3Bac- Sensitivity Analysis

  Sensitivity vs. Scenario Analysis

In finance, a sensitivity analysis is created to understand the impact a range of variables has on a given outcome. It is important to note that a sensitivity analysis is not the same as scenario analysis. As an example, assume an equity analyst wants to do a sensitivity analysis and a scenario analysis around the impact of earnings per share (EPS) on a company's relative valuation by using the price-to-earnings (P/E) multiple.

The sensitivity analysis is based on the variables that affect valuation, which a financial model can depict using the variables' price and EPS. The sensitivity analysis isolates these variables and then records the range of possible outcomes.

On the other hand, for scenario analysis, the analyst determines a certain scenario such as a stock market crash or change in industry regulation. He then changes the variables within the model to align with that scenario. Put together, the analyst has a comprehensive picture. He now knows the full range of outcomes, given all extremes, and has an understanding of what the outcomes would be, given a specific set of variables defined by real-life scenarios.

Benefits and Limitations of Sensitivity Analysis

Conducting sensitivity analysis provides a number of benefits for decision-makers. First, it acts as an in-depth study of all the variables. Because it's more in-depth, the predictions may be far more reliable. Secondly, It allows decision-makers to identify where they can make improvements in the future. Finally, it allows for the ability to make sound decisions about companies, the economy, or their investments.

But there are some disadvantages to using a model such as this. The outcomes are all based on assumptions because the variables are all based on historical data. This means it isn't exactly accurate, so there may be room for error when applying the analysis to future predictions.

How to perform sensitivity analysis

As we saw in the above examples, sensitivity analysis examines how independent input variables affect your organization’s outputs. It reveals how each variable will ultimately impact your finances and future. 

Mathematically, the dependent output formula for sensitivity analysis is written as follows:

Z = X2 + Y2

With this formula, you can adjust one input while keeping other inputs the same (or aligned with your base case). Run the numbers, and you’ll see how changes in a certain variable will impact your company, organization, or institution. 

It’s important to understand that there are other sensitivity analysis formulas you can use, depending on your organization’s situation. For instance, the net present value (NPV) formula is useful for deciding whether it would be worth it to make a certain investment:

NPV = (Cash Flow / (1 + Required Return))t – Initial Investment

With this formula, you can see how the value of an investment changes when cash flow changes. 

This is particularly useful during COVID-19—e-Commerce companies may have experienced a higher-than-anticipated cash flow from their earlier investments, while restaurants and brick-and-mortar stores may have experienced lower-than-anticipated cash flows. 

Finally, to determine just how “sensitive” your company is to a certain input, you would use another formula (the sensitivity formula): 

Sensitivity = Percentage change in output / Percentage change in input

It’s important that you calculate the sensitivity of each independent variable as you test it. This will enable you to see just how important each input is to your organization.