Usage Areas of Sensitivity Analysis

There is a very wide range of uses to which sensitivity analysis is put. An incomplete list is given in Table. The uses are grouped into four main categories: decision making or development of recommendations for decision makers, communication, increased understanding or quantification of the system, and model development. While all these uses are potentially important, the primary focus of this paper is on making decisions or recommendations.

Uses of sensitivity analysis

1.	Decision Making or Development of Recommendations for Decision Makers
1.1	Testing the robustness of an optimal solution.
1.2	Identifying critical values, thresholds or break-even values where the optimal strategy changes.
1.3	Identifying sensitive or important variables.
1.4	Investigating sub-optimal solutions.
1.5	Developing flexible recommendations which depend on circumstances.
1.6	Comparing the values of simple and complex decision strategies.
1.7	Assessing the "riskiness" of a strategy or scenario.
2.	Communication
2.1	Making recommendations more credible, understandable, compelling or persuasive.
2.2	Allowing decision makers to select assumptions.
2.3	Conveying lack of commitment to any single strategy.
3.	Increased Understanding or Quantification of the System
3.1	Estimating relationships between input and output variables.
3.2	Understanding relationships between input and output variables.
3.3	Developing hypotheses for testing
4.	Model Development
4.1	Testing the model for validity or accuracy.
4.2	Searching for errors in the model.
4.3	Simplifying the model.
4.4	Calibrating the model.
4.5	Coping with poor or missing data.
4.6	Prioritising acquisition of information.

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