AI curriculum
Course outline for Workflow Engineering Foundations
Work can stall at handoffs even when individual tasks are efficient. Model a real process to expose state, queues, and improvement opportunities before automating it.
About Workflow Engineering Foundations
Work can stall at handoffs even when individual tasks are efficient. Model a real process to expose state, queues, and improvement opportunities before automating it.
Workflow Engineering Foundations Course Objectives
- Map activities, cases, events, and state.
- Identify handoffs, queues, and bottlenecks.
- Draw a process model with explicit workflow boundaries.
Pre-requisites
- Familiarity with a workplace process.
- Basic diagramming skills; coding is not required.
Lab Setup
- Computer with a text editor and a diagramming tool.
- Use a supplied process scenario or a sanitized process description.
Detailed Course Outline
Proposed modulesModule 1: Describing work
- Understanding work as a system
- Activities and tasks
- Cases
- Events
Practical outcome: Map a case and its observable activities.
Module 2: Boundaries and flow
- State
- Workflow boundaries
- Handoffs
- Queues
Practical outcome: Record ownership and waiting states at handoffs.
Module 3: Process improvement
- Bottlenecks
- Feedback loops
- Workflow patterns
- BPMN
Practical outcome: Draw a process model and identify an improvement hypothesis.
Practical exercise
- Model a sample service process and propose a measurable change to one bottleneck.
How we train
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Ask about exercises, instructor feedback and the prior knowledge you need. Tool-specific courses marked provisional may become modules in a broader course.
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