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Sensitivity Analysis Examples: Learn How to Take Control of the Future

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Every financial model has multiple assumptions. That means the future could hold a range of possibilities, depending on how those assumptions change. 

The problem is predicting any of these possibilities with accuracy. And when left unsure of your business’s future, your control over that future—and your confidence in it—is limited. 

This is where sensitivity analysis can help. Sensitivity analysis is a type of financial analysis that examines different combinations of assumptions, allowing you to see all of a business’s potential future scenarios. 

Whether you’re a retailer, university, investment firm, or manufacturer, sensitivity analysis can be applied to your industry to answer questions such as:

  • What happens to your operating profit if you raise the price of your products or services?
  • How will your investment returns be impacted if the construction of a new building takes longer than expected?
  • How will your bottom line be affected if the cost of goods increases?
  • What will happen to cash flow if you raise employee wages?

Having the ability to answer such questions accurately and efficiently helps illuminate the best path forward. It also makes it easier for analysts and CFOs to reach consensus with stakeholders on the best possible decisions to make for an organization. 

Here, we’ll go over the importance of sensitivity analysis, how to conduct sensitivity analysis, and provide some examples of sensitivity analysis at work. We’ll also explore the different tools businesses use to perform sensitivity analysis and determine the best ones for the job.

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The importance of sensitivity analysis

Sensitivity analysis examines how independent variables (inputs) affect dependent variables (outputs). Without sensitivity analysis, it can be challenging to understand such relationships in depth. 

Let’s say, for example, that a university was deciding to invest in building a new dormitory in 2017, with the expectation that the ability to accommodate more students would lead to more revenue. Would it have been possible to plan for the COVID-19 pandemic in 2020–2021? 

The answer is obviously no. However, with sensitivity analysis, the university’s financial analysts and CFO could have explored how emergency situations, such as a natural disaster or pandemic, would affect room and board revenue. This surely would’ve enabled the institution to better prepare for something unprecedented, like COVID-19.

Furthermore, because conditions are always changing (regardless of exceptional instances like pandemics), it’s crucial that institutions have the ability to perform sensitivity analysis as quickly and effectively as possible. 

In sensitivity analysis, we often perform what’s referred to as ‘what-if’ analysis to isolate individual variables. This gives us the ability to calculate how different inputs will affect formulas. 

On a high level, what-if analysis allows analysts to test how changes in assumptions will affect outputs. By exploring all potential scenarios, businesses and organizations can make better-informed decisions and plan for even the most unpredictable circumstances with confidence. 

With the ability to quickly stress-test different situations, you can better understand how independent variables will affect your organization. This doesn’t only help you prepare for the unexpected—it also unveils key drivers of your organization. It allows you to see which metrics matter most, and, as a result, where you should focus your business’s efforts. 

In short, sensitivity analysis offers a more unified view of your business and simplifies decision-making for stakeholders and analysts. When used correctly, sensitivity analysis can shine a light on the best path forward.

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Sensitivity analysis examples

Before performing sensitivity analysis, you must first:

  1. Establish a base case, best case, and worst-case scenario. This is how you gain an understanding of where you most likely should end up. 
  2. Determine your independent variables. Independent input variables could include cost of goods sold, construction costs, financing charges, customer traffic, and other factors. 
  3. Determine which dependent variables you want to analyze. Do you want to examine outputs like revenue, profit margin, and more?

Once you’ve completed these three steps, you can begin testing these variables and seeing how they affect your organization. Based on the data gathered, you can identify which areas matter most and make decisions about how to allocate resources, what initiatives to undertake, who you need to hire, and much more. 

Let’s go over some examples of how sensitivity analysis helps companies make better, more well-informed decisions. 

The clothing store chain

Let’s say an apparel franchise owner wants to find the most cost-effective method of boosting revenue. To do so, they can test a variety of variables to determine:

  • The payoff of increasing sticker prices by 10% versus the decrease in sales caused by increased prices
  • The return on investment a more robust digital marketing plan would bring to e-Commerce sales
  • How offering more frequent promotions could impact their bottom line 

The government agency

Let’s say a state or local government agency has concerns about its budget for the next fiscal year. It’s a familiar scene—to make the best decision going forward, the agency performs sensitivity analysis to answer several questions: 

  • What would happen down the line if they tapped into their rainy day fund today?
  • What would be the most effective and realistic ways to increase tax revenue?
  • How could they reduce expenses without reducing constituents’ standard of living?

The investment firm

Let’s say a real estate investment firm wants to boost returns for its investors. To decide where to best allocate capital, they perform sensitivity analysis to see:

  • How taking on the construction of new single-family homes will impact returns
  • What selling low-performing assets would do for investors

How new opportunities, like investing in cold food storage, would deliver for clients

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. 

Learning from sensitivity analysis examples

Read over several examples of sensitivity analysis, and you’ll likely notice a trend: most analysts perform sensitivity analysis use one-at-a-time (OAT) or local sensitivity analysis

While this type of sensitivity analysis provides a clear view of how one aspect of a business could impact outcomes, it doesn’t consider the fact that many different factors are contributing to these outcomes at the same time. 

Combined with an unexpected event like the COVID-19 pandemic, lowering tuition rates, for instance, could create an unanticipated rise in enrollment at a university. Sensitivity analysis must be able to account for everything at play in order to be effective. 

So, how is that possible?

The best way to leverage sensitivity analysis

The fact is, you need a financial modeling tool that allows you to visualize all the simultaneous possibilities and test how sensitive your organization is to every possible change.

This is where Synario can help. Using patented layering technology, pre-mapped accounting, and automated object orientation, Synario takes the guesswork out of sensitivity analysis. We eliminate the need for manual, mistake-prone spreadsheets, and deliver an out-of-the-box solution that can answer questions unique to your organization’s financial future.

Synario can help you run sensitivity analysis on an infinite amount of scenarios. This will give you a clear picture of all your organization’s potential futures. 

Looking for greater insight into your risk exposure, where opportunities lie, and what decisions you should make? Explore all the possibilities with Synario.