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