Unit
- Definition: Sensitivity analysis examines how changes in independent variables affect a dependent outcome under a given set of assumptions. It quantifies the relationship between input uncertainty and output variability, enabling analysts to identify which inputs drive results most.
- Purpose: The primary goal is to enhance decision making by revealing which assumptions have the greatest impact on conclusions. This allows practitioners to focus data collection and risk mitigation efforts on the most influential factors.
- Applications: Used across corporate finance, investment analysis, project management, and operations research. For example, a financial model may test how variations in revenue growth or cost of capital affect net present value.
- Base Case: The starting point for analysis is the base case, which uses the most likely or expected values for each input. Sensitivity analysis then measures the effect of deviating from these central estimates.
- Input Variables: These are the assumptions or parameters that can be varied, such as interest rates, exchange rates, sales volume, or operating costs. Selection of relevant inputs is critical for meaningful analysis.
- Output Metrics: The outcomes being measured, like NPV, IRR, EBITDA, or return on equity. Sensitivity analysis quantifies how these metrics change in response to input fluctuations.
- Decision Support: By quantifying uncertainty, sensitivity analysis helps managers assess risk, set contingency plans, and communicate confidence levels to stakeholders. It supports both strategic planning and operational decisions.
- Limitations Awareness: Sensitivity analysis does not predict the probability of input changes; it only shows potential outcomes. Combining it with probabilistic methods provides a more complete risk picture.
Financial Formula
Output Sensitivity Index
SI = (ΔOutput / Output) / (ΔInput / Input)
SI = (ΔOutput / Output) / (ΔInput / Input)
Where:
- ΔOutput: Change in the output metric due to input variation
- Output: Base case output value
- ΔInput: Change in the input variable
- Input: Base case input value
- SI > 1: Output changes proportionally more than input (high sensitivity)
Quick Revision
- Sensitivity analysis measures how output uncertainty relates to input variability.
- It improves decision making by highlighting key drivers and risk concentrations.
- The base case serves as the reference point for all comparisons.
- The sensitivity index quantifies the relative impact of each input on the outcome.