Posted by Adam Gordon on May 6, 2009 in all, decision-making, failed predictions, forecast filtering, foresight tools & methods, Future Savvy, leadership, management, strategic foresight
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
read morePosted by Adam Gordon on Mar 5, 2009 in 2015, all, decision-making, economy & finance, foresight tools & methods, management, managing uncertainty, prediction markets, trend tracking
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.
read morePosted by Adam Gordon on Feb 26, 2009 in 2025, all, decision-making, economy & finance, forecast filtering, leadership, lifestyles & values, management, policy, politics of the future, risk management, social change
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.
read morePosted by Adam Gordon on Jan 13, 2009 in 2015, 2025, all, emerging technologies, failed predictions, forecast filtering, innovation, Perils of Prediction, scenario planning, strategic foresight, technology change
Microsoft - Computer Electronics Show 2009
Product prototype communication is a close cousin of scenario building. Typically the company creates their product or service in action, in the future, being used by happy customers, their “preferred future” scenario. Prototype communication doesn’t typically build in alternative scenarios, the litmus test of strategy-based scenario work. It’s more a kite-flying exercise, designed to put out a future-oriented message to stakeholders and the public, garner broad feedback, and (if you’re powerful like Microsoft) put up “this-is-the-future-of-the-industry” markers.
Nevertheless, with the caveat that they are one among many plausible outcomes, product showcase scenarios can be an eye-opening guide to what’s actually possible and what the future will be like.
A newly released Microsoft “Future of Computing” video, showcased at CES 2009 in Las Vegas in the past few days, is an example. The 10-minute piece, presented by Janet Galore, Program Manger: Strategic Prototyping, takes us through a scenario of interactive education in the future (when, exactly, is not said but the implication is it’s not too far off) showing how participants would find, use, and share information across devices and across platforms.
What we see is a tablet PC that can communicate seamlessly with other electronics and interact with Web info on the fly. Okay nothing new there. What’s interesting is how it’s all held together by surface computing, a smart desk with a screen, which allows information to be viewed in the process of collaboration, sharing, and filing. In some futurist fantasies it is thought that communication is ideally invisible (my phone e-handshakes your phone without me doing anything, etc.) But actually humans mostly seem to prefer to see what’s happening, and to have the choice to interact with what is happening while it’s happening – not least so they know what machines have done and don’t have to pull their hair out before they find their precious work buried four subdirectories into the Temp folder… sheesh. But I digress.
The scenario focuses on organizing and sharing multiple inputs, therein making a pretty clear statement about the future: what will be really valuable is not access to information anywhere, anytime (an assumed, table-stakes factor), but a way to share and collaborate with the information in an productive way. It refreshingly assumes that whiz-bang graphics – they are there too – are the easy stuff, but that collaboration and teamwork are the hard things to get right, and the truly valuable service given the chaos of billions of voices and trillions of data objects that pertain in any human-work future.
The other real strength of the prototype and related scenario is its close attention to natural (or, at least, strongly socialized, conventional, classic) human ways of doing things, which are slow to change, and therefore will change slowly. The smart desk is something one can really see oneself sitting around, because this is what we already do. Also this future of computing envisages no stylus, no mouse, no magic wand to master. Rather, we move digital stuff around the desk with our hands. We point to it and we shift it. That is, digital capability accommodates and interlaces with Stone Age human and organizational patterns. That’s why this view of the future is persuasive.
read morePosted by Adam Gordon on Oct 22, 2008 in all, failed predictions, forecast filtering, horizon scanning, lifestyles & values, social change
They say a definite cure for romantic notions about any previous era of human existence is to think about the dentistry. That fixes any nostalgia. However it’s safe to say that no one will be nostalgic for all prior eras of working with data which was – when findable (pre-search engines) – a matter of scouring through tables of figures in heavy books.
No longer. The paradigm was broken by the Hans Rosling (Gapminder) video “Debunking Myths About the Third-World,” 2006. By Rosling’s own admission, his analysis is not based on new or better data. The (UN) data has always been there (yes now it’s becoming more available). But the seachange is new software which makes it easy to filter and present it in dynamic, graphic form. And, no surprise, this is popular. According to Gapminder, this video has seen by 500,000 people, not bad for a 20-minute treatise on perceptions of developing world countries.
Data turned into dynamic moving pictures is, one might say, required in our era (trends: visual literacy, short attention span, computing power) so thankfully we can expect more of this. What’s important, for forecast evaluation purposes, is the power of explanation and mental-model challenge that the improved communication provides. As Rosling says of his Swedish graduate students: “Their problem was not lack of data, it was preconceived ideas” (an outdated world view of “1st world” vs “3rd world.”) An endless amount of poring over dusty tables of figures would be unlikely to change that. But it’s hard to watch Rosling’s moving bubbles and not have one’s paradigm shaken.
Another site, in a similar vein, is worldmapper, a University of Sheffield initiative. Worldmapper communicates hundreds of world indicators, from infant mortality to military spending and so on, by manipulating the size of territory of each country to indicate presence or absence of the variable in question, as the following maps show:
Prisoners as percentage of population
Girls not at secondary school
Strikes and lockouts, 2002
Again it is basically UN data that is being sourced, but now presented in a way that cuts through the obscurity tells and the story much more vividly. As we know, humans “get it” better and faster via images than via words or figures. It challenges our perceptions in a way that figures in dusty tables cannot. They payoff is it’s harder to miss what’s really going on. So we have a better view of the world: our mental model aka ‘paradigm” more closely approximates reality. That means we will make better assumptions going forward which will, on balance (no guarantees of course), convert into better predictions.
read morePosted by Adam Gordon on Aug 20, 2008 in all, failed predictions, foresight tools & methods, Future Savvy, prediction markets
Hmm. As the 2008 White House race hots up, we’re going to be hearing more and more – and then even more – about who prediction markets forecast to win, so it’s time to put down a thought or two about uses and limitation of this forecasting tool.
First, what’s if all about? If you already know, skip this section. Let’s start with the example in yesterday’s Telegraph: “Predicting the future – with the power of betting” Paul Parsons, August 19, 2008. As Parson’s reports, the University of Iowa is running a market where investors can buy “shares” in the two major US election candidates, each priced between $0 and $1. On election day, traders holding stock in the winner – Obama or McCain – receive $1 per share while the others lose their money. Investors can buy and sell their shares along the way, and as they do this the candidate more people will want to own (because they think he will win) will get more expensive. In other words, market forces will drive up the price of the outcome more people think more likely. As of August 19, the trading value of the Obama, at $0.62, suggests participants expect a 62 percent chance he will win. (Another prediction market site, midasoracle.org, has the figure currently at 59.8 percent.)
Prediction markets mimic stock market and deploy much the same software. Where a real market trades shares in an underlying asset, in a prediction market it is future outcomes which are “securitized”. The key principle at work is the sage market wisdom that “the price of a stock captures all the information known about it” – that is, all information is factored into the price (notwithstanding that some may have more or better information than others; some may be acting more wisely on their information). Therefore price is our guide to the cumulative knowledge of all participants and, in prediction markets, this “price discovery” allows us to know what most people think the future holds. They allow the “the wisdom of crowds” to be turned to a future problem, and tapped.
Serious Success
What’s exciting about all this is its success rate. Prediction markets are amazingly accurate in many circumstances, and by all accounts consistently beat more conventional quantitative and extrapolative methods. Prediction markets have consistently out-predicted election opinion polls and exit polls. Of course the predictive potential goes way beyond polling. Forecasting markets can and have been set up to predict the dollar movements to the success of same-sex marriage legislation, to who will win best actor Oscar. At one point there was even a US government market in future terror targets (trying to elicit public predictions of likely targets so as to plan accordingly) but this was deemed inappropriate and taken down.
As it has become clear that this method outstrips conventional forecasting methods, prediction markets have taken root in forward-looking businesses. Companies such as Google and Hewlett-Packard routinely use (internal) prediction markets to forecast sales figures, customer preferences, product adoption, and so on. HP is on the record as saying prediction markets consistently outperform their official forecasts.
The method has other advantages too. First, it requires no special techniques or expense. There are no fancy models to apply or complex algorithms to … to do whatever one does with such things. Second the forecasts are available in real time, all the time, and constantly update themselves. There’s no waiting for data collectors to collect, or statisticians to emerge with their answers.
The Limits
In my book, Future Savvy, I show how and why humans are poor at predicting, for dozens of reasons. The record of predicting is littered with failure. But, is that now all in the past? Do prediction markets solve the perennial problem of predicting the future, or at least get us closer? Yes and no.
Yes where prediction markets are appropriate. They work best under two conditions: first where there is a clear view of the options and operating conditions; second (related) where the time frame predicted is relatively short, usually under 18 months depending how fast things are moving. Where predicting the future means choosing between known alternatives, such as an election winner, or anticipating a point along a known continuum, for example the level of next year’s sales, prediction markets are great.
Where prediction markets run dry is in dealing with unfamiliar conditions, or unknown variables, or potential game-changing disjunctures in the world. Where the future is seriously fuzzy, where there are many variables, and the way they interact unknown, and drivers, blockers, and lags are hidden, prediction markets are of limited use because the outcomes can’t be framed adequately so that people can bet on them or against them. A prediction market for US president in 2012 would be far less useful than 2008. Similarly, while a market for the oil price in 2009 would be helpful, by 2010 or beyond factors driving the price may be so different (viz. developments in sustainable energy or geopolitics) that the result of a prediction market conducted in 2008 would be undependable.
So while prediction markets sort out probabilities between known likelihoods, they are not adequate to the task of investigating complex situations where we cannot frame the likely outcomes, or at least can’t know if we’ve framed them right. Also while prediction markets do help us, on aggregate, avoid some perceptual/cognitive fallacies, they are as likely as any other predictive tool to fall into the Zeitgeist effect. More on this soon…
A good list of articles on prediction markets is available here: http://www.midasoracle.org/best/
read morePosted by Adam Gordon on Jul 11, 2008 in 2015, 2025, all, failed predictions, forecast filtering, foresight tools & methods, Future Savvy, managing uncertainty, Perils of Prediction, strategic foresight, technology change, trend tracking
This is a how-to book: how to evaluate predictions about the future – how to assess which ones are credible and/or how credible they are (how likely the future will turn out similar to the prediction). It is not just a guide to bad forecasts, it is also about how to identify and extract what is valuable in any forecast. This benefits readers who are required to manage professional or personal situations that depend on correctly anticipating change. Whatever we want to achieve – help a company be more profitable – solve the world’s problems – develop their career – success depends on a good reading of the future. There are many guides to the future (predictions) but no guides to the guides. This book fills that gap. It helps readers assess predictions so they can make better judgments about the future for themselves and their organizations.
Decision success always implies congruence between decisions and the world in which those decisions play out. If we decide today to launch a product, buy a house, study for a degree, build a new light rail system, or take any similar decision of significance, the environment of tomorrow will be a key factor in the success or failure of that decision. What we do will be tested by the future conditions that emerge. Where there is a good “fit” between the initiative and the environment it plays out in — “the right product at the right time” — we can expect success. If not, we should expect to fail. Our decisions are only as good as the view of the future they rest on. All opportunities and successes and profits are realized in the future. All threats, failures, and losses are in the future.
In a fast-moving world, we know that the future environment will be different to that of today in big or small ways. New technologies, market shifts, changes in legislation, or evolving social values damage or destroy the traditional good fit we have between ourselves and the world. To achieve “future fit” we therefore use forecasts to position ourselves and our organizations, creating (or renewing) the fit between our initiatives and environment. In some cases we may be strong enough also to influence future events and outcomes for our own future benefit, and forecasts help us do this too.
All enterprises benefit from narrowing down what they must adapt to and plan for – all effort spent preparing for a future that will not emerge is a waste of personal or organizational resources. Good forecasts are a key ingredient in limiting the vagaries of uncertainty, and therein working smarter not harder, avoiding surprises, exploiting new opportunities and plugging weaknesses in fitting in with the future, and where possible influencing the future to suit the organization. This is true not only of business. People and institutions of all types position themselves for success by anticipating and adapting to events, or shaping them. Whether it is an NGO raising money for developing-world children, an urban planner advocating a light rail system, a homeowner deciding to sell a house, or a student making a career choice, identical principles apply — a higher-quality reading of the future operating environment in which these decisions will play out is what separates winners from losers. We should all be vitally concerned with forecasts as we are all effectively betting significant resources on their validity.
read morePosted by Adam Gordon on Jul 9, 2008 in 2015, 2025, all, decision-making, failed predictions, forecast filtering, foresight tools & methods, Future Savvy, horizon scanning, leadership, managing uncertainty, Perils of Prediction, scenario planning, strategic foresight, strategic planning, systems dynamics, technology change, trend tracking
The book Future Savvy shows readers how to critically judge forecasts for themselves. These are the chapters that take the reader there:
Chapter 1: Recognizing Forecast Intentions, deals with considerations of how forecasts come about, who makes them, and with what intention. Those who research and produce forecasts, those who invest in understanding trends and drivers of change, and those (including the media) who bring the forecasts and their implications to our attention, inevitably have reasons for doing so – to benefit from the knowledge by seizing opportunities or avoiding threats or by affecting outcomes in the world. Understanding a forecast’s “return on investment” gives us an important vantage point in assessing the merits of a forecast.
Chapter 2: The Quality of Information, shows how a forecast communicates information between forecaster and reader subject to the same standards of accuracy, truth-telling, and bias-control by which one would judge any communication. Forecasts can be very different in methods and goals, but all forecasts lay claim to factual truth, particularly truth in the data, and the argument deals with the various ways in which data can be less solid than it looks, even with the best intentions.
Chapter 3: Interpretation and Bias, considers how data – whether good or bad in itself – can be interpreted or misinterpreted in forecasting, that is, the “political” aspects of forecasting. Just as there is no value-free look at history, so too there is no value-free look to the future and asking the right questions allows us be ready to mentally rebalance forecasts that are presented.
Chapter 4: Paradigms and Perception, investigates how predictive statements are exposed to a broader form of interpretive bias that has to do with the forecaster’s mental model or “paradigm,” and the “zeitgeist” (spirit of the times) when the forecast is made. This chapter investigates situations where forecast failure is caused by failure to escape society’s current mental models – which often do not hold through the forecast period.
Chapter 5: The Utility Principle, considers economic and market forces, and the role of consumers, in promoting or resisting the future. Without reigning in creative thinking, some simple economic filters inevitably apply direction or timing realism to futurist flights of fancy.
Chapter 6: Drivers, Blockers, and Trends, consider drivers and blockers of change, and how viewing these dynamics improves forecast assessment. It identifies the roles of Drivers, Enablers, Friction, and Blockers acting on events to cause change or resist it, and problems in dumbly projecting current trends.
Chapter 7: The Limits of Quantitative Analysis, discusses the role of statistical analysis and quantitative modeling in predicting the future – where this is possible and useful and where it is not, and why not.
Chapter 8: The Systems Perspective, investigates “system effects,” which occur whenever different elements or variables that may appear isolated are in fact linked together, such that changes in one element cause changes in others. Anticipating future behavior of any variable hinges on identifying the broader systemic elements influencing it and failing to do this is a big part of what causes forecasts to fail.
Chapter 9: Living with Alternative Futures, investigates non-predictive ways of approaching change – where the tone is more about managing uncertainty than predicting the future. It acknowledges unfathomable complexity of most future questions and provides perspectives that raise chances of success in an inherently unpredictable future.
Chapter 10: Forecast Filtering in Action, illustrates the processes of the book by applying them in case studies to real-world sample forecasts that decision makers in business and policy areas might find themselves interacting with. This demonstrates how real everyday predictive material may be probed and critically evaluated, following the principles developed in previous chapters.
Chapter 11: A Forecast Filtering Checklist, is a cross-cutting checklist which summarizes the principles of the book in one convenient, thematic list.
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