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# Failure Mode Taxonomy
## Comprehensive Categories for Systematic Risk Identification
---
## The Two Primary Dimensions
### 1. Internal vs External
**Internal failures:**
- Under your control (at least partially)
- Organizational, execution, resource-based
- Can be prevented with better planning
**External failures:**
- Outside your control
- Market, regulatory, competitive, acts of God
- Can only be mitigated, not prevented
---
### 2. Preventable vs Unpreventable
**Preventable:**
- Known risk with available mitigation
- Happens due to negligence or oversight
- "We should have seen this coming"
**Unpreventable (Black Swans):**
- Unknown unknowns
- No reasonable way to anticipate
- "Nobody could have predicted this"
---
## Four Quadrants
| | **Preventable** | **Unpreventable** |
|---|---|---|
| **Internal** | Execution failure, bad hiring | Key person illness, burnout |
| **External** | Competitor launch (foreseeable) | Pandemic, war, black swan |
**Premortem focus:** Mostly on **preventable failures** (both internal and external)
---
## Internal Failure Modes
### 1. Execution Failures
**Team/People:**
- Key person quits
- Co-founder conflict
- Team burnout
- Cultural toxicity
- Skills gap
- Hiring too slow/fast
- Onboarding failure
**Process:**
- Missed deadlines
- Scope creep
- Poor prioritization
- Communication breakdown
- Decision paralysis
- Process overhead
- Lack of process
**Product/Technical:**
- Product quality issues
- Technical debt collapse
- Scalability failures
- Security breach
- Data loss
- Integration failures
- Performance degradation
---
### 2. Resource Failures
**Financial:**
- Ran out of money (runway)
- Failed to raise funding
- Revenue shortfall
- Cost overruns
- Budget mismanagement
- Fraud/embezzlement
- Cash flow crisis
**Time:**
- Too slow to market
- Missed window of opportunity
- Critical path delays
- Underestimated timeline
- Overcommitted resources
**Knowledge/IP:**
- Lost key knowledge (person left)
- IP stolen
- Failed to protect IP
- Technological obsolescence
- R&D dead ends
---
### 3. Strategic Failures
**Market fit:**
- Built wrong product
- Solved non-problem
- Target market too small
- Pricing wrong
- Value prop unclear
- Positioning failure
**Business model:**
- Unit economics don't work
- CAC > LTV
- Churn too high
- Margins too thin
- Revenue model broken
- Unsustainable burn rate
**Competitive:**
- Differentiation lost
- Commoditization
- Underestimated competition
- Failed to defend moat
- Technology leapfrogged
---
## External Failure Modes
### 1. Market Failures
**Demand side:**
- Market smaller than expected
- Adoption slower than expected
- Customer behavior changed
- Willingness to pay dropped
- Switching costs too high
**Supply side:**
- Input costs increased
- Suppliers failed
- Supply chain disruption
- Talent shortage
- Infrastructure unavailable
**Market structure:**
- Market consolidated
- Winner-take-all dynamics
- Network effects favored competitor
- Platform risk (dependency on another company)
---
### 2. Competitive Failures
**Direct competition:**
- Incumbent responded aggressively
- New entrant with more capital
- Competitor launched superior product
- Price war
- Competitor acquired key talent
**Ecosystem:**
- Complementary product failed
- Partnership fell through
- Distribution channel cut off
- Platform changed terms
- Ecosystem shifted away
---
### 3. Regulatory/Legal Failures
**Regulation:**
- New law banned business model
- Compliance costs too high
- Licensing denied
- Government investigation
- Regulatory capture by incumbents
**Legal:**
- Lawsuit (IP, employment, customer)
- Contract breach
- Fraud allegations
- Criminal charges
- Bankruptcy proceedings
---
### 4. Macroeconomic Failures
**Economic:**
- Recession
- Inflation
- Interest rate spike
- Currency fluctuation
- Credit crunch
- Stock market crash
**Geopolitical:**
- War
- Trade restrictions
- Sanctions
- Political instability
- Coup/revolution
- Expropriation
---
### 5. Technological Failures
**Disruption:**
- New technology made product obsolete
- Paradigm shift (e.g., mobile, cloud, AI)
- Standard changed
- Interoperability broke
**Infrastructure:**
- Cloud provider outage
- Internet backbone failure
- Power grid failure
- Critical dependency failed
---
### 6. Social/Cultural Failures
**Public opinion:**
- Reputation crisis
- Boycott
- Social media backlash
- Cultural shift away from product
- Ethical concerns raised
**Demographics:**
- Target demographic shrunk
- Generational shift
- Migration patterns changed
- Urbanization/de-urbanization
---
### 7. Environmental/Health Failures
**Natural disasters:**
- Earthquake, hurricane, flood
- Wildfire
- Drought
- Extreme weather
**Health:**
- Pandemic
- Endemic disease outbreak
- Health regulation
- Contamination/recall
---
## Black Swans (Unpreventable External)
### Characteristics
- Extreme impact
- Retrospectively predictable, prospectively invisible
- Outside normal expectations
### Examples
- 9/11 terrorist attacks
- COVID-19 pandemic
- 2008 financial crisis
- Fukushima disaster
- Technological singularity
- Asteroid impact
### How to Handle
**Can't prevent, can:**
1. **Increase robustness** - Survive the shock
2. **Increase antifragility** - Benefit from volatility
3. **Widen confidence intervals** - Acknowledge unknown unknowns
4. **Plan for "unspecified bad thing"** - Generic resilience
---
## PESTLE Framework for Systematic Enumeration
Use this checklist to ensure comprehensive coverage:
### Political
- [ ] Elections/regime change
- [ ] Policy shifts
- [ ] Government instability
- [ ] Geopolitical conflict
- [ ] Trade agreements
- [ ] Lobbying success/failure
### Economic
- [ ] Recession/depression
- [ ] Inflation/deflation
- [ ] Interest rates
- [ ] Currency fluctuations
- [ ] Market bubbles/crashes
- [ ] Unemployment
### Social
- [ ] Demographic shifts
- [ ] Cultural trends
- [ ] Public opinion
- [ ] Social movements
- [ ] Consumer behavior change
- [ ] Generational values
### Technological
- [ ] Disruptive innovation
- [ ] Obsolescence
- [ ] Cyber attacks
- [ ] Infrastructure failure
- [ ] Standards change
- [ ] Technology convergence
### Legal
- [ ] New regulations
- [ ] Lawsuits
- [ ] IP challenges
- [ ] Compliance requirements
- [ ] Contract disputes
- [ ] Liability exposure
### Environmental
- [ ] Climate change
- [ ] Natural disasters
- [ ] Pandemics
- [ ] Resource scarcity
- [ ] Pollution/contamination
- [ ] Sustainability pressures
---
## Kill Criteria Templates
### What is a Kill Criterion?
**Definition:** A specific event that, if it occurs, drastically changes your probability.
**Format:** "If [event], then probability drops to [X%]"
---
### Template Library
**Regulatory kill criteria:**
```
If [specific regulation] passes, probability drops to [X]%
If FDA rejects in Phase [N], probability drops to [X]%
If government bans [activity], probability drops to 0%
```
**Competitive kill criteria:**
```
If [competitor] launches [feature], probability drops to [X]%
If incumbent drops price by [X]%, probability drops to [X]%
If [big tech co] enters market, probability drops to [X]%
```
**Financial kill criteria:**
```
If we miss Q[N] revenue target by >20%, probability drops to [X]%
If we can't raise Series [X] by [date], probability drops to [X]%
If burn rate exceeds $[X]/month, probability drops to [X]%
```
**Team kill criteria:**
```
If [key person] leaves, probability drops to [X]%
If we can't hire [critical role] by [date], probability drops to [X]%
If team size drops below [X], probability drops to [X]%
```
**Product kill criteria:**
```
If we can't ship by [date], probability drops to [X]%
If NPS drops below [X], probability drops to [X]%
If churn exceeds [X]%, probability drops to [X]%
```
**Market kill criteria:**
```
If TAM shrinks below $[X], probability drops to [X]%
If adoption rate < [X]% by [date], probability drops to [X]%
If market shifts to [substitute], probability drops to [X]%
```
**Macro kill criteria:**
```
If recession occurs, probability drops to [X]%
If interest rates exceed [X]%, probability drops to [X]%
If war breaks out in [region], probability drops to [X]%
```
---
## Failure Mode Probability Estimation
### Quick Heuristics
**For each failure mode, estimate:**
**Very Low (1-5%):**
- Black swans
- Never happened in this industry
- Requires multiple unlikely events
**Low (5-15%):**
- Happened before but rare
- Strong mitigations in place
- Early warning systems exist
**Medium (15-35%):**
- Common failure mode in industry
- Moderate mitigations
- Uncertain effectiveness
**High (35-70%):**
- Very common failure mode
- Weak mitigations
- History of this happening
**Very High (>70%):**
- Almost certain to occur
- No effective mitigation
- Base rate is very high
---
### Aggregation
**If failure modes are independent:**
```
P(any failure) = 1 - ∏(1 - P(failure_i))
```
**Example:**
- P(regulatory) = 20%
- P(competitive) = 30%
- P(execution) = 25%
```
P(any) = 1 - (0.8 × 0.7 × 0.75) = 1 - 0.42 = 58%
```
**If failure modes are dependent:**
Use Venn diagram logic or conditional probabilities (more complex).
---
## Monitoring and Signposts
### Early Warning Signals
For each major failure mode, identify **leading indicators:**
**Example: "Key engineer will quit"**
**Leading indicators (6-12 months before):**
- Code commit frequency drops
- Participation in meetings declines
- Starts saying "no" more often
- Takes more sick days
- LinkedIn profile updated
- Asks about vesting schedule
**Action:** Monitor these monthly, set alerts
---
### Monitoring Cadence
| Risk Level | Check Frequency |
|------------|----------------|
| Very High (>50%) | Weekly |
| High (25-50%) | Bi-weekly |
| Medium (10-25%) | Monthly |
| Low (5-10%) | Quarterly |
| Very Low (<5%) | Annually |
---
## Practical Usage
**Step-by-Step:** (1) Choose categories (Internal/External, PESTLE), (2) Brainstorm 10-15 failure modes, (3) Estimate probability for each, (4) Aggregate, (5) Compare to forecast, (6) Identify top 3-5 risks, (7) Set kill criteria, (8) Define monitoring signposts, (9) Set calendar reminders based on risk level.
**Return to:** [Main Skill](../SKILL.md#interactive-menu)