This module introduces the foundations of business process modeling, including core concepts, frameworks, and techniques for capturing current and future states. You will explore what process models are, why they matter, and how they help organizations make better decisions and improve performance. You will examine frameworks and modeling approaches at both high and detailed levels, gaining awareness of tools such as Entity Relationship Diagrams (ERDs), Data Flow Diagrams (DFDs), flowcharts, swim lane diagrams, and BPMN. The module also covers use cases, scenarios, and the connection between process models and stakeholder perspectives, ensuring you can align technical methods with real-world business needs. Through labs and practice activities, you will apply a structured process modeling checklist, analyze business gaps, and create diagrams that clarify how work is (and should be) performed.

This module introduces practical mapping methods used to visualize and analyze how work is performed to uncover inefficiencies and prepare for process improvement work. You will explore different types of process maps—including basic flowcharts, cross-functional diagrams, and top-down views—and learn when and how to apply each. The module introduces best practices for using BPMN and swim lane diagrams to clarify roles and responsibilities, along with techniques for handling complex processes through decomposition. You will also examine process narratives, SIPOC analysis, and the FURPS framework as complementary tools for capturing requirements, identifying inefficiencies, and communicating with stakeholders. Hands-on labs and activities reinforce learning by allowing you to create maps, conduct SIPOC interviews, and analyze customer scenarios that highlight critical performance gaps.

This module focuses on methods for improving, optimizing, and transforming business processes and the role of AI in accelerating these initiatives. You will learn about different types of improvement efforts, such as process optimization, automation, and reengineering, and understand the responsibilities of process owners and improvement frameworks. The module also introduces prioritization techniques like MoSCoW and Kano to help evaluate which improvements deliver the most value. The module also focuses on how generative AI can support process analysis and improvement. You will identify how AI assists in documentation, visualization, and cost analysis, and practice using AI prompts to uncover insights in real-world scenarios. Hands-on labs and activities enable you to apply both traditional and AI-enhanced approaches to identifying inefficiencies and recommending improvements.

This module introduces systems thinking, Lean principles, and Six Sigma fundamentals as complementary approaches to the process improvement methods explored in earlier modules. You will discover how systems thinking reveals interconnections across processes, prevents sub-optimization, and supports the design of holistic, organization-wide solutions. You will gain guidance on planning, implementing, and sustaining improvements through structured change management and governance practices. The module focuses on Lean and Six Sigma as proven frameworks for driving efficiency and quality. You will learn about Lean’s philosophy of value creation and waste elimination, practice identifying the eight common wastes, and use value stream mapping to visualize workflow improvements. Six Sigma tools such as DMAIC and statistical process control are introduced to provide structured, data-driven approaches to solving problems and maintaining stability.

The final module gives you an opportunity to apply what you have learned throughout the course in a project. You will develop a process model and supporting narrative based on a real-world use case, integrating techniques from process modeling, mapping, improvement, and systems thinking. The module also includes a final quiz to assess knowledge gained across the course. In addition, the module highlights key takeaways, provides a glossary of terms, acknowledges contributors, and outlines potential next steps, including industry-recognized certifications (such as CompTIA Project+, ASQ CQIA, and AIGPE Process Mapping Specialist) to continue professional development.