Single Supplier Bottleneck Risk

Goal Supplier Risk Frequency Common Category Supply Chain Published View source on GitHub ↗

Issue: Supply Chain Optimization Concentrates All Sourcing from Single Supplier (Lowest Cost); Blind to Failure Risk

Frequency: Common

Symptoms

  • Model: “Supplier X has lowest cost; order 100% from X”
  • Supplier X experiences disruption (natural disaster, bankruptcy, labor strike)
  • Supply chain paralyzed; cannot fulfill orders
  • No backup supplier; recovery takes weeks/months

Root Cause Optimization models minimize cost without explicit supply chain resilience constraints. Single-supplier solutions are optimal cost-wise; models don’t quantify disruption risk. Nassim Taleb’s “fragility” — looks good until it breaks catastrophically.

Example

Scenario: Semiconductor component sourcing
Suppliers: Taiwan (cost $5/unit), Japan (cost $8/unit)
Model optimization: "Source 100% from Taiwan (lowest cost)"
Taiwan earthquake 2024: All chip fabs shut down
Supply disruption: 6-month recovery
Company impact: Cannot manufacture products; lost revenue $100M+

Expected: Model should diversify (80% Taiwan, 20% Japan) for resilience
Impact: Concentration risk not captured in cost model

Key Statistics

  • Single-supplier concentration: 30-50% typical in optimized supply chains
  • Disruption event frequency: Every 5-10 years per supplier
  • Recovery time: 1-12 months depending on event
  • Revenue loss: 10-50% during disruption

Mitigation Strategies

  1. Resilience Constraints: Require multi-supplier (min 2-3 suppliers per component)
  2. Disruption Modeling: Include disruption probability in cost model
  3. Supplier Diversification: Geographic + company diversification
  4. Safety Stock: Keep buffer inventory for critical components

Metrics

  • Supplier concentration ratio (should be <70% from single supplier)
  • Disruption recovery time (should be <4 weeks)
  • Redundancy cost vs. disruption risk (trade-off analysis)

Alerts

  • Single supplier >70% → Diversify sourcing

References