Actionable Agile Metrics Volume II

Preface

1. Why Write This Book
2. Assumptions
3. Who Should Read This Book
4. Conventions Used
5. How to Read
6. ActionableAgile.com

Section I: Variation and Predictability

Chapter 1 – Wilt the Stilt

Chapter 2 – Variation Defined

1. The Second Principle for Understanding Data
2. Two Types of Variation
3. Exceptional Variation
4. The Two Mistakes of Data Analysis
5. Flow Metrics and Variation
6. Conclusion

Chapter 3 – Variation and Predictability

1. A Definition of Predictable Process
2. Sequential Analysis for Predictability
3. What About Little’s Law?
4. Conclusion

Chapter 4 – Process Behaviour Charts

1. Table Data vs. Visualized Data
2. The Running Record
3. Rules for Presenting Data
4. The First Principle of Understanding Data
5. The X Chart
6. The Moving Range Chart
7. The XmR Chart
8. Conclusion

Chapter 5 - How Much Data?

1. How Much Data?
2. PBCs with less than 20 data points
3. When to Update Limits
4. Conclusion

Chapter 6 – Detecting Signals on PBCs

1. The Trend is Not Your Friend
2. Detection Rules for XmR Charts¹
3. Zero Bounded Data
4. Sign, Sign, Everywhere a Sign
5. Did Wilt Improve?
6. An Additional Rule?
7. An Example Using Cycle Time
8. Conclusion

Chapter 7 – XmR Charts and the Four Basic Metrics of Flow

1. XmR Charts and Cycle Time
2. XmR Charts and Throughput
3. XmR Charts and WIP
4. XmR Charts and WIP Age
5. Conclusion

Chapter 8 – Myths and Other Considerations

1. What If I Know I Have Bad Data?
2. PBCs Using Medians
3. The Wrong Ways to Use PBCs
4. The Only Data Considerations You Need
5. Conclusion

Chapter 9 - VoP, VoC, and Predictability

1. Predicable Process vs. Arbitrary Targets
2. VoC, VoP, and Scrum
3. Three Types of Action
4. Conclusion

Section II: Advanced Monte Carlo Simulation and Predictability

Chapter 10 - Monte Carlo Simulation Revisited

1. A Quick Thought Experiment
2. Probabilistic Thinking
3. Forecasts for Multiple Items
4. Conclusion
5. Key Learnings and Takeaways

Chapter 11 - Different Sampling Methods

1. Is Our Default Sampling Algorithm Incorrect?
2. All Models Are Wrong, But Some Are Random¹
3. What Happened To Our Team?
4. Conclusion

Chapter 12 - What Percentile Do I Choose?

1. Here Comes The Rain Again
2. Continuous Forecasting
3. Conclusion

Chapter 13 - Scaling Monte Carlo

1. Single Team With Work Item Hierarchy
2. Single Team Working On Multiple Items
3. Multiple Teams With Dependencies
4. Just When You Thought It Was Safe…
5. Conclusion

Chapter 14 - A Parting Thought

Appendices

Appendix A - The Basic Metrics of Flow

1. Work In Progress
2. Cycle Time
3. Work Item Age
4. Throughput
5. Conclusion

Appendix B - How To Construct an XmR Chart

1. The XmR Chart for Cycle Time
2. Conclusion

Endnotes

Bibliography

Acknowledgements

About The Author