What type of model asks what-if questions repeatedly to determine the impact on outcomes of changes in one or more factors?

The model that is designed to ask what-if questions repeatedly to assess the impact on outcomes of changes in one or more factors is sensitivity analysis. This approach is particularly powerful in scenarios where multiple uncertainties or variables interact, allowing analysts to see how variations in input data can affect overall results.

Sensitivity analysis works by systematically varying key input factors while keeping others constant (or fixed at a certain level) to observe how these changes influence the output. This method helps in identifying which variables have the most significant impact on outcomes, thereby allowing decision-makers to prioritize their focus on those critical factors.

For instance, in a financial model, if an analyst alters the estimated sales growth rate or cost assumptions, sensitivity analysis would allow them to see how these changes can affect profitability or cash flow. This iterative questioning process helps in understanding risks and making informed decisions based on the range of possible scenarios derived from the analysis.

In contrast, optimization models aim to find the best solution from a set of alternatives and often use techniques to maximize or minimize a particular outcome without necessarily exploring the effects of changing input variables in the same systematic way as sensitivity analysis. Statistical models focus on data relationships and predictions rather than on variable impacts, while forecasting primarily aims to predict future values based on historical data trends rather than