Classical event logs have the fundamental shortcoming of describing process behavior only in isolated process executions from the viewpoint of a single case entity. Most real-life processes involve multiple entities and process executions are not isolated but tightly connected - through actors and entities involved in multiple executions. This post summarizes how event graphs are … Continue reading How do Event Graphs help analyzing Event Data over Multiple Entities?
By Dirk Fahland. Analyzing processes supported by an ERP system such as Order-to-Cash or Purchase-to-Pay are one of the most frequent use cases of process mining. At the same time, they are one of the most challenging, because the processes operate on multiple related data objects such as orders, invoices, and deliveries in n:m relations. … Continue reading Artifact-Centric Process Mining for ERP-Systems with Multiple Case Identifiers
By Dirk Fahland. In this post, I show how simple data visualizations help understanding the multi-dimensional nature of processes. Even the most simple classical business processes have important dynamics that cannot be understood by cases in isolation. The Performance Spectrum was originally designed to deliver a useful process map for analyzing logistics processes over time. … Continue reading Performance Spectrum for Analyzing Business Processes