Future Savvy: Quality in Foresight

I was lucky enough to have Future Savvy included in a lengthy review of critical thinking in forecasting & foresight, done on the SmithySmithy “info-savvy” blog. The post also included Nassim Taleb’s ‘The Black Swan’ (2007) and ‘Fooled By Randomness’ (2005); Kenneth Posner’s ‘Stalking the Black Swan’ (2010), and Chris Luebkeman’s Drivers of Change (2009).

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?”

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I had a chat the other day to Stephan Magus for his Abenteuer Zukunft (Future Adventures) podcast channel, taking about the rationale behind making a stand for quality in foresight. That is, what’s under the hood of Future Savvy, and why.

The podcast is up at the Abenteuer Leben site, playable via the buttons on the right hand side.

Alternatively it can be accessed directly at

http://media1.roadkast.com/abenteuerzukunft/DAZ71_120410_6tt6.mp3

(If you don’t speak German, you need to fast forward through the first 3 minutes.)

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I couldn’t resist reposting this yesterday’s bit o’ fluff from the cleantech news portal Greenbang, itself reproduced from Forum for the Future, first, well because it cites yours truly; but even more agonizingly because the headline is exactly what I should have called Future Savvy if I knew the first thing about marketing, which I obviously don’t.

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.

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As of writing, Blockbuster clings to business life, with $1 billion in debt, unprofitable stores and continued losses, and it looks inevitable that it will file for bankruptcy protection. In Q4 ’09 the company posted a loss of $434.9m on revenue of $1.08bn. The stock price has fallen is $0.26 per share, down from lofty levels of over $15 in the early part of the decade. That’s a lot of shareholder value down the drain. *

Reading analysis by John Tamny in Forbes, I lighted on the following paragraph — as perfect an encapsulation of why looking to the future in timely and in a high-quality way is essential, and how quality horizon scanning is integral to it:

“As often happens as companies grow, Blockbuster concentrated on perfecting its existing service while beating competitors offering the same instead of looking into ways that outsiders might destroy its business model altogether… For Blockbuster, the “disrupter” in question was Netflix. Indeed, popular as the Blockbuster brand was, getting to the video store in order to take advantage of its services was a hassle for customers–as was returning videos on time to avoid paying late fees. The rise of Netflix from well outside the traditional retail space meant these problems were solved in one fell swoop.” (my italics)

Change that matters, that is, relatively sudden and acutely disruptive to incumbent business-model success, always comes from outside an industry. Britannica wasn’t beaten by another encyclopedia. Eastman Kodak was beaten by digital photo startups, not by Fuji. And so on, and so on, through industry failure, whether it leads merely to value hemorrhage or all the way to Chapter 11.

Looking vs seeing

Sure there are companies that lose because they are simply outcompeted, that is, are less capable than the competition in doing the same thing. Hertz is currently in this category. But when a clear market leader, with brand and capital and customers galore comes totally unstuck, it is always new technology and/or new business model coming from the outside that has done it. In these cases, as with Blockbuster, companies fall to industry entrants that change ways of doing things, solving pain or trade-offs that buyers suffer, or otherwise provide consumers with more value.

These are always, theoretically, innovations incumbents could have done themselves if they were ready to think ahead (and brave enough, when required, to cannabalize existing products that stood in the way of important future steps) and therein lies a conundrum about looking at new, external competitors. It’s seldom that the incumbent can’t see the intruder, that is, is not looking. Often they are looking intensively. It is that they don’t see the absolute disruption in the new until it is too late. It is a problem of perception. This is why industry horizon scanning is a little about the easy task of looking, and a lot about the much harder job of seeing. And why putting one’s corporate head down and making an existing product or service ‘more perfect’ is part of not seeing.

* Interestingly, the Blockbuster demise was called exactly right in November 2007 by Don Reisinger on CNET.

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We owe a debt to Nassim Taleb for memorably encapsulating the demerits of predicting by extrapolating trends as “The Turkey Problem,” and now seems the moment to reiterate it:

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.

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I’m pleased to have been invited to be one of a dozen or so regular contributors to the blog ‘Risk Matters,’ because, well, risk matters. It’s a key part of the reason why anyone or any group would look to the future… which of course also conditions how we look, what we look for, and what we find or miss.

So this stimulates me to put down a few thoughts about risk assessment and its relationship with industry and strategic foresight as a whole. This is a big topic of course, but seeing as the categories are confused a lot, it’s worth tackling even if just in summary terms.

When I reach the topic of Risk Assessment in my ‘Industry Foresight and Business Future Strategy’ MBA elective, I use the ‘Adidas-Salomon: Incorporating Risk into Corporate Strategy’ mini-case [Ref: ICFAI 304-141-1; sourced via Cranfield’s Case Clearing house.]

The case is a useful baseline in risk assessment because it describes the various risks a multinational company typically faces: marketing risks (market change, brand image); operations risks (quality; reliability of processes and suppliers); social & environmental risks (workforce & natural resources compliance); legal (liability, regulation, patent); information technology (compromise or disruption); and financial risks (currency, interest rate, credit).

Business disruptors
In sum these are the things that could damage or disrupt the business. Isolating such factors, keeping vigilance over them, and having thought through or enacted counter-measures in advance, allows the organization to better control or reduce the impact should risk become reality.

All risks are future events, so a risk assessment is undoubtedly a future study, but assuming a company looks diligently across all these categories for potential and emerging hazards, how prepared is it for a changing world? What kind of industry foresight does this give managers? Is a risk assessment a futures assessment?

The obvious first answer is that a risk assessment is only half the equation. It’s oriented to the downside potential of changes not the upside; looking for threats not opportunities. Obviously that means that opportunities are less likely to be identified.

The second thing is that a standard risk assessment operates in the realm of known risks, in known categories, that may cause disruption and damage in a known way. It doesn’t have the mechanism to expand conceptions of what could go wrong, or how it could go wrong, or what the full knock-on effects will be. The types of mental-model-expanding techniques that fuller foresight offers are not built into a typical risk assessment.

Strategy questions
Third, risk assessments never really broach the question: is the business idea or business model good and will it keep on being good? That is, what products or services will be appropriate going forward, or how will models of supply or manufacture or marketing or fulfillment need to change, due to technology change or shifting consumer preferences.

In other words, risk assessment doesn’t ask strategic questions of managers. It is part of the day-to-day management vigilance necessary with reference to the future – the hygiene factors in running an organization. It is about keeping the business going as is, not about changing it for a changing word.

There’s nothing wrong with this. The point is, it’s just ‘first base’ in building a quality view of the future, and therein a robust point-of-view about what to do next. Although no doubt companies such as Google or Apple or Virgin, etc., assess and mitigate their risks, they didn’t become successful in their future by doing risk assessment and saying ‘That’s it, were done. We’re ready for the future.”

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In Monday’s Washington Post, under an Op-Ed headed ‘Could America Go Broke?’ columnist Robert Samuelson raises the prospect of the U.S. or another major economy defaulting on its national debt. Says Samuelson: “It’s still a very, very long shot, but it’s no longer entirely unimaginable. Governments of rich countries are borrowing so much that it’s conceivable that one day the twin assumptions underlying their burgeoning debt (that lenders will continue to lend and that governments will continue to pay) might collapse… The question is so unfamiliar that the past provides few clues to the future.”

Well, this raises the question of whether the past tells us anything about the future, and if so what? There’s a common wisdom attributed to Mark Twain (why is it that aphorisms are always attributed to Twain or Winston Churchill?) that goes: “History doesn’t repeat itself, but it often rhymes,” and this is the position that most educated future-thinkers would hold.

So what would the ‘rhyme’ be? From cases such as Argentina, Russia, South Africa, and many developing world countries over the past 50 years: lenders loose confidence in a country’s ability to repay on its national bonds and stop lending; the country is faced with a choice of drastic spending cuts (great social and humanitarian cost) or major tax increases (pointless, because it stifles business, therefore lowers tax revenue) or default. Going broke, into national “Chapter 11,” suing for time and ‘debt restructuring’ becomes the best among the bad options event though it pretty much ensures a deep and dark recession.
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Thinking the unthinkable

Could this be the future of America? As I’ve written before here and other places, after the ‘unimaginable’ Credit Crunch was ignored due to its ‘low probability,’ it’s a relief to know that remote but plausible outcomes with serious consequences are getting attention, at least in the Washington Post.

Clearly major economies are in a more precarious situation than they were 5 years ago. Too much debt is always precarious, for the smallest household or the biggest country alike. On the other hand, an economy’s size and enduring wealth counts too. As Samuelson observes, it created the unexpected effect in Japan’s case where debt at 200% of GDP (America’s is currently about 40%) should have raised the cost of its debt (lower confidence of repayment) but this hasn’t happened because domestic Japanese households and businesses rather than foreigners have easily (and confidently) bought the debt — and this may well hold true for the U.S. too. In other words, the rhyme may go this way.

The ‘more likely’ future is incremental raising of taxes and lowering of public service provision as Western economies incrementally claw their way back to stability. But at least this default wild card on the margins of plausibility has the oxygen of some attention and this is no bad thing. As with all good foresight work, it predicts nothing, but it does allow us to think through the roadmap to the outcome, and press for the right decisions now, in plenty of time and in a measured way.

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Continuing the theme of financial types talking to each other about predictions and predictability, this ‘Tea with the Economist’ interview of Stephen Roach, Chairman, Morgan Stanley Asia by Economist New York Bureau Chief Mathew Birk, carries interesting lessons about the limits of prediction.

Birk commends Roach for being one of the few to have predicted the Credit Crunch problems, to which Roach demurs in saying he was “too early”. He then furthers his modesty in saying that the “breakage” in the financial system was “in excess of anything I envisioned.”

Self-deprecation in assessing one’s predictive abilities will endear anyone to me. Even Roach, who later in the interview burns this hard-won credibility by laying the blame for the credit crunch at the door of regulators, forgetting how hard financial institutions lobbied regulators for greater freedoms in the 1990s.

But I digress. The predictive issues the interview raises are as follows. Issue one: it’s not enough (as any stock short-seller will confirm) to get the direction of a future change right. One must get the timing right too. Issue two: it’s not enough to anticipate a change. One must be able to judge it’s impact. Getting either timing or impact wrong is effectively to have missed the future.

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Probability

On the latter topic — the problem of impact — Nassim Taleb is unrelenting, and he is right. Analysts routinely mix up probability and impact. They think that because an event has a low probability (‘it would be a 10-sigma event!’) it can be marginalized in the predictive number crunching. Of course, it can’t. The low-probability of a wildcard or black swan event is irrelevant because when it happens it will change the game, and that’s why, in every predictive situation of reasonable complexity and uncertainty, using statistical extrapolations (regressions and so on) to predict, is to dangerously paper over the cracks. It is precisely the cracks that businesses and policy makers need to worry about.

Determining the direction of change is hard enough. Assessing timing or extent of impact — a ‘total future impact index’ — is wickedly difficult. It’s a task not to be underestimated, and to simply extrapolate current trends (= assuming the trend’s timeline and impact stay the same as in the past) is the royal road to underestimating it.

This is the reason foresight for complex, uncertain, changing situations can only be grasped by NOT predicting (quantitatively or otherwise) but by exploring the limit-conditions of the plausible (What would happen if the timing of the change accelerated, or was significantly delayed? What if  the impact was 10x or one tenth of what we expect? And so on.)

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One of the benefits of scenario-based future thinking is the ‘permission’ to think through alternative future outcomes without necessarily predicting them. ‘Predictors’ focus, by contrast, on isolating the highest probability future in order not to have to think through or plan for less likely outcomes.

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.

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The sustained market rally, with stocks up over 40% on average since the lows in March 2009 (The Dow Jones Industrial Average was about 6,500 in March 09; it is now about 9,500) is taken to be a forecast that real future economic recovery is on the horizon. But is the market a reliable forecaster of anything? That is, from the perspective of real industry and strategic foresight professionals, using hard-won, battle-tested approaches to anticipating future outcomes, should we factor the market’s direction into our expectations of the economic future?

DJIA since Sept '08

The answer is, broadly, yes. Stocks are shares in the future earnings of a company. They are therefore a “bet” on (er, an “investment” in) the future performance of a company, or many companies. The trading price on any day is the price at which there are as many buyers as sellers for these future returns. Rising prices mean there are more buyers than sellers, that means general expectation of future profits is going up. Investors are putting a higher price on the future.

The market is therefore considered a leading indicator of economic conditions. (By contrast, employment figures are lagging indicators — due frictional forces, not to mention morality, it takes companies a while to downsize in recessions or upscale in booms, so employment levels track economic conditions but with a delay.)

But how valid and dependable is the market as a leading indicator? It is also apparent that markets move up slowly and steadily, but fall in a hurry. So the downward move can hardly be held to be predictive. But the upward move appears to hold some weight as harbinger of better times. How much weight?

What’s particularly important is that the aggregate insight into future returns from shareholding investments — across many investors and many stocks — cancels out individual errors. Any one person may have a dumb idea of the ‘future cash flows’ from one or many companies, and the price of any one company may be unreliable for innumerable reasons, including fraud, but the knowledge and intelligence of hundreds of thousands of people, when aggregated and spread over many thousands of stocks, corrects for all these errors. It becomes robust.

Prediction Markets

This reliability of shared, aggregated insight — the wisdom of crowds — is precisely what makes ‘prediction markets’ such a powerful forecasting tool, as I have mentioned in previous posts. (Prediction markets apply market-like wisdom to create foresight in areas that are not normally ‘tradeable.’) Any one person will, as likely as not, get it wrong, but everyone together, rather astoundingly, get it right.

Ironically, crowd wisdom is much more reliable than the technical forecasting models that investment institutions use to try to determine how business, macroeconomic, interest rate, or other conditions will affect future stock prices. These predictions, based on the assumptions of a handful of model programmers and/or model users, are deeply vulnerable because there is no crowd-wisdom balance. It’s no better than reading tea leaves, only apparently (and unaccountably) more respectable.

Having said all this, it is well known that the ‘crowd,’ aka the ‘herd’ can and do all get it wrong together. This is what happens in price bubbles, or panic market exits, with everyone buying or selling because they are making the same wrong assumptions, or just doing what everyone else appears to be doing. (Most players making the same mistake together is the basic problem when prediction markets fail too.)

However, what is clear is this case is there was a very hard sell-off in the months prior to March 09, following revelations of the gravity of the Credit Crunch, but that this has slide has been arrested and mostly reversed. This says that innumerable smart people with, collectively, billions of dollars at stake, are expecting future profits higher than they did in March. That’s a prediction one can rely on.

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