Future Savvy: Quality in Foresight

Charlie Munger, Vice-Chairman of Berkshire Hathaway Corporation, the diversified investment firm chaired by Warren Buffett, has a piece titled: ‘Basically, it’s Over‘ in Slate this week.

Charles Munger

First, let me say, what I like about investors (and managers and entrepreneurs) with long-term track records of success, is it means — it must mean, by definition — they have a high quality view of the future. Not only a high-quality view, but a high quality view that renews itself. There is no doubt that Berkshire Hathaway has consistently over time had a better view of the future than most expert forecasters, policy pundits, and futurists. The record is clear.

Anyway, Munger this week offers a parable about Basicland, a C18 Pacific island colonized by Europeans where: “Property rights were greatly respected and strongly enforced. The banking system was simple… Almost no debt was used to purchase or carry securities or other investments, including real estate and tangible personal property…  Speculation in Basicland’s security and commodity markets was always rigorously discouraged and remained small…

“(But) as their affluence and leisure time grew, Basicland’s citizens more and more whiled away their time in the excitement of casino gambling… Many of the gamblers were highly talented engineers attracted partly by casino poker but mostly by bets available in the bucket shop systems, with the bets now called “financial derivatives.”

And so it goes on, telling the history of America and the route to the Credit Crunch, and potential for new misery going forward, via this parable. He uses the parable as parables have always been used, to say something in ‘make-believe-land’ that cannot be said (or will not be heard) in reality. The folly of Basicland’s citizens and government is much easier to acknowledge than our own. Scenarios of the future are similar in function, similarly allowing mental and institutional ‘permission’ to think the unthinkable and ’say the unsayable.

The worst investor in America

Munger wouldn’t be the first to say: “Change yer ways or ye be doomed.” Isaiah and many before and since have said that. Nor would he be the first old white guy to espouse traditional ways of doing things. We factor that in. But he does look to basics and basics are important in having a high-quality view of the future. They signal the limits of the excess and reversion-to-the-mean imperatives.

I remember in the 1990s, when I was living in Washington DC, and Warren Buffet was “the worst investor in America” for missing out on the dot.com boom and Nasdaq bonanza. He just stuck to his guns saying, time after time, ‘there are no fundamentals behind these valuations (aka, this is just a casino) and fundamentals will prevail, which of course they did.

Now the brains at Berkshire Hathaway are saying that forums where risk, debt, currencies, etc., are up for speculation are ‘casinos,’ and their players therefore gamblers (rather than, as they would have it, ‘investors), and that they produce little fundamental value and fundamentals will prevail.

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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.”

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Economists make a handy, if mildly irreverent, distinction between “freshwater” and “saltwater” economics. Freshwater refers to economic theory that rests on the efficient markets hypothesis — a belief in the efficiency and rationality of free markets. It is associated with Milton Friedman and the University of Chicago school. It was the thinking behind Thatcher and Reaganomics and still more-or-less holds sway today, or it did up until the credit crunch.

Keynesian or saltwater economics by contrast holds that free markets often behave irrationally and inefficiently, and therefore need corrective policy from government. Saltwater economists say people and institutions often behave in ways contrary to the general good, or in ways that can bring markets (on which they depend) to their knees. Sound familiar?

Anyway, a recent Knowledge@Wharton article comments: “Like a natural science, freshwater economics lends itself to complex, often elegant mathematical modeling. The freshwater view is that consumers, offered an array of choices, will select the one that is best for them — a straightforward assertion that can be neatly expressed in mathematical formulae.

“In contrast, many assertions made in behavioral economics are more challenging to express mathematically. ‘Behavioralists’ argue that consumers don’t always act in their own interests, especially when they fail to understand the choices on offer or succumb to irrational impulses involving those choices… but such impulses are inherently vague and difficult to define.”

Cognitive bias

In other words mathematically modeling the economic future is possible if humans and the markets they create are rational, but far less possible if we act irrationally.

Now, as elaborated in Future Savvy, the fact that humans make irrational choices due to many cognitive biases and heuristics  is indisputable, not least since the work of  Tversky and Kahneman. Biases and heuristics such as “anchoring,” “recency effect,” “personal validation fallacy,” “herd mentality,” and so on, in which people make irrational choices, are well documented.

That’s why mathematical projections of economic behavior are unreliable. The economy may be counted in numbers, but it is still a human system, with associated inefficiency and irrationality. Blow this little debate in economic forecasting up large, and you have the essential problem with quantitative forecasting of any type. It assumes, erroneously, a freshwater view of humanity.

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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.

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Peter Bernstein, the author of “Against the Gods: The Remarkable Story of Risk,” died recently at the age of 90. In memoriam McKinsey Quarterly reposted this recent Bernstein interview. I put it up here because it’s a timely and timeless lesson in thinking about uncertainty and threats, and avoiding simplistic (quantitative) approaches to managing them – one of core themes of “Future Savvy.” Bernstein offers and endorsement of real options and explains why sophisticated Long Term Capital Management (LTCM) mathematical models to control risk created “a math dependency” that was blind to, among other things, unexpected systemic feedback to its own emergence:

One of the first things Bernstein says is that risk implies that we don’t know what will happen, which could be good things happening too. Risk management, as it is currently understood, gets executives to look at what could go wrong in the uncertain future of the enterprise. (Somehow threats are easier than opportunties to get departmental budget for.) The standard approach is to break risks down into commonly understood threat categories: a typical analysis would illuminated risks posed by technology failure, communications failure, security failure, natural disasters, accidents, or market/reputation risk, liability risk, financial/credit risk, and so on. This negative-outcome identification is typically followed by strategies to monitor, minimize, or control the risk event or its impact.

Doing all this is great, BUT it is just a narrow part of enterprise and industry foresight. Why? First, industry foresight or futures studies for business is focused as much on the opportunities change offers as on threats. Second, foresight tools (when correctly applied) set themselves the task of enlarging perspectives or mental maps so that we can see more things, or more possibilities than the generally expected set (whether good or bad). Set against this, risk management is little more than the catalog of known threats. The unknown or poorly understood threat, or unseen opportunity missed (and grabbed by others) is likely to be more damaging to the enterprise.

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I’ve been quite careful not to use this blog as a “brag wall” for Future Savvy. I can say reviewers have all been glowing, without exception. But this review, below, which recently appeared in the St Andrews Management Institute’s Vector Magazine, I felt was worth reposting here because – more than just saying nice things – it also captures the essence of what the book is trying to do. Here it is:

Book reviews by SAMI fellows and associates
“Future Savvy” by Adam Gordon (American Management Association, 2009)

“Forecasts and predictions are ubiquitous. We are bombarded with views of the future on a plethora of subjects from myriad sources, with a diverse set of motivations and self-interests. Adam Gordon seeks to provide a practical users guide to the assessment and interpretation of all things about the future, with special emphasis on the cautions and ‘health warnings’ that need to be applied, so as not to be misled by forecasts. However, the author is careful not to veer towards over-cynical dismissal of all future projections; rather, he seeks to provide guidance to the reader on how to apply the necessary caveats, and in the author’s words “profit from change”.

The book covers a very broad field, from the basic issues of the misuse of data and statistics, covering the quality and validity of data as well as their misinterpretation, through technology forecasting, trend and horizon scanning to quantitative modelling and scenarios. The one theme common to all these activities is the need to be alert to bias, whether it be a deliberate motive to influence behaviour through a dire prediction; or a bias inherent in futurologists needing to see rapid and pervasive change in all areas of society – if it exists or not – and evangelising it.

The track record of much futurology is mixed. Well-known examples are quoted: television did not lead to the end of the cinema industry. Nor has space exploration led to people taking foreign holidays on other planets – yet! Bias may also lie in the beholder. The ‘Zeitgeist’ tendency, whereby we are all influenced by contemporary perceptions, affects not only how “experts” and professionals see the world, but also how the audience receives the views of the future – often with unprepared minds. The internal “official future” of an organisation can pose a real blind spot to its progress.

The weaknesses of much quantitative modelling are highlighted, with such forecasts only being as good as the assumptions on which they are based, but which are often not overtly stated. In contrast to the conceptual and practical errors inherent in much futures output, the role and advantages of scenario planning are emphasised as a tool for challenging assumptions and developing alternative futures: “It’s better to be vaguely right than precisely wrong”.

The penultimate chapter takes examples of relatively recent forecasts from a range of organisations, whose subjects range from US agricultural production to UK dementia sufferers. These are subjected to a form of ‘retro wind-tunnelling’ to illustrate the deficiencies in their construction and how they would have benefited from the application of methodologies described earlier in the book. The final chapter provides a summary checklist, or framework, to apply in evaluating forecasts and future predictions.

Adam Gordon has written a shrewd and perceptive book that deserves a wide readership, especially among managers in both the private and public sectors, as well as the familiar ‘general reader’. Those wishing a more detailed technical guide to the various forecasting and futurist methodologies will need to consult other standard works. Professionals in the fields of management and strategy consulting and scenario practitioners might well be familiar with many of the points made in the book. However, those with some savvy might do well to recommend the book to their clients.

Michael Owen, 20 April 2009

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Prediction markets have been in the news a lot for their forecasting potential. These markets – where participants buy and sell bets as to whether future events happen or not – mimic “real” securities markets, so it stands to reason that real markets are predictive too, and they are.

My question, as the Dow Jones Industrial Average (DJIA), and the FTSE100, the DAX, the Hang Seng and so on have hit a decade lows is, what is this predicting, if anything? What is the long-term value of this prediction, and could it be used to make better decisions in the real world?
We know that the value of a common stock – a share in a company – is based ultimately on the returns (dividends) it will bring. Buyers and sellers therefore derive a daily market price based on their views of the share’s expected, that is, predicted future payback. The greater the expectation, the greater the price. A high price vis a vis earnings (P/E ratio) suggests confidence in future earnings, and vice versa.
Therefore the current steep fall in share prices is an expectation of (crowd prediction of) lower future payouts. Of course the complexity in human-prediction situations is that this basic level is also overlayed with a meta-level: people are not only trying to figure out what will happen, they are trying to figure out what others think will happen. So falling PE ratios are an expectation of what others will do (predicting they will continue to sell.)

Madness or not?
One of the perplexing things about the markets is they very often seem to react opposite to what is expected; to what would be common sense. They often fall on good news, rise on bad news, close unchanged on big news, and so on. Although there is – famously much irrational behavior and herd instinct in the market – you don’t get hundreds of thousands of decision-makers wagering significant money not using common sense.
What is going on, of course, is that the market has often already risen or fallen in prediction of the news. When a new condition – an interest rate move, for example – is imminent, the market will move to “price in” the expectation. If market participants as a whole have called the future correctly the market will not move much on announcement.

Pricing-in the future
Because of this predictive component to group decision-making in market situations, the stock market as a whole is a classic leading indicator of the real economy. When prices move they may be taken as the crowd “pricing-in” a future prediction. So markets will fall ahead of real economic problems (they may continue to fall, as now, during steep economic declines.) But they will also turn up well before any real, measurable upturn.

By the way, there is little doubt it will overshoot in this time, as it always does. This is because, as in prediction markets, the wisdom of crowds can predict the trend but not the turn. Trend extrapolation will never show you the key shifts, and this is why predicting the bottom or top of a market is so hard.

The point, for market speculators, is that long before the real gloom is over the markets will be zooming upwards. The point for the rest of us is that recession times will be with us even after the markets move up. In the long term the market will go up. Like death and taxes, it’s the surest thing there is.

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Publication of the Institute for the Future’s “Map of Future Forces Affecting Sustainability” on the same day that it is revealed that Sir Fred Goodwin (50) of failed & baled Royal Bank of Scotland (RBS) will get a £693,000 (about $1,000,000) a year payment for the rest of his life, gets me thinking about short-termism and its entrenchment.

The IFTF’s full map is available for download here.  Quick aside: these maps, putting complex forces into visuals, have defined IFTF’s public (and client, one presumes) communications for over five years, and have raised the bar of excellence in the foresight communications. The company has produced many such outstanding maps, some publicly available.

The new map and Sir Fred-gate are unrelated of course. But here was the connection for me: The IFTF map lists six “Key Driving Forces” (2007-2017) in the area of sustainability, and the first is:
“An Imperative for Looking Long: The 21st century will test our ability to grasp the future impacts of present choices, but even as we struggle to incorporate future knowledge into our day-to-day decisions, we’re tuning up our bodies and minds and even our cultural frameworks for a much longer view.”

My question is, “really?” Is the long view really a driver – something that will drive change and shape the future? Or do we hope it is. Are we trying to talk it into being?

No question that the long-term view is crucial. Solving just about any social, technological, or environmental problem requires sustained long-term action. And everyone who works in foresight keeps evangelizing long-termism. But, in fact, what we have in industry and government is rampant short-termism and there is no indication this will change, despite the crisis and many heartfelt calls.

Linking big to long

The problem with Sir Goodwin’s package (in career and in retirement) is that the reward numbers were based on short-term company returns. “Hey, we made lots of money this year, so you get a big bonus, and you get a big bonus,” etc. But a few years down the line  – in the long term – it turns out that no bonuses were valid (if a bonus is, truly, a reward for success).

Put it another way: in finance, as in other aspects of society, technology, and the environment, we don’t know if we’ve succeeded or failed until the long-term numbers are in. Few would have a problem with handsome rewards for a valuable job well done, but those rewards must surely be delayed, and delayed, until we are in command of the long view of the performance.

Easy in theory, hard in practice. Perhaps impossible in practice when most politicians and legislators are themselves on a short 3-7 year cycle, like CEOs. I have some inkling from the IFTF map that the thinking is that life-extending technologies will improve to the point where people will really see themselves in for the long haul, and so adopt a longer perspective on benefits and rewards.

Time on the clock

Perhaps. But, life-technologies aside, plenty of decision-makers – Goodwin included – still have a lot of time left on the clock and that doesn’t appear to stop them chasing and cashing in short-term incentives at the expense of the future. Or legislators (and the public who votes them in) structuring performance rating on our immediate perception of their performance.

What we have, and what we have increasingly had (the trend) over the past few decades, is systemic short-termism. Winning in the next annual report or the next election is what what leaders’ rewards are based on. Incentives for politicians or business leaders or even scientists or engineers to make a better world for 2025 or 2050 are negligable.

Until there is reason to anticipate that this fundamental underlying short-term incentive structure and mentality changes (that is – convince me – who will change it and how?) the future savvy perspective must say that the “long-term imperative” remains a nice sound-bite, but not a material driver of anything.

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All crises of the present can be viewed as a failure of foresight or planning at some previous point, and the current global economic crisis is no different.

The mood is justly sombre at the World Economic Forum’s Davos meeting this year, as grim-faced world leaders mull over the dismal state of the global economy and how to fix it. This is in marked contrast to recent years, when the top executives were warmly congratulating themselves on the general state of things.

In one sense this is perfectly understandable. The crisis is upon us and leaders should be directly and practically involved in tackling it. On another level it’s profoundly disturbing, because world leaders and senior managers should be doing more than merely responding to situations. When crises occur, crisis management becomes part of a leader’s job, but their real job is thinking ahead effectively to avoid crises and, on the positive side, develop opportunities.

Put another way: the heads of a companies or countries – Davos-level people – are tasked far beyond effective daily management. They are tasked, fundamentally, with negotiating the VUCA (volatile, uncertain, complex, ambiguous) world on behalf of the rest of us. If not them, then who?

This requires foresight and vision. In this sense, many who are at Davos this week are responsible for the current crisis. They failed to foresee it, in fact they generally endorsed the growth of complex financial instruments, the shadow banking system, and private equity growth –- much of which bypassed SEC or equivalent regulation, and which is now seen to be the root cause of the meltdown.

In fact much of the “new finance” system was thought to spread and therefore actually lower risk. Turns out that was a poor view of the future. In fact the present situation as a whole is the result of key decision-makers operating on a poor view of future. As a group, their mental model was not open to bad outcomes, or even just alternative outcomes to what was commonly expected.

Could we have thunk it?

Their response might be: “nobody can predict the future!” “Easy to say after the event!” This is true. But it’s common knowledge that there were those who foresaw the mess — The Times identified at least 10. As Davos attendees might now be forced to agree, some forecasts are clearly better than others.

This is where executive leaders can learn from the foresight field and particularly the history of failed predictions. Everyone relies on predictions for their guide to the future – nobody can be an expert in every field. And there’s never a shortage of them – they are frequently published in the media, offered by consultancies and think tanks, and are a key part of Davos.

While getting a prediction is easy, the key leadership skill is to be able to tell a good one from a bad one: that’s what turns a forecast into a strategic resource. That is what leads to better decisions, better plans, and better actions.

Can one do that? Can one critically assess a particular or consensus-held view of the future, to identify its strengths and weaknesses? Absolutely yes. Among the tests one can run on a prediction are:

•    assessing motivation – who is speaking and what their agenda might be, particularly if they have an interest in maintaining a current system or shaping the emergence of a new one
•    determining whether the tools used are appropriate to the level and type of uncertainty faced. High-uncertainty situations and long-term views require different approaches to standard modeling
•    questioning consensus mental-models and forcing consideration of alternative outcomes. All foresight is swayed by “zeitgeist” – spirit of the times – and good forecasts swim against this tide.

These are just a few among the many forecast tests one can run, as detailed in Future Savvy.  But even if Davos attendees had been applying just these three in previous years, their foresight would have been greatly improved. It won’t help with this crisis, but it might forestall the next.

* This article, authored by Adam Gordon, was first edited and published by Bnet.co.uk

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Happy New Year! Well, this time of year traditionally brings out the “January 1 quarterbacks,” poking fun at the wrong predictions for the year just past, awarding dunce caps, particularly (deliciously) to famous people.

This punditry is widely read, and sometimes published in respectable places. Some of it is just year-end fun, and nothing wrong with that. But there is also a failed-forecast “nyah-nyah” that is corrosive to the foresight field in general, which demands answers. So at the risk of giving the 20/20 hindsight artists undue oxygen of attention, here are a few thoughts:

Consider Foreign Policy’s “10 Worst Predictions for 2008.” (Dec, 2008). Highlights include:

“If [Hillary Clinton] gets a race against John Edwards and Barack Obama, she’s going to be the nominee. Gore is the only threat to her, then. … Barack Obama is not going to beat Hillary Clinton in a single Democratic primary. I’ll predict that right now.” —William Kristol, Fox News Sunday, Dec. 17, 2006

“Should I be worried about Bear Stearns in terms of liquidity and get my money out of there?’ No! No! No! Bear Stearns is fine! Do not take your money out … —Jim Cramer, responding to a viewer’s e-mail on CNBC’s Mad Money, March 11, 2008 [Bear Stearns was sold to J.P. Morgan Chase at about a 90% discount to it market capitalization at the time of the forecast]

“The possibility of $150-$200 per barrel seems increasingly likely over the next six-24 months.” —Arjun Murti, Goldman Sachs oil analyst, in a May 5, 2008, report [Oil was then around $130 a barrel. By late December it was below $40.]

Or this one from Business Week’s list of 10 (December 24, 2008)

“Existing-Home Sales to Trend Up in 2008″ —Headline of a National Association of Realtors press release, Dec. 9, 2007 [On Dec. 23, 2008, the group said November sales were running at an annual rate of 4.5 million—down 11% from a year earlier—in the worst housing slump since the Depression.]

The Future Savvy question is: how should we think about predictions like this? And how should we think about failed-forecast spotting?

1. Failed-forecast spotting is not remotely “scientific”
This should be obvious, but somehow never is. Purposefully extracting the failed forecasts from the total set of forecasts says nothing about the quality of the set in general. Many did predict Obama; did predict the downturn, etc.

2. Failed-forecast spotting raises a healthy skepticism, but runs to nihilism
Despite not passing any credible test of knowledge, at least failed-forecast spotting stokes apprehension about forecasts and the wisdom of experts. At base this is healthy. Prediction is hard, and it is mostly done poorly. And experts often transgress the boundaries of their expertise. (Typically, in this instance, they know a lot about their field, but often don’t know more than the next Joe about the future of their field, often because their expertise is wedded to existing practices and assumptions.)
Prediction skepticism is fine. What happens, however, is that tempts a “nobody can predict anything” nihilism. This is its own failing because many predictions are in fact excellent, producing good foresight, which is a key strategic and competitive advantage.

3. Often the short term future is harder to see.
This is the trickiest insight of the lot. As everyone knows, it’s impossible to accurately predict the future (which is not the same as usefully predict the future, see arguments in other posts). The world is just too complex, too chaotic. But there’s a wrinkle. It should be that the further we look into the future the harder it is to see. The world will change more – there is more time for unpredictable things to happen. The short-term future (one year, say) is closer to us, it should be more like today and we should be able to anticipate it better.

In fact, short-term foresight is the most impossible task: a casino game. In the longer term (10-20 years, say) strong trends can be relied on to have had their impact. For example, the move away from fossil fuels, or effective nanotechnology engineering, or simple domestic robotics, can be reliably forecast. But while the sweep of these and other similar evolutions are reliable over time, the short-term picture will suffer lags or reversals that follow no pattern at all. (It’s no accident that is this is just like the stock market. In the long term the market will go up, in the short term it can go anywhere.) Also short-term predictive failure is compounded by the fact that the standard to which it is held is higher – we expect specifics: dates, places, numbers, players, winners – that are not demanded of a long-term view. In other words, near-term predictions are all about “point forecasts,” and there’s nothing more impossible than a point forecast unless you believe in tea leaves and crystal balls.

The take away: short-term point forecasts really are a mugs game and the skeptics are right. Medium-long forecasts, when well done, are worthy of our strategic and competitive attention.

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