Nowadays, every business wants to predict the consequences of a change before its implementation. They want to know how the new change in the policy will bring profits and other things. To do this, sensitivity analysis is the best tool. Economists and financial analysts use this analysis technique to forecast the company’s growth. It allows forecasting by using historical and true data. By investigating all the independent and dependent variables and the possible outcomes, important decisions can be made about companies. Today’s article is all about sensitivity analysis and the steps required to analyse a particular problem. Let’s begin our discussion with a very basic question.

**Contents in the Article**hide

**What Is Sensitivity Analysis?**

This analysis measures how different values of independent variables affect the dependent variables. The changes are applied under a certain set of assumptions. In simple words, this analysis shows how various sources of uncertainty affect the overall uncertainty of the problem.

This analysis is also called what-if or simulation analysis. Economists and financial analysts use this to predict the outcome of a decision. They change the variables and test them by looking at their results. In this way, the sensitivity analysis helps them forecast the growth of a company based on its financial stability. Further details about the types and uses of sensitivity analysis are below;

**Uses Of Sensitivity Analysis**

- It uses to indicate the uncertainty of the model by varying different input values
- It helps companies in making effective decisions that lead to their growth
- The modelling of the problem through this analysis helps in forecasting the outcome of decisions
- Measuring the riskiness of a particular strategy is the main use of this analysis
- Helps in making accurate and informed decisions based on the factual modelling and presentation of constraints

**Methods Of Sensitivity Analysis**

There are several methods of performing this analysis. The names and a brief description of the two most common methods are below as shared by experts in **dissertation proposal writing services**;

- Modelling and simulation technique (LPP and Simplex)
- Scenario management through MS Excel

**What Is Sensitivity In LPP?**

Sensitivity analysis has great application in Linear Programming Problems (LPP). To understand this deep relationship, first, you need to look at the definition of LPP. LPP is a mathematical technique in which a linear function is maximised or minimised under some constraints. The researcher builds the model of the LPP and then tests it by changing the conditions.

So, sensitivity analysis is also about measuring the changes in a model by modifying the independent variables. Both sensitivity and LPP have a deep relationship. The smaller linear problems can be solved by using computation, but what about the larger problems? In case of larger problems, where thousands of calculations are involved, the investigator uses this analysis. This modelling technique has successfully guided quantitative decisions in business planning. Businesses use this analysis to predict their growth and other things.

**What Is A Sensitivity Analysis Of The Simplex Method?**

The simplex method is also a type of linear programming problem. This method is particularly used to solve optimisation problems in economics. It involves a function and some constraints. The investigator researches the problem based on those constraints. After careful study, he then proposes the optimised solution.

**What Are The Steps Involved In Sensitivity Analysis?**

A sensitivity analysis addresses some of the uncertainties in a problem by testing the discrete variables. The discrete variables and other factors are then changed to model the problem. Now, you must be thinking about what those discrete variables are. Another question is, what are the steps involved in sensitivity analysis?

Basically, there are five steps that you need to consider while working on this analysis. A brief description of each step is below.

**Identify the key cost drivers**

The first important step is the identification of key cost drivers. The cost drivers are the constraints that affect different activities in a model. Such drivers cause changes in the cost of various activities. Typical examples of key cost drivers are direct labour hours worked and the number of customer contacts made. The number of orders that customers have returned also comes under this.

**Identify ground rules**

Every decision which is to be made by the senior leadership of a company contains some basic rules and principles. Those basic principles of the company are the ground rules. The manager has to identify those first and incorporate them into the model.

For example, the problem is that employees demand an increment in salary. There are also those employees who are in their probation period. The ground rule says that there will be no increment in salary during the probation period. This is how ground rules work in sensitivity analysis.

**Identify the assumptions**

As described earlier, the basis of the analysis is the assumptions. By making several assumptions, you make decisions. You also change them as per the requirement of the model. Testing the problem is done based on the assumptions. Therefore, identifying the assumptions holds immense importance in a sensitivity analysis.

**Document results by changing variables**

After performing all the steps mentioned above, it is time to document the results. But one important thing is to make changes in the variables. Relying on a single input and deciding is not a wise move. You must change the variables and then see the results. Document the results when you are satisfied with the model.

**Evaluate the results**

The last step includes the evaluation of the results. It entails the implementation of the new model and then the evaluation of the analysis results. If the results are good, stay with the model and continue working. If you see some flaws, change the drivers and make a new assumption. It will give a new look to the model.

**Conclusion**

Sensitivity analysis is a tool that helps decision-makers by providing them with solutions more than one. Businesses grow with the help of those solutions. Different methods of performing this analysis are also very helpful in mitigating the problems. The LPP and simplex methods are the most widely used.

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