Pega Process Mining relies on events to build a Process Map and provides analysis tools that you can use to discover processes, check conformance, and enhance processes. Learn more about the purpose, source, and requirements of event logs.
Purpose of event logs
Organizations often use techniques such as focus groups or job shadowing to discover how work gets done. While these techniques are useful, they are also based on relatively small samples and require more manual analysis. Pega Process Mining helps organizations analyze large volumes of data to discover how work gets done. The source of this data is event logs.
Event logs capture the transitions between activities as employees perform their work. Pega Process Mining uses these transitions to build a process model, which is displayed as a Process Map that you can filter and analyze.
Data sources for event logs
- System logs (files, databases)
- Pega applications
- Enterprise resource planning (ERP)
- Customer relationship management (CRM)
- Robotic Process Automation (RPA)
- IT Service Management
- Work Force Management
- Interactive voice response (IVR)
- Web Servers
- Apps
- Legacy Systems
Requirements for event logs
- Case ID
- A unique identifier that denotes a single process instance. Examples
include a trouble ticket ID in an ITSM platform or an opportunity ID in
the CRM. A Case ID is an integral element that links the different parts
of a process together.
A Case ID must be unique across all of the applications involved in the process for inclusion in the process model.
- Timestamp
- The date and time when each event of the process instance occurred.
- Activity Name
- Short description of the event/action that took place for the process instance (Case ID) at a specific time (Timestamp).
Additional data in event logs
Pega Process Mining requires a Case ID, Timestamp, and Activity Name to build a working Process Map. Adding data beyond these requirements provides richer analysis opportunities. For example, you can filter the Process Map to show only activities and metrics for a particular geographic location.
The following figure shows how data extracted from an event log translates to a process model that is displayed for analysis as a Process Map: