Process mining in logistics: The need for rule-based data abstraction

Abstract

Organizations struggle to gain insight in how their business processes are conducted in reality. Process mining enables organizations to extract this knowledge by analyzing business events recorded in their information systems. However, the business events recorded in these systems do not always reflect the same level of abstraction as the desired process model that is used by the business. Current process mining approaches give insufficient attention to this gap. This paper proposes several data preparation methods that apply logistic domain knowledge for process mining the material movements within an organization. In addition, an adapted process mining project methodology is presented that explicitly includes these preparation methods.