What is scenario analysis?
Scenario analysis is a risk management and strategic planning process used to evaluate the risk and potential effects of a future event. Both investors and businesses employ scenario analysis to consider financial performance, various operational situations and even macroeconomic trends.
The process begins with the creation of multiple detailed hypothetical situations. Stakeholders analyze these scenarios and their variables to determine possible effects on the business. Scenario analysis examines shifts in key variables, such as market trends and operational costs, to quantify the impacts on business objectives and create better outcomes.
Scenario analysis is broadly applicable across industries and domains. It underpins financial and investment planning and is a foundational element of modern risk management frameworks.
How does scenario analysis work?
Scenario analysis uses a systematic, structured approach to evaluate hypothetical situations. It combines qualitative and quantitative modeling to produce a thorough assessment of a given situation.
This process helps organizations understand, prepare and tweak strategies for a range of situations. It typically involves the following:
- Variable identification. Research is conducted to identify key variables -- those likely to affect operations -- for analysis.
- Scenario development. Based on the identified variables, different hypothetical scenarios with detailed narratives are constructed. Core scenarios modeled on these variables typically fit into one of three broad categories: base-case, best-case or worst-case scenario, as shown in the chart that follows.
- Impact evaluation. The varying effects of these scenarios, within different outcome categories, are scrutinized from distinct perspectives: a financial, or quantitative, view and a strategic, or qualitative, vantage point.
Scenario development categories
Here's a closer look at the three primary categories used for scenario development.
Category | Outlook | Description |
Base-case scenario | Probable | Represents the expected or most likely outcome based on current trends and assumptions. |
Best-case scenario | Optimistic | Illustrates a positive outlook in which favorable conditions, such as low costs and high demand, flourish. |
Worst-case scenario | Pessimistic | Depicts a negative outlook with unfavorable conditions: Supply chain disruptions or economic slowdowns exist. |
How to perform scenario analysis
Performing scenario analysis appears overwhelming at first, but with a structured process, it's achievable. Here are six steps to perform scenario analysis:
- Define objectives and scope. First, clearly identify the specific strategy, product direction or item to be assessed. Also, define the scope to focus attention squarely on the chosen scenario.
- Identify critical variables. Next, pinpoint critical variables most likely to change and thereby influence outcomes. As part of this step, collect data on past events to gain a clearer understanding of these critical variables and their prior business impact.
- Develop different scenarios. Then, build out the scenario narratives for the specific objective and defined scope. Options include fully developed base-case, best-case and worst-case scenarios that change based on the included critical variables.
- Evaluate outcomes. Determine the effect of different scenarios. Include both quantitative and qualitative assessments to improve the depth and breadth of each evaluation.
- Define strategies. Based on outcomes from the scenario-impact analysis, create a detailed strategic plan to guide business decisions.
- Revisit and refine. Scenario analysis is not simply a point-in-time exercise. Monitor and adjust scenario analysis on a regular basis. Revisit scenarios. Refine if current conditions warrant.
Scenario analysis use cases and examples in business
Scenario analysis is widely used across different operations and industries. The following are common use cases and examples in business:
- Risk management. Financial institutions use scenario analysis to understand economic risk and how fluctuating conditions affect the availability of capital.
- Financial planning. For businesses of any size, forecasting revenues under different scenarios clarifies an organization's direction and likely profitability.
- Resource allocation. Scenario analysis helps a company determine resource allocation to navigate these various scenarios successfully.
- Mergers and acquisitions. When evaluating the merits of a merger or acquisition, businesses use scenario analysis, altering their critical variables to predict probable outcomes.
- Product launches. Companies include competitors' output and other variables to review possible outcomes of a product launch.
- Supply chain management. Supply chains are susceptible to countless variables. Businesses analyze different scenarios to discern their probable impact and then prepare and share an organizational response if needed.
- Enterprise carbon management. Companies assess their carbon management -- how pricing and regulations affect operations -- while addressing climate risk disclosure requirements.
Benefits of scenario analysis
Due to its broad applicability, many organizations recognize scenario analysis as a useful strategic tool, producing numerous benefits. These advantages include the following:
- Improved decision-making. Businesses employ scenario analysis to make informed decisions and minimize guesswork in planning.
- Proactive risk mitigation. Understanding the worst-case scenarios enables a business to react quickly and create a proactive risk mitigation strategy.
- Resource allocation optimization. Reviewing potential outcomes aids managers' resource allocation choices and boosts operational efficiency.
- Clearer communication about risk. Explaining risks in detail -- both opportunities and pitfalls -- gives stakeholders a clearer investment outlook.
Drawbacks of scenario analysis
Though helpful, scenario planning isn't perfect. Here's why:
- Reliance on historical data. Scenario analysis makes assumptions based on historical data, sometimes missing forward-looking innovations.
- Time and resource requirements. Properly building out detailed scenarios typically requires substantial time commitments and dedicated resources.
- Cognitive bias. A major drawback is the risk of cognitive bias. Moreover, among the many biases that skew data analysis, confirmation bias -- businesses building scenarios with data chosen because it supports the organization's goals -- is especially worrisome.
- Modeling complexity. Creating detailed and realistic scenarios isn't simple, requiring complex modeling techniques.
- Qualitative challenges. Not every variable is easily quantifiable or measurable. Scenario analysis sometimes misses intangible qualitative variables, such as an organization's culture.
What is the difference between scenario analysis and sensitivity analysis?
Scenario analysis is similar in some respects to sensitivity analysis. While scenario analysis looks at multiple variables to assess potential impact, sensitivity analysis narrows the focus to the impact of a single variable.
Aspect | Scenario analysis | Sensitivity analysis |
Goal | Explore a range of outcomes, and prepare strategies for various scenarios. | Identify variables with the most significant impact on outcomes, prioritizing risks and fine-tuning models. |
Scope | Its broad scope considers the combined effect of multiple variables to model comprehensive scenarios. | Its narrow scope focuses on the impact of a single variable in isolation. |
Example | A company analyzes a scenario in which high inflation, low sales and increased competition occur together. | A company adjusts the interest rate in a financial model to measure its effect on net present value. |
Complexity | Complexity increases due to the need to develop and analyze multiple scenarios and variables. | The process is simpler, pinpointing one variable at a time. |
Output | A range of outcomes across different scenarios indicates the effect of combined changes on those results. | Changes in a single variable indicate the outcome's level of sensitivity. |