Krahasoni metodat

	Analiza e Skenarëve dhe Simulimi "Çfarë-nëse"	Analiza e ndjeshmërisë globale
Fusha	Simulimi	Simulimi
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1950s (origins); widely adopted in management since 1970s	1973–2001
Krijuesi	Peter Schwartz (scenario planning formalization), Herman Kahn (RAND Corporation, 1950s–60s)	I.M. Sobol (indices, 2001); Morris (screening, 1991); Cukier et al. (FAST, 1973)
Lloji	Structured analytical approach / simulation	Variance-based sensitivity decomposition
Burimi themelues	Goodwin, P. & Wright, G. (2014). Decision Analysis for Management Judgment (5th ed.). Wiley. ISBN: 978-1118173671	Sobol, I.M. (2001). Global Sensitivity Indices for Nonlinear Mathematical Models and Their Monte Carlo Estimates. Mathematics and Computers in Simulation, 55(1–3), 271–280.
Emërtime të tjera	what-if analysis, what-if simulation, stress testing, scenario planning	variance decomposition, Sobol indices, Morris screening, FAST method
Të lidhura	3	4
Përmbledhja	Scenario analysis is a structured analytical approach that systematically compares system outputs across different combinations of uncertain input values. When paired with a quantitative model, it becomes a simulation — capable of stress-testing assumptions and projecting the range of plausible outcomes. Formalised in strategic planning by Peter Schwartz and Herman Kahn from the 1950s onward, the method is widely used in policy evaluation, business forecasting, financial risk assessment, and scientific model exploration.	Global sensitivity analysis (GSA) is a family of techniques that decompose the variance of a model's output across its input parameters, quantifying how much each input — and each combination of inputs — contributes to the total uncertainty in the result. Sobol's variance-based indices (2001), Morris's one-at-a-time (OAT) screening (1991), and the Fourier Amplitude Sensitivity Test (FAST, first proposed by Cukier et al. in 1973) are the three most widely used approaches. Together they serve as the standard toolkit for identifying which parameters drive model behaviour and which can be safely fixed.