Posted by Adam Gordon on Feb 4, 2010 in all, decision-making, foresight tools & methods, history, innovation, strategic foresight
I’ve been flying across the world recently, which has given me a few quiet moments to read a real bona fide book, and the one I have been busy with is Peter Bernstein’s Against the Gods: the Remarkable Story of Risk (Wiley, 1996). It’s aclaimed all over the place, particularly in risk management circles, but I’d never quite got to it.
Anyway, this is in the intro (p5), and I found it a perfect encapsulation of a core problem in foresight thinking — quantitative vs qualitative methods — well worth retyping out to have on hand for reflection. Here goes:
“The story that I have to tell is marked all the way through by a persistent tension between those who assert that the best decisions are based on quantification and numbers, determined by the patterns of the past, and those who base their decisions on more subjective degrees of belief about the uncertain future This is a controversy that has never been resolved.
The issue boils down to one’s view about the extent to which the past determines the future. We cannot quantify the future, because it is an unknown, but we have learned how to use numbers to scrutinize what happened in the past. But to what degree should we rely on the patterns of the past to tell us what the future will be like? Which matters more when facing a risk, the facts as we see them or our subjective belief in what lies hidden in the void of time? Is risk management a science or an art? Can we even tell for certain precisely where the dividing line between the two approaches lies?
It is one thing to set up a mathematical model that appears to explain everything. But when we face the struggle of daily life, of constant trial and error, the ambiguity of the facts as well as the power of the human heartbeat can obliterate the model in short order.”
Posted by Adam Gordon on Nov 19, 2009 in all, decision-making, emerging technologies, failed predictions, foresight tools & methods, Future Savvy, Perils of Prediction, scenario planning, strategic foresight, technology change
In a recent Times article ‘The future was never going to be the C5‘ actor-comedian Ben Millar offers a familiar criticism of foresight work. Inter alia he says: “For all our achievements in art, science, and technology, the human race has always been spectacularly bad at predicting the future. Literature is littered with shockingly wide-of-the-mark utopias, dystopias, shiny suits, flying saucers and whole meals contained in a single pill. As a child of the Seventies, I was taught that as an adult in a world run by machines my main challenge would be how to spend my endless hours of leisure time…”
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.
read morePosted by Adam Gordon on Oct 29, 2009 in all, economy & finance, failed predictions, forecast filtering, foresight tools & methods, managing uncertainty, Perils of Prediction, risk management, strategic foresight
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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read morePosted by Adam Gordon on Oct 19, 2009 in 2015, all, economy & finance, failed predictions, foresight tools & methods, managing uncertainty, scenario planning, strategic foresight
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.
read morePosted by Adam Gordon on Oct 2, 2009 in all, economy & finance, failed predictions, foresight tools & methods, managing uncertainty, prediction markets, strategic foresight
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.
read morePosted by Adam Gordon on Sep 14, 2009 in 2025, all, emerging technologies, failed predictions, foresight tools & methods, managing uncertainty, Perils of Prediction, technology change
I note from a link on the Ian Miles Futures blog that “2025: Scenarios of US and Global Society Reshaped by Science and Technology” by Coates, Hines, & Mahaffie, is now available free for full-text download.
For full disclosure, I should say I worked in the Coates office in Washington D.C. during the mid-late 1990s (but got there just after the book was done.)
There are deep and ultimately overwhelming problems with the book itself. It sees science-technology as the primary driver of change, when what science is done and what technology is produced is often the product of policy or economic or values / zeitgeist decisions further up the chain. It also has an astoundingly poor conceptual framework (‘Worlds 1, 2, 3′) for dealing with non-US societies and cultures, and their economic and social development: one that would make Tom Friedman (‘World is Flat’) giggle and Hans Rosling surely cry. Truly there are many reasons they have to give this book away for free.
But its importance is elsewhere. It remains remarkable for one thing — the thing that the Coates & Jarratt foresight firm was known for — a willingness to speculate confidently and in detail (and sometimes even stupidly) about future changes. The book is likewise exemplary in its commitment to concrete, interesting, ‘fearless’ long-range speculation, in a world where most analysts waste most of their foresight ink timidly equivocating and covering their back.
Quality, reloaded
Evocative, concrete speculation is important, even if it is wrong. It is commonly misapprehended that the purpose of foresight work is to “predict the future,” (and someone with this perspective is going to pop up in 2025 and say “so, how right or wrong was this book?”) But, nobody can be right. The real value of foresight work is other: to know as much as we can about the present, and the forces and factors changing it, to be able to preconceive the full range of possible future outcomes that pertain, in order to make decisions today towards an outcome we prefer. (Who “we” are and what “we” prefer — social welfare; shareholder value maximization; environmental sustainability, etc., — will vary hugely among interest groups of course.)
This preconception (of a range of scenarios, if you like) is what allows truly effective discussions and debates to take place in considering alternatives, and therefore promotes better decision-making regardless of whether the scenarios ultimately turn out to have been, in themselves, ‘right’ or ‘wrong.’ High-quality scenarios are to be preferred of course, but quality is in the ability to stimulate and provoke management attention to the right areas in a timely manner, not in having been right in prediction. As Coates used to say (and I echo this to my Industry Foresight students): “You don’t have to be right, you just have to be interesting.”
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