Pre Mortem

Risk Classification

Tigers (Real Risks)

Tigers are real, evidence-backed risks that could cause serious harm if not addressed.

Characteristics:

• Supported by data, past experience, or observable trends.
• The team can describe a plausible failure scenario in concrete terms.
• Ignoring them would be negligent.

Examples:

• "Our authentication service went down 3 times last month. A launch-day outage is plausible."
• "We have zero customers in the enterprise segment. Our sales team has no enterprise relationships."
• "The EU regulation takes effect in 60 days. We have not started compliance work."

Paper Tigers (Look Scary but Unlikely)

Paper Tigers are risks that sound alarming but, on closer inspection, are unlikely or have minimal real impact.

Characteristics:

• Based on hypothetical scenarios without supporting evidence.
• The probability is very low, or the impact would be manageable.
• Often raised because of general anxiety rather than specific knowledge.

Examples:

• "A competitor might copy our feature" -- possible, but their execution timeline is 6-12 months.
• "The server might not handle 100x traffic" -- but our realistic projection is 5x, with auto-scaling.
• "Users might hate the new UI" -- but usability testing with 8 users showed high satisfaction.

Elephants (Unspoken Concerns)

Elephants are the risks everyone knows about but nobody talks about. They are the "elephant in the room."

Characteristics:

• The team avoids discussing them due to politics, hierarchy, or discomfort.
• Often involve people, process, or organizational issues rather than technical ones.
• Frequently the actual cause of failure when projects fail.

Examples:

• "The tech lead does not believe in this project and has been disengaged for weeks."
• "The CEO's pet feature is driving the roadmap, but customers have not asked for it."
• "We do not have a plan for what happens when the contractor's contract ends next month."

Tiger Urgency Classification

Once a risk is classified as a Tiger, assign an urgency level:

Methodology

Phase 1: Set the Scene (5 minutes)

The facilitator reads this prompt to the group:

"Imagine it is 14 days after our launch. The product has failed. Users are not adopting it, key metrics are down, and leadership is asking what went wrong. Take 10 minutes to write down every reason you can think of for why we failed. Be specific. Be honest. Nothing is off limits."

Ground rules:

• Anonymous contributions (sticky notes or digital equivalent).
• No attribution, no blame, no judgment.
• Quantity over quality in the first round.

Phase 2: Generate Risks (10 minutes)

Each participant independently writes down failure scenarios. One risk per sticky note. Aim for 5-10 per person.

Prompts to stimulate thinking:

• What technical system is most likely to break?
• What customer objection have we not addressed?
• What team dynamic could derail us?
• What external event could change our assumptions?
• What are we pretending is not a problem?
• What decision are we avoiding?

Phase 3: Share and Cluster (15 minutes)

1. Read each risk aloud (without attribution).
2. Place on the board.
3. Group similar risks together.
4. Merge duplicates.

Phase 4: Classify (15 minutes)

For each cluster, the group decides:

For each Tiger, assign urgency: Launch-Blocking, Fast-Follow, or Track.

Phase 5: Mitigation Plans (15 minutes)

For each Launch-Blocking Tiger, complete:

Phase 6: Address Elephants (10 minutes)

Elephants require a different approach than Tigers:

1. Acknowledge -- Name the elephant explicitly. "The team is concerned that..."
2. Assess -- Is this actually a Tiger in disguise? If so, reclassify.
3. Decide -- Either address it (assign an owner) or consciously accept it (document the acceptance and rationale).

Python Tool: risk_categorizer.py

Categorize and analyze risks using the CLI tool:

# Run with demo data
python3 scripts/risk_categorizer.py --demo

# Run with custom input
python3 scripts/risk_categorizer.py input.json

# Output as JSON
python3 scripts/risk_categorizer.py input.json --format json

Input Format

{
  "risks": [
    {
      "description": "Authentication service has had 3 outages in the last month",
      "category": "tiger",
      "evidence": "Incident reports from last 30 days",
      "urgency": "launch_blocking"
    }
  ]
}

Output

Risk distribution summary, action plans for launch-blocking tigers, and flags for elephants that may need investigation.

See scripts/risk_categorizer.py for full documentation.

Output Format

Pre-Mortem Summary

Pre-Mortem Analysis: [Product/Feature Name]
Date: YYYY-MM-DD
Participants: [list]
Total risks identified: N
  - Tigers: X (Launch-Blocking: A, Fast-Follow: B, Track: C)
  - Paper Tigers: Y
  - Elephants: Z

Risk Registry

Use assets/pre_mortem_template.md for the full document template.

Integration with Other Discovery Skills

• Use after brainstorm-ideas/ and brainstorm-experiments/ -- pre-mortem is the final check before committing to build.
• Feed launch-blocking Tiger mitigations back into identify-assumptions/ if they surface new assumptions.
• Elephants often reveal assumptions that the team has been avoiding.

Troubleshooting

Success Criteria

• Pre-mortem conducted before every major launch, migration, or significant resource commitment
• At least 5-10 risks generated per person during the silent writing phase
• Risk distribution includes all three categories (not all tigers, not all paper tigers)
• Every launch-blocking tiger has an assigned owner, concrete mitigation plan, and decision date
• Elephants are explicitly named and either addressed or consciously accepted with documented rationale
• Pre-mortem findings are reviewed against actual outcomes post-launch to calibrate future sessions
• Session duration stays within 60-90 minutes total across all 6 phases

Scope & Limitations

In Scope:

• Prospective hindsight exercises using the "14 days after launch failure" framing
• Tiger / Paper Tiger / Elephant risk classification with urgency levels
• Automated elephant escalation detection based on keyword signals
• Risk registry generation with category distribution and action plans
• Facilitation methodology for both in-person and remote teams

Out of Scope:

• Ongoing risk management and tracking (see senior-pm/risk_matrix_analyzer.py)
• Quantitative risk analysis with probability/impact scoring (see senior-pm/ skill)
• Product discovery and hypothesis validation (see brainstorm-experiments/)
• Technical architecture risk assessment (see engineering/ skills)

Important Caveats:

• Pre-mortems are most effective with 4-8 participants. Fewer than 4 limits perspective diversity; more than 10 makes classification unwieldy.
• The elephant escalation keyword check is a heuristic. It catches common patterns but cannot detect all political or organizational risks.
• Pre-mortems complement, not replace, assumption mapping. Use identify-assumptions/ for systematic risk categorization and pre-mortem/ for surfacing unspoken concerns.
• Psychological safety is a prerequisite. If the team cannot speak honestly, the pre-mortem will produce sanitized results.

Integration Points

Tool Reference

risk_categorizer.py

Categorizes pre-mortem risks as Tigers, Paper Tigers, or Elephants. Generates action plans for launch-blocking tigers and flags elephants with escalation signals.

Input fields per risk:

• description (required): Clear description of the risk scenario
• category (required): One of tiger, paper_tiger, elephant
• evidence (required): Supporting data or observations
• urgency (required for tigers): One of launch_blocking, fast_follow, track

References

• Gary Klein, "Performing a Project Pre-Mortem," Harvard Business Review (2007)
• Daniel Kahneman, Thinking, Fast and Slow (2011) -- prospective hindsight
• Chip Heath & Dan Heath, Decisive (2013) -- decision-making under uncertainty
• Amy Edmondson, The Fearless Organization (2018) -- psychological safety for surfacing elephants