The increased integration of global supply networks with a reduction in stock and time buffers has raised their vulnerability to disturbances (i.e. events) that erode efficiency and competitiveness. The complex interrelationships in these networks lead to a cascade of knock-on effects that affect company performance in varying degrees. Hence, causality analysis is the key for early identification of critical events. To this end, a dynamic model is developed in this contribution. It describes the basic cause-effect relationship between events, their knock-on effects and company-internal performance indicators. To make the complexity of this task manageable, an effects-based classification of events is delineated from the EPCIS format. The utility and functionality of the model is illustrated on two examples. It is proposed that it serves as a basic outline for the logic foundation of the discovery component of supply chain event management (SCEM) systems.
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