Scenario analysis and sensitivity analysis share a common goal: evaluating how changes in market conditions, costs and other variables could affect business goals.
Both methods provide valuable insights to help your organization manage risks and prepare for uncertainty, but their approaches differ.
While sensitivity analysis adjusts one variable at a time to assess its individual impact, scenario analysis changes all possible variables at once to provide an overview of potential outcomes.
But when do you use sensitivity analysis vs. scenario analysis? Let's dig a little deeper.
Scenario analysis is a technique used in financial modeling for predicting and evaluating how different conditions (such as market conditions, economic trends and operational changes within a business) can impact a company's future financial performance.
FP&A analysts use scenario analysis to assess the potential impacts of positive and negative events on critical metrics such as revenue, expenses, profit and cash flows.
These insights help stakeholders make informed decisions and develop strategic plans that can withstand challenges in uncertain times (like economic downturns).
An example of an analysis comparing various budget scenarios created using Vena.
Scenario analysis considers multiple variables simultaneously (such as revenue growth, operating expenses and interest rates) and examines how different combinations of these variables can impact your company’s financial health.
It explores a range of potential outcomes from best-case to worst-case scenarios that represent different combinations of these variables.
FP&A analysts create financial models based on these insights to simulate the potential financial outcomes under each scenario and identify potential risks and opportunities.
This allows the entire company to:
Overall, scenario analysis lets you proactively assess potential risk, as it focuses less on definitive outcomes and more on predicting several possible outcomes that are all valid, though uncertain. These insights help to improve strategic planning in your organization and provide clarity on how to best allocate resources.
Let’s say a manufacturing company that makes consumer electronics wants to understand how different market conditions and operational changes might impact its performance over the next five years. Here's how the company will likely proceed:
They project key financial metrics such as revenue, expenses, profit and cash flow based on the assumptions for each scenario.
For example, in the best case scenario, the company will likely invest in new product lines, expand its market presence and increase marketing efforts.
In the base or moderate scenario, the company could adopt a balanced approach, maintaining operational efficiency, while cautiously exploring growth opportunities.
And in the worst case scenario, the company might decide to focus on reducing costs, streamlining operations and seeking alternative markets or revenue streams.
Sensitivity analysis is a technique used to determine how changes in one variable affect the possible outcome of a company's future financial performance. It aids in identifying which variables have the most influence on performance results and shows how changes in them affect the overall outcome.
FP&A analysts use sensitivity analysis to validate assumptions and provide detailed forecasts. This process helps with determining the likelihood of an initiative’s success or failure under different business conditions.
For example, sensitivity analysis could help you understand how changes in revenue growth or cost of goods sold (COGS) would impact net profit or share prices when preparing financial projections for the upcoming year. By varying these inputs, you can observe the corresponding changes and make informed decisions based on these insights.
Source: Corporate Finance Institute
The sensitivity analysis process starts with determining the important input variables that could affect your financial outcome, such as sales volume, costs or interest rates.
You’ll then choose a range of possible values for each variable (for instance, how a 10% increase or decrease in sales volume would impact your results).
You’ll have to adjust one variable while keeping all other variables constant to isolate the effect of that single variable on the outcome.
While doing so, record how changes in the variable affect the output (such as your profit). This shows the sensitivity of the outcome to changes in that variable. Comparing the results of each of your analyses helps you see which variables have the most significant impact on critical business goals.
Sensitivity analysis, in contrast to scenario analysis, involves altering one input at a time to see how it impacts a specific outcome.
Using the same consumer electronics example as earlier, let’s say we want to understand how changes in sales volume impact net profit.
Start with a baseline scenario where sales volume is at its current level:
Then, incrementally increase and decrease the sales volume by a certain percentage (e.g., ±5%, ±10%) from the baseline scenario.
Ensure that all other factors affecting net profit (such as production costs, pricing, and operating expenses) remain unchanged during each iteration of the analysis. Then, calculate the net profit for each scenario based on the adjusted sales volume.
Sales Volume: 11,000 units
Total Revenue: 11,000 units * $50 = $550,000
Total Production Cost: 11,000 units * $30 = $330,000
Net Profit: $550,000 - $330,000 = $220,000
Sales Volume: 10,000 units
Total Revenue: 10,000 units * $50 = $500,000
Total Production Cost: 10,000 units * $30 = $300,000
Net Profit: $500,000 - $300,000 = $200,000
Sales Volume: 9,000 units
Total Revenue: 9,000 units * $50 = $450,000
Total Production Cost: 9,000 units * $30 = $270,000
Net Profit: $450,000 - $270,000 = $180,000
Focusing on the individual impact of changes in sales volume helps you see how sensitive the organization’s net profit is to variations in sales volume:
For each input change in a sensitivity analysis, you get a clearer picture of which factors have the most significant influence on the company's net profit.
The difference between sensitivity analysis and scenario analysis lies in their focus.
Sensitivity Analysis evaluates the impact of changes in individual input variables on the output of a financial model, one variable at a time, while keeping others constant.
Scenario Analysis, on the other hand, assesses the impact of changes in all variables at once, providing a broader view of potential outcomes under varying conditions.
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Difference Between Sensitivity Analysis and Scenario Analysis |
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Sensitivity Analysis |
Scenario Analysis |
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Purpose |
Assesses the impact of changes in individual input variables on the financial performance of a company or project |
Assesses the impact of multiple variables changing simultaneously on the financial performance of a company or project |
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Focus |
Identifies which specific variables have the most significant influence on the outcome and how changes in those variables affect the results |
Explores different scenarios to understand how variations in multiple factors can affect outcomes |
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Methodology |
One variable is changed at a time while keeping all other variables constant |
Multiple variables are changed simultaneously to create different scenarios representing various future conditions |
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Use Case |
Allows for a detailed examination of the sensitivity of the output to changes in each input variable |
Allows for a broader assessment of the potential outcomes under different circumstances |
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Best For |
Best for short-term, focused risk assessment and operational decision-making |
Best for long-term planning under high uncertainty and preparing for a range of possible futures |
Use scenario analysis when:
Planning for the long-term or making decisions that involve multiple interrelated factors
Handling situations with high uncertainty where external factors (like market trends and regulatory changes) could significantly impact outcomes
Trying to understand the implications of various distinct future scenarios
Evaluating potential risks and rewards when entering new markets, launching significant new products or making large capital investments
Use sensitivity analysis when you want to:
Understand how changes in a single variable affect a particular outcome
Identify and prioritize areas that need closer monitoring and control
Test the robustness of your financial models
Inform short-term operational decisions, such as pricing adjustments
Understand how sensitive your financial projections are to changes in specific inputs like sales volume, cost of goods sold or interest rates when budgeting
Both financial modeling techniques offer complementary benefits, especially for risk management and decision making.
Scenario Analysis is ideal for holistic, multi-variable evaluations to understand the interplay between different factors. It's most useful for strategic planning and risk management in complex situations.
Sensitivity Analysis, on the other hand, is great for identifying how specific changes in one variable impact the overall outcome. It’s valuable for quick, focused analysis to pinpoint critical factors and understand how they directly affect an outcome.
Scenario analysis can be complex and time-consuming, as it requires you to assess multiple variables at the same time and develop detailed narratives for each scenario.
Creating scenarios also involves making subjective judgments about future events and trends, which can introduce bias and lead to inaccurate or misleading conclusions. It also requires sourcing an extensive amount data, which might not always be available or easily accessible.
Sensitivity analysis, on the other hand, can overlook the potential for interaction between variables, as it examines one variable at a time while holding others constant. Focusing on individual variables could oversimplify complex situations where variables interact in non-linear ways.
Sensitivity analysis and scenario analysis can complement each other effectively.
For example, you can use sensitivity analysis as a preliminary step to identify critical variables that significantly impact a company or project's financial performance, such as cost of goods sold and sales volume. You could then explore them in more detail using scenario analysis to gain deeper insights, plan better, manage risks and maximize opportunities for the business.
Combining both methods also helps you and your team allocate resources better.
Scenario analysis provides the big picture—it considers the simultaneous impact of changes in multiple variables, offering a more holistic view of potential outcomes. Sensitivity analysis, on the other hand, pinpoints which drivers have the biggest impact on revenue. Together, they help avoid over-preparing for unlikely scenarios and under-preparing for the most likely ones.
For example, let’s say a post-secondary school is considering developing a new learning center on campus. They decide to create a financial forecasting model to determine the potential impact of their investment.
First, they do a scenario analysis to determine the base-, best- and worst-case scenarios. From there, conducting a sensitivity analysis would supply more nuanced information regarding one of these possible scenarios.
In this case, the school may be looking at how a potential 5% increase or decrease in revenue would affect their bottom line if they were to move forward with this investment. Which costs are flexible or inflexible to this change in revenue? Rent is inflexible, but will the ability to control the salaries of the center's staff, the overhead costs, etc. be enough to keep their revenue positive?
Conducting a sensitivity analysis can help the school's leadership better understand the optimal budget for a project of this size.
Standalone analysis—either sensitivity or scenario analysis on its own—would not provide the full picture. Ultimately, using both scenario planning methods in conjunction with one another will help you forecast more accurately and diminish potential for risk.
The future is full of uncertainties, but that doesn't mean you can't be prepared—and with Vena's help, unknowns are manageable when backed by predictive modeling.
With Vena’s scenario planning and analysis capabilities, you're able to mitigate risk with agile scenario modeling. Vena pulls live data from your various source systems and unites it in a secure, centralized database so that you're able to capture a precise picture of your organization's financial health, enabling you to make business decisions much more confidently.
Additionally, with Vena, you can:
Reduce data inaccuracies due to human error
Increase efficiency through automatic data loading
Generate more reliable predictive analytics
Scale your processes while staying within Excel
Try this free scenario analysis template on Excel to model different monthly forecasting scenarios and view variances between forecasted inputs and scenario models.