Digitalizing Business Processes, Knowledge Workflows and Compliance

After the course you will

• Be able to digitalize decisions, regulations and business processes with notations and tools used in practice today, notably BPMN, DMN and DCR.
• Have knowledge of a number of advanced, research-based uses of process technologies, such as process mining, predictive process monitoring, process querying, compliance-by-design and process verification, of which some are already available in commercial tools and others are on the way.

Based on concrete examples, the course will take you through the steps needed for digitalizing business processes and regulations, from the identification of activities and roles to the modelling of decision logic and process flows that can be executed by modern, low- or no-code process-aware information systems.

Core elements:

• Process identification in practice: How do you identify activities, roles, decision rules and dependencies in the business and work processes your organization do today ? Concrete examples from e.g. HR, healthcare, finance and local government
• Digitalizing knowledge workflows and compliance-by-design: What is the difference between digitalizing knowledge work and repetitive business processes ? How do you map regulations and use them to ensure compliance?
• Process notations: Introduction to Business Process Model & Notation (BPMN), Decision Model & Notation (DMN), Dynamic Condition Response (DCR) and Petri Nets.
• Process execution: Introduction to the theory and practice of Business Process Management Systems (BPMS), Workflow and Case Management tools.
• Process Mining: Introduction to the theory and practice of process mining, challenges and possibilities and concrete examples of algorithms on example event logs from e.g. healthcare, finance and local government
• The road ahead: Possibilities and pitfalls in AI-based process digitalization and decision support

Tools/methods introduced

• Methods and tools for using Business Process Model & Notation (BPMN), Decision Model & Notation (DMN) and Dynamic Condition Response (DCR)
• Selected process mining tools mapping event logs to imperative process models (BPMN) and declarative process models (DCR)

We will primarily be working with pen & paper and no-code/low-code digitalization tools. However, pointers can be given to participants interested in the integration with general purpose programming languages such as Python.

The course assumes academic maturity corresponding to a bachelor degree but deliberately targets a broad audience: Both participants with no programming experience but knowledge of e.g. law or process and decision support in practice or participants with knowledge of classical programming, but not process-aware information systems.