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The primary purpose of sensitivity analysis is to understand the effect of changes in variables on a given outcome or decision-making process. This technique allows professionals to assess how different values of an independent variable will impact a particular dependent variable under a set of assumptions. By systematically varying the inputs, one can identify which variables have the most significant effect on the results, thus facilitating better decision-making and risk assessment.

Sensitivity analysis is particularly valuable in financial modeling, project evaluation, and risk management, where uncertainties in input parameters can lead to different outcomes. By clearly illustrating these relationships, sensitivity analysis helps stakeholders make more informed choices and prepare for potential fluctuations in key metrics. Overall, it enhances the understanding of how sensitive a model's output is to changes in input values, which is crucial for planning and strategy development.