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FLOW FROM BLOCKERS
How to Use Blocker Clustering to Improve Predictability
WHAT IS FLOW?
The movement of customer value through a process.
— Dan Vacanti
— Photo from Woodland Trust
WHAT IS A BLOCKER?
An abnormal condition that prevents
a committed work item from progress
WHAT IMPACTS DELIVERY TIME?
— From Real-World Kanban
@mattphilip #ale15
BLOCKER CLUSTERING @mattphilip #ale15
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…
© 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
ANALYSIS SESSION
We started on a monthly cadence.
CLUSTERS EMERGE
After dividing into Internal and External, the team further clusters the blockers
into reasons for blocks.
ANALYZE ROOT-CAUSE
We used fishbone technique.
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
35 Dependent Story blockers
BLOCKERS BY COUNT @mattphilip #ale15
69 days lost to Dependent Story blockers
BLOCKERS BY DAYS @mattphilip #ale15
141 stories in the release
66 stories were blocked at some
point — nearly half!
WHAT WE DISCOVERED (TEAM 2) @mattphilip #ale15
WHAT DOES THIS DO TO FLOW?
85th percentile
@mattphilip #ale15
IMPROVED FLOW
85th percentile
@mattphilip #ale15
TAKEAWAYS
You can learn from our mistakes

and try some things that worked for us.
1 2 3 4 5
Teams
UNEXPECTED INSIGHTS
Biggest blocker cluster for each?
@mattphilip #ale15
1
2
3
UNEXPECTED INSIGHTS
Dependent
Stories
@mattphilip #ale15
THINGS TO AVOID
Most blockers were of “unknown” reason
@mattphilip #ale15
Differing definitions of “blocker”
Misunderstanding your commitment point
Bad (or no) data
THINGS TO TRY @mattphilip #ale15
Manage empirically as a safe-to-fail
experiment
Start simple, with invitation
Tell others about it
Klaus Leopold and Troy Magennis
bit.ly/SimResources
mattphilip.wordpress.com
@mattphilip
THANK YOU/Благодаря
Esmé

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Flow From Blockers: How to Use Blocker Clustering to Improve Predictability, ALE 2015 Conference