What Is Sensitivity Analysis?

What Is Sensitivity Analysis?

Sensitivity analysis shows how different values of an independent variable affect a dependent variable under a given set of assumptions. Companies use sensitivity analysis to identify opportunities, mitigate risk, and communicate decisions to upper management.

Sensitivity analysis is deployed in business and economics by financial analysts and economists and is also known as a "what-if" analysis.

How Sensitivity Analysis Works

Sensitivity analysis is a financial model that determines how target variables are affected based on changes in input variables. By creating a given set of variables, an analyst can determine how changes in one variable affect the outcome.

Sensitivity analysis enables forecasting based on historical, true data. By studying all the variables and the possible outcomes, decisions can be made about business activities and investing decisions,

Sensitivity analysis can be used to:

• Make predictions about the share prices of public companies. Some variables that affect stock prices include company earnings, the number of shares outstanding, the debt-to-equity ratios (D/E), and the number of competitors in the industry.
• Determine the effect that changes in interest rates have on bond prices. In this case, the interest rates are the independent variable, while bond prices are the dependent variable.

How Businesses Use Sensitivity Analysis

Sensitivity analysis can provide management feedback useful in many different scenarios including:

• Understand influencing factors. What external factors can affect the outcome of a specific project or undertaking, and how they affect it. This allows management to see what input variables may impact output variables.
• Reduce uncertainty. Complex sensitivity analysis models inform project members what to be alert for or what to plan for.
• Catch errors. The original assumptions for the baseline analysis may have had some uncaught errors. By performing analytical iterations, management can catch mistakes in the original analysis.
• Simplify the model. The analysis reveals what factors don't matter and can be removed from the model.
• Communicate results. Upper management may already be defensive. Compiling analysis on different situations helps inform decision-makers of other possible outcomes.
• Achieve goals. Management sets specific benchmarks for long-term strategic plans. By performing sensitivity analysis, a company can better understand how a project may change and what conditions must be present for the team to meet its targets.
  

Example

A sales manager wants to understand the impact of customer traffic on total sales. The company determines that sales are a function of price and transaction volume. The price of a widget is $1,000, and the company sold 100 last year for a total sales of $100,000.

The manager determines that a 10% increase in customer traffic increases transaction volume by 5%. This allows the company to build a financial model and sensitivity analysis based on what-if statements. It can tell the manager what happens to sales if customer traffic increases by 10%, 50%, or 100%.

Based on 100 transactions, a 10%, 50%, or 100% increase in customer traffic equates to an increase in transactions by 5%, 25%, or 50% respectively. The sensitivity analysis demonstrates that sales are sensitive to changes in customer traffic.

Advantages and Disadvantages

Sensitivity analysis provides several benefits for managers considering major decisions. It acts as an in-depth study that reveals potential hazards as well as the potential rewards to an undertaking. It allows decision-makers to identify where they can make improvements in the future to avoid some adverse outcomes.

However, the outcomes can only be estimates, not hard facts. Forecasting is by definition based on historical data.

Models with too many variables may distort a user's ability to evaluate influential variables.

The Bottom Line

When a company wants to understand the range of potential outcomes for a given project, it may perform a sensitivity analysis. Sensitivity analysis entails manipulating independent variables to determine the resulting financial impacts. Companies employ it to identify opportunities, mitigate risk, and communicate decisions to upper management.