Future Savvy: What’s Under the Hood

Posted 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 | 1 comment

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.