What is sensitivity analysis primarily used for?

Sensitivity analysis is primarily used to assess how different variables impact project success. This technique involves changing one or more input variables to see how these changes affect the output of a model or a particular outcome, such as project profitability or risk. By performing sensitivity analysis, decision-makers can determine which variables have the greatest impact on results and can prioritize their focus based on this understanding. This is particularly useful in areas such as forecasting, budgeting, and risk assessment, where understanding the variability in key assumptions can help in making informed decisions.

The use of sensitivity analysis enables organizations to identify critical factors that could affect their projects significantly, allowing for better planning, resource allocation, and risk management. For example, if a project’s success heavily depends on a specific cost or revenue variable, sensitivity analysis would reveal how fluctuations in that variable could jeopardize the project's overall viability, prompting preemptive strategies to mitigate that risk.

Other methods, such as comparing qualitative data, understanding complex theories, or gathering primary data, do not directly focus on analyzing the impact of variable changes on outcomes, as sensitivity analysis does. Thus, the use of sensitivity analysis is unique and crucial in evaluating the dynamics of different influencing factors in project success.