01
CHAPTER 01
Why Hybrid Exists
Concepts: Predictive vs iterative • uncertainty • complexity • compliance • fixed dates • tailoring
Practice: Diagnose why a project needs more than one delivery mode.
Open chapter →HYBRID · 5 chapters
Hybrid Delivery Path
Learn to design a delivery model around the nature of the work: predictive control where certainty matters and iterative learning where uncertainty is high.
HOW TO USE THIS PATH
Learn → apply → produce proof.
Do not treat the chapters as reading material only. Read the concept, work through the example, complete the practice task, and keep the output. By the end, you should have artifacts you can explain in an interview.
1Understand the idea
2Apply it to a scenario
3Produce an artifact
4Explain your decision
TABLE OF CONTENTS
Complete chapter map
Each chapter below shows the concepts you are expected to understand and the practical proof you should be able to produce.
02
CHAPTER 02
Tailoring the Delivery Model
Concepts: Workstream design • lifecycle choices • governance • decision rights • cadence • tailoring principles
Practice: Design an operating model for a mixed project instead of simply labelling it hybrid.
Open chapter →03
CHAPTER 03
Governance in a Hybrid Project
Concepts: Controls • baselines • approvals • review gates • reporting • change • decision forums
Practice: Create lightweight governance that gives leadership visibility without blocking iteration.
Open chapter →04
CHAPTER 04
Hybrid Planning & Dependencies
Concepts: Integrated planning • interfaces • dependencies • milestones • release planning • uncertainty
Practice: Map dependencies between predictive and iterative workstreams and protect key interfaces.
Open chapter →05
CHAPTER 05
A Practical Hybrid Example
Concepts: eCommerce transformation • fixed launch • iterative UX • migration • governance • learning
Practice: Design a complete hybrid approach for a realistic eCommerce transformation.
Open chapter →You're ready to move on when you can...
Explain the concepts without reading notes, apply them to a new scenario, produce a clean artifact, defend your choices, and identify what information you would need before making a real-world decision.