As supply chains become more dynamic, there is a need for a sense-and-respond capability to react to events in a real-time manner. In this paper, we propose Petri nets extended with time and color (to represent case data) as a formalism for managing events. We designed seven basic patterns to capture modeling concepts that arise commonly in supply chains. These basic patterns may be used by themselves and also combined to create new patterns. We also show how to combine the patterns to build a complete Petri net and analyze it using dependency graphs and simulation. Dependency graphs can be used to analyze the various events and their causes. Simulation was, in addition, used to analyze various performance indicators (e.g., fill rates, replenishment times, and lead times) under different strategies. We showed it is possible to perform sensitivity analysis to study the effect of changing parameter values on the performance indicators. This approach thus makes a very complex problem tractable.