方法对比

	Intuitive Logics Scenario Planning	Trend Impact Analysis
领域	Futures Foresight Studies	Futures Foresight Studies
方法族	Process / pipeline	Process / pipeline
起源年份	1995	1972
提出者	SRI International / Royal Dutch Shell tradition; Paul J. H. Schoemaker (codification)	Theodore J. Gordon (The Futures Group / Millennium Project)
类型	Deductive scenario-construction pipeline using two critical uncertainties	Probabilistic trend-extrapolation pipeline perturbed by future events
开创性文献	Schoemaker, P. J. H. (1995). Scenario planning: A tool for strategic thinking. Sloan Management Review, 36(2), 25-40.	Gordon, T. J., & Hayward, H. (1968). Initial experiments with the cross-impact matrix method of forecasting. Futures, 1(2), 100-116.
别名	Intuitive Logics, 2x2 Scenario Matrix, Deductive Scenario Method, SRI Scenario Planning	TIA, Trend-Impact Forecasting, Probabilistic Trend Perturbation, Event-Adjusted Trend Extrapolation
相关	3	3
摘要	Intuitive logics is the most widely used family of scenario-planning methods, in which a small set of internally consistent, plausible stories about the future is constructed deductively from a few critical uncertainties. Rooted in the practice pioneered at SRI International and at Royal Dutch Shell in the 1970s, and codified for strategic thinking by Paul Schoemaker in his 1995 Sloan Management Review article, the approach asks a planning team to identify the driving forces shaping a focal decision, rank them by how much they matter and how uncertain they are, and select two critical uncertainties that become the orthogonal axes of a two-by-two matrix. The four quadrants define four contrasting but coherent futures, each developed into a narrative. The aim is not to predict but to stretch managers' mental models and to stress-test strategy against a manageable spread of qualitatively different worlds.	Trend impact analysis (TIA) is a forecasting method that marries quantitative extrapolation with expert judgment about disruptive future events. Developed by Theodore Gordon and colleagues at The Futures Group in the early 1970s and later codified in the Millennium Project's Futures Research Methodology, it starts from a 'surprise-free' baseline produced by fitting and projecting a historical time series. It then asks which unprecedented events — events with no historical analog that ordinary extrapolation cannot anticipate — could deflect that trend, and with what probability, magnitude, and timing. Through Monte Carlo simulation those probabilistic impacts perturb the baseline, yielding not a single line but a probability envelope that shows how the trend might bend if the unexpected occurs.