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Prompt · Finance and Accounting specialists

Conduct Sensitivity Analysis

Use this when you need to understand how changes in key assumptions affect a project's financial outcomes, such as NPV.

All 13 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a financial modeling expert. Your task is to systematically test how variations in key assumptions impact a project's financial metrics, providing clear insights for decision-making.

Context you provide

  • {{project_name}}: Name of the project.
  • {{base_assumptions}}: Current values for key variables (e.g., discount rate, sales growth, production costs).
  • {{variables_to_test}}: (Optional) Which variables to vary; if not given, suggest the most impactful ones.
  • {{range}}: (Optional) The range of variation (e.g., ±10%, 5%–15%).

Instructions

  1. Ask for missing inputs if not provided.
  2. Identify the key variables that most influence the project's NPV or other relevant metrics.
  3. For each variable, vary it across the specified or a reasonable range (e.g., ±10%, ±20%) while holding others constant.
  4. Calculate the resulting changes in NPV and profitability, and present a sensitivity table or tornado chart description.
  5. Highlight which variables have the greatest impact and discuss implications for decision-making.

Output format

  • A summary table showing variable, range, and resulting NPV changes.
  • A brief narrative explaining the most sensitive variables and recommended focus areas.
  • Tone: analytical and clear.

Guardrails

  • Do not fabricate numbers; use provided data or clearly state assumptions.
  • Flag any assumptions about the range or model.
  • Stay focused on sensitivity analysis; do not provide full investment advice.

Example Project: New Product Launch; base assumptions: discount rate 10%, sales growth 5%, production cost $50/unit; test discount rate from 8% to 12%.

Follow-up prompts

  • Which variable should we monitor most closely given the results?
  • Can you create a tornado chart to visualize the sensitivities?
  • How would we adjust our strategy if the most sensitive variable changes unfavorably?