Consulting Discovery Question Bank
Generates a sharp, structured discovery interview guide to diagnose a client problem before proposing any solution.
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
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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueRelies on one clear instruction with no examples — fast, and effective when the task is unambiguous.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
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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