# 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)