Unit Economics · Risk Assessment · Scenario Analysis · Sensitivity Analysis · Notes

Risk Assessment: Scenario and Sensitivity Analysis

Business risk assessment methods, including scenario and sensitivity analysis, for making more informed decisions.

Risk Assessment: Scenario and Sensitivity Analysis

A financial model without risk analysis is a neat illusion. The numbers are beautiful, but the first market shock—and the plan turns into fan fiction.

Scenario and sensitivity analysis help make the model living: to see what will happen if the world doesn't behave according to our plan.

This note explains how to read and use these two tools in practice.

1. Why Analyze Risks at All?

Business always lives in uncertainty:

• demand may sag;
• the cost of acquiring a customer may increase;
• exchange rates, interest rates, logistics—can go to the moon.

Risk assessment through a model answers three questions:

1. What can go wrong?
2. How painful is it in terms of money?
3. What will we do if it happens?

Scenario analysis answers "what if the world changes complexly," sensitivity analysis—"to which parameters are we particularly fragile."

2. Scenario Analysis: Optimistic, Realistic, Pessimistic

What it is

Scenario analysis is a set of complete pictures of the future: you change several assumptions at once and see how the result changes.

The minimum set:

• Pessimistic—"the result is worse than we expect"
• Realistic (base)—"as we believe now"
• Optimistic—"if everything turns out a little better than planned"

What Changes Between Scenarios

Usually:

• revenue (prices, volumes, conversions);
• variable costs (cost price, commissions);
• fixed costs (team size, office);
• discount rate (risk).

How to Build Scenarios: Steps

1. Define the base You already have a financial model: this is the realistic scenario.

2. Set assumptions for the pessimistic scenario Examples:

   • sales −20–30%;
   • conversion lower by a few p.p.;
   • CAC higher;
   • feature launches are delayed.

3. Set assumptions for the optimistic scenario Here we don't dream, but take a moderately positive option:

   • sales +10–20%;
   • conversion higher;
   • churn lower.

4. Recalculate key metrics For each scenario, get:

   • revenue;
   • EBITDA;
   • net cash flow;
   • NPV, IRR (if it's a project/investment).

5. Compare how decisions change For example:

   • in optimistic—we scale;
   • in realistic—we live calmly;
   • in pessimistic—we cut costs and slow down hiring.

Simple Scenario Table

3. Sensitivity Analysis: What the Model is Particularly Sensitive to

Idea

Sensitivity analysis answers the question: "If I slightly move one parameter, what will happen to the result?"

You choose one KPI, for example:

• NPV,
• EBITDA,
• net profit,
• cash on account,

and in turn "move" the input parameters:

• price;
• conversion;
• CAC;
• churn;
• exchange rate;
• cost price.

Steps of Sensitivity Analysis

1. Choose a target indicator For example: project NPV or EBITDA next year.
2. Choose key parameters 3–7 pieces, no more:
   • average check;
   • lead-to-sale conversion;
   • CAC;
   • share of variable costs.
3. Define change ranges
   • For example: −20%, −10%, 0, +10%, +20% for each parameter.
4. Recalculate the model For each parameter—you calculate the change in KPI with the others fixed.
5. Compare sensitivity Where the indicator "falls the most"—that's where the real risks and levers are.

Mini-calculator of sensitivity (logic)

Base_KPI = KPI at initial parameters

New_KPI = KPI at changed parameter

Change_KPI_% = (New_KPI / Base_KPI - 1) * 100%

Sensitivity = Change_KPI_% / Change_Parameter_%

For example:

• you raised the price by 10%,
• EBITDA grew by 25%,

Then sensitivity ≈ 2.5 — that is, EBITDA grows about 2.5 times faster than the price (in this range).

4. How to Use the Results in Management, Not in a Presentation

For risk analysis not to remain a picture, it must be linked to decisions.

What Scenario Analysis Gives

• Understanding the range of outcomes. You see not one line, but a "corridor" of future results.
• Rules of the game in advance.
  • You can agree in advance:
    • "If we go into a pessimistic scenario (sales -20% for three months in a row)—we..."
    • Freeze hiring,
    • Reduce marketing,
    • Revisit the price/product.
• A conversation with an investor/co-owner in the same language. Instead of "everything will be fine"—you show a range and a plan of action.

What Sensitivity Analysis Gives

• Focus on key drivers. You stop improving what has almost no effect on the result.
• Prioritization of experiments. If EBITDA hardly reacts to a small price change, but reacts strongly to conversion—the focus is on the product and funnel, not the price.
• Limits and triggers. You can set thresholds:
  • "If CAC > X—we stop the campaign"
  • "If margin falls below Y%—we change terms with suppliers."

📌 Checklist for Risk Analysis in a Model

• [ ] There are at least three scenarios: pessimistic, realistic, optimistic.
• [ ] In each scenario, assumptions are changed, not just "mood in the comments."
• [ ] Key metrics are calculated for the scenarios: revenue, EBITDA, cash on account, NPV (if needed).
• [ ] Sensitivity analysis has been conducted for 3–7 key parameters.
• [ ] It's clear which parameters have the greatest impact on the result.
• [ ] Specific actions for the pessimistic scenario have been formulated.
• [ ] There are pre-agreed thresholds/triggers (what we consider a "red zone").

If there are many "no's" in the checklist—your model is still more like a good weather forecast: beautiful, but without obligations.

Short Conclusion

Scenario analysis shows the range of the future. Sensitivity analysis shows which levers in the model are worth pulling at all.

Together, they turn a financial model from a beautiful table into a working risk management tool: you see where you can take bold risks, and where you should play carefully.