Flexible Workflows with Ripple Down Rules

How can workflows adapt automatically to exceptions and unforeseen situations?
This video explains how ripple-down rules provide dynamic flexibility in YAWL workflows by enabling adaptive, data-driven decision-making during execution.

Ripple-down rules are organized as binary decision trees in which conditions are evaluated against case data and conclusions trigger the execution of specific worklets. The video explains the two-phase evaluation mechanism that allows rules to evolve incrementally over time without disrupting existing behavior. This approach supports systematic exception handling and gradual refinement of process logic as new situations arise.

Using the YAWL editor, the tutorial demonstrates how ripple-down rules are defined, how they are connected to worklets and exlets, and how they influence workflow execution at runtime. A walkthrough example illustrates how workflows can adapt automatically while remaining controllable and understandable.

This tutorial is part of the playlist “Learn how to automate business processes with YAWL (BASIC)”:
https://www.youtube.com/playlist?list=PL4BZgFsmRzfSEP_8nCqHt3N2X_XzRNen2

Supplementary material, including the YAWL models and rule definitions used in this tutorial, is available on GitHub:
https://github.com/ahense/YAWL  
(Download via “Code” → “Download ZIP”. The material is located in the folder corresponding to the tutorial number.)

This is video #19 of the YAWLSeries.