Forecast Premortem

Forecast Pre-Mortem

Table of Contents

• What is a Forecast Pre-Mortem?
• When to Use This Skill
• Interactive Menu
• Quick Reference
• Resource Files

What is a Forecast Pre-Mortem?

A forecast pre-mortem is a stress-testing technique where you assume your prediction has already failed and work backward to construct the history of how it failed. This reveals blind spots, tail risks, and overconfidence.

Core Principle: Invert the problem. Don't ask "Will this succeed?" Ask "It has failed - why?"

Why It Matters:

• Defeats overconfidence by forcing you to imagine failure
• Identifies specific failure modes you hadn't considered
• Transforms vague doubt into concrete risk variables
• Widens confidence intervals appropriately
• Surfaces "unknown unknowns"

Origin: Gary Klein's "premortem" technique, adapted for probabilistic forecasting

When to Use This Skill

Use this skill when:

• High confidence (>80% or <20%) - Most likely to be overconfident
• Feeling certain - Certainty is a red flag in forecasting
• Prediction is important - Stakes are high, need robustness
• After inside view analysis - Used specific details, might have missed big picture
• Before finalizing forecast - Last check before committing

Do NOT use when:

• Confidence already low (~50%) - You're already uncertain
• Trivial low-stakes prediction - Not worth the time
• Pure base rate forecasting - Premortem is for inside view adjustments

Interactive Menu

What would you like to do?

Core Workflows

1. Run a Failure Premortem - Assume prediction failed, explain why 2. Run a Success Premortem - For pessimistic predictions (<20%) 3. Dragonfly Eye Perspective - View failure through multiple lenses 4. Identify Tail Risks - Find black swans and unknown unknowns 5. Adjust Confidence Intervals - Quantify the adjustment 6. Learn the Framework - Deep dive into methodology 7. Exit - Return to main forecasting workflow

1. Run a Failure Premortem

Let's stress-test your prediction by imagining it has failed.

Failure Premortem Progress:
- [ ] Step 1: State the prediction and current confidence
- [ ] Step 2: Time travel to failure
- [ ] Step 3: Write the history of failure
- [ ] Step 4: Identify concrete failure modes
- [ ] Step 5: Assess plausibility and adjust

Step 1: State the prediction and current confidence

Tell me:

1. What are you predicting?
2. What's your current probability?
3. What's your confidence interval?

Example: "This startup will reach $10M ARR within 2 years" - Probability: 75%, CI: 60-85%

Step 2: Time travel to failure

The Crystal Ball Exercise:

Jump forward to the resolution date. It is now [resolution date]. The event did NOT happen. This is a certainty. Do not argue with it.

How does it feel? Surprising? Expected? Shocking? This emotional response tells you about your true confidence.

Step 3: Write the history of failure

Backcasting Narrative: Starting from the failure point, work backward in time. Write the story of how we got here.

Prompts:

• "The headlines that led to this were..."
• "The first sign of trouble was when..."
• "In retrospect, we should have known because..."
• "The critical mistake was..."

Frameworks to consider:

• Internal friction: Team burned out, co-founders fought, execution failed
• External shocks: Regulation changed, competitor launched, market shifted
• Structural flaws: Unit economics didn't work, market too small, tech didn't scale
• Black swans: Pandemic, war, financial crisis, unexpected disruption

See Failure Mode Taxonomy for comprehensive categories.

Step 4: Identify concrete failure modes

Extract specific, actionable failure causes from your narrative.

For each failure mode: (1) What happened, (2) Why it caused failure, (3) How likely it is, (4) Early warning signals

Example:

Step 5: Assess plausibility and adjust

The Plausibility Test:

Ask yourself:

• How easy was it to write the failure narrative?
  • Very easy → Drop confidence by 15-30%
  • Very hard, felt absurd → Confidence was appropriate
• How many plausible failure modes did you identify?
  • 5+ modes each >5% likely → Too much uncertainty for high confidence
  • 1-2 modes, low likelihood → Confidence can stay high
• Did you discover any "unknown unknowns"?
  • Yes, multiple → Widen confidence intervals by 20%
  • No, all known risks → Confidence appropriate

Quantitative Method: Sum the probabilities of failure modes:

P(failure) = P(mode_1) + P(mode_2) + ... + P(mode_n)

If this sum is greater than 1 - your_current_probability, your probability is too high.

Example: Current success: 75% (implied failure: 25%), Sum of failure modes: 40% Conclusion: Underestimating failure risk by 15%, Adjusted: 60% success

Next: Return to menu or document findings

2. Run a Success Premortem

For pessimistic predictions - assume the unlikely success happened.

Success Premortem Progress:
- [ ] Step 1: State pessimistic prediction (<20%)
- [ ] Step 2: Time travel to success
- [ ] Step 3: Write the history of success
- [ ] Step 4: Identify how you could be wrong
- [ ] Step 5: Assess and adjust upward if needed

Step 1: State pessimistic prediction

Tell me: (1) What low-probability event are you predicting? (2) Why is your confidence so low?

Example: "Fusion energy will be commercialized by 2030" - Probability: 10%, Reasoning: Technical challenges too great

Step 2: Time travel to success

It is now 2030. Fusion energy is commercially available. This happened. It's real. How?

Step 3: Write the history of success

Backcasting the unlikely: What had to happen for this to occur?

• "The breakthrough came when..."
• "We were wrong about [assumption] because..."
• "The key enabler was..."
• "In retrospect, we underestimated..."

Step 4: Identify how you could be wrong

Challenge your pessimism:

• Are you anchoring too heavily on current constraints?
• Are you underestimating exponential progress?
• Are you ignoring parallel approaches?
• Are you biased by past failures?

Step 5: Assess and adjust upward if needed

If success narrative was surprisingly plausible, increase probability.

Next: Return to menu

3. Dragonfly Eye Perspective

View the failure through multiple conflicting perspectives.

The dragonfly has compound eyes that see from many angles simultaneously. We simulate this by adopting radically different viewpoints.

Dragonfly Eye Progress:
- [ ] Step 1: The Skeptic (why this will definitely fail)
- [ ] Step 2: The Fanatic (why failure is impossible)
- [ ] Step 3: The Disinterested Observer (neutral analysis)
- [ ] Step 4: Synthesize perspectives
- [ ] Step 5: Extract robust failure modes

Step 1: The Skeptic

Channel the harshest critic. You are a short-seller, a competitor, a pessimist. Why will this DEFINITELY fail?

Be extreme: Assume worst case, highlight every flaw, no charity, no benefit of doubt

Output: List of failure reasons from skeptical view

Step 2: The Fanatic

Channel the strongest believer. You are the founder's mother, a zealot, an optimist. Why is failure IMPOSSIBLE?

Be extreme: Assume best case, highlight every strength, maximum charity and optimism

Output: List of success reasons from optimistic view

Step 3: The Disinterested Observer

Channel a neutral analyst. You have no stake in the outcome. You're running a simulation, analyzing data dispassionately.

Be analytical: No emotional investment, pure statistical reasoning, reference class thinking

Output: Balanced probability estimate with reasoning

Step 4: Synthesize perspectives

Find the overlap: Which failure modes appeared in ALL THREE perspectives?

• Skeptic mentioned it
• Even fanatic couldn't dismiss it
• Observer identified it statistically

These are your robust failure modes - the ones most likely to actually happen.

Step 5: Extract robust failure modes

The synthesis:

Focus adjustment on the robust failures that survived all perspectives.

Next: Return to menu