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
Dirk Fahland One of the core challenges of process analytics from event data is to enable an analyst to get a comprehensive understanding of the process and where problems reside. In business process mining such an overview is obtained with a process map. It can be discovered from event data to visualize the flow in … Continue reading The Performance Spectrum
Dirk Fahland I am trying to sketch the landscape of describing, analyzing, and managing processes outside the well-established paradigm of a "BPMN process" where a process is executed in instances, and each instance is completely isolated from all other instances. Thinking about Processes Let me introduce the term "process thinking". Process-thinking is the fundamental paradigm … Continue reading Multi-Dimensional Process Thinking