On Risk Management with Information Flows in Business Processes

This article investigates the economic consequences of data errors in the information flows associated with business processes. We develop a process modeling‐based methodology for managing the risks associated with such data errors. Our method focuses on the topological structure of a process and takes into account its effect on error propagation and risk mitigation using both expected loss and conditional value‐at‐risk risk measures. Using this method, optimal strategies can be designed for control resource allocation to manage risk in a business process. Our work contributes to the literature on both ex ante risk management‐based business process design and ex post risk assessments of existing business processes and control models. This research applies not only to the literature on and practice of process design and risk management but also to business decision support systems in general. An order‐fulfillment process of an online pharmacy is used to illustrate the methodology.