Predictability & Measurement

with Kanban
OOP 2012
Munich
January 2012

Twitter: agilemanager

David J. Anderson
David J. ...
Book Published
April 2010

Available from
djaa.com

Advanced
Kanban

A 72,000 word
intro to the topic
German
published January, 2011

Kanban
2012

Translation by
Arne Roock &
Henning Wolf
of IT-Agile
http://leankanbanuniversity.com
http://www.limitedwipsociety.org

LinkedIn Groups: Software Kanban

Yahoo! Groups: kanband...
Delivering predictability with
Kanban
requires some different techniques
for different types of work such as
software main...
Service-oriented work

Advanced
Kanban
Create a regular delivery cadence
Develop a strong config management capability

Develop capability to deploy effectively
...
Understand capability by studying the natural
philosophy of the work
MARCH

Lead Time Distribution
2.5

# CRs

2
1.5
1
0.5...
Observe Flow with a spectral analysis histogram
of lead time
Lead Time Distribution
3.5
3

CRs & Bugs

2.5
2
1.5
1
0.5

1
...
44 or 51 days will not be good enough for some
feature requests, so offer a package of classes of
service

Advanced
Kanban
Package of Classes with SLAs


As soon as possible




100% on-time




providing 24 days advance notice

Up to 51 da...
Lead time

Standard Class Items

Fixed Date Items

Advanced
Kanban

Expedite Item

Features Delivered
Allocate capacity across classes of service in
order to deliver against anticipated demand
5

4

Analysis
Input
Queue In P...
Major Project Work

Advanced
Kanban
Requires all the same underlying
data as used in service oriented
work
plus

Advanced
Kanban
Major Project with two-tiered kanban board

Advanced
Kanban
Observe Flow with a Cumulative Flow
Diagram

Avg. Lead Time

Time
Inventory

Started

Designed

Coded

Complete

30
-M
ar
...
Throughput

=

Little’s Law
WIP
Lead Time

Kanban
2012
Cumulative Flow and
Predictive Modeling with S-Curve

Inventory

Started

Designed

Coded

Complete

30
-M
ar

23
-M
ar

1...
Simulating S-Curve with a Z

60%
Slope in middle
3.5x - 5x slope
at ends

5x

20%

Time
Inventory

Started

Designed

Code...
Track actual throughput against projection

Inventory

Started

Designed

Coded

Complete

30
-M
ar

23
-M
ar

16
-M
ar

9...
Unplanned Work Report
Scope Creep

Dark Matter

Advanced
Kanban
Planning a large project
Device Management Ike II Cumulative Flow

2008

30
-M
ar

23
-M
ar

16
-M
ar

9M
ar

2M
ar

5x

K...
Little’s Law

Determines staffing level

Target to achieve plan

Throughput

=

WIP
Lead Time
From observed capability

Ka...
Changing the WIP limit without
maintaining the staffing level ratio
represents a change to the way of
working. It is a cha...
Plan based on currently observed
capability and current working
practices. Do not assume process
improvements.
If changing...
Little’s Law

Determines staffing level

Target to achieve plan

55 / week

WIP

=

0.4 week
WIP = 22, round up to 25.
5 t...
Conclusions

Advanced
Kanban
For Service-oriented work, create
predictability with
a regular delivery cadence
a strong config management capability
cap...
Thank you!

Advanced
Kanban

dja@djaa.com
http://djaa.com/
About…
David Anderson is a thought leader in
managing effective software teams. He leads
a consulting, training and publis...
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OOP 2012 - Predictability & Meansurement with Kanban

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Metrics, measurement, probabilistic forecasting and setting expectations to enable predictable delivery with Kanban. Track session from OOP 2012 Munich

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OOP 2012 - Predictability & Meansurement with Kanban

  1. 1. Predictability & Measurement with Kanban OOP 2012 Munich January 2012 Twitter: agilemanager David J. Anderson David J. Anderson & Associates Email: dja@djaa.com
  2. 2. Book Published April 2010 Available from djaa.com Advanced Kanban A 72,000 word intro to the topic
  3. 3. German published January, 2011 Kanban 2012 Translation by Arne Roock & Henning Wolf of IT-Agile
  4. 4. http://leankanbanuniversity.com http://www.limitedwipsociety.org LinkedIn Groups: Software Kanban Yahoo! Groups: kanbandev Yahoo! Groups: kanbanops
  5. 5. Delivering predictability with Kanban requires some different techniques for different types of work such as software maintenance and support or Advanced Kanban major project work
  6. 6. Service-oriented work Advanced Kanban
  7. 7. Create a regular delivery cadence Develop a strong config management capability Develop capability to deploy effectively Build code with high quality Advanced Kanban
  8. 8. Understand capability by studying the natural philosophy of the work MARCH Lead Time Distribution 2.5 # CRs 2 1.5 1 0.5 106 101 96 91 86 81 76 71 66 61 56 51 46 41 36 31 26 21 16 11 6 1 0 Days Lead Time Distribution APRIL 3.5 Majority of CRs range 30 -> 55 2 Outliers 1.5 1 0.5 Days 8 14 1 14 4 13 0 3 6 7 12 12 11 10 99 92 85 78 71 64 57 50 43 36 29 22 15 8 0 1 CRs & Bugs 2.5 Advanced Kanban 3
  9. 9. Observe Flow with a spectral analysis histogram of lead time Lead Time Distribution 3.5 3 CRs & Bugs 2.5 2 1.5 1 0.5 1 4 7 0 3 6 8 14 14 13 12 12 11 10 99 92 85 78 71 64 57 50 43 36 29 22 8 15 1 0 Days SLA expectation of 44 days with 85% on-time Advanced Kanban Mean of 31 days SLA expectation of 51 days with 98% on-time
  10. 10. 44 or 51 days will not be good enough for some feature requests, so offer a package of classes of service Advanced Kanban
  11. 11. Package of Classes with SLAs  As soon as possible   100% on-time   providing 24 days advance notice Up to 51 days  98% on-time guarantee Up to 51 days  50% on-time Advanced Kanban  Full transparency
  12. 12. Lead time Standard Class Items Fixed Date Items Advanced Kanban Expedite Item Features Delivered
  13. 13. Allocate capacity across classes of service in order to deliver against anticipated demand 5 4 Analysis Input Queue In Prog Done 3 4 Development Dev Ready In Prog Done 2 Build Ready 2 = 20 total Test Release Ready ... Allocation 4 = 20% 10 = 50% 6 = 30% Advanced Kanban +1 = +5%
  14. 14. Major Project Work Advanced Kanban
  15. 15. Requires all the same underlying data as used in service oriented work plus Advanced Kanban
  16. 16. Major Project with two-tiered kanban board Advanced Kanban
  17. 17. Observe Flow with a Cumulative Flow Diagram Avg. Lead Time Time Inventory Started Designed Coded Complete 30 -M ar 23 -M ar 16 -M ar 9M ar 2M ar eb Avg. Throughput Kanban 2012 24 -F eb WIP 17 -F eb 240 220 200 180 160 140 120 100 80 60 40 20 0 10 -F Features Device Management Ike II Cumulative Flow
  18. 18. Throughput = Little’s Law WIP Lead Time Kanban 2012
  19. 19. Cumulative Flow and Predictive Modeling with S-Curve Inventory Started Designed Coded Complete 30 -M ar 23 -M ar 16 -M ar 9M ar 2M ar eb Time Kanban 2012 24 -F eb Typical S-curve 17 -F eb 240 220 200 180 160 140 120 100 80 60 40 20 0 10 -F Features Device Management Ike II Cumulative Flow
  20. 20. Simulating S-Curve with a Z 60% Slope in middle 3.5x - 5x slope at ends 5x 20% Time Inventory Started Designed Coded Complete 30 -M ar 23 -M ar 16 -M ar 9M ar 2M ar eb 24 -F eb 20% Kanban 2012 17 -F eb 240 220 200 180 160 140 120 100 80 60 40 20 0 10 -F Features Device Management Ike II Cumulative Flow
  21. 21. Track actual throughput against projection Inventory Started Designed Coded Complete 30 -M ar 23 -M ar 16 -M ar 9M ar 2M ar eb Time Kanban 2012 24 -F eb Track delta between planned and actual each day 17 -F eb 240 220 200 180 160 140 120 100 80 60 40 20 0 10 -F Features Device Management Ike II Cumulative Flow
  22. 22. Unplanned Work Report Scope Creep Dark Matter Advanced Kanban
  23. 23. Planning a large project Device Management Ike II Cumulative Flow 2008 30 -M ar 23 -M ar 16 -M ar 9M ar 2M ar 5x Kanban 2012 24 -F eb 2006 eb Slope in middle 3.5x - 5x slope at ends 17 -F eb 240 220 200 180 160 140 120 100 80 60 40 20 0 10 -F Features Required throughput (velocity) During the middle 60% of the project schedule Time we need Throughput (velocity) to average 220 Inventory Started Designed Coded Complete features per month
  24. 24. Little’s Law Determines staffing level Target to achieve plan Throughput = WIP Lead Time From observed capability Kanban 2012 Treat as Fixed variable
  25. 25. Changing the WIP limit without maintaining the staffing level ratio represents a change to the way of working. It is a change to the system design. And will produce a change in the observed ‘common cause’ capability of the system Kanban 2012
  26. 26. Plan based on currently observed capability and current working practices. Do not assume process improvements. If changing WIP to reduce undesirable effects (e.g. multitasking), get new sample data (perform a spike) to observe the new capability Kanban 2012
  27. 27. Little’s Law Determines staffing level Target to achieve plan 55 / week WIP = 0.4 week WIP = 22, round up to 25. 5 teams, 5 per team If current working practice is 1 unit WIP per person then 5 people are needed to per team Kanban 2012 From observed capability
  28. 28. Conclusions Advanced Kanban
  29. 29. For Service-oriented work, create predictability with a regular delivery cadence a strong config management capability capability to deploy effectively code with high quality For major projects Advanced Kanban understand peak throughput (velocity) model the s-curve on work complete treat the avg. lead time as the fixed variable use Little’s Law to calculate WIP limits and staffing levels
  30. 30. Thank you! Advanced Kanban dja@djaa.com http://djaa.com/
  31. 31. About… David Anderson is a thought leader in managing effective software teams. He leads a consulting, training and publishing business dedicated to developing, promoting and implementing sustainable evolutionary approaches for management of knowledge workers. He has 30 years experience in the high technology industry starting with computer games in the early 1980’s. He has led software teams delivering superior productivity and quality using innovative agile methods at large companies such as Sprint and Motorola. David is a founder of the Lean Kanban University, a business dedicated to assuring quality of training in Lean and Kanban throughout the world. http://leankanbanuniversity.com Email: dja@djaa.com Twitter: agilemanager Advanced Kanban David is the author of two books, Agile Management for Software Engineering – Applying the Theory of Constraints for Business Results, and Kanban – Successful Evolutionary Change for your Technology Business.

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