This paper is aimed at formalizing an objective method to analyze and assess operational risk in supply chains. The proposed approach consists of exploiting the analogy among logistic networks and dynamical systems; in particular, it proposes to identify the risky events characterizing a generic supply chain by studying its attributed Petri net and the corresponding coverability graph, whereas it suggests to assess the risky events effects by building the logistic network simulation model, experimenting on it and applying ANOVA to the experimental campaigns results. Finally, the method has been applied to a single-item, 3-stages supply chain to show how it can be practically used.