What does sensitivity analysis help identify in simulation models?

Sensitivity analysis is a critical tool when dealing with simulation models because it helps identify which variables have the most significant impact on the model's outcomes. By systematically varying the input parameters and observing the changes in the results, one can pinpoint the crucial factors that drive the model's behavior. This understanding is essential for decision-making, as it allows practitioners to focus on the most influential variables, allocate resources effectively, and prioritize areas for further investigation or optimization.

In conducting sensitivity analysis, it becomes evident which inputs are critical for achieving desired outcomes and which ones have minimal effect. This prioritization is particularly valuable in complex simulations with numerous variables, guiding stakeholders on where to direct their attention and efforts.

While the other options might touch upon aspects related to simulations, they do not encapsulate the main purpose of sensitivity analysis, which is fundamentally about understanding the impact of input variables on outcomes.