Ford, Henry, 12
Forecast filtering
applying, 217–62
assumptions and paradigm paralysis,
276–77
complexity, managing, 274–76
drivers and blockers, 278–83
information quality, 269–70
interpretation and bias, 270–72
methods and models, 272–73
quantitative limits, 273–74
specificity in, 267–69
summary of steps, 265–83
zeitgeist and Groupthink, 277–78
Forecasts
anticipating for virtuous cycles,
187–88
benefits of, 25
bias, probing for, 77–78
editorial oversight, lack of, 75–76
election and government, 71
errors in, 13
evaluating, 9
expectations, 200–201
expert, 97–99
filtering, 13–15
future-aligning, 24–19, 266–67
future and, 5–7
future-influencing, 24–29, 266–67
insider, 72–74
internal, motivational, 68–69
learning from, 11–13
long-medium, 20, 22
long-term, 20–21, 22
optimistic versus pessimistic, 32–34
origins of, 7–9
period, 19, 20–23
point, 23–24
political aspects of, 63–81
poor, 9–11
primary data and, 44
publicity and, 71–72
purpose of, 266
qualitative, 168
scenario planning, 201–3
self-asserted, 67–68
short-medium, 20, 22
short-term, 20, 22
skepticism, 11
sponsored, 70–71
standardization, lack of, 4–5
technology-push, 116–21
ultra-long term, 21
validity of, 4–5
zeitgeist bias in, 93–97
Foresight, determining approach, 168–71
Forrester Research, 8, 80
Foucault, Michel, 86
Fraud, 52
Friction, 141, 147
Funding, foresight and, 69–70
Future-aligning forecasts, 41, 266–67
future-influencing versus, 24–29
identifying, 30–31
Future-influencing forecasts, 41, 266–67
extremes of, 35–36
future-aligning versus, 24–29
goals, 28–29
identifying, 30–31
intentional bias and, 66
power and politics and, 36
G
Gartner Inc., 8, 80
Gates, Bill, 12
General Motors, 73
Google, 73
Government forecasts, 71
Groupthink, 277–78
H
Hamel, Gary, 73
Herd bias, 92
Hitler, Adolf, 36
Housing and mortgage finance forecast,
219–25
Human bias, 91–92
Hypothesis
errors, 51
testing, 51
I
IBM, 12
IMF, 8
Inference, data and, 57
Inflection points, 145–47
INDEX
291

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