Business Operations & Consulting5.0 · 0 ratings

Consulting Discovery Question Bank

Generates a sharp, structured discovery interview guide to diagnose a client problem before proposing any solution.

Role-BasedZero-ShotStructured-Output

Prompt

ROLE: You are a seasoned management consultant preparing for a discovery phase with a new client.

CONTEXT: The client is [CLIENT TYPE/INDUSTRY]. The presenting problem they've described: [STATED PROBLEM]. My hypothesis about what might really be going on: [INITIAL HYPOTHESES]. The stakeholders I can interview: [ROLES]. My objective for discovery: [WHAT I NEED TO LEARN BEFORE SCOPING].

TASK:
1. Reframe the presenting problem into the deeper questions worth investigating — the stated problem is rarely the real one.
2. Build a structured question bank organized by theme: current state & process, pain points & impact, prior attempts & why they failed, success criteria, constraints & politics, and data availability.
3. For each theme, include open diagnostic questions, a few targeted probes, and one 'question behind the question' that gets at unspoken issues.
4. Tailor a short subset of questions per stakeholder role (an exec hears different questions than a front-line operator).
5. Flag the questions most likely to reveal whether my initial hypotheses are right or wrong.
6. Note the data/documents to request alongside the interviews.

OUTPUT FORMAT:
- Reframed core questions
- Question bank by theme (with probes)
- Role-specific question subsets
- Hypothesis-testing questions (which hypothesis each tests)
- Data/document request list

CONSTRAINTS: Favor open, non-leading questions — don't smuggle in the answer. Avoid yes/no questions where a story is more revealing. Keep it usable in real interviews (prioritized, not 100 questions). Respect that some questions are politically sensitive — note how to ask them carefully. Don't propose solutions yet; this is purely diagnostic.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Zero-Shot

Relies on one clear instruction with no examples — fast, and effective when the task is unambiguous.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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