Explain my Excel model to a non-technical executive
Turns a complex spreadsheet or model into a plain-English walkthrough an executive can follow, trust, and question.
The prompt
Help me explain my Excel model or spreadsheet to a senior executive who will not open the file.
What the spreadsheet is for: [e.g. "pricing model for the new plan", "headcount plan", "store profitability analysis"]
How it works: [PASTE the tab list, key inputs, key formulas or logic, and the main outputs]
The answer it produces: [the headline numbers]
The executive and what they need to decide: [e.g. "COO approving next year's hiring"]
Format of the conversation: [5-minute verbal update / one slide / email / meeting with the file on screen]
Produce:
1. The one-sentence answer: what the model says, in business terms.
2. How it works in plain English: 3-5 steps from inputs to answer, as a simple flow, with no formula names or cell references.
3. The assumptions that matter most: the 3-4 inputs that drive the result, where each number came from, and how confident we are.
4. What would change the answer: if [assumption] is X% higher or lower, the result moves by [ADD from the model]. Do not calculate sensitivities I haven't given you - mark them [ADD].
5. What the model does not cover: limits and exclusions, stated honestly.
6. Likely executive questions (5-7) with short answers I can give.
7. The version for my format: a 150-word script, or one slide's title and three bullets, or a short email.
Tone: confident and plain. Translate jargon (e.g. "run-rate", "weighted average") or leave it out. Do not overstate certainty - the executive should understand where the judgment calls are.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Data & Analysis prompts
What to fill in
- the headline numbers
- e.g. "COO approving next year's hiring"
- assumption
- ADD from the model
- ADD
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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