Martin Sheen as Josiah 'Jed' Bartlet. Picture: @Pres_Bartlet

Even by the standards of modern political media prattle, this was odd: the Guardian yesterday invited and ran a “response” to Barak Obama’s State of the Union address, from Jed Bartlet the fictional president in The West Wing.

One should immediately add that the response was not that of Martin Sheen (the actor who played Bartlet) or anyone from the show. It was that of an unnamed tweeter who can be found here.

The reader vox-pop box was quick to cry foul, asking what next: a piece on space exploration by Captain Jean-Luc Picard, or 007’s analysis of the War on Terror?

Fair enough. But if there is a serious point to be made, and I think there is, it is that fictional leaders do have a role in real world business and policy leadership.

Fiction and storytelling is important and enduring in all human societies because it is an excellent vehicle for considering complex human situations, reflecting on competing motivations and interpretations, assessing choices made with incomplete information, and following these through to their win-or-lose conclusion. Fiction allows multifaceted situations to be captured without losing the complexity.

Parallels

Incidentally, this is why scenario method, which tells stories of alternative future situations, is such an effective planning device. But the point here is that fiction captures complex human situations and senior executives would be the first to recognize parallels between the challenges that imaginary leaders are put through and what they do in a real working day.

If fiction captures and communicates tricky situations well, it therein becomes a learning vehicle. Whether reading a difficult modern novel or watching a soapy TV show, we put ourselves in others’ shoes, vicariously experiencing their conundrums and learning from the outcomes of their decisions.

Would-be successful leaders could do worse than take note of the leadership attributes of winners such as Sherlock Holmes or Superman or Andy Dufresne; or unpick the illusions and ultimate failures of dark lords such as Voldemort or Mr Kurtz.

Furthermore, a good way to learn is to judge real performance against an ideal template. (Judging me against my clarinet teacher, for example.) Whether your politics aligns with the positions and preferences of The West Wing White House or not, there is no denying that Bartlet is set up as a model president in a model administration. He is thoughtful, caring, effective; manifests an ideal balance of intellect, EQ, and decisiveness; is respected and loved by his staff who will go to the ends of the earth for him. He is a template leader.

So it’s hardly off-the-wall to wonder what Bartlet would have made of Obama 2012. That said, it would have been far more interesting to know what West Wing screenwriter Aaron Sorkin or even Sheen, rather than abitrary unnamed tweeter, thought of the State of the Union address.

For the record:

The Lion: President Obama. Mangy, patchy, apparently underfed. Definitely caged. But he has a heart. Whether it is the lion heart of the ruler of Narnia … time will tell.

The Witch: Here we have to go with Shakespeare; in fact there are three witches: Romney, Gingrich, Santorum. On Tuesday Obama called for a fairer country. Notice they responded: fair is foul, and foul is fair.

The Warmonger: he that exited the presidency in 2008, having wasted 4,000 lives and $800,000,000,000 on a war as poorly judged as that of Douglas Haig at Somme, 1916.

Herman Kahn

Interesting times we live in, when most of the world’s business media has a front-page tab on their Web sites that says something like “Euro Crisis – Live – Follow Here” as if there was a hostage drama or bank heist on the go.

Perhaps it is a bank heist of sorts, in the frantic run up this week and next to the Brussels summit in on 8-9 December, where the 27 Eurozone leaders are expected to make some binding, if not bold, decisions.

There has been short-term market relief following the US and China’s undertakings to make dollars more easily available into the European banking system. But everyone knows that liquidity, while a problem in itself, is a symptom of the larger problem of sovereign debt. And sovereign debt is only a problem when lenders don’t see future growth such that loan capital looks safe at less than, say, 7%.

In the world of foresight we talk about the need to “think the unthinkable,” a phrase coined about Herman Kahn in the 1960s when he was making scenarios about the road to US-Soviet thermonuclear war. So I was curious to see this exact phrase pop up in various media analyses where implications of Euro-demise, such as redenomination risk, cross-border contract liability, and so on are getting a thinking through, at least in the media, for example here in the WSJ.

Adaptive Measures

This is scenario planning “lite”: thinking down the path to, and implications of, a plausible operating environment — even if it is highly unlikely — and determining best responses, necessary hedges, and other adaptive measures. (Non-lite would be to do the background work, not just the journalistic summary.)

As the unthinkable forces itself to be thought, even the Corporate Executive Board was motivated to put the injunction to their executive partners as follows: ”As the threat of a potential euro zone breakup looms, we strongly advise companies to enhance their scenario planning disciplines. Leading companies in our network begin by documenting project assumptions and building scenarios off of those variables to test profitability under a range of outcomes before committing capital.”

But to this they add the intelligent real-world rider, often missed by scenario-ists: ”Don’t make the mistake of assuming that entire projects, P&L’s, or budgets need to be reconfigured under volatile outcomes. Instead, build your contingency plans around critical, controllable line items.”

As Stoyko’s is head-and-shoulders the most insightful and thorough assessments of the book itself, and the book in context, I’m reposting it here, with thanks. There are also fabulous graphics added, such as these (see more below):

“My search led to Adam Gordon’s Future Savvy. Like Posner, Gordon challenges Taleb’s blanket dismissal of forecasting. Gordon does not deny the existence of Black Swan events. And his book is a giant compendium of all of the things that usually go wrong with predictions. Moreover, Gordon offers a sceptical discussion of the subject that chastises simple-minded futurists, tech enthusiasts, and various other prophets of doom and boom. The difference between Taleb and Gordon is that Gordon doesn’t dismiss out-of-hand the usefulness of structured thinking about the future. Many important decisions require us to speculate about what the future might hold. Gordon wants us to be savvy in the way we anticipate the future instead of flying by the seats of our pants, so to speak.

“To set the stage, Gordon talks about how the forecasting industry is rife with problems. There are no standards, no accepted methods, no standard terminology. There are no penalties for failure given that people tend to forget forecasts by the time they can be proven wrong. And when dealing with the forecasts offered by pundits, stakeholders, and activists, Gordon reminds us, “we are knee deep in predictive wishful thinking, scare-mongering, or blatant self-promotion.” (p. 5) Buyer beware.

“Then there are the data problems. Forecasters use data from the past to project trends into the future. They rely heavily on data gathered for other purposes, not gathered for the task at hand. Availability is patchy. The data comes from multiple sources and is created using different methods. Important statistical caveats get lost. The context of the original studies gets forgotten. Variables are often defined loosely … and change over time … and are measured differently in different places. Data gathering methods often change over time in ways that exaggerate or obscure a trend. Sensationalist “newsy” data often commands the most attention. Some things are inherently difficult or impossible to measure accurately. All sorts of assumptions get embedded in data projected into the future. Furthermore, Gordon talks about the ways in which numbers can be finessed in an underhanded way. He advocates “number scepticism”, warning: “But no matter how scientific the data appears, choices have been exercised at every point about what to observe, what to count, how to measure it, and how to report it. … But numbers are not bedrock. There is no bedrock.” (p. 59)

“As an aside, statisticians have a snide nickname for analysts who mix’n’match statistics from a hodgepodge of sources to create complicated models or story-lines. That nickname is junk-yard dog. Gordon gives the impression that the forecasting business is, by necessity, heavily populated with these collectors.

“The sources of potential error don’t end with data. Our biases cause us to misinterpret and misreport the data.

“Some bias is intentional manipulation. Rascally analysts ignore or downplay countervailing evidence. They give evidence less scrutiny if it confirms the desired result. Emotionally charged language and associations are used. Terms are defined in leading ways. Extreme cases are used to represent the norm. Forecasts that don’t accord with an agenda get ignored, especially if the forecast is sponsored by a powerful interest. Organisational incentives can cause those being scrutinised to fudge the numbers. When forecasts are presented to the media, the most extreme trends get attention and important caveats remain unreported. Gordon is particularly critical of the so-called futurists who use “stretch thinking” and “big-picture thinking” to imagine a world full of only big changes. Many have a technophile bias, or the assumption that technology is the sole motive-force of large-scale societal change. Gordon’s advice is to keep your guard up and be wary of motives.

“Setting aside the thinness of this advice, Gordon has a strange attitude when talking about manipulation. He makes a distinction between forecasts that attempt to be accurate and forecasts that attempt to influence. Employee-prodding managers, partisan policy wonks, and alarmist activists use loaded forecasts to move minds. Humility, qualification, and tentativeness don’t have a place in these circles. There may be a legitimate reason for using leading forecasts, such as communicating the art-of-the-possible or giving someone an ambitious target to strive for. However, leading forecasts without full disclosure are instruments of underhanded manipulation. Gordon is eerily agnostic. His advice and tone of voice suggests that he is oblivious to the ethical problems posed by the manipulative use of forecasts. It’s a strange contrast with Gordon’s advice about being careful and pragmatically sceptical. [Editor's note: Agnostic? Moi? Hardly, but perhaps the chill of my irony was not chilly enough.]

“Back to the sources of error.

“Gordon itemises a number of cognitive biases that are inherent to the way we think. We often miss Black Swan events and abrupt changes in prevailing wisdom (“paradigm shifts”), he argues, because we are always filtering information based on perceived relevance. This “inattentional blindness” causes us to not notice important influences on the future. We also overemphasize recent happenings over older events (the recency effect). We’re susceptible to herd thinking and faddish ideas. A few chance events are often mistakenly interpreted as a trend or other pattern. Gordon places particular emphasis on how our current context frames the way we see and think (situational bias), especially how the prevailing mindset and preoccupations of an era skew the way we think about the future (Zeitgeist bias). For example, nuclear-powered airplanes may have seemed inevitable to someone living in the 1950s, a time preoccupied with thoughts of nuclear technology, suggests Gordon. That notion seems absurd today. To counter this problem, he argues for the need to extract the assumptions underpinning our expectations. Those assumptions need to be questioned and tested. And one good test is to reverse the assumption; that is, consider how the future would be different if the opposite (or very different) assumption were used.

I would add that people habitually rely on lazy assumptions about the future in general. As Howard Segal points out in his book Technological Utopianism in American Culture (2005), late-19th and early-20th-Century intellectuals assumed a technological plateau when describing the future. Even today, we assume our arrival at some destination—a future steady state—instead of a world of on-going change that is unevenly distributed and erratically paced, as exists now.

Gordon invites us to consider the utility people derive from a particular technology before jumping to conclusions about how it will revolutionise everyone’s lives. Tech-happy futurists are too quick to assume broad public acceptance of a new technology while ignoring the trade-offs of adoption. There are costs to be considered. In many cases, the price is too high and existing technologies do a good enough job. Or old technologies have an inertia, such as when users are “locked in” to a particular technology. Or social values change. Or switching creates undue inconvenience and aggravation. Or the technology has uneven appeal across diverse groups in society. Or, or … Gordon reminds us that simple technological domino effects almost never happen. The pace of change is usually slower than anticipated. A variety of factors determine how successful an innovation will be.

That leads us to the dynamics of change. I’m not going to describe each dynamic in detail. Gordon devotes a lot of space to them. Instead, I’ve listed them iconographically in the following diagram. Note that the darker lines signify consequences (and consequences of consequences; a.k.a. second-order and third-order events).

“A trend observed today may not continue onward along a straight-forward path. Trends peter out … change course … hit limits … get caught in reinforcing loops … have side-effects … provoke reactions … et cetera. The same goes for underlying causes. Trends can be particularly difficult to track within the complex systems that govern our lives. Thus, Gordon offers a chapter on system analysis.

“As someone who studies organisations, I’m often seeing policies and strategies change with sadly predictable pendulum swings. Gung-ho leaders push in one direction with gusto only to get a lesson in humility. Their efforts hit limits and opposition. Their assumptions hit reality. Subsequent leaders see wreckage everywhere and push in the opposite direction, looking for balance. Balance alludes them and they go to far. Another pendulum swing begins. Some swings happen from season to season. Others happen over decades. These swings may be predictable, but their exact timing certainly isn’t.

“Gordon rounds out Future Savvy with a utilitarian survival-guide of sorts. His big advice is that “it’s better to be vaguely right than exactly wrong.” Success is being alert to important changes and being prepared to cope, not with having accurate predictions. Narrowing down the things that need to be prepared for is an important practical benefit. In that spirit, Gordon talks about the strengths and weaknesses of using multiple scenarios instead of pat forecasts. He steps the reader through the analysis of some forecasts while looking for weaknesses. A chapter-long battery of questions is offered to guide the analysis. These questions do a good job of summarising the book.

“All told, Future Savvy is an excellent textbook for those who want to discipline the way they think about the future. I disagree with Gordon’s tangents about the inherently subjective nature of truth. I also have a few qualms about his take on scepticism. But these tangents rarely get in the way of his stock-taking exercise. That exercise has led me to be even more suspicious of forecasting, especially forecasts in volatile industries where data is patchy and assumptions are legion. I’d love to know the success rate of high-tech cheer-leaders … er, research firms that peddle forecasting numbers. Gordon dismisses the tracking of forecast failures as “smirk lists”. I’m with Taleb and his tsk tsking. If these numbers are just part of the hype machine and have a dismal track-record, then what good are they? Validation for reckless investment strategies? Fodder for misleading Power­Point slides? Numbers that give a false sense of being in-touch with the market? Tsk tsk.

“That said, Future Savvy has increased my interest in foresight more generally. Gordon’s guide left me wondering how I can better prepare groups of decision-makers to think about the future. How do we get them to see the many changes afoot with greater foresight?”

Controversy has resulted from lack of transparency in the tests, leading to speculation that they are designed to have most banks “pass” in order to boost confidence — as clear an example of mixing up judgment and advocacy as one is likely to get.

The key measure for determining which of the 91 banks fail the test — and need to raise capital — is whether their Tier 1 capital ratio would fall below 6% under the “loss assumptions” imposed by the test. This is the same level that was required in the stress tests of U.S. banks in its similar May 2010 test.

Model worlds

Anyhow, what is particularly interesting to this author is that the concept “scenario planning” has not been used through the bank test process, but these tests are fundamentally future scenarios, this is what scenarios are all about: creating model future worlds that express the evolution of important uncertainties towards somewhere at the limits (but not beyond) of plausibility, with the specific intent to use these worlds to stress test current decisions as to what a company is and does — from its business model to its resource base to product line to marketing, and so on.

If the organization’s key decisions would hold up (produce profitability or however success is defined) in different, alternative tests, this tells managers theirs are probably good decisions for the future. If they would flop in any test, this points to what needs to be urgently addressed. In this way an organization explores and becomes robust to its unknowable and unpredictable future.

Notably, it is precisely the stress-test purpose of scenarios that stops this foresight technique becoming (as it does all-too-often in the wrong hands) a “wishing well” for better times. When scenarios cease to be direct stress tests of present decisions, they become floaty indeed.

Full scenarios

Having said all this, the difference between the US and European banking stress tests and full scenario work is the bank tests are considering only economic factors, only adverse (risk) conditions, and only “known unknowns.” Full scenarios would include the full range of important drivers of change — and potential surprises — outside of economics or finance in their construction. In operating as stress tests, they would look at threats to the status quo as the bank tests do, but also provide a testbed for exploring opportunities in change.

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The point is, this is not the future of housing. Many hyper-efficient solutions have been designed over the years — many such “machines for living in,” that worked perfectly as rational solutions but failed the social-market adoption test, and therefore did not become part of the future. The future is always what we (as a whole) choose from among what designers and technologists can create.

This prototype will fail it’s future-adoption test. Humans don’t live rationally. If I rolled my desk to the ceiling, I’d be showered with papers and headphones and flying coffee cups. You would too, no doubt.

Having said that, the inventive thinking here is intense and admirable. This prototype is like a good scenario in that it functions in the liminal zone between the plausible and implausible, allowing us to consider options and problems (and their solutions) that otherwise we would be blind to.

I can see some elements of this prototype finding their way into urban hyper-density new-build apartments, and when they do it will be fair to say the “futures thinking” was done here, in this project.
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I was lucky enough to be asked to do the opening address at the conference, and even luckier in that this Web site: South Africa – The Good News summarized some of what I and others said:

“Adam Gordon, Foresight Project Director and author of “Future Savvy” gave us some pointers:

1. Beware of sector experts, they are deeply entrenched in the present.
2. The consumer and choice is the determinant, not technology.
3. Change is about overestimating followed by underestimating.
4. Trends are patterns in the data, behind the trend are enablers and drivers, but frictional forces exist and in front of the trend are turners and blockers.
5. Trend extrapolation is limited, don’t fall foul of the turkey syndrome.
6. There is well behaved and badly behaved change. Both can be predictable and unpredictable. The potential of sudden shifts always lurks.
7. Scenario planning wraps up the key uncertainties over which we have no control.

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“The ‘BIG’ question he asks is ‘when do we influence the future and when do we adapt?’ There are big predictable forces out there (like population growth / the diminishing availability of oil etc), and there are big unpredictable forces out there (ja, well no fine!). Importantly, we can design our ability to influence and we can design the way we adapt. It is critical that we are able to do both.

“But managing the future is more than just about scenario planning, it is also about the implementation of the plan. It is about developing a methodology that prioritises, engages with stakeholders, and enables proactive actions on the ground.

So how?

Some important considerations (from various speakers):

1. Often we know what causes the problem (poverty, crime, HIV) but we don’t know what to do about it.
2. Often the logic that gives rise to the problem is not the logic that will solve the problem.
3. Mostly the problem does not contain the makings of the solution.
4. Solutions in one area can exacerbate problems in another.
5. The current situation has momentum, change to the system should happen concurrently not suddenly.

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“What is critical is the foresight process, it must be well-informed so that the implementation strategies that follow have buy-in, are doable, are relevant and far-reaching. There is a very real danger of visions being disconnected, unachievable and, at the end of the day, a pipe-dream.”

Dr Elizabeth Dostal talked of a stakeholder democracy in which she promoted the design of a matrix that recognised different stakeholder levels on the vertical axis and different environmental dimensions on the horizontal axis. A multi-level, multi-dimensional model.

“Imagine” she said, “putting four Nobel Peace laureates together and asking them what the causes of global conflict are. One may argue poverty, another ideology, another resources, and another greed. In no time, they would all be in different silo’s defending their view, in one sense they are all right, but in another sense they have not looked at the whole picture. A multi-level, multi-dimensional model would reveal this, the gaps in their logic, and the opportunities for agreement.”

So may I say, this is what I was trying to say: When trying to predict the future, watch for dog poop!

Or perhaps: apparently helpful guides to the future are often dog poop disguised as chocolate, and here’s how to know the difference.

Something like that.

Note that this Greenbang story, below, is damaged by letting the most extreme predictions (the howlers) stand in for the general item. Prediction howler-spotting is sobering, but misses how many people got the future right, or right enough to make excellent decisions, and therefore overly damages the foresight field.

Also, howlers are actually the low-hanging fruit. Being future savvy is ultimately about the more subtle job of correcting weighing apparently very credible and well-founded predictions, some of which are excellent, but others of which are far flimsier than they appear.

There are various other minor problems such as not knowing the difference between the Gartner Hype Cycle and Zeitgeist bias, etc. And I would never call myself, not even in my most self-deprecating moments, a “futurologist.” But anyway, as I said, just a bit of fun:

Greenbang (13th April 2010) by Trish Lorenz & Martin Wright: Prediction is very difficult, especially about the future.” Niels Bohr’s words are a wise warning to reckless forecasters.

“Combining a nuclear reactor with a home boiler is no longer a problem. It would heat and cool the house, provide unlimited hot water and melt the snow from sidewalks and driveways. All that could be done for six years on a single charge of fissionable material costing about $300.” — Robert Ferry, US Institute of Boiler and Radiator Manufacturers, 1955

“Nuclear-powered vacuum cleaners will probably be a reality in ten years.” — Alex Lewyt, President of vacuum cleaner company Lewyt Corp, also 1955

Lewyt and Ferry both stumbled into a risky habit of all amateur futurists: extrapolating from present trends. In this case, they were caught up in the surge of excitement over the rise of nuclear power. They were not alone. In the tech-fuelled optimism of the ’50s, magazines, radio and the infant TV were buzzing with predictions of flying cars and lunar settlements.

They had fallen victim to what later became known as the Gartner Hype Cycle. This maps the enthusiasm and subsequent disillusionment typical in the introduction of new technology — a useful reality check for those caught up in “irrational optimism.”

By contrast, there are those whose feet are too firmly rooted in present realities, and fail to see how innovation can combine with social changes to speed the widespread adoption of new technology.

“The Americans need the telephone, but we do not. We have plenty of messenger boys.” — Sir William Preece, Chief Engineer, Royal Mail, 1878

“The horse is here to stay, but the automobile is only a novelty, a fad.” — President of the Michigan Savings Bank, advising Henry Ford’s lawyer not to invest in Ford Motors, 1903

It is difficult to consider any factor that doesn’t apparently exist at the time of making a prediction, but that’s essentially what looking ahead requires. It wasn’t all that long ago when people were predicting a bright future for teletext and fax machines. Few would have anticipated that both would be made almost obsolete by the internet and email. And yet the weak signals were there for those who chose to hear them. A fax machine, after all, is simply a modem with a rather complex print interface attached. It only evolved as it did because people were unused to reading information solely on screen, and computers were too big to carry around with them. Once laptops took off in the early ’90s, the fax was doomed.

“There is no reason why anyone would want a computer in their home.” — Ken Olson, Chairman, Digital Equipment Corp, 1977

Australian Senator Dr Russell Trood sums it up neatly when he says: ” ‘Nowism’ is a serious occupational hazard for those in the prediction game.”

Today’s futurologists no longer try to predict a single outcome for the future; instead they map a variety of scenarios. For Adam Gordon of Future Savvy, scenario-based thinking gives people “permission to think through alternative outcomes without necessarily predicting them.” Instead of trying to forecast precisely what might happen, he says, “we can ask ‘What if it does?,’ and then explore the outcomes and our responses.” Such thinking characterises much of the strategy adopted by forward-looking governments on tackling climate change.

James Goodman, head of Futures at Forum for the Future, agrees: “People think it’s the output that’s important, but actually it’s the process.” And, he adds, “All future planning has uncertainty at its heart.”

Or as Martin Raymond, Strategy and Insight Director at The Future Laboratory, says, “We always try to spot the dog
poop in our forecast.”

Greenbang Editor’s note: This was a guest article by Trish Lorenz and Martin Wright at Forum for the Future. This piece originally appeared in Green Futures, which is published by Forum for the Future and is the leading magazine on environmental solutions and sustainable futures. Its aim is to demonstrate that a sustainable future is both practical and desirable — and can be profitable, too.

Imagine you are a turkey. Every day someone comes to feed you. Every day you get bigger. Your portion sizes get bigger too, brought by a nice man at regular intervals. You extrapolate the trend and you confidently predict a bigger you, with more to eat. Regularly too.

But what happens is … Thanksgiving. Or Christmas

Taleb, N., The Fourth Quadrant: a Map of the Limits of Statistics, Edge Foundation, September 2008

The hard reality for those who predict the future by extrapolating trends (and those gullible enough to believe them) is that even if our turkey had excellent data points (carefully observed and accurately recorded in, for example, a time series analysis) and, moreover, even if our turkey was a mathematically sophisticated — not merely simply projecting trends, but applying all the latest modeling techniques, from moving averages to compound regression — he is still going to be wrong about the future. Dead wrong.

All the data analysis in the world, all the fancy computer software, all the consulting time paid for, and he is still a dead duck.

Ouch. The lesson: there may be (or, vexingly, may not be) something outside the trend, a framing condition, which where it does exist is invisible within the trend projector’s mental model. The only way to get a view of the future that is “robust to Thanksgiving” is (a) to question assumed framing conditions, for example through properly done scenarios, and (b) to hold a view of the future which assumes fundamental ‘game-changing’ surprises can and will occur.

If, as they say, “the trend is your friend” it is assuredly only your fair-weather friend.

Yes, Ben. I’m sure you know this has all been said before ad nauseam. But more importantly, 40 years on many lessons have been learned, and it wouldn’t run foul of quality journalism standards to reflect this.

First, let’s be clear: nobody can predict the future. Anyone who says they can is a charlatan. Also, yes, unconscionably dreadful and irresponsible predictions have been made and are continually being made. But there are three problems with the ‘no-flying-car-so-there-we-can’t-predict-the-future’ argument:

(1) The kinds of predictions Millar cites are a product of a particular moment in Western thought and therefore foresight. The 1960s and early 70s were a time of Post-War American emergence, unleashing for a while a techno-futurist predictive rapture, most of which has indeed proved to be rubbish. There are still people, very famous talking-head futurists, promoting techno-rapture for the 21st century (caveat emptor) but as a whole the foresight field has moved on to become much more circumspect about what can be predicted.

Balancing techno-fantasy

Foresight practitioners are these days more likely to balance technology wowee with economic, social, and environmental friction; see systemic (often indirect or counter-intuitive) effects where once only simple cause-and-effect was seen; and create scenarios of key alternative outcomes rather than predict one.

(2) The second thing that is missed in gleefully deriding foresight work, is how many people and institutions get it right, or right enough.  It’s axiomatic that in order to be successful a person or organization must have correctly assessed both key changes and rate of change in their operating environment. To take a famous case, as quoted in Future Savvy, while Nixon’s Vice President Spiro Agnew in 1972 erroneously forecast super-sonic passenger air travel, Herb Kelleher, founder of SouthWest Airlines, foresaw the low-cost air travel industry. Bingo. Billionaire. Similarly, behind every success one can find future thinking that, while sometimes latent, was present and correct.

(3) The purpose of foresight work is misunderstood. We cannot predict the future and it’s pointless to try. We can only assess signals of change, trends, and potential for surprises and reversals, including challenging our all-too-easily calcified mental models, and take this into a process of understanding alternative outcomes and pre-considering best strategic actions. In other words, actively stimulating the investigation and analysis of future conditions in order to create the basis of better decision-making today.

In fact sometimes the ‘strategic conversation’ that results from poor predictions is instructive to managers. As I say to clients: the goal of foresight work is better decisions not better predictions.

Back-street abortionists

The reality is that there is good and bad foresight work. Yes, some futurists are the technical and moral equivalent of back street abortionists. But the good work remains, and quality foresight is a critical advantage to decision-makers. The key thing is to be able to tell good foresight work from bad.

Simplistic trashing of foresight work en bloc ignores the weight of case evidence that people and organizations can improve their management of future uncertainty and/or create a situation where they manage the future better than competitors. Further, it encourages managers to fly blind into changing environments, often resulting in spectacularly poor decisions that deeply and widely punish their dependent stakeholders.

Predictions of the dollar’s demise are as old as the greenback itself of course, but over recent weeks the specter of the dollar heading way way below its trading range — a dollar crunch — has entered the zone of the credible, or, in scenario terms, the ‘cone of plausible uncertainty.’ That means decision-makers with lots at stake are taking it seriously.

Like the British pound, the dollar has been under a cloud due to perceptions of economic fallout from the credit crunch and global recession, but particular questions about the US currency have recently surfaced, driven by reports [Robert Fisk's 'The Demise of the Dollar' story in The Independent (Oct 6)]  that “Gulf Arabs are planning – along with China, Russia, Japan and France – to end dollar dealings for oil, moving instead to a basket of currencies including the Japanese yen and Chinese yuan, the euro, gold and a new, unified currency planned for nations in the Gulf Co-operation Council” (Saudi Arabia, Abu Dhabi, Kuwait and Qatar).

The subtext is far from merely financial. Practically, it would mean that on any day, the real cost of oil to US consumers and businesses would go up or down depending on the strength of the currency. This is something America is not used to. But, more deeeply, dropping dollar-denomination of oil is a direct shot across the bows of Washington’s say over oil affairs, and the hegemony of the dollar as the dominant global reserve currency.

De-dollarizing oil would not in itself push the US currency below its 25-year range. But it is portentous of the clear trend to a genuinely multi-power world, for better or worse, in which the dollar will get no favors. That will push the dollar down, at least while the news and fallout make their way through the financial and real economic systems.

Rumors of de-dollarization have been hotly denied, as further reported here, but as the Independent points out, denials are to be expected, and are always issued in these situations. They mean nothing. Even cub reporters know that.

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Scenario thinking

What’s particularly interesting to me is that a ‘scenario’ of dollar demise has become not only plausible in the mainstream view of the future, but scenario thinking is being used as a way to consider the nature of this outcome, and how best to respond without predicting the outcome either way. As recently as directly pre-credit crunch, the media question would have been: ‘what is the best prediction for the dollar (or the housing market, or credit default swaps?) and that, rather then scoping out the implications of the lesser-likelihood, would have dominated the discussion.

So, what struck me forcefully in the Business Week video interview above, where BW Chief Economist Mike Mandel interviews the news magazine’s Economics Editor Peter Coy (see Coy’s underlying story here), is how the less-likely, non-predicted, but very significant outcome is actively addressed:

Says Coy: “It’s so hard to know what the dollar is going to do. We don’t argue that we know… what we do is we say, ‘it could happen’ and let’s take that possibility seriously, in the same way we should have taken the possibility of falling housing prices seriously…”

This is not formal scenario-building of course. But it is, fundamentally an adoption of the framework, saying in the classic ‘scenarios’ way: “we can’t predict if it will happen or it won’t, but if it does it will have significant impact. So let’s just ask: ‘what if ‘ it does and explore the outcomes and our responses. What will the word look like? What would be the implications, the knock-ons and spinoffs? If it comes to pass, what would be wish we had done today?”

Perhaps failing to predict the credit crunch has dented predictors’ halos enough to cause a mini-zeitgeist-shift towards the only real way to cope with important uncertainty: exploring all outcomes that pass the plausibility and significance test, whether or not we actually believe they will happen.

Amazon the new Wal-Mart? pic:Huffington Post

According to yesterday’s LA Times Amazon says the whole thing was a cataloging error. But when author Mark Probst had previously contacted Amazon for an explanation, he got this: “In consideration of our entire customer base, we exclude “adult” material from appearing in some searches and best seller lists.”

Aside: Everyone is trying to figure out what Twitter is good for, or how it will be used, and it has become clear that one application is to quickly aggregate mass protest, evidenced in the anti-Amazon outrage, see Twitter “Amazonfail.”

Author Maya Reynolds has been connecting the dots in the future of publishing, watching Amazon move via acquisitions such as Abe Books, Audible, BookFinder, BookSurge, Brilliance Audio, FillZ, GoJaba, Library Thing, Mobipocket and Shelfari.

She is among various industry watchers who claim, with fair evidence, that Amazon is following a “Wal-Mart” strategy – the well-documented essence of which is to gain enough retailer power to be able to pressure suppliers (telling them what to make or what to charge, or exacting special discounts) to achieve better retail prices and get more retailer power, in a reinforcing spiral which, inter alia, squeezes all the healthy mom-’n-pop-shop diversity and other balances of power out of the industry.

In a post of July 08 she paints the full dystopia scenario:
“1. First, the smaller presses, POD presses and e-publishers will disappear as Amazon’s margins squeeze them out of business. Amazon will help the process along by offering better terms to authors if they will use BookSurge’s POD press and Kindle’s e-book to publish. Even if authors don’t embrace Amazon initially, as their publishers go out of business, they will be forced to do so.
“2. Brick-and-mortar stores have two constraints which Amazon does not: (1) limited shelf space and (2) a limited geographic range. Bookstores carry books “on spec,” filling their shelves with stock they hope readers will seek. Amazon, on the other hand, has unlimited virtual shelf space and unlimited geographic reach. Amazon does not have to warehouse stock. They can wait until a book is actually ordered and the money is in hand before using a digital file and BookSurge to print the book. Because they cannot match the deep discounts Amazon offers, bricks-and-mortar bookstores–already under siege–will be squeezed out of existence.
“3. Like Wal-Mart, Amazon will continue to apply pressure on publishers to give more favorable terms. Wal-Mart’s suppliers used cheaper materials and out-sourced to cheaper overseas labor. As the publishing houses’ profit margins are squeezed, their cost-cutting efforts will take three directions: (1) Focus even more attention on signing best-selling authors whose work is guaranteed to sell; (2) Begin to pressure their mid-list authors to accept lower advances and lower royalty percentages; and (3) Sign fewer and fewer new authors because of the uncertainty and the expense of growing a new writer.

Where will they go?

“4. Mid-list authors and new authors, unable to either find a publisher or unwilling to accept the low royalties, will seek to self-publish. Where will they go? Since, by that time, most of the self-publishing houses will have gone out of business, they will go to Amazon’s BookSurge or to Amazon’s e-book division, Kindle. Amazon will welcome them.
“5. The next death on the food chain will be the publishers and agents themselves. First the mid-level publishers will die. Well-known agents and the larger houses will be protected for a period of time by their best-selling authors who are loyal to them. However, as those cash cows die off, so will the agents and larger houses. A new paradigm will emerge: Amazon as both publisher and retailer.
“6. Eventually Amazon will have so much power, they will be able to decide WHAT is worthy of being published. Welcome to the future of publishing.”

Is this the future of publishing? The logic of unregulated industry power suggests it is. But Future Savvy says response – regulation – is also likely. As with Microsoft and many before them, when Amazon gets too powerful, anti-trust regulators should be in business. But only if their hand is pushed. Articulate and persuasive dystopias such as Reynolds’ are the single most powerful mechanism by which the word is spread (spread it! forward it, tweet it!) so that enough consumers get to see and believe threatening future outcomes early enough, and pressure regulators to act.

Microsoft - Computer Electronics Show 2009

Product prototype communication is a close cousin of scenario building. Typically the company creates their product or service in action, in the future, being used by happy customers, their “preferred future” scenario. Prototype communication doesn’t typically build in alternative scenarios, the litmus test of strategy-based scenario work. It’s more a kite-flying exercise, designed to put out a future-oriented message to stakeholders and the public, garner broad feedback, and (if you’re powerful like Microsoft) put up “this-is-the-future-of-the-industry” markers.

Nevertheless, with the caveat that they are one among many plausible outcomes, product showcase scenarios can be an eye-opening guide to what’s actually possible and what the future will be like.

A newly released Microsoft “Future of Computing” video, showcased at CES 2009 in Las Vegas in the past few days, is an example. The 10-minute piece, presented by Janet Galore, Program Manger: Strategic Prototyping, takes us through a scenario of interactive education in the future (when, exactly, is not said but the implication is it’s not too far off) showing how participants would find, use, and share information across devices and across platforms.

What we see is a tablet PC that can communicate seamlessly with other electronics and interact with Web info on the fly. Okay nothing new there. What’s interesting is how it’s all held together by surface computing, a smart desk with a screen, which allows information to be viewed in the process of collaboration, sharing, and filing.  In some futurist fantasies it is thought that communication is ideally invisible (my phone e-handshakes your phone without me doing anything, etc.) But actually humans mostly seem to prefer to see what’s happening, and to have the choice to interact with what is happening while it’s happening – not least so they know what machines have done and don’t have to pull their hair out before they find their precious work buried four subdirectories into the Temp folder… sheesh. But I digress.

The scenario focuses on organizing and sharing multiple inputs, therein making a pretty clear statement about the future: what will be really valuable is not access to information anywhere, anytime (an assumed, table-stakes factor), but a way to share and collaborate with the information in an productive way. It refreshingly assumes that whiz-bang graphics – they are there too – are the easy stuff, but that collaboration and teamwork are the hard things to get right, and the truly valuable service given the chaos of billions of voices and trillions of data objects that pertain in any human-work future.

The other real strength of the prototype and related scenario is its close attention to natural (or, at least, strongly socialized, conventional, classic) human ways of doing things, which are slow to change, and therefore will change slowly. The smart desk is something one can really see oneself sitting around, because this is what we already do. Also this future of computing envisages no stylus, no mouse, no magic wand to master. Rather, we move digital stuff around the desk with our hands. We point to it and we shift it. That is, digital capability accommodates and interlaces with Stone Age human and organizational patterns. That’s why this view of the future is persuasive.

In many ways, focusing on whether “this” or “that” is predicted, or not predicted, is to put the cart before the horse. The horse is the adequacy of our approach to anticipating outcomes and the quality of our foresight as a whole. When this is good, the cart – not missing important changes – will follow.

Credit: http://www.lewrockwell.com/blog

In this, it’s important to realize that many did predict the financial crisis (as many predicted 9/11 in various ways). Sticking with the financial crunch for now: it has generally been portrayed it as a “why-didn’t-anyone-see-it-coming” event. It wasn’t. Hats off to The Times for their October 12 piece: “10 People Who Predicted the Financial Meltdown.”(Summary here). Allowing for a fairly loose definition of “predicted,” the article shows that among those who foresaw the crunch were: Vince Cable, deputy leader of the Liberal Democrats (2003); US congressman Ron Paul (2003); Stephen Roach, senior executive at Morgan Stanley (2004); Christopher Wood – chief strategist of a broking firm in the Asia-Pacific Market (2005); and Nouriel Roubini, economics professor at NYU (2006)… and there were many others.

A different problem

So this reframes the problem entirely. It’s not that the predictions were not there. It was that not enough people believed them and, particularly, important decision-makers didn’t believe them or didn’t have the institutional capacity to respond. So there are two halves to the problem: the ability to see the full spectrum of what may happen, including unexpected outcomes; and the ability to act on what we see. Quality in foresight work – the raison d’etre of Future Savvy – makes it possible to see more outcomes more clearly, and to act with more confidence in choosing what to prepare for. (In the real world we can’t prepare for every outcome.)

There was a good letter published in the FT from eminent futurist Peter Schwartz on December 2, which describes this very well. It shows predictions for what they are (one-horse scenarios), and how decision-makers are typically bound into inaction or wrong action not only by working on the basis of a wrong prediction, but by the predictive mindset itself. This mindset – the habit or culture of picking “one right answer” in the face of a complex situation with many competing outcomes, prematurely closes alternatives and leaves us open to surprise. As Schwartz says, as scenario planners have always said (and he was one of the people who defined the field in the first place), a compelling set of alternative future scenarios encourages decision-makers to recognize unlikely and unpopular outcomes, along with expected outcomes, and therefore to be able to respond earlier and more effectively whatever happens.

Scenarios also contribute to the “act” side of the problem. In a well-done set for the banking industry, a financial-meltdown scenario would at least have been in play, institutionalizing the consideration of less unlikely, less popular outcomes in company and government forums, forcing serious consideration of necessary strategies and contingencies, and therein creating the ability to act early and effectively without having predicted the crisis.

The letter is well worth quoting in full:

Sir, The real question regarding the financial crisis is not, as the Queen asked: “Why did nobody see this coming?” In fact, any number of thoughtful people in academia, politics and business had been compiling the data and sounding warnings for several years.
The question we should be asking is: “Why didn’t decision-makers believe that a global financial meltdown was increasingly likely and then act on that belief?” Or, to put it another way: “What would it take to make decision-makers both believe and act?”

The problem is that decision-makers believe that they are forced to pick one right answer: the most likely scenario. Their approach to decision-making does not afford them the opportunity to consider apparently low probability but highly consequential scenarios. The answer, therefore, to the “believe” half of the question is a decision-making process that considers several scenarios: compelling stories about alternative futures that incorporate the analysis of “outliers” and describe three or four plausible paths forward.
Good scenarios force decision-makers to challenge their own assumptions and reconsider what is possible. As a result, they can take seriously those scenarios that seemed less likely at first, but whose plausibility increases over time.

The second part of the question – “What would it take to act?” – is much harder to address. Suppose that Ben Bernanke or Hank Paulson had come to believe a year or two ago that the house of cards was about to collapse and trigger cascading, global failures. What would they have done, given the realities of the complex interconnected systems at the heart of the problem? Perhaps if they had good scenarios with appropriate indicators to start with, they could have rehearsed different strategies and contingencies. Importantly, these decision-makers could have used these scenarios to persuade others on all sides of the issue also to recognise the complexity of the impending crisis in a more timely way. It’s never easy to convince everyone around you that the game they have been playing to their great benefit is about to change. But with a shared recognition of the magnitude of the risks and the ways they might unfold, they could have acted far earlier to prevent some of the dire consequences that have occurred, let alone what is to come.

This was a fairly typical example of the Intro Workshop in Scenarios program that I run, so I’ve decided to post it on SlideShare, see link below. Let me know what you think.

What is different about this course at this venue, particularly, is that the attendees come from a wide spectrum of industries and sectors (from Nestle strategist to the Canadian military planners, to Mauri sustainability experts, and beyond), and have a very wide background/preparation in futures tools and methods. There were relative experts in the room, and some absolute novices. … nothing like a challenge for the facilitator!

Slides from the day are at http://www.slideshare.net/adgo/how-to-build-and-use-scenarios-day-workshop

some pix:

1. First, what do you use scenario planning for?
Initially stated everyone did scenario planning, every time you find yourself doing something unusual it implies you’ve done something wrong with scenario planning. We think about the future all the time, constantly making scenarios in head, if move to London think about what need to earn, where live, family, critical uncertainties. We run forward, think about various challenges, we rehearse the future.

CL wondered about ill thought through scenarios?

AG felt it was inevitable that people will disagree. End of day scenarios boil down to politics. Visionary scenario planning gets everyone talking – firstly need to find common threads (if not grounds), that most buy into – even if it is a low common denominator, thus creating a shared vision, then dystopias, but remember the end point is never total agreement.

RS Acknowledgment of importance of politics? Is that your experience of foresight?
AG believes he is a political animal, but no longer involved in protest. Belief is power is absolutely important when thinking about the future. He then amends it to power and money – as often groups without power have public opinions so they can shape the future. There is a danger that they only talk about market forces and technology and that’s it.
RS Is it a struggle working with other foresight groups – is that view not shared?
AG says they can give a shared opinion, but politics mostly overlooked by the groups

RS describes that we all have a political agenda (social inclusion, voices excluded) within this project – it makes it interesting to deal with those who have an economic/gov background, it’s difficult to pretend futures neutral.

2. Could you talk me through a brief overview of your scenario planning method? (How long does each stage take? What preparation is required for each stage? How many people are involved in each step?)

There is an underlying method – but each stage has some degree of flexibility and can use a variety of methods.

A. Handshaking stage
Firstly deciding what you’re doing, basic project stuff – who’s involved, what resources, what deliverables – key is choosing method and who’s involved, may have varying degree of democracy – heads or grass roots, be inter disciplinary or not, have a broad or narrow focus, and what type of input is required. Believes it needs to have mixed agenda. Note that relying totally on academics is bad.
Then you need to decide the dates your final scenarios will relate to – further in the future the more radical but less relevant to other people and harder to action. Most future scenarios are around 10 years ahead – as a rule not less than 5 or more than 20.

To decide the focus you must:
1) Drive management team towards understanding how much influence they have over the future, can they drive future or does external events influence them? Percentage, never exact but idea.
2) Based on the amount of control can decide if creating a visionary scenario or anticipatory (not good word) scenario building. Visionary trying to develop an idea, multiple stakeholders get shared ideal, easier if pressure group, one organisation, as they can develop enrich and jump on to focusing on how we would put this into practice. They create a vision and dystopia. Influence future (money, opinion etc).
In anticipatory, or “Businessy type scenario”, participants don’t mind how things turn out, what they want is to be successful in the world however it turns out. Within organisation goal is to anticipate broad set of possible worlds, particularly critical uncertainties. So they do have research scenarios and different takes on how things emerge, BUT no preferred future. Look at resource and competence so they may have preferences but can adapt. To same extent they look at legacy competencies but this is not a determining factor. Scope alternatives and plan.
The Handshaking stage takes a few meetings to do, small with key meeting, then larger with various stakeholders – perhaps half a day.
In terms of materials one could send out stimulating piece to encourage thought so not stone cold but which doesn’t colour the agenda. Could also have to read a synopsis of what the process is about and the sort of things to think about and expect.

B. Horizon scanning
There are 100s of ways of doing this. Basically need to go into world and do research on what’s going on in key dimensions, technology, markets – broad scan of world relevant to issue area, bring in people outside of own industry. Best tool in this area is “learning journey” – jazzy word for anthropology of own society, structured agenda for talking to people about concerns, what they know, what they’d like, focusing on future – so need to be carefully done to avoid reiteration of now or what they think you want to hear.
Note that you can commission this – but it is not market research.
No answer to how long, dependent on time and resources, but should budget third of total time.

C. Pulling it together
Mulch through the data gathered – preferably in funky creative meetings, collate, output into things like forces, drivers of change, trends, blockers of change, critical uncertainties. What comes out is a picture of world that’s relevant to us.
This activity could be whole group or just the scenario developing team – it’s to pull out what’s important.
The format could be something like workshop, sleep/gap, then another half day or so.

D. Separating critical from predetermined
This could require a Mini Delphi, talk to experts to find out what are the sorts of things in forces of change list that are predetermined – so things we know will happen in 2020, perhaps the number of students, or trends to sustainability.
The various issues will have lifecycles in being a key focus, they’ll always be there but the amount of interest will vary, eg sustainability. In the future sustainability will be less of a concern, but not less important, it will just be integrated into our expectations we won’t focus on it. An example relating to education is how we’ve shifted views on punishment; it was a stick, then detentions, then exclusion…
[Divergent conversation about the failure to correctly predict overpopulation – they just extrapolated – AG argues it was not a failed forecast, just bad forecasting - a failed forecast is interlocked bad assumptions. There was a discussion whether carbon credits will have the same results.]

E. Question all assumptions/Test lists
Note: This stage might highlight the need for more research or stakeholder engagement.
The goal is to end up with two lists that rank for importance. One is about predetermined things – things that we are sure about for our purposes – note that we may, or may not, need to talk about them. Then there are uncertainties (anything we can’t clarify with further research). They are sometimes called “strategic uncertainties”.

F. Create scenarios
These lists form basis of scenarios, they allow us to try out alternate resolutions of the unknowns. AG hates the 2 by 2 matrix approach (from Boston management), but it is sometimes a useful tool. Shell use a fork in the road approach, or possibly a roundabout, where there are clear alternatives. For example, they know sustainability will happen but they have various scenarios predicting the demand for resources. [RS comments that Shell also have a trilemma approach, so deal with three worries.]
More generally scenarios are structured round uncertainties. The van der Heijden approach is to list things and tell stories – NEEDS creative facilitators. He has a pack of cards which people develop stories around. Each group is given part of the puzzle to resolve. Basically you need judgement to choose how.
The groups then write stories and the facilitator ensures the scenarios cover the cone of plausible uncertainties. Note there must be multiple scenarios, a single story is not helpful.
The creation of scenarios will take a minimum of 2 days to talk through, write, draw or tell.

Note: Jump scenarios are conversations over a day. There is no learning journey and it’s hard work for the facilitator. The result is paragraphs rather than stories. These are good for management to emphasis the alternatives and broaden thinking

G. Check and test scenarios
Vital outside people criticise. What could and would work? This stakeholder analysis is meant to be a practical exercise.

H. Put them out
Visioning scenarios (including preferred outcome) get published, they need to get folks on board. Business ones tend to be more internal.
Then test existing strategic agenda within scenarios. They’re a test bed for strategy and choices. How would things work?
Or backcast using the scenarios – so how to reach or avoid scenarios.
AG keen to promote that there needs to be standards, just like testing a pram, you need to exhaust all the things that could happen before it gets its kite mark.
[There was a conversational aside over the time spent on this. AG worried not enough time spent using them and that politics will block change – “if broke don’t fix it”. People need to be desperate to be receptive.]

3. Do you use any tools for scenario planning? If so, can you briefly describe them?

Classic management tools – so getting people to communicate, being experienced based.

4. Are any of those tools online?

Nothing practical is online but there are resources and case studies (see his website). Although then amended that can do Delphi online. Note that learning journey is not market research, not supposed to be investigating people’s mental models – “good foresight is not predictive”.

5. What scenario planning tools would you ideally like to have available?

Something that follows stages explaining steps, timelines, who’s involved, explaining predetermined and uncertainties when listing – basically scaffolding.

6. If time was restricted for a scenario planning exercise, which parts would you keep because they’re the most important?

Would go through all stages (tick all boxes) but go lightly on some. However the less knowledge bought in the more focus on facilitation. The key is to get people to develop interesting motivating diverse stories appropriate to their needs.

7. What tools or approach would you recommend if a non-expert wanted to do scenario planning?

When asked AG said that don’t need a facilitator but would do better if had one. They focus the time and can support the whole process – not just when in workshops. Those involved aren’t experts and have a stake in the present so they’re going to struggle to change their minds.

When asked if it could be done alone AG said yes, BUT that it would be better if one could do at least step G, testing scenarios, with others.

which is produced by a group called Squint/Opera, as part of a set of images of how London population would adapt to raised sea levels. The images, set in the year 2090, are on exhibition at the Medcalf Gallery in Clerkenwell, and the full set can be found here.

The “Flooded London 2090″ images are, of course, a scenario of the future. They evoke a time long after the impact of global warming / a rising sea has past. People have adapted and London is a tranquil utopia. It is not all bad – the rat race gone – swept away with other forms of current (2008) worldly obsessions in a kind of Noah’s flood. The world has become a slower, less complicated place.

As a piece of futures work there are various things to say. First of course, this is a scenario not a prediction. Nobody can predict 2090. Yet, as a scenario, with that intrinsic license to explore the margins of plausibility, it fabulously fulfils one of the primary functions of scenarios: to evoke a mental and possibly even an emotional response. Most scenarios – for example about global warming – are backed up by data and spreadsheets and citations (often necessary and correct) but these images tell the story in a somehow more direct and therefore compelling way, and the old adage a picture is worth 1000 words was never more apt. As all classic scenario analysts, from Pierre Wack to Peter Schwartz to … etc, say: a good scenario should provide a gentle jolt to management – forcing them to consider unexpected events and outcomes and prepare themselves mentally and practically to respond, and these images do that.

Scenarios: the artistic function
Now the question I pose myself – and anyone out there reading – is what is the relationship between scenario’s and art? Is the picture of the future that jolts – whether in a written narrative form or by pictures or film – not jolting in the same way as art does and for the same reason. Isn’t this the classic defamiliarization function of art (possibly mixed with social critique. Here of course it is not merely a warming about global warming that is being communicated, but also commentary about the pace of life, stress, time-crunch, and how this may not be so in the future. Everyone sees the future as more, faster, complexity. But maybe it is not.) Anyway, these images are a scenarios, and they are art, and all good scenarios should work in part “artistically” to defamiliarize the world as art does. (For background on Schklovsky and defamiliarization in art see here)

Squint/Opera is an interestingly multi-disciplinary group. It is a film and media studio that makes visualisations about the built environment, in their terms: “combining humour and narration with imaginative design, innovative visual effects and illustrative techniques.” A scenario firm, in other words, with apologies to the scenario planning traditionalists.

Chapter 1: Recognizing Forecast Intentions, deals with considerations of how forecasts come about, who makes them, and with what intention. Those who research and produce forecasts, those who invest in understanding trends and drivers of change, and those (including the media) who bring the forecasts and their implications to our attention, inevitably have reasons for doing so – to benefit from the knowledge by seizing opportunities or avoiding threats or by affecting outcomes in the world. Understanding a forecast’s “return on investment” gives us an important vantage point in assessing the merits of a forecast.

Chapter 2: The Quality of Information, shows how a forecast communicates information between forecaster and reader subject to the same standards of accuracy, truth-telling, and bias-control by which one would judge any communication. Forecasts can be very different in methods and goals, but all forecasts lay claim to factual truth, particularly truth in the data, and the argument deals with the various ways in which data can be less solid than it looks, even with the best intentions.

Chapter 3: Interpretation and Bias, considers how data – whether good or bad in itself – can be interpreted or misinterpreted in forecasting, that is, the “political” aspects of forecasting. Just as there is no value-free look at history, so too there is no value-free look to the future and asking the right questions allows us be ready to mentally rebalance forecasts that are presented.

Chapter 4: Paradigms and Perception, investigates how predictive statements are exposed to a broader form of interpretive bias that has to do with the forecaster’s mental model or “paradigm,” and the “zeitgeist” (spirit of the times) when the forecast is made. This chapter investigates situations where forecast failure is caused by failure to escape society’s current mental models – which often do not hold through the forecast period.

Chapter 5: The Utility Principle, considers economic and market forces, and the role of consumers, in promoting or resisting the future. Without reigning in creative thinking, some simple economic filters inevitably apply direction or timing realism to futurist flights of fancy.

Chapter 6: Drivers, Blockers, and Trends, consider drivers and blockers of change, and how viewing these dynamics improves forecast assessment. It identifies the roles of Drivers, Enablers, Friction, and Blockers acting on events to cause change or resist it, and problems in dumbly projecting current trends.

Chapter 7: The Limits of Quantitative Analysis, discusses the role of statistical analysis and quantitative modeling in predicting the future – where this is possible and useful and where it is not, and why not.

Chapter 8: The Systems Perspective, investigates “system effects,” which occur whenever different elements or variables that may appear isolated are in fact linked together, such that changes in one element cause changes in others. Anticipating future behavior of any variable hinges on identifying the broader systemic elements influencing it and failing to do this is a big part of what causes forecasts to fail.

Chapter 9: Living with Alternative Futures, investigates non-predictive ways of approaching change – where the tone is more about managing uncertainty than predicting the future. It acknowledges unfathomable complexity of most future questions and provides perspectives that raise chances of success in an inherently unpredictable future.

Chapter 10: Forecast Filtering in Action, illustrates the processes of the book by applying them in case studies to real-world sample forecasts that decision makers in business and policy areas might find themselves interacting with. This demonstrates how real everyday predictive material may be probed and critically evaluated, following the principles developed in previous chapters.

Chapter 11: A Forecast Filtering Checklist, is a cross-cutting checklist which summarizes the principles of the book in one convenient, thematic list.