방법 비교

	Strategic Technology Roadmapping	Cross-Impact Analysis
분야	전략경영	전략경영
계열	Process / pipeline	Process / pipeline
기원 연도	2004	1968
창시자	Robert Phaal, Clare Farrukh & David Probert	Theodore Gordon & H. Hayward; Olaf Helmer
유형	Time-based strategic planning and visualization framework	Conditional-probability simulation of interacting future events
원전	Phaal, R., Farrukh, C. J. P., & Probert, D. R. (2004). Technology roadmapping - A planning framework for evolution and revolution. Technological Forecasting and Social Change, 71(1-2), 5-26.	Gordon, T. J., & Hayward, H. (1968). Initial experiments with the cross impact matrix method of forecasting. Futures, 1(2), 100-116.
별칭	Technology-Product-Market Roadmapping, T-Plan Roadmapping, Strategic Roadmapping, Innovation Roadmapping	Cross-Impact Matrix Method, Cross-Impact Forecasting, Conditional-Probability Futures Analysis, Event Interaction Analysis
관련	4	4
요약	Strategic technology roadmapping is a planning and visualization method that links what an organization should develop, when, and why by aligning three time-based layers - market drivers, products, and technologies - on a single chart. Robert Phaal, Clare Farrukh, and David Probert of the University of Cambridge synthesized the approach in their influential 2004 Technological Forecasting and Social Change paper, presenting roadmapping as a flexible framework that supports both incremental ('evolution') and disruptive ('revolution') strategic change. A roadmap answers, layer by layer, why the organization needs to act (market and business drivers), what products or capabilities will respond, and how technologies and resources will deliver them, all positioned against time. By making these connections explicit, roadmapping coordinates strategy, innovation, and resource allocation across functions and exposes the timing gaps and dependencies that threaten a technology strategy.	Cross-impact analysis is a forecasting technique that models how a set of possible future events influence one another, so that forecasts account for the fact that real events are interdependent rather than isolated. Theodore Gordon and H. Hayward introduced the cross-impact matrix method in their 1968 Futures paper, motivated by the observation that judgmental forecasts such as Delphi estimate the likelihood of each event separately and ignore that the occurrence of one event can sharply raise or lower the odds of others. Olaf Helmer's 1977 work refined the approach, distinguishing the original correlational formulation from a causal cross-impact model and addressing the internal-consistency problems that plagued early matrices. The method specifies prior probabilities for events and conditional 'cross-impact' probabilities between them, then simulates the system to produce internally consistent joint outcomes and revised probabilities.