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Sensitivity Analysis Explained: Definitions, Formulas and Examples

Sensitivity analysis is an indispensable tool utilized in corporate finance and business analysis to comprehend how the variability in key input variables influences the performance of a business. By methodically adjusting the inputs and observing the ensuing effect on outputs, analysts can discern which variables have the most profound impact on the bottom line. This enables companies to concentrate on managing the most sensitive factors to enhance profitability and mitigate risk.

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What is a sensitivity analysis, sensitivity analysis formula, how to do a sensitivity analysis in excel, sensitivity analysis methods, advantages and disadvantages of sensitivity analysis, exercises and examples for sensitivity analysis, key takeaways, sign-up for our free sensitivity analysis template.

A sensitivity analysis measures how susceptible the output of a model is to alterations in the value of the inputs. It aids in identifying which input variables drive most of the variation in the output. For example, in a financial model measuring a company’s profitability, key inputs typically encompass sales growth, cost of goods sold, operating expenses, interest rates, inflation and tax rates. By increasing and decreasing each of these inputs and observing the impact on profits, you can determine which inputs are most sensitive – where minor changes instigate major swings in profits.

While there isn’t a single formula for sensitivity analysis, the general approach is to select an input, modify it by a specified amount, and ascertain the impact on the output. Analysts typically vary inputs up and down by a fixed percentage, such as 10%, to assess sensitivity. The simplistic formula is:

New Output = Base Output x (1 + Change in Input)

For instance, if revenue is amplified by 10% from $100 to $110, the formula is:

New Profit = Base Profit x (1 + 10%) = Base Profit x 1.10

Note: This formula represents a straightforward scenario and actual scenarios may exhibit more complex relationships between input changes and output results.

Diagram of formula for Sensitivity Analysis

Typically, in reviewing client forecasts as a credit analyst, the “base case” provided by the client will show steady growth in sales and margins.  The analyst will typically sensitise this, making a no growth and no margin improvement case, to see if debt ca still be serviced satisfactorily. A separate Combined downside will also typically be modelled where the company is deemed to have experienced difficult trading such as might occur in a recession.

Data services like S&P Capital IQ and FactSet allow analyst to look back and see exactly how variable sales and margins have been in previous recessions.  This can provide a very concrete and rational basis for designing a “downside/recession” scenario.

Excel is a practical tool for conducting sensitivity analysis. Here are the general steps:

  • Build a financial model to calculate the baseline output, such as net income.
  • Create input variables for the major value drivers, like unit sales, price per unit, variable costs per unit, fixed costs , tax rate, etc.
  • Save a copy of the baseline model. Then change one input variable at a time by a fixed amount, like 10%. Recalculate the new output.
  • Repeat step 3 for each input variable. Record the new output values each time.
  • Compare the range of outputs to determine which inputs had the greatest impact. Produce charts in Excel to visualize the sensitivity analysis.
  • Optionally, automate the process using Excel Data Tables.
  • More complex inputs can be modelled in Excel using tools like index or choose together with data validation or VBA tools such as combo boxes.

Below, we’ve created an example of a Sensitivity Analysis for an operating income statement, using Excel’s data analysis functions to perform the analysis:

Excel example of a sensitivity analysis performed on an operating income statement

To implement the sensitivity analysis DATA TABLE:

  • Input a cell reference for the operating income (=D14) in as the starting value for the table (D17), and your sensitivity variance factors in below (C18 to C21).
  • Select your sensitivity factors and operating income column (C17:D21)
  • Navigate the Excel menu ribbon to Data, What if analysis, Table, and you will see the following dialog box.

Excel window requesting data entry for sensitivity analysis table

  • Input the cell for your initial Sensitivity Factor (D9) into the “Column Input cell box”. Press OK.

Excel will then perform your sensitivity analysis: it will take your sensitivity factors (from C18 to C21) one by one, enter them into your given sensitivity factor (D9) and then return the corresponding result from (D17, the cell at the top of the table). It will output the result into the cell next to the input tested. Try them out individually by typing them one by one into D9 using the initial table.

There are several common methods and techniques for performing sensitivity analysis:

  • One-at-a-time (OAT) analysis: Alter one input variable while maintaining others constant. This method is straightforward but can miss interactive effects between variables.
  • Differential analysis: Calculate the rate of change in output based on minute changes in input, thereby allowing ranking of sensitivity.
  • Scenario analysis: Adjust multiple inputs simultaneously to model various scenarios, like worst-case and best-case, which offers a spectrum of possible outcomes.
  • Monte Carlo simulation: Utilize repeated random sampling of input variables to generate a probability distribution of potential outcomes. This is especially useful for models incorporating uncertainty.
  • Tornado diagrams: Graphically illustrate the sensitivity ranking of inputs. The wider the bar, the larger the impact.

Advantages:

  • Identifies pivotal value drivers upon which to focus management attention.
  • Helps in quantifying the risk in a project or forecast.
  • Guides decisions and mitigates risk.
  • Explores scenarios and formulates contingency plans.
  • Enhances comprehension of the nature of the key success variables.
  • Static analysis might overlook dynamic interactions.

Disadvantages:

  • Can be time-consuming when testing numerous scenarios.
  • Necessitates resources and specialized skills.
  • Does not optimize inputs.
  • Limited to model inputs, even if the model itself is incomplete or inaccurate.

Here are some examples to practice conducting sensitivity analysis:

  • A company has fixed costs of $100,000. Unit variable costs are $50, and units sold are projected at 5,000
  • Calculate operating income sensitivity to a 5%, 10%, and 15% variation in units sold.
  • A loan has a principal of $500,000, an interest rate of 6%, and a term of 10 years. Calculate the sensitivity of total repayments to a 0.5%, 1%, 1.5% change in interest rate.
  • An oil company’s net income is based on revenue of $2 million, operating costs of $1.2 million, and a tax rate of 40%. Test sensitivity to 10% changes in revenue, costs, and tax rate.
  • For a capital budgeting project with: NPV = -$1250, Investment = $5000, Lifespan = 5 years, and Discount Rate = 15%, determine the sensitivity of NPV to changes in each input.

Sensitivity analysis is a critical financial modelling technique in the sphere of corporate finance. By discerning which inputs have the most substantial impact on outcomes, companies can hone their efforts on the value drivers that matter most. Performing sensitivity analysis leads to better-informed, data-driven decisions, providing a structured approach towards understanding financial variability and risk.

sensitivity analysis of business plan

Learn Essential Skills Needed to Build Robust Financial Models

Sensitivity analysis faqs, what is an example of a sensitivity analysis.

A sensitivity analysis is a technique used to determine how changes in the values of input variables affect the output or outcome of a model or decision. A common example is varying the interest rate assumptions in a financial model to see how it impacts the net present value or internal rate of return.

How do you conduct a sensitivity analysis?

To conduct a sensitivity analysis, you typically:

  • Identify the key input variables that have the greatest impact on the output.
  • Determine the likely range of values for those input variables.
  • Systematically change the values of the input variables within their ranges and observe the resulting changes in the output.
  • Analyze the sensitivity of the output to changes in each input variable.

What is a sensitivity analysis for P&L?

A sensitivity analysis for a profit and loss (P&L) statement involves examining how changes in revenue, expenses, or other key factors would impact the overall profitability of a business. This can help identify the most critical drivers of financial performance and inform strategic decision-making.

What is DSS sensitivity analysis?

DSS stands for Decision Support System. A DSS sensitivity analysis is the process of evaluating how changes in the input variables of a decision support system model affect the outputs or recommended decisions. This helps quantify the uncertainty and risk associated with the model’s recommendations, allowing decision-makers to make more informed choices.

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A Guide on Sensitivity Analysis for Startup Founders

  • November 6, 2022

Sensitivity analysis is an integral part of financial modeling and business planning. It helps startups analyze how different values of an independent variable will impact a dependent variable under a given set of assumptions.

However, many startup founders are unfamiliar with sensitivity analysis and its potential benefits. As a result, they often make decisions without considering how sensitive their business plans are to changes in key assumptions.

The guide will introduce startup founders to sensitivity analysis and its usage. Keep reading to learn more.

What Is Sensitivity Analysis?

Sensitivity analysis studies how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided into different sources of uncertainty. A model is said to be sensitive to an uncertain parameter if a small change in that parameter results in a significant change in the model output.

In the context of financial modeling, sensitivity analysis shows how the value of a financial model output changes in response to changes in certain inputs, known as drivers. Some drivers include interest rates, commodity prices, exchange rates, and company-specific variables such as revenue growth.

How Does Sensitivity Analysis Work?

Sensitivity analysis is also often termed a what-if analysis. The name is apt since it is often used to analyze what would happen to the results of a given decision if one or more assumptions underlying the original decision were changed.

An early-stage startup can use sensitivity analysis in its financial models to do the following:

  • Forecast : Since a startup is typically a high-growth company, its financial situation can change rapidly. By plugging in different values for key drivers of revenue and expenses, a startup can get a better idea of how its financial situation might change in the future.
  • Plan for Different Outcomes : A startup can use sensitivity analysis to see how different changes in assumptions might affect its financial forecast. What if the marketing campaign doesn’t deliver the expected results? What if a government regulation impacts business processes? It can help the startup plan for different outcomes and make more informed decisions.

So how does this work? The basic idea is to vary one or more inputs to a model and see how the outputs change. For example, in a financial model, the inputs might be assumptions about revenue, expenses, and interest rates. The outputs might be profit, cash flow, or return on investment.

To do a sensitivity analysis, you must choose the inputs you want to vary. Then, you need to decide how much you want to vary them. For example, you might want to increase revenue by 10% and decrease expenses by 5%.

Once you’ve chosen the inputs and the amount you want to vary them, you can run the model with the new inputs and see how the outputs change.

Benefits of Sensitivity Analysis

Sensitivity analysis can help startups make their financial models more dynamic. Here are some benefits of sensitivity analysis.

Helps Determine Impactful Variables

When inputs in a financial model are changed, not all changes will have an equal impact on the model’s results. Sensitivity analysis can help determine which inputs impact the model most. It can help startups focus on the most important inputs and make more accurate predictions.

Allows for Reliable Predictions

Since sensitivity analysis considers multiple scenarios, it can give startup founders a more accurate idea of what to expect. For instance, what will happen if the number of customers decreases? What if costs go up?

Making reliable predictions is imperative for startup success. It also helps create pitch decks that convey the most accurate story to potential investors.

Creates a Cohesive Financial Model

No investors will be confident in your business if you only present a single scenario. They want to see best and worst-case scenarios. They want to know that you’ve thought about the potential risks and rewards of your business.

Sensitivity analysis helps startups create a cohesive financial model by running multiple scenarios. In addition, it gives startups a well-rounded view of their business, which is essential for attracting investors.

Limitations of Sensitivity Analysis

While sensitivity analysis is a powerful tool, it does have limitations. Here are some of them.

Doesn’t Account for the Probability

A sensitivity analysis shows you how far a variable must change to give a certain output. However, it doesn’t consider the probability of this change occurring.

For example, a sensitivity analysis might show that a 10% increase in the price of a product will lead to a 5% decrease in demand. However, there is no indication of how likely this scenario is.

Is Not Relative

In most cases, a sensitivity analysis only focuses on a single variable. However, in real-world scenarios, variables are interconnected.

For instance, inflation is connected to wages, which is, in turn, connected to the cost of living. However, a sensitivity analysis of inflation would not take this into account. It would only focus on the effects of inflation without considering the other variables. That can lead to oversimplified results that don’t reflect reality.

Requires Detailed Data

To be effective, a sensitivity analysis requires detailed data. It can be difficult and time-consuming to obtain so much information.

Should You Include Sensitivity Analysis In Your Financial Model?

As a startup, you must look for ways to optimize your financial model. One way to do this is through sensitivity analysis, which allows you to see how changes in certain variables impact your business.

Therefore, you should include it in your financial model. But then again, a sensitivity analysis for a startup is different from that of an established business. Thus, you must take a custom route rather than a generic approach.

Incorporate Sensitivity Analysis in Your Custom-Made Financial Model

Customized financial models are more comprehensive than generic ones since they consider your specific business situation and goals. At Numberly , we create financial models tailored to your level of maturity and financial situation.

Since our models forecast cash flow requirements well in advance, there’s no room for surprises. Plus, our models answer all the ‘what if’ questions stakeholders may have about your business.

The dashboard has all the ready-to-go KPIs that you can present to potential investors to show your company’s progress. Schedule a 30-minute free call with our experts to learn more about how we make financial modeling a breeze for early-stage founders.

Get investor-ready with a simple and easy to follow, yet fully customized financial model.

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What is Sensitivity Analysis in Finance?

what is sensitivity analysis

Financial forecasting and modelling is all about trying to predict the future of your business – and sensitivity analysis is just a single part of that. If you’ve just created your financial forecast, then sensitivity analysis is the next logical step in planning your business’ future.

What is sensitivity analysis?

Sensitivity analysis is a method used across different industries to understand how changes in variables or assumptions affect the results of a model, system, or decision. It helps businesses to see the connection between input variables and output results and how uncertainties  in those variables can change the outcomes.

In simpler terms, sensitivity analysis helps us figure out which factors have the biggest impact on our results and how small changes in those factors can affect what we’re trying to achieve.

Sensitivity Analysis

What is sensitivity analysis used for?

Sensitivity analysis is a versatile technique with several applications. It is used in:

  • Assessing the impact of changes in variables or assumptions on the outcomes of a model, system, or decision
  • Gaining understanding of the relationships between input variables and output results
  • Analyzing how uncertainties or variations in variables can influence the final outcomes
  • Supporting decision-making processes by providing insights into the effects of different factors
  • Identifying critical factors that have a significant impact on the results
  • Enhancing awareness of model limitations and potential risks associated with the analysis.

How does sensitivity analysis work?

Here’s a simplified explanation of how sensitivity analysis typically operates:

  • Identify input variables : First, you need to identify the variables or assumptions that have an impact on the model or system you are analyzing. These are the factors that you want to examine in terms of their influence on the output.
  • Define the range : Determine the range or values that each input variable will take during the sensitivity analysis. This range can be based on expert judgment, historical data, or other relevant information.
  • Select a method : Choose a specific sensitivity analysis method based on your objectives. Common methods include one-way sensitivity analysis, multi-variable analysis, tornado diagrams, or Monte Carlo simulations.
  • Analyze the variations : Apply the chosen method to evaluate the effects of varying the input variables. This involves running the model multiple times while changing one variable at a time or simultaneously changing multiple variables.
  • Observe the output changes : Monitor and record the resulting changes in the output measures of each variation of the input variables. This allows you to see how the output is influenced by different values or assumptions.
  • Interpret the results : Analyze the collected data to identify trends, patterns, and relationships between input variables and output results. Determine which variables have the most substantial impact on the outputs and understand how changes in these variables affect the overall outcomes.
  • Draw conclusions : Based on the sensitivity analysis results, draw conclusions about the reliability, and stability of the model or system. This information can guide decision-making, risk assessment, and further analysis or adjustments.

Sensitivity analysis helps to enhance understanding of the relationships and dependencies between variables, aiding decision-makers in making informed choices and managing uncertainties.

What does sensitivity analysis work

An example of sensitivity analysis

Suppose you are a project manager planning to launch a new product. You have created a financial model that estimates the project’s profitability based on several input variables. These variables include the selling price of the product, the production cost per unit, the sales volume, and the marketing expenses.

To perform sensitivity analysis, you decide to vary each of these input variables to assess their impact on the project’s profitability. Here’s how the analysis may unfold:

  • Selling price : You start by analyzing the sensitivity of the selling price. You choose a range of possible prices, such as $50 , $60 , and $70 per unit, and evaluate the profitability for each price point.
  • Production cost per unit : Next, you examine the sensitivity of the production cost per unit. You consider different cost scenarios, such as $20 , $25, and $30 per unit, and analyze the impact on profitability.
  • Sales volume : Moving on, you investigate the sensitivity of the sales volume. You explore various sales projections, such as 1,000 units , 1,500 units , and 2,000 units , and observe the profitability for each volume.
  • Marketing expenses : Lastly, you explore the sensitivity of marketing expenses. You consider different marketing budget allocations, such as $10,000 , $15,000 , and $20,000 , and evaluate the corresponding impact on profitability.

By conducting sensitivity analysis on these variables, you can identify which factors have the most significant influence on the project’s profitability. This information helps you make informed decisions, prioritize your focus on key factors, and develop contingency plans to manage uncertainties effectively.

Sensitivity analysis vs scenario analysis

Sensitivity analysis and scenario analysis are both techniques used to assess the impact of changes or variations on the outcomes of a model or system. While they have some similarities, there are distinct differences between the two:

  • Focus : Sensitivity analysis focuses on examining the impact of changes in individual input variables on the model’s outputs. It aims to understand the relationships between specific variables and the outcomes. In contrast, scenario analysis focuses on exploring different sets of input values or assumptions together, creating different scenarios to understand their combined impact on the outputs.
  • Variation approach : Sensitivity analysis typically involves systematically varying one input variable at a time while keeping others constant, allowing for a more isolated analysis of each factor’s influence. Scenario analysis, on the other hand, involves creating and analyzing multiple scenarios by simultaneously changing multiple input variables, considering different combinations of values or assumptions for a holistic analysis.
  • Range of possibilities : Sensitivity analysis often focuses on exploring a specific range of values for each input variable to understand how the output responds. In contrast, scenario analysis considers a broader range of possible scenarios, each with its own set of input values, to capture a wider spectrum of potential outcomes.
  • Purpose : Sensitivity analysis primarily aims to identify the most influential factors and quantify their impact on the model’s outputs. It helps understand the model’s sensitivity to changes in input variables and supports decision-making and risk assessment. Scenario analysis, on the other hand, is more focused on exploring different plausible future scenarios and assessing their potential impact on the outcomes. It helps in evaluating the model’s robustness under different conditions and aids in strategic planning and contingency preparation.

In practice, sensitivity analysis and scenario analysis can be complementary and used together. Sensitivity analysis can provide detailed insights into the impact of individual variables, while scenario analysis allows for a broader examination of different combinations of variables to explore a range of potential outcomes. The choice between the two techniques depends on the specific objectives, available data, and the complexity of the model or system being analyzed. Take a look at the features of a scenario planning software today.

Sensitivity analysis vs scenario analysis

Sensitivity analysis advantages

Sensitivity analysis offers several advantages that make it a valuable tool for decision-making and analysis. Here are some key advantages of sensitivity analysis:

  • Identifies critical factors : Sensitivity analysis helps identify the input variables that have the most significant impact on the model or system outputs. This allows decision-makers to focus their attention and resources on the most influential factors.
  • Quantifies relationships : By systematically varying input variables and observing output changes, sensitivity analysis provides a quantitative understanding of the relationships between inputs and outputs. It helps quantify the degree of influence that each variable has on the results, enabling better assessment of potential risks and opportunities.
  • Enhances robustness : Sensitivity analysis helps assess the robustness of a model or system. By identifying the variables that have the most significant impact, decision-makers can understand the potential vulnerabilities and uncertainties associated with the system, allowing for improved planning and risk management.
  • Supports decision-making : Sensitivity analysis provides valuable insights into the potential outcomes associated with different variables or assumptions. It helps decision-makers understand the potential risks, benefits, and uncertainties associated with alternative courses of action, facilitating informed decision-making.
  • Enables scenario exploration : Sensitivity analysis can be extended to explore multiple scenarios by varying multiple input variables simultaneously. This allows decision-makers to evaluate different combinations of variables and understand the range of potential outcomes under various conditions, enabling better scenario planning and analysis.
  • Improves communication : Sensitivity analysis enables effective communication of complex relationships and uncertainties to stakeholders, promoting a better understanding of the analysis results and supporting collaborative decision-making.

Overall, sensitivity analysis enhances understanding, quantifies relationships, supports decision-making, and improves the robustness of models and systems. Its advantages make it a valuable tool for assessing the impact of input variables and assumptions on outcomes, helping to make more informed and effective decisions.

Sensitivity analysis disadvantages

While sensitivity analysis offers various advantages, it also has some limitations and potential disadvantages. Here are a few considerations to keep in mind:

  • Simplifying assumptions : Sensitivity analysis often involves simplifying assumptions, such as holding other variables constant while varying one at a time. This simplification may not fully capture the complex interactions and dependencies among variables.
  • Limited scope : Conducting sensitivity analysis on a limited number of variables may overlook important factors that could significantly impact the outcomes. If key variables are omitted or if the analysis does not capture all relevant uncertainties, the results may not accurately represent the real-world complexity.
  • Linear relationships : Sensitivity analysis assumes linear relationships between variables and outcomes, which may not hold true in all cases. Nonlinear relationships and complex interactions among variables can lead to more intricate dynamics that sensitivity analysis alone may not fully capture.
  • Lack of probabilistic information : Sensitivity analysis often focuses on deterministic changes in input variables, disregarding the probabilistic nature of uncertainties. This limitation can be addressed by integrating probabilistic methods, such as Monte Carlo simulation, into sensitivity analysis to account for the distribution and variability of input variables.
  • Limited guidance for decision-making : While sensitivity analysis provides insights into the relative importance of variables, it may not offer clear guidance on specific actions or decisions. It highlights which variables have a significant impact, but additional analysis and judgment are often required to determine the most appropriate course of action.
  • Data limitations : The quality and availability of data for sensitivity analysis can be a challenge. Lack of accurate or comprehensive data on input variables may affect the reliability and validity of the analysis results.
  • Unrealistic assumptions : Sensitivity analysis relies on certain assumptions, such as linear relationships or static conditions, which may not always align with the real-world complexities of the system or model being analyzed. These assumptions can limit the applicability and accuracy of the analysis.

It is important to recognize these limitations and consider them when interpreting the results of sensitivity analysis. Sensitivity analysis should be used in conjunction with other analytical techniques and tools to gain a comprehensive understanding of the system or model under study.

Sensitivity analysis disadvantages

Sensitivity analysis in Brixx

Brixx allows users to create detailed financial models and perform various analyses, including sensitivity analysis, to assess the impact of changes in input variables on financial outcomes.

Within Brixx , you can define different scenarios by varying input variables and observing the resulting changes in the projected financials. By specifying ranges or specific values for variables like sales volume, prices, costs, or other relevant factors, you can analyze how these changes affect key financial metrics such as revenue, profit, cash flow, or valuation.

Brixx’s interface allows you to specify different values or ranges for the variables of interest. It then automatically calculates and presents the corresponding outcomes based on the defined scenarios. This allows you to explore the sensitivity of your financial forecasts to changes in different input variables, helping you understand the potential risks, opportunities, and uncertainties associated with your financial projections.

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From Planning to Valuation: Mastering Business Planning and Sensitivity Analysis for Your Startup

  • First Online: 26 September 2023

Cite this chapter

sensitivity analysis of business plan

  • Sinem Derindere Köseoğlu 2  

Part of the book series: Contributions to Finance and Accounting ((CFA))

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Starting a new business can be a daunting task, but having a solid business plan, building a good financial model, and performing sensitivity analysis can help mitigate risks and increase the chances of success. In this chapter, I discuss the importance of business planning and sensitivity analysis in startup valuation, as well as how to develop an effective business plan and build a financial model.

The chapter starts by defining the key components of a business plan, including the executive summary, market analysis, marketing strategy, financial projections, and implementation plan. The chapter also provides tips on how to write each section effectively, and how to tailor the plan to the needs of the startup and its target audience. Creating a solid business plan, building a financial model, and performing sensitivity analysis are critical for startups to succeed, but it can be challenging to apply these concepts to real-life scenarios. In this chapter, I take a deep dive into a real case study of a startup, and demonstrate how financial modeling and sensitivity analysis were used to develop a successful business plan and secure funding. The chapter also indicates how the financial model was used to create a proforma balance sheet and proforma income statement, which provide a snapshot of the company’s financial performance and position over time. By the end of this chapter, readers will have a practical understanding of how financial modeling and sensitivity analysis can be used to develop a successful business plan and drive value creation.

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Goker, O., & Derindere Köseoğlu, S. (2020). Challenges in valuation by using discounted free cash flow method. In S. D. Köseoğlu (Ed.), Valuation challenges and solutions in contemporary businesses (p. 67). IGI Global.

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Köseoğlu, S.D. (2023). From Planning to Valuation: Mastering Business Planning and Sensitivity Analysis for Your Startup. In: Derindere Köseoğlu, S. (eds) A Practical Guide for Startup Valuation. Contributions to Finance and Accounting. Springer, Cham. https://doi.org/10.1007/978-3-031-35291-1_3

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Why Your Startup Pitch Needs Sensitivity Analysis

To impress risk-averse investors, you have to prove that you’re ready for whatever may come.

Why Your Startup Pitch Needs Sensitivity Analysis

By Nicholas Piscani

Nicholas is a corporate strategy and FP&A expert who works with businesses to optimize their operations and execute high-priority strategic initiatives. He has helped entrepreneurs raise more than $600 million through financial modeling and pitch deck development.

Previous Role

PREVIOUSLY AT

It takes more than an all-star team, a product with a competitive advantage , and a sizable potential market to guarantee fundraising success for your startup. With thousands of proposals flooding investors’ inboxes each year, and venture capital facing an uncertain future , it’s crucial that you distinguish your startup by showing your deep, realistic understanding of the impact even small changes can have on performance. The key is to include sensitivity analysis in your pitch.

As an FP&A specialist who has supported multiple successful eight- and nine-figure fundraising efforts through financial modeling and pitch deck development , I’ve learned firsthand the nuances that separate founders who get funding from those who leave the table empty-handed. To present a convincing case, founders must show that they’re effectively balancing risk and responsibility by demonstrating that they have thoroughly evaluated the consequences of every decision.

While it’s understandable that founders want to project optimism when they’re pitching investors , ignoring challenges can damage the trust they need to build with potential funders. Venture capital firms are quickly turned off by implausibly positive financial forecast assumptions, such as overly generous market share predictions or unrealistic unit economics . What they want to see are model assumptions that have been tested and validated.

That’s especially important when capital is scarce. In 2023, raising money has been particularly tough for startups, with global funding diving to $76 billion in the first quarter, a 53% decrease from the $162 billion recorded in the same quarter of 2022, according to Crunchbase. What’s more, in the same period, every funding stage experienced a steep decline of around 44% to 54%. These figures suggest that venture capital firms are growing more risk-averse . The best response to this trend is to exhibit strong fundamentals and provide persuasive evidence of viability through sensitivity analysis.

What Is Sensitivity Analysis?

Sensitivity analysis, also called what-if analysis, measures the effects of changing inputs in a mathematical model. In a financial model, sensitivity analysis can reveal the inputs with the greatest impact on a business, and help managers develop KPIs and strategies to monitor and address changes in those areas of the business. For instance, if variables such as market size , unit cost, price, or sales volume were to change, how might that affect financial performance—and which one has the biggest impact?

In my experience, founders can sometimes confuse sensitivity analysis and scenario analysis . While both practices evaluate the impact of changes on business models, they’re not the same.

Sensitivity analysis typically focuses on the one or two most important variables in a business model—that is, the ones that will generally cause the largest degree of change, depending on the industry and how the model is built. For example, you might want to sensitize sales price per square foot in a real estate development model , customer churn rates in a subscription-based model , or product mix in a manufacturing model.

Scenario analysis, on the other hand, is used to measure how businesses perform with variations in macro factors that influence the whole organization or an entire business unit. Scenario analysis would be appropriate for evaluating the probable impact of a recession or changing industry regulations—two situations that have a significant effect on a company’s performance even if some key variables and assumptions remain the same.

Sensitivity analysis is one of the most helpful ways a founder can calm investors’ nerves, because it provides them with a view of the margin of safety associated with their investments. If an investor is using a minimum internal rate of return (IRR) as one of their investment qualification metrics, for example, sensitivity analysis can easily demonstrate how significantly the forecasted performance would need to change before the investment fell below the minimum IRR.

From an investor’s perspective, knowing that an investment can still achieve the minimum IRR over the life of the investment despite a 10% drop in sales volume, for instance, gives additional credibility to the founder, the model, and the management team. In this case, even if a prospective investor disagrees with some of the growth prospects and assumes sales will be only 95% of the forecast, they can know that the investment is still a viable one.

Now let’s take a deeper look at the many things sensitivity analysis can help you do to impress potential investors—and benefit your company.

Understand How Small Changes in Assumptions Drive Big Changes in Value

When you’re building projections over long periods, say five to 10 years, small changes in the financial model’s underlying assumptions can cause large changes in the growth of cash flows and valuation . In the first table we can see how significantly small changes in assumed unit sales growth and revenue per sale can impact profitability and cash flows for a retail company.

In Table 1, the present value (PV) of future cash flows , including the terminal value, is just under $130 million.

Table 2 illustrates the same forecast, with unit sales growth reduced by 2% and revenue per sale reduced by 1% starting in the first year. The present value of total future cash flows, including the terminal value, drops to just under $94 million, a 27.7% decrease compared with Table 1.

Again, that’s a 27.7% decrease in cash flows caused by a 2% drop in unit sales growth and a 1% drop in revenue per sale. And unit sales are not the only variable that can change. What if marketing expenses are higher? What if return rates are greater than expected? What happens if net working capital (NWC) doesn’t improve as forecasted?

Successful companies cannot just assume things will go their way: They need to know precisely what they’ll do if costs rise or sales fall unexpectedly. This is why startup companies need to assure investors they’ve stress-tested their models and developed risk management strategies for rainy days.

Identify What Is Most Significant

Sensitivity analysis enables organizations with well-constructed business and financial models to pinpoint and communicate pivotal assumptions. I can’t overemphasize what profound implications this can have for you as a startup founder—not only from a strategic perspective, but also from a fundraising perspective. Not every startup founder can confidently tell investors that they know which assumptions will have the most significant impact on cash flow, and be able to quantify the change in cash flow for every percentage point change in the relevant assumption. When you walk into a pitch meeting with this information in hand, you reassure investors that you’ve thought thoroughly and concretely about the future of the business—and their equity.

Let’s look at this in practice using our earlier retail company example. Starting with the assumptions in Table 1, the model forecasts 10% unit sales growth in Year 1. But how sensitive are cash flows to that assumption versus other assumptions? The following sensitivity analysis tables show how sensitive the present value of future cash flows is to changes in three assumptions that could have significant impacts: unit sales growth, wages paid per unit sold, and annual rent escalations.

Looking at Tables 3 to 5, it’s clear that unit sales growth is the most significant factor on cash flow, with a 1% change causing a roughly 8% change in the present value of cash flows. With this information, you can zero in on the most important drivers of the business model.

To take this analysis a step further and look at a more complicated situation, you can evaluate the potential impact of two of these factors occurring. In the current economic climate of high inflation, there’s a real risk that landlords will require higher rents as leases expire. Let’s say that you’re concerned about cash flow sensitivity to the compound effect of changes in both unit sales growth and annual rent escalations. Continuing with the retail example, we can construct the following table.

A look at Table 6 shows that a 1% increase in annual unit sales growth on the value of cash flows has about six times the impact that a 1% increase in annual rent escalations has. Performing similar analyses for all assumptions in the model will reveal how they interact.

Create Data-driven Strategies

Once you have sensitized your assumptions and identified the areas of greatest impact, you’ll have valuable data for developing strategies to monitor and optimize those parts of your business. In the example model, key drivers of unit sales growth would consist of customer acquisition costs (CAC) , repeat customer rates, return rates, and cross-sell and upsell rates. Let’s say that, after sensitizing the unit sales growth rates against these individual variables, as we did with the annual rent escalations, you determine that return rates and CAC are the primary factors. Your team can then pinpoint the specific levels of performance that would be required to attain the forecasted unit sales growth targets. These performance levels would become the key performance indicators (KPIs) that are monitored and managed by leadership.

From there, you can identify leading indicators for daily monitoring that will inform management if the KPIs are expected to come in above or below the acceptable target. For example, a leading indicator for return rate may be customer satisfaction levels or a Net Promoter Score .

A comprehensive sensitivity analysis of this kind provides the entire management team with the greatest chance of fully understanding and preparing for the opportunities and threats. Not only does this benefit your business, but it helps you formulate persuasive, data-driven answers to hard investor questions.

Prove to Investors That They Can Trust You

If there’s anything the business community has learned from the 2007-2008 financial crisis and the economic shock caused by the COVID-19 pandemic, it’s to expect the unexpected. Sensitivity analysis is a powerful tool in this environment. The ability to sensitize nearly all variables in a business model provides tremendous analytical flexibility and can illuminate potential opportunities and threats.

Lack of funding and cash flow problems can substantially impede a startup’s growth and ability to take advantage of opportunities. Startup funding has declined significantly since 2021, meaning competition for it is fierce. By integrating sensitivity analysis into your pitch and valuation projections, you can also answer potential investor concerns, validate your assumptions, and exhibit prudent risk management. In an era of heightened investor caution, this kind of foresight and preparedness can set up your pitch—and your company—for success.

Further Reading on the Toptal Blog:

  • What Is a Financial Model?
  • Top Pitch Deck Mistakes
  • How to Build a 3-statement Model: Best Practices for Valuations and Projections
  • Industry Analysis and Porter’s 5 Forces: A Deeper Look at Buyer Power
  • How to Build Your Startup’s Financial Model to Grab Investor Interest
  • Justifying Investments With the Capital Budgeting Process

Understanding the basics

What is the purpose of sensitivity analysis.

The purpose of sensitivity analysis is to measure the effects of changing the inputs in a mathematical model. In a financial model, sensitivity analysis can reveal the inputs with the greatest impact and help managers develop KPIs and strategies to monitor and address changes to those areas of the business.

What is an example of sensitivity analysis?

A trucking company may want to know how much a change in the average price of gas would have on the firm. It would perform a sensitivity analysis by developing a model to calculate the effect different gas prices would have on other important parts of the business, such as cash flows or profits. Those results would help the company plan for high gas prices and take advantage of low gas prices.

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Member since July 29, 2022

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What is sensitivity analysis in business.

Sensitivity analysis is a key tool used in business decision making. It helps to uncover the impact of changes in a single variable on the overall outcome of a given situation. In other words, it is an evaluation of what would happen if one variable changed while all other variables remained constant. This type of analysis can be used in a variety of different contexts such as analyzing financial performance, evaluating marketing strategies, or predicting future outcomes. In this article, we’ll explore the concept of sensitivity analysis in detail and discuss its applications in business.

What is sensitivity analysis?

Sensitivity analysis is a technique that is used to determine how different values of an independent variable will affect a particular dependent variable under a given set of assumptions. In business, sensitivity analysis is often used to evaluate the potential impact of changes in sales volume, costs , or other factors on profitability.

For example, a company might use sensitivity analysis to estimate the effect of a 10 percent increase in the price of its product on sales volume. If the company finds that its sales would not be significantly affected by the price increase, it may decide to implement the price increase. On the other hand, if the company finds that its sales would decrease significantly, it may decide against implementing the price increase.

In addition to being used to evaluate the potential impact of changes in business conditions , sensitivity analysis can also be used to compare different courses of action. For instance, a company might use sensitivity analysis to compare the relative impact of two marketing strategies on profitability.

Sensitivity analysis is an important tool for managers because it can help them make better decisions by taking into account how changes in key variables will affect outcomes.

Why is sensitivity analysis important in business?

Sensitivity analysis is important in business for a number of reasons . First, it can help identify potential risks and opportunities. Second , it can help decision-makers understand how changes in key assumptions can impact results. Third, it can help businesses develop contingency plans . Finally, sensitivity analysis can help businesses communicate their risk tolerance to stakeholders .

How to conduct a sensitivity analysis

Sensitivity analysis is a technique used to determine how different values of an independent variable will affect a particular dependent variable under a given set of assumptions. Sensitivity analysis is often used in business in order to make decisions about pricing, investment, and other strategic decisions.

There are three main types of sensitivity analyses: univariate, multivariate, and scenario. Univariate sensitivity analyses vary only one parameter at a time while holding all other variables constant. Multivariate sensitivity analyses vary two or more parameters simultaneously. Scenario analyses vary multiple parameters according to different hypothetical situations.

To conduct a sensitivity analysis, businesses first need to identify the important inputs or factors that will affect the outcome of interest. Once these inputs have been identified, businesses must then determine the range of possible values for each input. The range of values can be based on historical data, expert opinion, or other information sources .

After the ranges of values have been determined, businesses will need to choose a method for conducting the analysis. The most common methods are Monte Carlo simulation and grid search. Monte Carlo simulation generates random values for each input within its defined range and then calculates the output for each combination of inputs. Grid search involves systematically varying the input values within their defined ranges and calculating the corresponding outputs.

Once the chosen method has been used to generate results, businesses can analyze the results to identify which inputs have the greatest impact on the output of interest. Results can also be analyzed to identify areas

What are the different types of sensitivity analyses?

There are many different types of sensitivity analyses that businesses can use to evaluate the potential risks and rewards of different courses of action. Some common types of sensitivity analyses include:

1. What-if analysis: This type of analysis involves considering what would happen if a certain variable was changed . For example, a business might consider what would happen if interest rates increased or if a key supplier went out of business.

2. Monte Carlo simulation: This type of analysis uses random numbers to model different possible outcomes. This can be helpful in understanding the potential range of outcomes that could occur and how likely each outcome is.

3. Scenario analysis: This type of analysis involves creating different scenarios, or hypothetical situations, and then evaluating what would happen under each one. This can be helpful in identifying which factors have the biggest impact on results and in planning for different contingencies .

How to interpret the results of a sensitivity analysis

When conducting a sensitivity analysis, businesses typically analyze a range of potential outcomes in order to identify which factors have the greatest impact on the overall results. To interpret the results of a sensitivity analysis, businesses need to consider both the magnitude and direction of the effect that each factor has on the results.

The magnitude of the effect is represented by how far away from the baseline result a particular factor moves the outcome. For example, if the baseline result is a profit of $100 and one factor increases profits by $10, then that factor has a small positive effect. However, if another factor decreases profits by $30, then that factor has a bigger negative effect .

The direction of the effect is represented by whether a particular factor increases or decreases profits . For example, if one factor increases profits by $10 and another decreases profits by $30, then the first factor has a positive effect while the second has a negative effect.

Sensitivity analysis is used in business to help identify areas of potential risk and highlight opportunities for improvement. It helps managers make informed decisions by taking into account the potential impact of different variables on their businesses. This article has outlined the basic principles behind sensitivity analysis, as well as some practical examples that can be used to better understand how it works in practice. By incorporating sensitivity analysis into your decision-making process, you’ll have a much clearer view of the risks and rewards associated with any particular strategy or action.

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Home » Feasibility Study

How to Do Risk & Sensitivity Analysis in a Feasibility Study

Are you conducting feasibility study on a business project and need help doing the analysis? If YES, here is a complete guide on how to do risk and sensitivity analysis.

The rate at which businesses fail can be traced to lack of business training. Most people jump into a new business once they notice that the business is trending and highly profitable. They fail to carry out their due diligence to know if the business is worth investing in. Part of what you need to do aside undergoing business training before starting your business is to conduct risks and sensitivity analysis for your business.

What is Risk and Sensitivity Analysis?

Conducting risks and sensitivity analysis involves accessing all the risks and sensitive areas that is associated with the type of business you want to start. As a matter of fact, there is no business that is not prone to risks and it is your responsibility as an entrepreneur to access the risks involved in running the type of business you are about to start and also to know whether you have what it takes to shoulder the risks.

Likewise, sensitivity analysis will help you put measure in place that will help you predict the outcome of all the business decisions you make. Simply put, sensitivity analysis will help you increase your understanding of the existing relationship between input and output variables in your business. It is a known fact that succeeding or failing in business is all about the decisions you make.

Although conducting risks and sensitivity analysis will not help you to totally eliminate all the uncertainties of making business decision, but you are sure that it will help you minimize the uncertainty to the barest minimum. Now here the steps you would need to follow to be able to effectively conduct risks and sensitive analysis for your business;

How to Do Risk & Sensitivity Analysis in a Feasibility Study

1. Study and Research

To start with, if you have never conducted a risk and sensitivity analysis for a business before, then you have a lot of work to do. What is expected of you is to spend enough time studying and researching on the subject – risk and sensitivity analysis.

There are materials online and in libraries that will help you achieve your aim of conducting a risk and sensitivity analysis for your business. The truth is that conducting risks and sensitivity analysis is usually done by experts because of the technicality involved, but you can do it yourself if you spend time to study existing models.

2. Collect and Analyze Data and Graphs

Part of what you need to do when studying and researching on risks and sensitivity analysis is to collect and analyze data and graphs that are related to your business. Once you are able to properly analyze data and interpret graphs, it will give you an edge when conducting your risks and sensitivity analysis.

You will be able to pin point areas where you would need to concentrate on. As a matter of fact, you can not effectively conduct risks and sensitivity analysis without the skills to properly analyze graphs and interpret data.

3. Develop a Theoretical Framework for Using Risks and Sensitivity Analysis for Decision Making

Once you are able to analyze the required data and graphs, what is expected of you to do is to develop a theoretical framework for using risks and sensitivity analysis for decision making. The essence of conducting risks and sensitivity analysis for your business is to put structures in place that will help you mitigate risks and uncertainty in your business and in turn maximize profits. You can work with experts to help you create a model that is suitable for your business.

4. Run the Model a Number of Times before Adopting It

It is one thing to develop a theoretical framework that will guide you in decision making in your business, it is entirely another thing for the model to work in real life situation. It is important to run the model you developed for risks and sensitivity analysis for your business a number of times before adopting it in your business.

What is the use of having a fantastic theoretical framework on paper without it working in real life situation? The best time to adjust your theoretical framework is during the process of test running it; once you discover any drawback, then you should go back to the drawing board and restructure or adjust your framework.

5. Review the Document Generated From Your Risks and Sensitivity Analysis

Once you are done with all the steps listed above, you would have succeeded in completing your risks and sensitivity analysis for your business and also you will be able to produce a comprehensive document in that regard. The process will not be complete if you do not review the document generated from your risks and sensitivity analysis. You can engage the services of a professional to help you review the document.

Over and above, if you are successful in conducting your own risks and sensitivity analysis for your business, you would have succeeded in finding the possible outcomes of most of the business decisions that you will make in your business and you will be well guided.

As a matter of fact, some folks consider risks and sensitivity analysis as a systematic common sense technique adopted by many business owners to minimize making wrong decisions that will cost the company.

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Sensitivity Analysis Definition

sensitivity analysis of business plan

Sensitivity analysis determines how different values of an independent variable affect a particular dependent variable under a given set of assumptions. In other words, sensitivity analyses study how various sources of uncertainty in a mathematical model contribute to the model's overall uncertainty. This technique is used within specific boundaries that depend on one or more input variables.

Sensitivity analysis is used in the business world and in the field of economics . It is commonly used by financial analysts and economists and is also known as a what-if analysis.

Key Takeaways

  • Sensitivity analysis determines how different values of an independent variable affect a particular dependent variable under a given set of assumptions.
  • This model is also referred to as a what-if or simulation analysis.
  • Sensitivity analysis can be used to help make predictions in the share prices of publicly traded companies or how interest rates affect bond prices.
  • Sensitivity analysis allows for forecasting using historical, true data.
  • While sensitivity analysis determines how variables impact a single event, scenario analysis is more useful to determine many different outcomes for more broad situations.

Investopedia / Lara Antal

How Sensitivity Analysis Works

Sensitivity analysis is a financial model that determines how target variables are affected based on changes in other variables known as input variables. It is a way to predict the outcome of a decision given a certain range of variables. By creating a given set of variables, an analyst can determine how changes in one variable affect the outcome.

Both the target and input—or independent and dependent—variables are fully analyzed when sensitivity analysis is conducted. The person doing the analysis looks at how the variables move as well as how the target is affected by the input variable.

Sensitivity analysis can be used to help make predictions about the share prices of public companies . Some of the 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. The analysis can be refined about future stock prices by making different assumptions or adding different variables. This model can also be used to 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.

Sensitivity analysis allows for forecasting using historical, true data. By studying all the variables and the possible outcomes, important decisions can be made about businesses, the economy, and making investments.

Investors can also use sensitivity analysis to determine the effects different variables have on their investment returns.

Financial models that incorporate sensitivity analysis can provide management a range of feedback that is useful in many different scenarios. The breadth of the usefulness of sensitivity analysis includes but is not limited to:

  • Understanding influencing factors. This includes what and how different external factors interact with a specific project or undertaking. This allows management to better understand what input variables may impact output variables.
  • Reducing uncertainty. Complex sensitivity analysis models educate users on different elements impacting a project; this in turn informs members on the project what to be alert for or what to plan in advance for.
  • Catching errors. The original assumptions for the baseline analysis may have had some uncaught errors. By performing different analytical iterations, management may catch mistakes in the original analysis.
  • Simplifying the model. Overly complex models may make it hard to analyze the inputs. By performing sensitivity analysis, users can better understand what factors don't actually matter and can be removed from the model due to its lack of materiality.
  • Communicating results. Upper management may already be defensive or inquisitive about an undertaking. Compiling analysis on different situations helps inform decision-makers of other outcomes they may be interested in knowing about.
  • Achieving goals. Management may lay long-term strategic plans that must meet specific benchmarks. 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 metric targets.

Because sensitivity analysis answers questions such as "What if XYZ happens?", this type of analysis is also called what-if 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 a 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 a scenario analysis, an analyst determines a certain scenario such as a stock market crash or change in industry regulation. The analyst then changes the variables within the model to align with that scenario. Put together, the analyst has a comprehensive picture and 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.

Advantages 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.

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. Very complex models may be system-intensive, and models with too many variables may distort a user's ability to analyze influential variables.

Provides management different output situations based on risk or changing variables

May help management target specific inputs to achieve more specific results

May easily communicate areas to focus on or greatest risks to control

May identify mistakes in the original benchmark

Generally reduces the uncertainty and unpredictability of a given undertaking

Heavily relies on assumptions that may not become true in the future

May burden computer systems with complex, intensive models

May become overly complicated which distorts an analysts ability to

May not accurately integrate independent variables (as one variable may not accurately the impact of another variable)

Example of Sensitivity Analysis

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

Sue also determines that a 10% increase in customer traffic increases transaction volume by 5%. This allows her to build a financial model and sensitivity analysis around this equation based on what-if statements. It can tell her what happens to sales if customer traffic increases by 10%, 50%, or 100%.

Based on 100 transactions today, 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 highly sensitive to changes in customer traffic.

What Is Sensitivity Analysis in NPV?

Sensitivity analysis in NPV analysis is a technique to evaluate how the profitability of a specific project will change based on changes to underlying input variables. Though a company may have calculated the anticipated NPV of a project, it may want to better understand how better or worse conditions will impact the return the company receives. 

How Do You Calculate Sensitivity Analysis?

Sensitivity analysis is often performed in analysis software, and Excel has built in functions to help perform the analysis. In general, sensitivity analysis is calculated by leveraging formulas that reference different input cells. For example, a company may perform NPV analysis using a discount rate of 6%. Sensitivity analysis can be performed by analyzing scenarios of 5%, 8%, and 10% discount rates as well by simply maintaining the formula but referencing the different variable values. 

What Are the Two Main Types of Sensitivity Analysis?

The two main types of sensitivity analysis are local sensitivity analysis and global sensitivity analysis. Local sensitivity analysis assesses the effect of a single parameter at a time while holding all other parameters constant, while global sensitivity analysis is a more broad analysis used in more complex modeling scenarios such as Monte Carlo techniques.

What Is the Difference Between Sensitivity Analysis and Scenario Analysis?

Sensitivity analysis is the technique of taking a single event and determining different outcomes of that event. For example, a company may analyze its valuation based on several factors that may influence the calculation. On the other hand, scenario analysis relates to more broad conditions where the outcome is not known. For this example, imagine economists trying to project macroeconomic conditions 18 months from now. 

When a company wants to determine different potential outcomes for a given project, it may consider performing a scenario analysis. Scenario analysis entails manipulating independent variables to see the resulting financial impacts. Companies perform scenario analysis to identify opportunities, mitigate risk, and communicate decisions to upper management.

Stanford University, Department of Aeronautics and Astronautics. " Chapter 4, Sensitivity Analysis ," Pages 77.

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Sensitivity Analysis in Business Valuation: DCF Method Focus

Sensitivity analysis is a crucial tool in the field of business valuation, particularly when employing the Discounted Cash Flow (DCF) method. By systematically examining how changes in key assumptions or variables impact the estimated value of a company, sensitivity analysis provides valuable insights into the robustness and reliability of the valuation model. For instance, consider a hypothetical case study where an investor intends to acquire a manufacturing firm. Through sensitivity analysis, various scenarios can be explored, such as fluctuations in revenue growth rates, discount rates, or capital expenditure projections. This allows for a comprehensive assessment of potential risks and uncertainties that may affect the accuracy and validity of the final valuation outcome.

In recent years, there has been growing recognition among researchers and practitioners regarding the significance of conducting sensitivity analysis within DCF-based business valuations. The complex nature of these models necessitates capturing variations across multiple input parameters to ensure more accurate estimations and mitigate inherent biases. Sensitivity analysis aids decision-makers by providing them with a range of possible outcomes under different circumstances, enabling better risk management strategies. By identifying which factors have the most substantial influence on overall enterprise value, stakeholders can focus their attention on addressing those specific areas in order to enhance financial performance and minimize potential downside risks associated with investment decisions. Thus, understanding Thus, understanding the sensitivity of a business valuation model to changes in key assumptions or variables allows decision-makers to make more informed and strategic choices. It helps them identify potential areas of uncertainty and risk, enabling them to develop contingency plans and evaluate the impact of different scenarios on the estimated value of the company. By incorporating sensitivity analysis into the valuation process, stakeholders can gain greater confidence in their investment decisions and improve overall financial planning and management.

Definition of Sensitivity Analysis

Sensitivity analysis is a crucial technique used in business valuation, particularly when employing the discounted cash flow (DCF) method. It allows analysts to assess how changes in key assumptions and variables impact the overall value of a business. By systematically varying these inputs within certain ranges, sensitivity analysis provides valuable insights into the robustness and reliability of a company’s financial projections.

To better understand this concept, let us consider an example: Imagine a retail company that wants to evaluate its investment opportunities for expanding into new markets. The company estimates future cash flows based on various factors such as sales growth rates, operating expenses, and discount rates. However, there is inherent uncertainty regarding these assumptions due to market volatility or changing economic conditions. Sensitivity analysis helps quantify the potential effects of these uncertainties on the estimated value of the expansion opportunity.

In conducting sensitivity analysis, several techniques can be employed to explore different scenarios and their corresponding impacts on business valuations:

  • One-variable-at-a-time : This approach involves altering one variable at a time while keeping all other assumptions constant. For instance, by increasing or decreasing the projected sales growth rate without adjusting any other input parameters, analysts can observe how sensitive the valuation result is to variations in this particular factor.
  • Tornado diagrams : These graphical representations display multiple variables simultaneously and provide an overview of their relative influence on the final valuation output. Variables with larger bars indicate greater sensitivity compared to those with smaller ones.
  • Monte Carlo simulation : This probabilistic modeling technique incorporates random sampling from defined probability distributions for each assumption. By running numerous simulations using Monte Carlo methods, it becomes possible to capture a range of potential outcomes and evaluate their corresponding probabilities.
  • Scenario analysis : This qualitative approach entails creating specific scenarios by combining different values for multiple variables simultaneously. Analysts can then examine how varying combinations affect business valuations under distinct circumstances.

By utilizing these techniques along with others tailored to specific valuation contexts, sensitivity analysis offers invaluable insights into the uncertainty and risk associated with business valuations. It allows decision-makers to assess the potential impact of changing assumptions and make more informed choices.

Moving forward, understanding the importance of sensitivity analysis in business valuation will shed light on its wider applications in strategic planning, investment decisions, and risk management.

Importance of Sensitivity Analysis in Business Valuation

Sensitivity Analysis: An Essential Tool in Business Valuation

In the previous section, we discussed the definition of sensitivity analysis and its relevance to business valuation. Now, let’s delve deeper into why sensitivity analysis holds such importance in this context.

To illustrate the significance of sensitivity analysis, consider a hypothetical case study involving Company X, a manufacturing firm. The valuation of Company X is based on discounted cash flow (DCF) method, which estimates the present value of future cash flows. However, as with any financial projection model, there are inherent uncertainties and assumptions involved that can impact the final valuation figure. This is where sensitivity analysis comes into play.

One compelling reason for conducting sensitivity analysis during business valuation is its ability to provide decision-makers with valuable insights into potential risks and opportunities. By systematically varying key inputs within reasonable ranges and observing their effect on the company’s value, analysts can identify critical factors driving uncertainty and make more informed decisions based on different scenarios.

Let us now explore some essential benefits of incorporating sensitivity analysis in business valuation:

  • Risk Assessment : Sensitivity analysis allows analysts to assess the level of risk associated with various assumptions made during valuation by quantifying their impact on the final result.
  • Scenario Planning : By considering multiple scenarios through sensitizing different variables, businesses gain a comprehensive understanding of how changing market conditions or internal factors may affect their value.
  • Optimization Opportunities : Sensitivity analysis facilitates identifying areas where improvements could be made to enhance overall performance and profitability.
  • Effective Communication : Through visual representations like tables and graphs generated from sensitivity analyses, complex financial information can be communicated effectively across stakeholders.

The table below provides an example of how changing one input variable affects Company X’s estimated enterprise value:

By examining the variations in enterprise value resulting from different scenarios, decision-makers can gain a clearer understanding of the potential impact of changing key inputs.

In conclusion, sensitivity analysis is an invaluable tool for business valuation that helps assess risk, plan for various scenarios, identify optimization opportunities, and facilitate effective communication among stakeholders.

Key Inputs in DCF Method

Previous section H2 Transition: Having established the importance of sensitivity analysis in business valuation, we now turn our attention to understanding the key inputs in the discounted cash flow (DCF) method.

In order to grasp the practical implications and significance of sensitivity analysis within business valuation using the DCF method, let us consider a hypothetical case study. Imagine a company that is considering an investment opportunity in expanding its manufacturing facilities. The decision hinges on estimating future cash flows and determining an appropriate discount rate. By conducting sensitivity analysis, various scenarios can be explored to assess how changes in these input variables affect the overall valuation.

To effectively carry out a sensitivity analysis, it is crucial to follow a structured approach. Here are four important steps:

Identify Key Variables: Begin by identifying the critical variables that have a significant impact on the valuation outcome. In our case study, this could include projected revenue growth rates, cost assumptions, or expected terminal value multiples.

Define Ranges: Determine the range over which each variable will be varied during the analysis process. For instance, revenue growth might fluctuate between conservative and aggressive estimates, while costs may vary based on best- and worst-case scenarios.

Evaluate Outcomes: Calculate the resulting valuations for each combination of input values within their respective ranges. This evaluation provides insights into potential outcomes under different circumstances and helps identify areas of vulnerability or opportunities for improvement.

Interpret Results: Analyze and interpret the results obtained from varying input values as part of sensitivity analysis. Consider both quantitative metrics such as net present value (NPV) or internal rate of return (IRR), as well as qualitative factors like risk exposure or market dynamics.

Table – Hypothetical Scenario Analysis:

By conducting sensitivity analysis in this manner and exploring various scenarios of input variations within the DCF method framework for business valuation, decision-makers are better equipped to understand the potential impact of changes on the final outcome. This approach supports informed decision-making by identifying risks and opportunities associated with different assumptions.

Process of Conducting Sensitivity Analysis – Armed with an understanding of the importance of sensitivity analysis in business valuation and familiarity with its key inputs under the DCF method framework let us now delve into the process itself.

Process of Conducting Sensitivity Analysis

Transitioning from the previous section on “Key Inputs in DCF Method,” it is essential to examine how these inputs can impact the overall valuation of a business. This analysis, known as sensitivity analysis, allows for a comprehensive understanding of the potential variations and uncertainties that may arise during the valuation process.

To illustrate this concept, let us consider a hypothetical case study involving Company XYZ, a technology firm seeking an accurate valuation before a merger. The discounted cash flow (DCF) method is applied to determine the present value of future cash flows generated by Company XYZ. However, given the inherent unpredictability in projecting future financials, conducting a sensitivity analysis becomes crucial for assessing various scenarios and their corresponding impacts on valuation.

Sensitivity analysis can be performed by adjusting specific key inputs within reasonable ranges and observing how these changes affect the calculated value of a company. Some common factors examined during this process include revenue growth rates, discount rates, terminal values, and working capital requirements. By altering one variable at a time while keeping others constant, analysts gain valuable insights into which inputs have the most significant influence on the final valuation figure.

Evaluating different scenarios through sensitivity analysis enables decision-makers to understand the potential risks associated with varying assumptions made during valuation. To visualize these outcomes effectively, bullet points outlining possible scenarios could be utilized:

  • Optimistic Scenario: Assumes higher-than-projected revenue growth rate and lower discount rate.
  • Pessimistic Scenario: Considers lower-than-projected revenue growth rate and higher discount rate.
  • Base Case Scenario: Reflects projected revenue growth rate and discount rate according to industry standards.
  • Extreme Scenario: Examines extreme cases where revenues significantly exceed or fall short of projections.

Furthermore, presenting information in table format can provide additional clarity when comparing results across multiple variables. A sample table showcasing different valuations based on varying input parameters might look like this:

By incorporating sensitivity analysis into business valuations using the DCF method, decision-makers can gain a deeper understanding of the potential outcomes and risks associated with different assumptions. Such analyses contribute to more informed decision-making processes that consider various scenarios and their corresponding impacts on valuation results.

The next section will delve into interpreting the results obtained from conducting sensitivity analysis and how they aid in making well-informed decisions during the business valuation process.

Interpreting Sensitivity Analysis Results

Having discussed the process of conducting sensitivity analysis, we now delve into interpreting its results. To illustrate this, let us consider a hypothetical case study involving Company XYZ, a technology start-up seeking funding for expansion. In valuing the company using the Discounted Cash Flow (DCF) method, various assumptions are made regarding future cash flows and discount rates. Conducting a sensitivity analysis allows us to assess how changes in these key variables impact the overall valuation.

Interpreting the results of sensitivity analysis involves analyzing potential scenarios and their corresponding effects on business valuation. By varying one assumption at a time while keeping other factors constant, different outcomes can be observed. This helps decision-makers understand the level of uncertainty associated with their valuations and identify critical drivers that significantly affect value.

  • A decrease in projected revenue growth by 10% leads to an approximate decrease in business valuation by 15%.
  • An increase in discount rate by 2% results in a reduction of business valuation by approximately 20%.
  • Higher operating expenses than anticipated may lead to a lower valuation due to reduced profitability.
  • Changes in market conditions or competitive landscape could have significant impacts on future cash flows and ultimately influence business valuation.

The table below summarizes some possible scenarios derived from sensitivity analysis:

By understanding these potential variations and their corresponding impacts on business valuation, stakeholders gain valuable insights into the robustness of their investment decisions. Such knowledge enables them to make informed choices based on risk appetite and strategic objectives. However, it is essential to recognize the limitations of sensitivity analysis in business valuation, which we will explore in the subsequent section.

Transitioning into the next section about “Limitations of Sensitivity Analysis in Business Valuation,” it is crucial to acknowledge that while sensitivity analysis provides valuable insights into potential variations and their impacts on valuation, its effectiveness can be constrained by certain factors.

Limitations of Sensitivity Analysis in Business Valuation

Building upon the understanding of sensitivity analysis in business valuation, this section focuses on interpreting the results obtained from such analyses when using the discounted cash flow (DCF) method. To illustrate its practical application, consider a hypothetical case study where Company A is being valued for potential acquisition.

In this scenario, the DCF model was used to estimate the value of Company A based on projected future cash flows and discount rates. Sensitivity analysis was then conducted by varying key inputs within reasonable ranges to assess their impact on the final valuation. The results of this analysis can provide valuable insights into the robustness and reliability of the estimated business value.

Interpreting sensitivity analysis results involves examining how changes in specific variables affect the outcome of the valuation exercise. This examination can be facilitated through various means, including visual representations such as tornado diagrams or tables summarizing findings. For instance:

  • Changes in revenue growth assumptions may reveal that Company A’s value is highly sensitive to fluctuations in sales performance.
  • Alterations in discount rates could highlight the significance of interest rate movements or market uncertainties.
  • Variations in terminal value calculations might expose potential risks associated with long-term projections.
  • Adjustments to cost parameters may shed light on operational efficiency issues impacting overall company worth.

To further demonstrate these interpretations, a table summarizing sensitivity analysis findings can be employed:

Examining the table, it becomes apparent that a higher revenue growth assumption and lower discount rate contribute to an increase in Company A’s valuation. Conversely, a more conservative terminal value calculation or higher operating costs may lead to a decreased estimated worth.

In summary, interpreting sensitivity analysis results is crucial in understanding the potential impact of input variations on business valuations conducted using the DCF method. By analyzing these outcomes through visual representations and summarizing findings in tables, analysts can gain valuable insights into key drivers affecting company value. Such interpretations aid decision-makers in comprehending the risks and uncertainties associated with different assumptions made during the valuation process.

Related posts:

  • Discounted Cash Flow (DCF) Method: A Guide to Business Valuation

Free Cash Flow: Business Valuation and the Discounted Cash Flow (DCF) Method

  • Terminal Value in Business Valuation: An Overview of the Discounted Cash Flow (DCF) Method
  • The Importance of Discount Rate in Business Valuation: Exploring the Discounted Cash Flow (DCF) Method

Inventory Valuation: Understanding the Asset Accumulation Method in Business Valuation

The Importance of Discount Rate in Business Valuation: Exploring the Discounted Cash…

Terminal Value in Business Valuation: An Overview of the Discounted Cash Flow (DCF)…

Understanding the Cost of Equity in DCF Business Valuation

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Sensitivity Analysis

Last updated 20 May 2018

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This short revision video introduces and illustrates the concept of sensitivity analysis.

Sensitivity analysis is a technique which allows the analysis of changes in assumptions used in forecasts. As such, it is a very useful technique for use in investment appraisal, sales and profit forecasting and lots of other quantitative aspects of business management.

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Creating Your Forecasted Sensitivity Analysis

After completing your Financial Budgets (step 1) , your First Year Forecasted Cash Flow Statement (step 2), your First Year Forecasted Income Statement (step 3), your First Year Forecasted Balance Sheet (step 4) your First Year Forecasted Ratios (step 5), and your First Year Forecasted Break-even Point (step 6), the next step is to develop your Forecasted Sensitivity Analysis (remember to create your forecasted financial statements and analysis one year at a time).

Recall from previous discussions, a Sensitivity Analysis is a "what-if"tool that examines the effect on a company's Net Income (bottom line) when forecasted sales levels are increased or decreased. For example, a sensitivity analysis can answer the following questions:

  • "WHAT" would be my forecasted net income, "IF" my sales forecast is 30%, 20%, or 10% too high ?
  • "WHAT" would be my forecasted net income, "IF" my sales forecast is 20% or 10% too low ?

As you might suspect, an original Forecasted Income Statement is needed to create a Forecasted Sensitivity Analysis. In other words, before you can create a 200Z Forecasted Sensitivity Analysis, for example, you MUST prepare a 200Z Forecasted Income Statement (IE the 200Z Forecasted Income Statement becomes the foundation for the 200Z Sensitivity Analysis).

Many business plan writers generally prepare only one Sensitivity Analysis. That is, a sensitivity analysis for their FIRST forecasted year of operation. Therefore, in our example, Murray would prepare a Forecasted Sensitivity Analysis for 200X only (IE his first forecasted business year). Below illustrates Murray's 200X Sensitivity Analysis. (Please Note: Murray can develop a Forecasted Analysis for 200Y if he chooses; however, he elects not too).

As you can see, the sensitivity analysis consist of three main components; namely, 1) The Heading, 2) Sales Percentage Factors, and 3) The Body.  Below briefly explains each component; beginning with "The Heading".  For a complete examination of these three components as they relate to Murray Wilson's company, please click HERE .

Below summaries the Forecasted Financial Statements and/or Budgets that need to be completed before you can develop your Forecasted Sensitivity Analysis.

ADDITIONAL EXAMPLE ON THE SENSITIVITY ANALYSIS

J&B Incorporated

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You are currently viewing Sensitivity Analysis Examples: Learn How to Take Control of the Future

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

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:

  • 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. 
  • Determine your independent variables . Independent input variables could include cost of goods sold, construction costs, financing charges, customer traffic, and other factors. 
  • 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

sensitivity analysis of business plan

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 = X 2 + Y 2

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?

T he 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.

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3.3 Perform Break-Even Sensitivity Analysis for a Single Product Under Changing Business Situations

Finding the break-even point or the sales necessary to meet a desired profit is very useful to a business, but cost-volume-profit analysis also can be used to conduct a sensitivity analysis , which shows what will happen if the sales price, units sold, variable cost per unit, or fixed costs change. Companies use this type of analysis to consider possible scenarios that assist them in planning.

Link to Learning

Watch this video that shows what happens if one or more of the variables in a break-even analysis is changed to learn more.

The Effects on Break-Even under Changing Business Conditions

Circumstances often change within a company, within an industry, or even within the economy that impact the decision-making of an organization. Sometimes, these effects are sudden and unexpected, for example, if a hurricane destroyed the factory of a company’s major supplier; other times, they occur more slowly, such as when union negotiations affect your labor costs. In either of these situations, costs to the company will be affected. Using CVP analysis, the company can predict how these changes will affect profits.

Changing a Single Variable

To demonstrate the effects of changing any one of these variables, consider Back Door Café, a small coffee shop that roasts its own beans to make espresso drinks and gourmet coffee. They also sell a variety of baked goods and T-shirts with their logo on them. They track their costs carefully and use CVP analysis to make sure that their sales cover their fixed costs and provide a reasonable level of profit for the owners.

Change in Sales Price

The owner of Back Door has one of her employees conduct a survey of the other coffee shops in the area and finds that they are charging $0.75 more for espresso drinks. As a result, the owner wants to determine what would happen to operating income if she increased her price by just $0.50 and sales remained constant, so she performs the following analysis:

The only variable that has changed is the $0.50 increase in the price of their espresso drinks, but the net operating income will increase by $750. Another way to think of this increase in income is that, if the sales price increases by $0.50 per expresso drink and the estimated sales are 1,500 units, then this will result in an increase in overall contribution margin of $750. Moreover, since all of the fixed costs were met by the lower sales price, all of this $750 goes to profit. Again, this is assuming the higher sales price does not decrease the number of units sold. Since the other coffee shops will still be priced higher than Back Door, the owner believes that there will not be a decrease in sales volume.

When making this adjustment to their sales price, Back Door Café is engaging in target pricing , a process in which a company uses market analysis and production information to determine the maximum price customers are willing to pay for a good or service in addition to the markup percentage. If the good can be produced at a cost that allows both the desired profit percentage as well as deliver the good at a price acceptable to the customer, then the company should proceed with the product; otherwise, the company will not achieve its desired profit goals.

Change in Variable Cost

In March, the owner of Back Door receives a letter from her cups supplier informing her that there is a $0.05 price increase due to higher material prices. Assume that the example uses the original $3.75 per unit sales price. The owner wants to know what would happen to net operating income if she absorbs the cost increase, so she performs the following analysis:

She is surprised to see that just a $0.05 increase in variable costs (cups) will reduce her net income by $75. The owner may decide that she is fine with the lower income, but if she wants to maintain her income, she will need to find a new cup supplier, reduce other costs, or pass the price increase on to her customers. Because the increase in the cost of the cups was a variable cost, the impact on net income can be seen by taking the increase in cost per unit, $0.05, and multiplying that by the units expected to be sold, 1,500, to see the impact on the contribution margin, which in this case would be a decrease of $75. This also means a decrease in net income of $75.

Change in Fixed Cost

Back Door Café’s lease is coming up for renewal. The owner calls the landlord to indicate that she wants to renew her lease for another 5 years. The landlord is happy to hear she will continue renting from him but informs her that the rent will increase $225 per month. She is not certain that she can afford an additional $225 per month and tells him she needs to look at her numbers and will call him back. She pulls out her CVP spreadsheet and adjusts her monthly fixed costs upwards by $225. Assume that the example uses the original $3.75 per unit sales price. The results of her analysis of the impact of the rent increase on her annual net income are:

Because the rent increase is a change in a fixed cost, the contribution margin per unit remains the same. However, the break-even point in both units and dollars increase because more units of contribution are needed to cover the $225 monthly increase in fixed costs. If the owner of the Back Door agrees to the increase in rent for the new lease, she will likely look for ways to increase the contribution margin per unit to offset this increase in fixed costs.

In each of the prior examples, only one variable was changed—sales volume, variable costs, or fixed costs. There are some generalizations that can be made regarding how a change in any one of these variables affects the break-even point. These generalizations are summarized in Table 3.1 .

Watch this video that walks through, step by step, how to calculate break even in units and dollars and at a desired profit or sales level to learn more.

Changing Multiple Variables

We have analyzed situations in which one variable changes, but often, more than one change will occur at a time. For example, a company may need to lower its selling price to compete, but they may also be able to lower certain variable costs by switching suppliers.

Suppose Back Door Café has the opportunity to purchase a new espresso machine that will reduce the amount of coffee beans required for an espresso drink by putting the beans under higher pressure. The new machine will cost $15,000, but it will decrease the variable cost per cup by $0.05. The owner wants to see what the effect will be on the net operating income and break-even point if she purchases the new machine. She has arranged financing for the new machine and the monthly payment will increase her fixed costs by $400 per month. When she conducts this analysis, she gets the following results:

Looking at the “what-if” analysis, we see that the contribution margin per unit increases because of the $0.05 reduction in variable cost per unit. As a result, she has a higher total contribution margin available to cover fixed expenses. This is good, because the monthly payment on the espresso machine represents an increased fixed cost. Even though the contribution margin ratio increases, it is not enough to totally offset the increase in fixed costs, and her monthly break-even point has risen from $4,125.00 to $4,687.50. If the new break-even point in units is a realistic number (within the relevant range), then she would decide to purchase the new machine because, once it has been paid for, her break-even point will fall and her net income will rise. Performing this analysis is an effective way for managers and business owners to look into the future, so to speak, and see what impact business decisions will have on their financial position.

Let’s look at another option the owner of the Back Door Café has to consider when making the decision about this new machine. What would happen if she purchased the new machine to realize the variable cost savings and also raised her price by just $0.20? She feels confident that such a small price increase will go virtually unnoticed by her customers but may help her offset the increase in fixed costs. She runs the analysis as follows:

The analysis shows the expected result: an increase in the per-unit contribution margin, a decrease in the break-even point, and an increase in the net operating income. She has changed three variables in her costs—sales price, variable cost, and fixed cost. In fact, the small price increase almost gets her back to the net operating income she realized before the purchase of the new expresso machine.

By now, you should begin to understand why CVP analysis is such a powerful tool. The owner of Back Door Café can run an unlimited number of these what-if scenarios until she meets the financial goals for her company. There are very few tools in managerial accounting as powerful and meaningful as a cost-volume-profit analysis.

Concepts In Practice

Value menus.

In January 2018, McDonald’s brought back its $1 value menu. After discontinuing its popular Dollar Menu six years previously, the new version has a list of items priced not only at $1, but at $2 and $3 as well. How can McDonald’s afford to offer menu items at this discounted price? Volume! Although the margin on each unit is very small, the food chain hopes to make up the difference in quantity. They also hope that consumers will add higher priced (and higher margin) items to their orders. 1 The strategy is not without its risks, however, as rising food or labor costs could put franchisees in a position where the value pricing does not cover their product costs. Rivals Taco Bell and Dunkin’ Donuts have aggressively marketed their value menus, making it almost impossible for McDonald’s to ignore the growing trend among consumers for “value pricing.” Watch this video to see what McDonald’s is offering consumers.

  • 1 Zlati Meyer. “McDonald’s Hope Customers Buck Up Thursday to New Dollar Menu.” USA Today. January 3, 2018. https://www.usatoday.com/story/money/2018/01/03/mcdonalds-hopes-customers-buck-up-thursday-new-dollar-menu/996350001/

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  • Authors: Mitchell Franklin, Patty Graybeal, Dixon Cooper
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Home > Financial Projections > Sensitivity Analysis vs Scenario Analysis

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Sensitivity Analysis vs Scenario Analysis

Financial projections show a single outcome based on a set of assumptions and inputs. Uncertainty in the various assumptions and inputs creates risk, and will determine how the investor interprets the projections. Sensitivity analysis is carried out in order to assess risk.

With sensitivity analysis only one input is changed at a time in order to assess the impact of that input on the financial projection. By changing each input seperately it is possible to assess the significance of each variable on the business

Scenario Analysis and Sensitivity Analysis in a Business Plan

The difference between sensitivity analysis and scenario analysis is that sensitivity analysis changes only one input at a time in order to assess the sensitivity of the financial projection to that variable. With scenario analysis, all inputs changes are made at the same time with the purpose of assessing the effect on the business plan of a complete change in circumstances.

The three main scenarios are usually referred to as the best case, base case and worst case scenarios and the procedure for carrying out the analysis using the financial projections template is as follows:

Step 1 – Develop the Base Case Scenario

Step 2 – develop the best case scenario.

Make a copy of the base case scenario financial projections template developed in step 1, and amend the inputs to show what will happen if your positive expectations are met, and you can seize all the opportunities available to the business.

For example, in the base case scenario, you might estimate that revenue will increase by 5% each year, in the best case scenario, you might want to show what will happen if revenue increases by 10% each year. When carrying out sensitivity analysis, it is important to remember that the projections still have to be feasible and achievable, they are not simply hypothetical what ifs.

Step 3 – Develop the Worst Case Scenario

Again, make a copy of the base case scenario financial projections template developed in step 1, and change the inputs to reflect what will happen if your negative expectations are met, if all the problems anticipated do happen, and projections develop worse than expected.

For example, in the base case scenario, you might have anticipated opening an export market in year three, show what will happen if that market does not develop or is delayed until a later year.

Investors will look at the sensitivity analysis and in particular the worst case scenario, to see how vulnerable the business is to assumption and input changes in order to assess the risks involved in the business.

When presenting the best case, worst case, and base case scenarios a brief description should be provided to show how the major assumptions and inputs have been changed between scenarios. In addition, for the base case scenario a detailed description should be given, and for the best and worse case scenarios, a summary of the key financial information should be provided.

About the Author

Chartered accountant Michael Brown is the founder and CEO of Plan Projections. He has worked as an accountant and consultant for more than 25 years and has built financial models for all types of industries. He has been the CFO or controller of both small and medium sized companies and has run small businesses of his own. He has been a manager and an auditor with Deloitte, a big 4 accountancy firm, and holds a degree from Loughborough University.

You May Also Like

Sensitivity Analysis – Excel Template

Ned Krastev

Ned Krastev

One of the best ways to model uncertainty is by creating a sensitivity analysis. It represents a table that shows how a given end result would change based on one or two of the variables that are used as an input for its calculation. It is rather easy to create a sensitivity table. The tool that you need to use is located in the Data tab under ‘What if analysis’. Its Excel name is Data table.

Some other related topics you might be interested to explore are Pivot Tables , GETPIVOTDATA , and Slicers .

This is an open-access Excel template in XLSX format that will be useful for anyone who wants to work as a Financial Analyst, Business Analyst, Consultant, Corporate Executive, or everyone preparing a corporate presentation.

You can now download the Excel template for free.

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COMMENTS

  1. How to complete a sensitivity analysis

    Consider a business with revenues of $1,000,000, cost of goods sold of $450,000 and fixed costs of $550,000. The business's break-even point is as follows: Total revenue ($1,000,000) - cost of goods sold ($450,000) = gross profit ($550,000) This calculation tells us that with 1 million dollars of sales the business will reach its break-even point.

  2. Sensitivity Analysis Explained: Definitions, Formulas and Examples

    Sensitivity analysis is an indispensable tool utilized in corporate finance and business analysis to comprehend how the variability in key input variables influences the performance of a business. By methodically adjusting the inputs and observing the ensuing effect on outputs, analysts can discern which variables have the most profound impact on the bottom line. This enables companies to ...

  3. A Guide on Sensitivity Analysis for Startup Founders

    Sensitivity analysis is an integral part of financial modeling and business planning. It helps startups analyze how different values of an independent variable will impact a dependent variable under a given set of assumptions. However, many startup founders are unfamiliar with sensitivity analysis and its potential benefits.

  4. Sensitivity Analysis in Business: Definition & Examples

    Sensitivity analysis is a versatile technique with several applications. It is used in: Assessing the impact of changes in variables or assumptions on the outcomes of a model, system, or decision. Gaining understanding of the relationships between input variables and output results. Analyzing how uncertainties or variations in variables can ...

  5. What is Sensitivity Analysis and Why it Will Help Your Business

    Sensitivity analysis is especially useful for complex "black box" scenarios that are very difficult to analyze using conventional methods. Sensitivity analysis is also a reliable way to uncover the hidden levers that have the greatest impact on business decisions. Analysts adjust independent variables using one-at-a-time (OAT) analysis to ...

  6. What is Sensitivity Analysis?

    Sensitivity Analysis is used to understand the effect of a set of independent variables on some dependent variable under certain specific conditions. For example, a financial analyst wants to find out the effect of a company's net working capital on its profit margin. The analysis will involve all the variables that have an impact on the ...

  7. How to Perform a Financial Sensitivity Analysis

    Define the specific independent variables that will affect the outcome of your project. Change one input and observe the effect it has on your output, while leaving all other independent variables the same. Calculate the percentage change in both the input and the output. Determine the dependent variable's sensitivity to the independent ...

  8. Cornerstones of startup business planning: Sensitivity analysis

    Sensitivity or scenario analysis is aimed to test the business model by considering changes of one or a combination of the variables defining the model. Usually it is also referred to as a ...

  9. From Planning to Valuation: Mastering Business Planning and Sensitivity

    Starting a new business can be a daunting task, but having a solid business plan, building a good financial model, and performing sensitivity analysis can help mitigate risks and increase the chances of success. In this chapter, I discuss the importance of business planning and sensitivity analysis in startup valuation, as well as how to develop an effective business plan and build a financial ...

  10. Why Your Startup Pitch Needs Sensitivity Analysis

    The purpose of sensitivity analysis is to measure the effects of changing the inputs in a mathematical model. In a financial model, sensitivity analysis can reveal the inputs with the greatest impact and help managers develop KPIs and strategies to monitor and address changes to those areas of the business.

  11. What Is Sensitivity Analysis in Business?

    Sensitivity analysis is a key tool used in business decision making. It helps to uncover the impact of changes in a single variable on the overall outcome of a given situation. In other words, it is an evaluation of what would happen if one variable changed while all other variables remained constant. This type of analysis can be used in a ...

  12. How Is Sensitivity Analysis Used?

    One simple example of sensitivity analysis used in business is an analysis of the effect of including a certain piece of information in a company's advertising, comparing sales results from ads ...

  13. How to Do Risk & Sensitivity Analysis in a Feasibility Study

    The essence of conducting risks and sensitivity analysis for your business is to put structures in place that will help you mitigate risks and uncertainty in your business and in turn maximize profits. You can work with experts to help you create a model that is suitable for your business. 4. Run the Model a Number of Times before Adopting It.

  14. Sensitivity Analysis Definition

    Sensitivity Analysis: A sensitivity analysis is a technique used to determine how different values of an independent variable impact a particular dependent variable under a given set of ...

  15. Sensitivity and Risk Analysis Techniques

    Sensitivity and Risk Analysis Techniques Every Business Owner Should Know. Sensitivity analysis aims to eliminate uncertainty about the future by modeling financial risks and decisions. Also called what-if analysis, this type of analysis examines how changes in inputs affect outputs. The process helps with long-term decision-making.

  16. Sensitivity Analysis in Business Valuation: DCF Method Focus

    Sensitivity analysis is a crucial technique used in business valuation, particularly when employing the discounted cash flow (DCF) method. It allows analysts to assess how changes in key assumptions and variables impact the overall value of a business. By systematically varying these inputs within certain ranges, sensitivity analysis provides valuable insights into the robustness and ...

  17. Sensitivity Analysis

    Sensitivity analysis is a technique which allows the analysis of changes in assumptions used in forecasts. As such, it is a very useful technique for use in investment appraisal, sales and profit forecasting and lots of other quantitative aspects of business management. Sensitivity Analysis (Business Forecasting) This short revision video ...

  18. Creating a Sensitivity Analysis & Forecast

    Many business plan writers generally prepare only one Sensitivity Analysis. That is, a sensitivity analysis for their FIRST forecasted year of operation. Therefore, in our example, Murray would prepare a Forecasted Sensitivity Analysis for 200X only (IE his first forecasted business year). Below illustrates Murray's 200X Sensitivity Analysis.

  19. Sensitivity Analysis Examples: Take Control of the Future

    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.

  20. 3.3 Perform Break-Even Sensitivity Analysis for a Single ...

    Learn how to perform break-even sensitivity analysis for a single product under changing business situations with OpenStax's free online textbook.

  21. Sensitivity Analysis vs Scenario Analysis

    The difference between sensitivity analysis and scenario analysis is that sensitivity analysis changes only one input at a time in order to assess the sensitivity of the financial projection to that variable. With scenario analysis, all inputs changes are made at the same time with the purpose of assessing the effect on the business plan of a complete change in circumstances.

  22. Sensitivity Analysis

    One of the best ways to model uncertainty is by creating a sensitivity analysis. It represents a table that shows how a given end result would change based on one or two of the variables that are used as an input for its calculation. It is rather easy to create a sensitivity table. The tool that you need to use is located in the Data tab under ...

  23. Business Plan

    Building detailed financial model and sensitivity scenarios: Under this, we prepare a detailed financial model, with options for you to undertake sensitivity testing and based on the same, we design subset models for you to use as your operating budgets. SuperCFO provides a range of Business Plan, Financial Forecasting, Budgeting and Financial ...