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Scenarios & Sensitivities

Exploring uncertainty and understanding what drives your results

Reading time: ~8 minutes

1. What Scenarios Are

Scenarios at a Glance

A scenario is a coherent set of assumptions that represent one possible version of the future. Scenarios help you explore "what if" questions by changing key inputs and observing how outputs respond.

Common Scenario Types

Most models include multiple scenarios to capture a range of possibilities:

  • Base Case — Your best estimate of what is likely to happen given current information
  • Upside Case — What happens if key assumptions turn out better than expected
  • Downside Case — What happens if key assumptions turn out worse than expected

Structured Assumptions, Not Predictions

Scenarios are not forecasts of what will happen. They are structured explorations of what could happen under different conditions. The value is in understanding the range of outcomes, not in selecting the "right" scenario.

Internal Consistency Matters

A good scenario is internally consistent. If you assume higher growth, you should also consider whether that requires more investment, affects margins, or changes risk. Scenarios work best when assumptions are logically connected.

2. How Scenarios Are Used in the Platform

FinanceModel provides a structured approach to scenario analysis that maintains consistency and enables comparison.

Scenario-Specific Inputs

Each scenario has its own set of input values. When you switch between scenarios, the model recalculates outputs using the assumptions specific to that scenario. This lets you maintain multiple versions of your analysis without duplicating the entire model.

Consistent Structure Across Scenarios

All scenarios share the same model structure, calculations, and output format. Only the input assumptions differ. This ensures that differences in outputs are attributable to assumption changes, not structural differences.

Comparison of Outputs

The platform allows you to compare outputs across scenarios side by side. This makes it easier to see how different assumptions affect key metrics and identify which scenarios produce the most significant differences.

Working with Scenarios

  • Start with your base case assumptions
  • Create additional scenarios by varying key drivers
  • Keep scenarios focused on meaningful differences
  • Document what each scenario represents

3. What Sensitivities Show

Sensitivity analysis shows how changes in individual inputs affect outputs. It helps you understand which assumptions have the biggest impact on your results.

Relationship Between Drivers and Outputs

Sensitivities reveal how strongly an output responds to changes in a specific input. Some inputs may have large effects; others may have minimal impact. Knowing this helps you prioritize where to focus analytical effort.

Directional Insight, Not Certainty

Sensitivities tell you the direction and magnitude of change: "If revenue growth increases by 1%, the output increases by X." This is directional guidance, not a prediction of what will happen. Real-world relationships may be more complex.

One Variable at a Time vs. Multiple Variables

Basic sensitivity analysis changes one variable while holding others constant. In reality, multiple variables often move together. Use sensitivities to understand individual effects, but remember that combined effects may differ.

4. How to Interpret Changes

Interpreting scenario and sensitivity results requires understanding what the numbers represent and what they don't.

Relative vs. Absolute Changes

Pay attention to whether you're looking at absolute changes (e.g., "value increases by $1M") or relative changes (e.g., "value increases by 5%"). A large percentage change on a small base may be less significant than a small percentage change on a large base.

Identifying Key Drivers

Look for inputs that produce large output changes. These are your key drivers—the assumptions that matter most. Focus your diligence, validation, and monitoring on these variables.

Avoiding False Precision

Sensitivity tables may show precise numbers, but precision is not accuracy. A table showing value changes to the dollar does not mean those values are reliable to the dollar. Treat outputs as directional indicators within reasonable ranges, not exact predictions.

Questions to Ask When Reviewing

  • Which assumptions have the biggest impact on the outcome?
  • Are those assumptions well-supported or highly uncertain?
  • What is the range of plausible outcomes across scenarios?
  • Do the results make intuitive sense given the assumptions?

5. When to Use Scenarios & Sensitivities

Scenarios and sensitivities are most valuable when you need to explore uncertainty and prepare for different outcomes.

Strategic Planning

Use scenarios to explore how different market conditions, competitive dynamics, or strategic choices affect long-term outcomes. This helps you develop plans that are robust across multiple possible futures.

Risk Assessment

Use downside scenarios and sensitivity analysis to understand what could go wrong and how bad it could get. This supports risk management by identifying vulnerabilities and stress-testing assumptions.

Decision Preparation

Before making significant decisions, use scenarios to understand the range of possible outcomes. This helps you make informed choices and set appropriate expectations with stakeholders.

Additional Use Cases

  • Investment evaluation — Compare returns under different market conditions
  • Budgeting and forecasting — Prepare for favorable and unfavorable outcomes
  • Stakeholder communication — Show decision-makers the range of possibilities
  • Assumption validation — Test whether results are sensitive to uncertain inputs

6. Limitations & Responsible Use

Understanding limitations helps you use scenarios and sensitivities responsibly and avoid common pitfalls.

Key Limitations

  • Sensitivities are not forecasts — They show how outputs respond to input changes, not what will actually happen
  • Results depend entirely on assumptions — Garbage in, garbage out. Unrealistic scenarios produce unrealistic outputs
  • Models simplify reality — Real-world interactions may be more complex than model relationships
  • Scenarios may not capture extremes — Black swan events often fall outside the range of scenarios considered

Human Judgment Required

Scenarios and sensitivities inform judgment—they do not replace it. Responsible use requires:

  • Critically evaluating whether scenario assumptions are plausible
  • Recognizing that important factors may not be captured
  • Supplementing quantitative analysis with qualitative judgment
  • Seeking diverse perspectives on assumptions and interpretations

Best Practices for Responsible Use

  • Document what each scenario represents and why
  • Don't treat the base case as "the answer"
  • Consider scenarios beyond the obvious upside and downside
  • Update scenarios as new information becomes available
  • Communicate uncertainty clearly to stakeholders

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