Flow From Blockers: How to Use Blocker Clustering to Improve Predictability, ALE 2015 Conference
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The document discusses the concept of blocker clustering as a method to enhance predictability and reduce risks in team workflows. It outlines steps for teams to identify and analyze blockers, revealing insights into internal and external delays caused by these blockers. The findings highlight the impact of dependent story blockers and suggest empirical management as a strategy to improve team flow.
Flow From Blockers: How to Use Blocker Clustering to Improve Predictability, ALE 2015 Conference
- 1. FLOW FROM BLOCKERS How to Use Blocker Clustering to Improve Predictability
- 2. WHAT IS FLOW? The movement of customer value through a process. — Dan Vacanti
- 3. — Photo from Woodland Trust WHAT IS A BLOCKER? An abnormal condition that prevents a committed work item from progress
- 4. WHAT IMPACTS DELIVERY TIME? — From Real-World Kanban @mattphilip #ale15
- 5. BLOCKER CLUSTERING @mattphilip #ale15
- 6. THE INVITATION @mattphilip #ale15 Subject: Improve planning and reduce risk Dear Asynchronites, Would you like to improve planning and reduce risk in your team? I'm offering to coach up to two teams in the practice of blocker clustering…
- 7. © 2012, Asynchrony Solutions, Inc. All rights reserved. 1. Talk with teammates about the experiment. 2. Define “block” for your team. 3. Start gathering blocker data, including reason and duration — simply and easily. GETTING STARTED @mattphilip #ale15
- 8. ANALYSIS SESSION We started on a monthly cadence.
- 9. CLUSTERS EMERGE After dividing into Internal and External, the team further clusters the blockers into reasons for blocks.
- 10. ANALYZE ROOT-CAUSE We used fishbone technique.
- 11. Internal blockers caused 20 days of delay External blockers caused 147 days of delay The biggest blocker cluster accounted for 86 days of delay WHAT WE DISCOVERED (TEAM 1) @mattphilip #ale15
- 12. 35 Dependent Story blockers BLOCKERS BY COUNT @mattphilip #ale15
- 13. 69 days lost to Dependent Story blockers BLOCKERS BY DAYS @mattphilip #ale15
- 14. 141 stories in the release 66 stories were blocked at some point — nearly half! WHAT WE DISCOVERED (TEAM 2) @mattphilip #ale15
- 15. WHAT DOES THIS DO TO FLOW? 85th percentile @mattphilip #ale15
- 16. IMPROVED FLOW 85th percentile @mattphilip #ale15
- 17. TAKEAWAYS You can learn from our mistakes and try some things that worked for us.
- 18. 1 2 3 4 5 Teams UNEXPECTED INSIGHTS Biggest blocker cluster for each? @mattphilip #ale15
- 20. THINGS TO AVOID Most blockers were of “unknown” reason @mattphilip #ale15 Differing definitions of “blocker” Misunderstanding your commitment point Bad (or no) data
- 21. THINGS TO TRY @mattphilip #ale15 Manage empirically as a safe-to-fail experiment Start simple, with invitation Tell others about it
- 22. Klaus Leopold and Troy Magennis bit.ly/SimResources mattphilip.wordpress.com @mattphilip THANK YOU/Благодаря Esmé