Supply Chain VaR Calculator

Educational Tool Disaster Resilience Climate Scenarios Developed by Jeff Schlegelmilch with Claude Sonnet 4.6 · Anthropic · Rev. May 2026  ·  Illustrative & Educational Use Only — Not Intended for Operational Decision Support
Node Exposure
Asset Value at Node$50M
Total value of assets, inventory & operations at this node
Daily Revenue$500K
Revenue flowing through this node per operating day
Recovery Time45 days
Days to restore full operations after a major disruption
Hazard & Vulnerability
Baseline Annual Probability5%
Historical annual probability of a major disruption event
Vulnerability60%
% of asset value lost if a disruption event occurs
Climate Scenarios
Toggle scenarios and adjust how much climate change increases annual disruption probability.
2030 Scenario
+30% probability increase
2040 Scenario
+70% probability increase
2050 Scenario
+130% probability increase
2030 multiplier +30%
2040 multiplier +70%
2050 multiplier +130%
Resilience Investment
Enable Resilience Measures
Vulnerability Reduction -40%
Reduction in asset loss % due to hardening, redundancy, or backup systems
Probability Reduction -20%
Reduction in annual disruption probability (e.g. flood barriers, supplier diversification)
Recovery Time Reduction -30%
Faster recovery via pre-positioned resources, backup suppliers, or response plans
Implementation Timeline
Start Year 2026
Ramp-up Period 3 yrs
Years until full effectiveness is reached after implementation begins
Effectiveness @ 2030 100%
Effectiveness @ 2040 100%
Effectiveness @ 2050 100%
Investment not yet implemented for some scenarios
VaR Confidence Level
Confidence95%
PML threshold — where the VaR line crosses each exceedance curve
Exceedance Probability Curve — Annual Loss vs. Probability of Exceedance
Interactive exceedance probability curves.
How to read this chart Where each curve crosses the dashed line → that scenario's VaR (PML).

Purple dashed curves show the post-resilience outcome — shifted left = lower risk.

Implementation lag means resilience may not be fully effective for near-term scenarios.