Sensitivity Analysis

What is Sensitivity Analysis?

Sensitivity analysis is an investigation that is driven by data. It determines how independent variable of a business can have an impact on the dependent variables. This ultimately leads to change in the output and profitability of the business. The concept of sensitivity analysis is employed to evaluate the overall risk and identify critical factors of the business. By doing so, the business tries to find alternative solutions for different problems.

After sensitivity analysis definition, let’s take an example to further clarify the concept.

Example of Sensitivity Analysis

Suppose an organization is making mobile cases and covers. Every month many new mobile releases and many older mobiles go out of the market. In the given case, the business has two options i.e. either to wait for the new launch of mobiles every month or keep producing the cases for older mobiles. If the business keeps waiting for the launch of new phones, the number of cases that it could have sold will not contribute to the profits. Therefore, the business will have to determine how many cases need to be produced. Hence, a number of cases to be produced are dependent variable here.

It is very important to rightly interpret the sensitivity analysis study. So, let us have a look at how to interpret sensitivity analysis.Sensitivity Analysis

How to Interpret Sensitivity Analysis

The interpretation of the sensitivity analysis can be done by keeping the following factors in mind:

Create Experimental Design

It is important to create an experimental design of the business model and find what parameters can affect it the most. By assigning different values to different variables ranging from minimum to maximum, one can know the immediate and long-term effect of various parameters on business. Find the best suitable combination and apply it in the business model.

What are the Parameters

To correctly interpret the sensitivity analysis, the parameters selected should be right. The parameters can be different for different models of business. However, the common parameters may include technical parameters, number of activities involved in business, number of bottlenecks, risk, and effect of bottlenecks on business, etc. Selection of right parameters will help in arriving at a right interpretation of the analysis.


Once the analysis is done with different parameters and combinations, the next step is observation. Observation is important as it determines which strategy must be followed by the business for higher growth and profit maximization. The observation may involve; the outcome of analysis based on different decision variables, the impact of different variables and parameters on the strategy of the business, any ratifications to be made in the strategy, etc.

Sensitivity analysis can be evaluated by using different methods. Let us have a look at the different methods of sensitivity analysis.

Methods of Sensitivity Analysis

There are two methods for carrying out a sensitivity analysis. They are as follows.

  • Simulation and Modeling technique
  • Scenario management using Microsoft Excel


There are various advantages and disadvantages of sensitivity analysis and it provides a solution to different problems of business under different situations. It helps the decision makers of business to learn about the different parameters that drive a business. Along with that, the business knows how each parameter affects its functioning and profitability. The sensitivity analysis evaluates the best business model after considering the different bottlenecks and variables. The aim of sensitivity analysis is to arrive at such business model that results in higher EPS. To sum up, every business must conduct sensitivity analysis to stay ahead of its competitors and for higher growth as well as sustainability.



Last updated on : June 1st, 2018

** Disclaimer: This post may contain Affiliate Links marked as ** and we may earn a commission on sale.

What’s your view on this? Share it in comments below.

Leave a Reply