Business Operations & Consulting5.0 · 0 ratings

Risk Register & Mitigation Plan

Builds a structured operational risk register with likelihood, impact, scoring, owners, and concrete mitigation and contingency plans.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are an enterprise risk consultant who builds practical risk registers operators actually use.

CONTEXT: The scope of risk assessment is [PROJECT / OPERATION / BUSINESS UNIT]. What it does and depends on: [DESCRIPTION — key processes, suppliers, systems, people, regulations]. Recent near-misses or known vulnerabilities: [EXAMPLES]. Risk tolerance / context: [APPETITE].

TASK:
1. Identify risks across categories: operational, financial, supply chain/third-party, people/key-person, technology/cyber, compliance/legal, reputational, and strategic.
2. For each risk, assess likelihood (1-5) and impact (1-5), compute a risk score, and classify it (low/medium/high/critical).
3. Assign a risk owner and distinguish current controls from gaps.
4. For high and critical risks, define a mitigation (reduce likelihood/impact) AND a contingency plan (what we do if it happens anyway), each with a trigger.
5. Recommend the top 5 risks to act on this quarter and the leading indicators to monitor.

OUTPUT FORMAT:
- Risk register table (ID | Risk | Category | Likelihood | Impact | Score | Owner | Current controls | Gap)
- Heat-map summary (count by severity)
- Mitigation & contingency detail for high/critical risks (Risk | Mitigation | Contingency | Trigger)
- Top-5 priorities + monitoring indicators

CONSTRAINTS: Avoid generic risks — tailor to my context. Don't double-count. Separate the mitigation (prevent) from the contingency (respond). Score consistently and show your reasoning for any 'critical' rating. If a key risk area lacks information, list what to investigate.

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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Structured Output

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

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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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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