Sensitivity Analysis (Tornado Diagram)
Sensitivity analysis is a quantitative technique that determines which individual risks or uncertainties have the greatest potential impact on project outcomes. The tornado diagram is its primary visual output.
Explanation
Sensitivity analysis examines how variations in individual uncertain elements (activity durations, costs, resource availability) affect the overall project outcome while holding all other variables at their baseline values. This "one-at-a-time" approach isolates the influence of each variable.
The results are displayed in a tornado diagram—a horizontal bar chart where each bar represents one uncertain element. The bar length shows the range of impact that element has on the project outcome. The bars are sorted from longest (most impact) to shortest, creating a funnel shape resembling a tornado. Elements at the top deserve the most management attention.
Sensitivity analysis is often used alongside Monte Carlo simulation. While Monte Carlo shows the aggregate probability distribution, the tornado diagram identifies which specific elements are driving the uncertainty. This helps the team focus risk response efforts on the variables that matter most.
Key Points
- •Isolates the impact of each uncertain variable on project outcomes
- •Tornado diagram displays results with the most influential variable at the top
- •Helps focus risk response efforts on the highest-impact uncertainties
- •Often used in conjunction with Monte Carlo simulation
Exam Tip
If an exam question shows a tornado diagram or asks which risks have the greatest influence on a project outcome, the answer involves sensitivity analysis. The longest bar = most influential risk.
Frequently Asked Questions
Related Topics
Perform Quantitative Risk Analysis
Perform Quantitative Risk Analysis is the process of numerically analyzing the combined effect of identified individual risks and other sources of uncertainty on overall project objectives.
Monte Carlo Simulation
Monte Carlo simulation is a quantitative risk analysis technique that uses random sampling of probability distributions for cost and schedule estimates to model possible project outcomes and calculate the probability of achieving targets.
Expected Monetary Value (EMV)
Expected monetary value (EMV) is a quantitative risk analysis technique that calculates the average outcome of a risk event by multiplying the probability of occurrence by the monetary impact. EMV for threats is negative; for opportunities, it is positive.
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