very rare and needs and innovation are scarcely matching. Technical inventions are always the fruit of a culture and inventors, engineers or users all share the will to have a better world so they try, like Sisyphe.
• Social appropriation is always slower than technical innovation. 5-10 years are needed to go from the fantasy phase to find a niche of users. 10 or 20 years are then needed so that the innovation is entirely appropriated in daily life.

Being interested in technological failures, I read “Where’s My Jetpack?: A Guide to the Amazing Science Fiction Future that Never Arrived” by Daniel H. Wilson. Some excerpts that I found interesting, related to causes of failures:

“Jetpack: “the development of the jetpack effectively ceased the day Wendell Moore passed away, and there are plenty of reasons why. As it turns out, the government frowns on the notion of everyday people equipped with jetpacks and the ensuing midair collisions, air range, and transformation of drunk drivers into inebriated human torpedoes. Worse yet, jeptacks are nearly useless in military applications - a soldier strapped to a jetpack is a sitting duck”

Moving sidewalk: “a few litigious pedestrians have spoiled it for the rest of us with their skull-cracking falls and attendant lawsuits”

Self-steering cars: “Obstacles abound, but without a broader understanding of the world, a robot car cannot tell the difference between a harmless clump of grass and a farmers’ market. Negative obstacles, such as holes in the ground, are particularly difficult for robot cars to identify. Navigation is also more difficult in cities, where tall buildings and bridges can block crucial GPS signals and soft, delicate targets (called pedestrians) abound.”

Flying car: “Merely providing the vehicles is not enough, however; if everyday people are to use them, scientists must know how to track thousands of these car-planes. And knowing is half of the battle. Collision-deterring navigation systems are key to transforming highways into skyways. Regular people just can’t be trusted”

Hoverboard: “They may be perfect for cruising over flat surfaces like water, ice, or a well-manicured lawn. but they are dangerously inept on city streets”.

Why do I blog this? currently collecting material about technological failures and failed (micro-)visions of the future for a project.

Near-Future Laboratory colleague Julian Bleecker wrote an important piece about manufacturing (as part of the Share Festival Catalog 2008):

“First, we’re not talking about manufacturing (…) Manufacturing evokes cavernous, cold, awesomely huge assembly lines with scales all out of proportion to the experiences of mere mortals.
(…)
If anything, we’re talking about a kind of materialization of ideas. Slick connections between an your imagination, a circuit board and a 3D printer. It’s artful for its scale and personalization. Small-scale, passionate, individual ideas made material.
(…)
The sad consequences of manufacturing’s scale is that it defaults to the least common denominator. (…) True customization means materializing one’s own designs, one’s own imagination. This is where we begin. (…) What makes it worth talking about is that it is the power of creation that manufacturing is able to achieve, but done at an entirely different scale - quicker, cheaper, individually, with fewer intermediaries and fewer incumberances.
(…)
The “manufacturing process” is a kind of extended sketching activity. Ideas are first expressed informally, perhaps with a simple “wouldn’t it be cool if..?” question at a moment of inspiration.“

And why this is important to interaction design:

“these expressive objects form their interactivity around physical actions that may include the Nabaztag’s articulating rabbit-like ears, or Clocky the coy alarm clocks that roll away when you try to hit the snooze button, or Maywa Denki’s punch-drunk dancing BitMan character. These are distinct kinds of digital objects that mix physical space, digital technology and design.
(…)
The weak signals suggest kinds of design-art-technology that are growing tired of the screen.
(…)
What is emerging is an ability to make your own stuff - not just “skinning” your mobile or modding an MP3 player. Materializing ideas is about making your own - “whatever” - unanticipated, unknow, visionary, expressive things. It is not a manufacturing process“

Why do I blog this? some important points here about why manufacturing is important, what is is and what does that mean for human practices. This is relevant at a time where hardware fabrication and manufacturing has been left over to south asian countries and that we should not give away our effort to build concrete things (and do only so called “virtual” building).

Still a struggle to find time to blog my notes from the LIFT08 conference. Here are some notes from the session about foresight.

Scott Smith
As defined by his complany tagline, Scott talked about “seeing change differently” or how to help people to see change more clearly. He defined foresight as “keeping your mind and your eyes aware of the periphery as well as what is in the immediately linear future, as there is always something that could disrupt your path“. Following William Gibons’s quote that the “future is already here but it’s not evenly distributed”, Scott then described how the future is hidden in little places or pockets we are not always aware of and insisted on the important of qualitative data (over quantitative extrapolations). Hence the importance of ethnographical approaches. He insisted on a set of tips to adopt a qualitative foresight approach: (1) be aware of what’s going on around you, (2) scan, collect, organize, (3) look for patterns and deep currents, (4), understand the role of values, (5) have a view, but not an ideology (and be ready to step outside your boundaries), (6), stay grounded, (7), be prepared to leave behind the artifacts of your experience.

Francesco Cara
Francesco works at Nokia, he’s design strategist and basically described the sort of approach to innovation he favors. He started by insisting on the notion of ecosystem and complex systems drawn from Piaget that shaped his vision hereafter. Looking at the evolution of mobile communication, he showed how the ecosystem got more complex over time: from GSM phone units (closed by regulators, carriers, manufacturers) to WAP-based phone with more capabilities to exchange “with the outside” and finally a third stage with new services that tap into the Internet (maps, email…) and new entrants (Google, Apple).
To do so, he actually used visualization from a project conducted at our EPFL lab called “Mapping the Digital World, Visualizing the fundamental structure of the digital world in mobile devices . This last stage forms a sort of “cloud” of services that is so complex that our way to interact with it are totally different. But the problem is the one of the interface: how to interact with this complex ecosystem?

(Picture taken by Bruno Giussani)

Francesco showed the different approaches adopted by companies such as Blacberry (specialized: email), chaotic interface with various ways to use services (Sony Ericcson), desktop-based (Apple iPhone) or portal-based (Windows). He then advocated for “fresh” innovation. And why is this in a foresight session? Francesco’s point is that sometimes innovation does not lie in observing the past or looking for weak signals but rather to develop brand new approach and create new metaphor (that can of course be based on analogical reasoning, taken from other domains). His claim was not that the stuff presented by Scott is wrong but rather that innovation if a combination of both and it all boils down to the level of granularity in the data you need to inform design.

Bill Cockayne
Bill started off by making a strong point that what he talks about is not “futurism” but “foresight” and the role it plays in the innovation process. What he means is rather how to inform the building of something that is 1-2 product life cycle away. Depending on the products (car: 10 years+, nokia: closer), what happen is generally 1st product cycle (made now), 2nd product cycles (strategized now) and what happen for the 3rd product cycles?

Bill focuses on where you kind of start the whole process. He explained how the ideas he presents has been developed as Stanford. For instant, they adopted the ambiguity curve as a way to decribe the process. It’s used by Prof. Leifer at Stanford and it’s inspired by work from MIT+Buckminster Fuller. The ambiguity curve is not explicitly referenced but it shows how the situation evolves. At the beginning, you have ideas (beginning of a problem) with a vast ambiguity (”but we have to live in it”). All the way to shipping a product you retain ambiguity but there are different stages:

The thing is that people are having a problem to figure out where to fit in this process, to be aware of one’s strength or how to maximize them. What is design, what is foresight? How to connect d+f? The problem between r+d= people from research why what they give to developers is shipped and people from development never visit the researcher’s office because they have work to do today. And there are same issues with foresight and design. However, there are no breaks between r and f or between r and d, eventually you have to ship products! There are 3(+1) stages: (0), wallow (what Scott described: looking for the future, not ready to start the projects, be aware and intuitive, scan/look/analyze data), (1) foresight (prepare and sense), (2) research (form and analyze) and (3) design (integrate, develop)

What is important here is the notion of roles, which was developed afterwards. I strongly recommend here to have a look at at the impressive work done by Michele Perras, who recreated the images form Bill’s slides. For example the one that shows the different types of roles (see also Bill’s discussion of the role on her blog which nicely covers the topic in greater details):

(Re-created by Michele Perras)

Bill then described what roles can fit with what part of the process and along the ambiguity curve. He also presented what sort of process takes place: informal/formal/corporate.

His last advice was to know yourself, and what role you can play:
1) if you wanna be an expert, please remain an expert; stay at school kids, focusing on what you’re good at
2) t-person: learn another language, something complementary (take a design degree if you’re en business expert), vast need for this people
3) break your breadth, take a new expertise
4) come talk to people like scott, francesco, bill and read widely

Why is that important? why did he talk about roles and not tools to predict the future? Because change is constant, which means that new opportunities appear constantly and “we love opportunities because that’s where innovation comes from” and knowing where you excel at will help you to know who you are and make you more comfortable in the change environment and help you tell other people where you’re good at.

Some notes from Michele Bowman’s podcast entitled “The Role of Ethnofutures and Environmental Scanning”:

“2 things to keep in mind:
“Any truly useful idea about the futures should first seem to be ridiculous.”: The idea that airplanes would carry people, the fall of the berlin wall, paying bottled water

“not all change is created equal”: The general consensus in the business world is that change happens really, in fact this is not the case at all. There are all sorts of degress of change:
- environmental change, demographic change: takes decade to be felt
- evolutionary change: rising of women in the workforce… incremental… almost predictable timeframe
- faster furious change: the cost of sequencing the genetic alphabet that dropped

Environmental scanning is the understanding the dynamic of change, where and when, how fast? how slow? a collection, interpretation about trends and emerging issues And it needs to be external: “I don’t know who discovered water but it wasn’t a fish” because challenges will come form external environment

Roles of scanning
- as a decision-making capacity
- organizational learning, increasing the sensitivity to change“

Why do I blog this? curiosity towards different methods about foresight research, lots of resonance with the LIFT08 session about this theme.

In this NYT piece called “The Risk of Innovation: Will Anyone Embrace It?“, G. Pascal Zachary deals with interesting issues regarding innovation. Some excerpts:

“Even today, when adding video to a phone is a trivial cost, consumers may rebel. Video-conferencing often remains an activity forced on people by their employers. Resistance to technology is an omnipresent risk for every innovator. Even a device as fabulously freeing as the personal computer struck some people as an abomination
(…)
Adaptable humans usually trade one technology for another, rather than reject any and all. To be accepted, innovations must deliver benefits — enough benefits to make change worthwhile.
(…)
FOR technological innovators, the cash register can ring either way. They may achieve a smash-hit breakthrough, or simply make a slight improvement in a technology that humans already feel comfortable with. Most innovators no longer even try to predict human reactions to their creations. Henry Kressel, a partner at Warburg Pincus and a co-author of “Competing for the Future: How Digital Innovations Are Changing the World,” says, “You throw technologies into the market and see what sticks.” The hope is that passionate “early adopters” will blaze a path toward mass acceptance of a new technology. Yet the truth is that no one can tell in advance which innovations people will adapt to and which will become the next example of the Picturephone.“

Why do I blog this? some general-and-controversial thoughts about tech/usage foresight.

I’ve recently encountered two times this quote from Lewis Caroll taken in Alice in Wonderland:

‘There is no use in trying’, said Alice; ‘one can’t believe impossible things.’ ‘I dare say you haven’t had much practice,’ said the Queen. ‘When I was your age, I always did it for half an hour a day. Why, sometimes I’ve believed as many as six impossible things before breakfast.’

Why do I blog this? One of the occurrence with it was in “After Method: Mess in Social Science Research (International Library of Sociology)” (John Law), where the author use it to stress the need to have “metaphors and images for what is impossible or barely possible, unthinkable or almost unthinkable.” His claim is that it’s important to open space for the indefinite.

This surely seems very abstract but the practice itself of such weird exercice is intriguing in terms of the implications for foresight. In a sense, it reminds of Donald Rumsfeld matrix of known/unknown.

Going through the last articles of 2007 (in newspapers), I found this interesting “The World of Tomorrow” in the NYT (via the Dr. Fish mailing list). The article describes how on Jan. 1, 1908 (New Year’s Day one century ago), the New York World had a piece called “1808 - 1908 - 2008) about the past and the future of America (“What will the year 2008 bring us? What marvels of development await the youth of tomorrow?”). The NYT now tried to replicated this by “ruminating” at 2108.

Interestingly, more than the predictions the following quote attracted my attention:

“The point of such predictions was not necessarily that they were accurate but that people cared enough about the future to bother thinking about it. Whether their visions turn out to be right or wrong, whether they are bleak or tongue-in-cheek, all are generous efforts to wonder about the lives of New Yorkers of 2108, as those New Yorkers of 1908 once wondered about ours“

Why do I blog this? Although the predictions are interesting, reading them without the few lines above is very important as it shows the purpose of foresight per se: not predicting but caring about the future.

In “Profiles of the Future: An Inquiry into the Limits of the Possible”, Arthur C. Clarke describes these 3 laws that are relevant wrt foresight research:

“

1. When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.
2. The only way of discovering the limits of the possible is to venture a little way past them into the impossible.
3. Any sufficiently advanced technology is indistinguishable from magic.

(…)
As three laws were good enough for Newton, I have modestly decided to stop there.”

Why do I blog this? these very basic laws are interesting to understand Clarke’s approach to writing science-fiction and what are the underlying traits of his prognostications. Although, it’s sci-fi, there is a lot to learn from his novels and these quotes act as valuables rules for foresight research; the implications of each of them would be good to discuss.

As Jules Verne expressed it about H.G. Wells in “Invasion of the Sea“:

“We do not proceed in the same manner. It occurs to me that his stories do not repose on very scientific bases. . . I make use of physics. He invents. I go to the moon in a cannonball discharged from a cannon. Here there is no invention. He goes to the Mars [sic] in an airship which he constructs of a metal which does away with the law of gravitation. . . But show me this metal. Let him produce it.“

Why do I blog this? both Vernes and Wells were great futurists hidden under their novelist stance. I found that quote interesting and it exemplified the different way they proceeded.

Reading Ballard lately, I am always struck by his fascination with empty swimming pools. See for example in “Notes Towards A Mental Breakdown” (1967):

“Usually accompanied by Leonora Carrington, he visited the Mullard radio-observatory near Cambridge and the huge complex of early warning radar installations on the Suffolk coast. For some reason, empty swimming pools and multi-storey car parks exerted a particular fascination. All these he seems to have approached as the constituents of a mental breakdown which he might choose to recruit at a later date.“

And much later in “Super Cannes”:

“Ten thousand years in the future, long after the Côte d’Azur had been abandoned, the first explorers would puzzle over these empty pits, with their eroded frescoes of tritons and stylized fish, inexplicably hauled up the mountainsides like aquatic sundials or the altars of a bizarre religion devised by a race of visionary geometers.“

Why do I blog this? this is related to some current train of thoughts about representations of the future.

Well, maybe it’s not important at all, and spotting 2 references to empty swimming pool may seen weird. However, in the context of J.G Ballard’s work, it makes sense and I find intriguing this sort of recurring representation of the future.

Why is that so? First because it may represent the future of a distopyan future one would fear. Second because an empty swimming pool is no longer used by humans, as if that facility was left for other inhabitants. What remains is the empty infrastructure, with its shape and emptiness. I am personally more interested in this second issue and what it tells about infrastructures.

I already mentioned how “Foundations of Futures Studies: Human Science for a New Era: History, Purposes, Knowledge (Human Science for a New Era, 1)” by Wendell Bell was a relevant reference about future studies/foresight.

One of the book chapter deals with the assumptions of future studies:

“

1. Time is continuous, linear, unidirectional and irreversible (…) the continuum of time defines the past, present and future.
2. Not everything that will exist has existed or does exist. Thus the future may contain things that never existed before.
3. Futures thinking is essential for human action.
4. In making our way in the world, both individually and collectively, the most useful knowledge is “knowledge of the future”. In making plans, exploring alternatives, choosing goals, and deciding how they ought to to act, humans have a need to know the future and how past and present causes will produce future effects.
5. The future is non-evidential and cannot be observed; therefore there are no facts about the future. Nonetheless (…) it is possible to have ‘conjectural’ knowledge.
6. The future is not totally predetermined. It is more or less open.
7. To a greater or lesser degree future outcomes can be influenced by individual and collective action.
8. The interdependence in the world invites a holistic perspective and a transdisciplinary approach both in the organization of knowledge for decision making and in social action.
9. Some futures are better than others

“

Why do I blog this? these assumptions give an interesting frame as they give rationales and directions for future studies. As the author mentions, it’s a selection of them that he exemplifies in his book in more actionable ways.

Just found this article about “the future of futurology” in The World in 2008 of The Economist. It starts of by describing how the word “futurologist” has disappeared from the business and academic world, so has the so-called “futurology” discipline (although “there are still some hold-outs prophesying at the planetary level“). The new thing is rather about scenario-building and storytelling, which is not a surprise.

What is interesting is the underlying reason proposed by the author:

“We can see now that the golden age of blockbuster futurology in the 1960s and 1970s was caused, not by the onset of profound technological and social change, but by the absence of it. The great determining technologies—electricity, the telephone, the internal combustion engine, even manned flight—were the products of a previous century, and their applications were well understood. The geopolitical fundamentals were stable, too, thanks to the cold war. Futurologists extrapolated the most obvious possibilities, with computers and nuclear weapons as their wild cards. The big difference today is that we assume our determining forces to be ones that 99% of us do not understand at all: genetic engineering, nanotechnology, climate change, clashing cultures and seemingly limitless computing power. When the popular sense of direction is baffled, there is no conventional wisdom for futurologists to appropriate or contradict.“

The author also points out to some advices:

1. the next rule lays in thinking short term (“Microtrends”… “nanotrends”)
2. “ say you don’t know. Uncertainty looks smarter than ever before“
3. “for the budding futurist: get embedded in a particular industry, preferably something to do with computing or national security or global warming. All are fast-growing industries fascinated by uncertainty and with little use for generalists. Global warming, in particular, is making general-purpose futurology all but futile. When the best scientists in the field say openly that they can only guess at the long-term effects, how can a futurologist do better?“
4. “talk less, listen more. Thanks to the internet, every intelligent person can amass the sort of information that used to need travel, networking, research assistants, access to power“

Why do I blog this? quite interesting food for thought here, and I agree with the rules.

A very interesting corollary to William Gibson’s assertion “the future is already there, it’s jut not evenly distributed” is discussed by Bill Buxton in “Sketching User Experiences:

“we should not count on any deus ex machina. We should not expect any magic bullets. It is highly unlikely that there will be any technology that we don’t know about today that will have a major impact on things over the next 10 to 20 years.
(…)
innovation is not primarily about alchemy. Rather than trying to make gold, it has far more to do with learning how to find it, mine it, refine it and then work it into something of value. If Gibson is right, then the innovator is likely best to trade in his or her alchemist’s chemistry set for some prospecting tools, and learn about geology, mining, smelting, design, goldsmithing, sales and marketing, so to speak.
(…)
it is generally not the underlying technology itself, but its deployment and associated value proposition that brings us suprise and delight, as well as generated wealth for those who executed well on their insights“

Why do I blog this? I like the analogy with geology and digging stuff about things to come.