Future Savvy: Identifying Trends to Make Better Decisions, by Adam Gordon

By Adam Gordon

There is not any scarcity of predictions on hand to organisations seeking to expect and make the most of destiny developments. it sounds as if priceless forecasts are ubiquitous in daily communications resembling newspapers and enterprise magazines, and in really expert resources equivalent to executive and think-tank forecasts, advisor stories, and stock-market courses. those assets are the most important yet also they are of very combined caliber. whereas we all know a future-focus is essential for strategic imaginative and prescient and organizational readiness, what info from the unending sea of resources is legitimate? How are you aware which predictions to take heavily, which to be cautious of, and which to throw out solely? which of them do you enable consultant your judgements? destiny Savvy offers a hands-on method of judging predictive fabric of all kinds, together with delivering a battery of severe exams to use to any forecast to evaluate its validity, and choose tips on how to healthy it into daily administration pondering. In a colourful e-book with many examples, Adam Gordon synthesizes details evaluation talents and destiny reports instruments right into a unmarried template that permits managers to use systematic "forecast filtering" to bare strengths and weak spot within the predictions they face. the higher leaders' view of the longer term, the higher their judgements - and successes - should be. destiny Savvy empowers either company and policy/government decision-makers to exploit forecasts correctly and so increase their judgment in watching for possibilities, fending off threats, and coping with uncertainty.

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In this specific case, we have a carefully contained basis of projection and little scope for error. Sample Validity Sampling is central to statistics. It rests on the assumption that what is true of a random sample of the population is true of the population as a whole. Therefore, we need only test a sample, which is much easier and cheaper to do. But the pivotal question is whether the sample is in fact representative of the whole, such that the inferences drawn about it will also be true of the larger population.

Survey Data and Delphi Studies Surveys are a notoriously difficult area because the nature of the questions influences the responses given. Leading questions will create bias in the responses. Questions not asked will leave holes in the information. Better-quality survey design methods go a long way to eliminating bias from a question set, but there’s no law to say these techniques must be used or have been used in the forecast you happen to be reading.

Alternatively, the data may be privately researched, and there for sale, but getting it requires an investment on the part of the forecasting institution. For one reason or another, forecasters may continue to use old information and may fudge how old it really is. Good forecasts will date the data and will adjust or discount inferences made on old data. CHAPTER 2: THE QUALITY OF INFORMATION ✧ 49 Projected Data By definition there can be no data from the future. Yet it often appears that data about the future is presented in the forecast.

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