Sensitivity Analysis is a method of evaluating the model and the effects of input variables to the target variables. Sensitivity analysis or “What-If analysis” fully analyze the relationship between variables and could provide critical information on the model’s mechanism and boundaries.
It is widely used in financial modelling such as determining effects of changing interest’s rates and prices. In the context of Operations Research, it is useful for determining the limit of the objective functions and effects of changing constraints to the objective function. Other purposes of sensitivity analysis include testing robustness, reducing uncertainty, and model simplification.
We provide an example for sensitivity analysis. A café manager wants to sell a new type of dish with the cost of the weekly ingredients (for that dish only) of €1000. Then he surveyed multiple cafés around the town and acquired information that the price of similar dish ranges from €3 to €8 and based on historical data his café sold around 20 to 30 dishes per day.
He wants to know the right price and quantity such that it is affordable and profitable for him. The simplest method of sensitivity analysis is using EXCEL Table and applies the one-at-a-time (OAT) Method. This technique evaluates one parameter at a time and holding the other parameters fixed. For example, the manager sets the price to €5 to see the effects of sales on his profits.
From this example, the price of €5 Euro is not profitable with the current average sales and he has to sell at least 29 dishes to at least make a profit. He is either has to promote the new dish to increase the sales and maintain them or adjust the price slightly higher. Since creating a marketing campaign is financially infeasible, he decides the simulate the sales with the price of €7.
With the new price, the dish is more profitable with a minimum sales of 21 per day. The manager seems confident that he could sell 21 dishes per day, hence he decides that the price of the new dish will be €7.
This example shows that sensitivity analysis provides the relationship and correlation between sales and price affect the total profit. Moreover, the manager could also use the same method to predict his profit if the number of sales changes in the future and could adjust his business strategy accordingly.
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