Sensitivity Analysis

Sensitivity analysis in a method used to incorporate uncertainty into decision making by taking each uncertain factor in turn, and calculates the change that would be necessary in that factor before the original decision is reversed. Typically, it involves posing 'what-if' questions.

By using this technique it is possible to establish which estimates (variables) are more critical than others in affecting a decision.

The process is as follows:

• Best estimates for variables are made and a decision arrived at.
• Each of the variables is analysed in turn to see how much the original estimate can change before the original decision is reversed. For example, it may be that the estimated selling price can fall by 5% before the original decision to accept a project is reversed.
• Estimates for each variable can then be reconsidered to assess the likelihood of the estimate being wrong. For example, what is the chance of the selling price falling by more than 5%?
• The maximum possible change is often expressed as a percentage. This formula only works for total cash flows. It cannot be used for individual units, selling prices, variable cost per unit, etc.

Illustration

A manager is considering a make v buy decision based on the following estimates:

You are required to assess the sensitivity of the decision to the external purchase price.

Step 1: What is the original decision?

Comparing contribution figures, the product should be bought in and re-badged:

Step 2: Calculate the sensitivity (to the external purchase price)

For indifference, the contribution from outsourcing needs to fall to $5 per unit. Thus the external purchase price only needs to increase by $1 per unit (or $1/ $6 = 17%). If the external purchase price rose by more than 17% the original decision would be reversed.

Strengths of sensitivity analysis

• There is no complicated theory to understand.
• Information will be presented to management in a form which facilitates subjective judgement to decide the likelihood of the various possible outcomes considered.
• It identifies areas which are crucial to the success of the project. If the project is chosen, those areas can be carefully monitored.

Weaknesses of sensitivity analysis

• It assumes that changes to variables can be made independently, e.g. material prices will change independently of other variables. Simulation allows us to change more than one variable at a time.
• It only identifies how far a variable needs to change; it does not look at the probability of such a change.
• It provides information on the basis of which decisions can be made but it does not point to the correct decision directly.

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