• Introduction to Business Process Management (BPM)
• Introduction to Process Mining: History of process mining; Role in the BPM lifecycle; Value proposition; Overview of categories of process mining techniques (automated discovery, performance mining, conformance checking, variants analysis, predictive monitoring); Process mining vs Business Activity Monitoring and Business Intelligence.
• Case studies: Process mining uptake in practice; Case studies in different application areas (finance, healthcare, IT service provider, etc.); Results achieved and lessons learned.
• Automated process discovery: Anatomy of an event log; Ingredients of a process map; Overview of main discovery algorithms (Inductive Miner, Split Miner); Alternative discovery views (social networks, object lifecycle models); Visual analytics and results interpretation; Practical exercises.
• Performance mining: Process performance metrics (time, cost, quality and flexibility dimensions); Overview of main performance mining techniques (dotted charts, summary statistics, statistics over process maps/models, stage-based cumulative flow diagrams); Visual analytics and results interpretation; Practical exercises
• Conformance checking: Conformance checking concepts (play-in, play-out, replay); Overview of conformance checking techniques (token replay, alignments, event structures); Conformance of process data and resources; Visual analytics and results interpretation; Practical exercises; Variants analysis and Predictive monitoring; Drivers for variants analysis and overview of techniques; Visual analytics and results interpretation; Practical exercises; Overview of predictive monitoring; Prediction targets and methods; Predictive monitoring dashboards.
• How to run a process mining project: Types of process mining project (exploratory, question-driven); Phases of a question-driven project and role of stakeholders; Data acquisition and pre-processing; Common pitfalls of process mining projects; Overview of process mining tools.