Probabilistic Chain Analysis (PCA): A Framework for Running Projects in a Probabilistic World

This whitepaper introduces Probabilistic Chain Analysis™ (PCA) — a risk methodology that models project risks as dependent chains rather than independent events. PCA quantifies cascade amplification through Bayesian lift factors and builds institutional memory through cross-project posterior updating via full Metropolis-Hastings MCMC (R̂ < 1.1 verified). Validated on a UK Highways Survey & Investigation scenario across 16,000+ projects in 8 infrastructure sectors. Implemented in RiskPulseV12 — a Bayesian Monte Carlo risk engine. Version 1.1: Intelligence Log MCMC upgrade, schedule-cost separation-with- conjunction methodology documented.