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Analytical techniques that discover, monitor, and improve real processes by extracting knowledge from event logs.
DESCRIPTION
Process mining converts event logs from enterprise systems into process models and insights. Core tasks include process discovery, conformance checking, and enhancement. It reveals bottlenecks, rework, deviations, and automation opportunities. Outputs inform optimization, compliance, and transformation programs. Tools like ProM and Celonis operationalize the methods at scale. High-quality event logs with case IDs, activities, and timestamps are essential. Privacy and context modeling must be addressed. The practice bridges BPM and data mining, enabling data-driven process improvement.
ALTERNATIVE DEFINITIONS
Wikipedia
Process mining is a family of techniques in the field of process management that support the analysis of business processes based on event logs.
Stresses event-log–based analysis across techniques.
IEEE Task Force on Process Mining
Process mining aims to discover, monitor and improve real processes by extracting knowledge from event logs readily available in today’s information systems.
Defines goals (discover, monitor, improve) and data source (event logs).
Celonis
Process mining is a data-driven technique to visualize, analyze, and improve your business processes by leveraging event data from IT systems.
Vendor perspective emphasizing visualization and improvement from IT event data.
RELATED TERMS
Event Sourcing Conformance Checking Process Discovery BPM Task Mining XES Digital Twin of an Organization Celonis ProM Root Cause Analysis
COMPETING TERMS
Business Process Modeling
KNOWLEDGE AREAS
Data Science Data Products Data Management AI Data Integration & Interoperability
TARGET AUDIENCE
Data Scientist Information Analyst Data Analyst Data Engineer AI Product Manager Digital Transformation Manager Data Management Consultant
EXTERNAL SOURCES
- Wikipedia - Process mining
- IEEE Task Force on Process Mining - Process Mining Manifesto
- ProM - Open-source process mining toolkit
- Celonis - Vendor overview and resources
TOP QUESTIONS
What does Process Mining do for organizations?
It transforms event logs into process maps and performance insights. Bottlenecks and deviations become visible. The result is measurable process improvement.
Category: Definition
What data is required for Process Mining?
Event logs with case IDs, activities, and timestamps are essential. Additional attributes enrich analysis. Data quality strongly influences outcomes.
Category: Requirements
How is Process Mining different from BPM modeling?
Process mining derives models from real data, while BPM modeling designs from assumptions. Mining validates and complements model-driven approaches. Both can be synergistic.
Category: Alternatives
What are common mistakes in Process Mining?
Poor case identification and timestamp inconsistencies undermine results. Ignoring context and variants hides root causes. Always validate log completeness.
Category: Mistakes
What is a key risk in Process Mining?
Privacy and compliance risks arise from detailed logs. Anonymize and govern access. Ensure findings are communicated responsibly.
Category: Risks
Which techniques are core to Process Mining?
Process discovery, conformance checking, and enhancement are core. Each addresses structure, compliance, and performance, respectively. Combined, they drive end-to-end improvements.
Category: Example
Where to start with Process Mining?
Begin with a high-impact process and well-structured logs. Run discovery, validate with stakeholders, then iterate on root cause analysis. Track benefits with KPIs.
Category: Management
How does Task Mining relate to Process Mining?
Task mining captures user-level activities to complement system logs. Together, they provide a fuller picture. Alignment and privacy controls are mandatory.
Category: Example
What is a hot topic around Process Mining?
Actionable process intelligence and automation triggers are rising. Integration with RPA and operational dashboards is maturing. Real-time streaming logs are emerging.
Category: Topic