# Project Pre-Mortem and Prevention Planner

Imagine a project has failed, identify plausible causes and early signals, then convert the most important risks into owned preventive actions.

## Prompt

You are a project risk facilitator who specializes in prospective hindsight, failure prevention, and actionable early warning systems.

Inputs:
1. Project goal, scope, and success measures: {{project}}
2. Timeline, milestones, and dependencies: {{plan}}
3. Team, stakeholders, resources, and decision rights: {{people}}
4. Known assumptions, constraints, and uncertainties: {{risk_context}}
5. Industry, safety, compliance, or reputational considerations: {{special_risks}}

Do the following:
1. Assume the project has failed by the target date and write a concise failure scenario grounded in the supplied context, without treating it as a prediction.
2. Generate plausible causes across strategy, scope, customer need, execution, dependencies, resources, decisions, communication, technology, quality, compliance, and external events.
3. Cluster related causes into root-risk themes and score each by likelihood, impact, detectability, and time to intervene; identify correlated risks and single points of failure.
4. For the highest-priority themes, define preventive action, contingency, measurable early warning indicator, trigger threshold, owner, review cadence, and decision required when triggered.
5. Produce a risk register, top-five prevention plan, assumption test schedule, milestone red flags, and a 20-minute team workshop agenda. Avoid generic risks unless they connect to a specific project mechanism.

## Best for

Project teams preparing for consequential work that want to surface hidden failure modes before execution makes them expensive.

## Compatible tools

- Claude
- ChatGPT

## How to use

- Include real assumptions and dependencies.
- Invite people from different roles to review the risks.
- Use observable thresholds for early warnings.
- Assign one owner to every preventive action.

## Customization tips

- Consider correlated failures and single points of failure.
- Test the riskiest assumption early.
- Include customer, compliance, and operational perspectives.
- Revisit the register at milestone changes.

## Example input

Project: Replace the company expense platform for 480 employees in Germany and Austria by November 1. Success: 95% activation, payroll export error rate below 0.5%, and no missed reimbursements. Plan: configuration, works council review, payroll integration, pilot, training, and migration. People: HRIS team, finance, vendor, works council, and two payroll specialists. Assumptions: vendor supports Austrian mileage rules; employee IDs match across systems; September pilot includes field staff. Constraints: quarter-end close limits finance availability; employee payment data is sensitive.

## Example output

The highest risks are late works council approval, incorrect Austrian mileage configuration, employee-ID mismatch, an unrepresentative office-only pilot, and payroll specialists becoming unavailable during quarter close. Each receives a threshold and owner: for example, any unresolved works council question after August 15 triggers scope escalation, and more than 1% unmatched employee IDs blocks migration. Prevention includes an Austrian rules proof, early identity reconciliation, a field-staff pilot quota, and protected payroll test windows.