The Kanban Method represents the alternative path to agility. It is the "start with what you do now" approach that promotes evolutionary change to improve business agility rather than adopting a defined Agile method. This presentation explains the mechanics of virtual kanban systems and their implications. It defines the Kanban Method and explains how it creates an evolutionary capability in your organization
Key Note - Path to Agility 2013 - Kanban - the alternative path to agility
1. Kanban
An Alternative Path to Agility
What is Kanban?
How do you implement it?
What are the benefits?
Path to Agility
Columbus, Ohio 2013
dja@djaa.com, @djaa_dja
3. What Agile Methods Seek to Achieve
Agile methods ask us
to…
Agile methods ask us
Enable aMake trust (yet with
Let’s not high to… culture
boreProgress
you
Create slide showing &
again) with craftsmanship
a Feedback Loops
imperfect information
Create a work-in-progress
enable a capability to
Treat
The trust dividend eliminates adapt
the Manifesto!
work ethic liability
bureaucracy & encourages
as Reworking & course correcting
if it were a
collaborative working & use of this was
Withas new Agile methods tacit is
1st gen than an asset
rather information arrives
knowledge
limited to adapting to changing
Encourage high quality, well & faster
better risk management
requirements or “perfect”
engineered code that is for scope
than delaying easily
Knowledge work as new
adapted (refactored)is perishable.
information
Focus on finishing things quickly
information arrives and requires
before they go stale
very little rework due to
errors
dja@djaa.com, @djaa_dja
4. The Kanban Method – an
alternative path to agility!
dja@djaa.com, @djaa_dja
5. Kanban Method
A management & cultural approach to
improvement
View creative knowledge work as a set
of services
Encourages a management focus on
demand, business risks and capability of
each service to supply against that
demand
dja@djaa.com, @djaa_dja
6. The Kanban Method is not…
A project management or software
development lifecycle process
Nor, does it encourage a processcentric approach to improvement!
dja@djaa.com, @djaa_dja
8. Kanban Method
Uses visualization of invisible work and
virtual kanban systems
Installs evolutionary “DNA” in your
organization
Enables adaptability in your business
processes to respond successfully to
changes in your business environment
dja@djaa.com, @djaa_dja
9. Kanban Method
• “Kanbanize” your existing process
• Provoke existing processes to change and
service delivery to improve
• Each workflow will evolve a uniquely
tailored process solution, “fitter” for its
context
• Customer & employee satisfaction will
improve
dja@djaa.com, @djaa_dja
10. 6 Practices for Evolutionary DNA
The Generalized Version
Visualize
Limit Work-in-progress
Manage Flow
Make Policies Explicit
Implement Feedback Loops
Improve Collaboratively, Evolve
Experimentally
(using models & the scientific method)
dja@djaa.com, @djaa_dja
11. What is a kanban system?
dja@djaa.com, @djaa_dja
12. A Kanban Systems consists of
“kanban” signal cards in
circulation
dja@djaa.com, @djaa_dja
16. Discard rates are often high
Pool
of
Ideas
Engineering
Ready
5
Development
Test
Ready
Testing
UAT
3
5
3
∞
Ongoing
Done
The discard rate with XIT was 48%.
~50% is commonly observed.
Change
Requests
F F
F
F
G
Reject
Deferring commitment and
Options have value because the
avoiding interrupting
future is
Dworkersuncertain
for estimates
E
0%makes rate implies there is
discard sense when discard
no uncertainty about the future
rates are high!
PTCs
I
Discarded
I
dja@djaa.com, @djaa_dja
Deployment
Ready
∞
17. Replenishment Frequency
Pool
of
Ideas
Engineering
Ready
5
Replenishment
Change
Requests
Pull
F F
F
F F
F
F
Development
Test
Ready
Testing
UAT
3
5
3
∞
Ongoing
Done
Frequent replenishment is
more agile.
On-demand replenishment is
D
most agile!
G
PTCs
Discarded
I
dja@djaa.com, @djaa_dja
E
The frequency of system
replenishment should reflect
arrival rate of new
information and the
transaction & coordination
I
costs of holding a meeting
Deployment
Ready
∞
18. Delivery Frequency
Pool
of
Ideas
Change
Requests
Pull
F F
F
F F
F
F
Engineering
Ready
Development
Test
Ready
Testing
UAT
3
5
3
∞
Ongoing
Done
Frequent deployment is
more agile.
5
Deployment buffer size can
On-demand deployment
reduce as frequency of
D deliveryagile!
most increases
G
PTCs
Discarded
I
dja@djaa.com, @djaa_dja
is
E
The frequency of delivery
should reflect the transaction
& coordination costs of
deployment plus costs &
toleranceI of customer to take
delivery
Deployment
Ready
∞
Delivery
19. Specific delivery commitment may be
deferred even later
DeployEnginPool
of
Ideas
eering
Ready
5
Development
Test
Ready
Testing
UAT
3
5
3
∞
Ongoing
Done
ment
Ready
∞
Change
Requests
Pull
F F
F
F F
F
F
D
G
E
PTCs
We are now committing to a
specific deployment and
delivery date
Discarded
*This may happen earlier if
I
circumstances demand it
I
dja@djaa.com, @djaa_dja
2nd
Commitment
point*
20. Defining Kanban System Lead Time
Pool
of
Ideas
Engineering
Ready
5
Deployment
Ready
∞
The clockTest
starts ticking when
UAT
we
customers
Ready
Development accept the Testing
is
5
∞
3 order, not when it 3 placed!
Ongoing
Done
Until then customer orders are
merely available options
Change
Requests
Pull
F F
F
F F
F
F
D
G
E
System Lead Time
PTCs
I
Discarded
I
dja@djaa.com, @djaa_dja
Lead time
ends when
the item
reaches the
first ∞
queue.
21. Little’s Law & Cumulative Flow
Delivery Rate
Pool
of
Ideas
=
Lead Time
Avg. Lead Time
WIP
dja@djaa.com, @djaa_dja
WIP
Ready
To
Deploy
Avg. Delivery Rate
22. Flow the
Efficiency
Flow efficiency measures
Pool
Enginpercentage of total lead time
of spent actually adding value
eering
is
Development
Ideas
Ready
(or knowledge) versus waiting
3
Ongoing
2
Done
Testing
3
Verification Acceptance
Deployment
Ready
∞
Until then customer orders are
merely available options
Flow efficiency = Work Time
Multitasking means time spent
E in working columns is often
waiting time
PB
GY
DE
Waiting Working
MN
AB
Waiting
Working
Waiting
Lead Time
* Zsolt Fabok, Lean Agile Scotland, Sep 2012, Lean Kanban France, Oct 2012
dja@djaa.com, @djaa_dja
x 100%
Lead Time
Flow efficiencies of 2% have been
F
reported*. 5% -> 15% D normal, P1
is
>
40% is good!
G
I
Done
23. Observe Lead Time Distribution as an enabler
of a Probabilistic Approach to Management
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
This is multi-modal data!
Mean of 31
days
The workexpectation of
SLA is of two types:
Change Requests (new
105 and Production
features);days with 98 %
Defects
SLA expectation of
44 days with 85% on-time
dja@djaa.com, @djaa_dja
on-time
24. Mean
5 days
Change Requests
Production Defects
Filter Lead Time data by Type of Work (and
Class of Service) to get Single Mode
Distributions
98% at
25 days
85% at
10 days
dja@djaa.com, @djaa_dja
98% at
150 days
Mean
50 days
85% at
60 days
25. Allocate Capacity to Types of Work
Pool
of
Ideas
Engineering
Ready
Ongoing
2
Change
Requests
Development
4
3
Done
Testing
3
Verification Acceptance
Consistent capacity allocation
E
some consistency to
should bring more consistency to
MN
delivery rate of work of each
D
AB
type
F
Lead Time
PB
DE
Productio
n
Defects
I
Deployment
Ready
3
G
P1
GY
dja@djaa.com, @djaa_dja
Separate understanding of
Separate understanding of Lead
Lead Time for each type of
Time for each type of work
work
Lead Time
∞
Done
26. Infinite Queues Decouple Systems
Pool
Enginof
eering
The infinite queue Development
decouples
Ideas
Ready
the systems. The deployment
3 Done
Ongoing
system uses batches and is
2
separate from the kanban
system
F
The 2nd commitment is
actually a commitment for
PB
the downstream deployment
system
DE
Deployment
Ready
Testing
3
Verification Acceptance
D
∞
MN
G
P1
E
AB
The Kanban System gives us
confidence to make that
I
downstream commitment
GY
2nd Commitment point
dja@djaa.com, @djaa_dja
Done
29. Defining Customer Lead Time
Pool
of
Ideas
Engineering
Ready
Development
Test
Ready
Testing
UAT
3
5
3
∞
Ongoing
5
Change
Requests
Done
The clock still starts ticking
when we accept the customers
order, not when it is placed!
Deployment
Ready
∞
Pull
F F
F
F F
F
F
D
G
E
Customer Lead Time
PTCs
Discarded
I
dja@djaa.com, @djaa_dja
The frequency of delivery
cadence will affect customer
I
lead time in addition to system
capability
Done
∞
30. impact
The Optimal Time to Start
If we start too early, we forgo
the option and opportunity to do
something else that may provide
value.
If we start too late we risk
Ideal Start
incurring the cost of delay
When we
need it
Here
With a 6 in 7 chance of on-time
delivery, we can always expedite
to insure on-time delivery
85th
percentile
Commitment point
dja@djaa.com, @djaa_dja
31. Metrics for Kanban Systems
Cumulative flow integrates
demand, WIP, approx. avg. lead time and
delivery rate capabilities
Lead time histograms show us actual
lead time capability
Flow efficiency, value versus failure
demand (rework), initial quality, and
impact of blocking issues are also
useful
dja@djaa.com, @djaa_dja
32. Implementing a Virtual Kanban System
Do not copy an existing (virtual) kanban
system!
Each system must be designed from 1st
principles using the system thinking
approach to implementing kanban
A study of demand including business
risks & capability is essential to design
an appropriate (virtual) kanban system
for any given knowledge work service
dja@djaa.com, @djaa_dja
33. Reminder…
The Kanban Method is not….
A project management or software
development lifecycle process
Nor, does it encourage a processcentric approach to improvement!
You must “kanbanize” your existing
processes and workflows!
dja@djaa.com, @djaa_dja
35. Feedback Loops
The Kanban Kata
Operations
Review
Improvement
Kata
Standup
Meeting
dja@djaa.com, @djaa_dja
36. Standup Meeting
Disciplined conduct
and acts of leadership
lead to improvement
opportunities
Improvement
discussions & process
evolution happen at
after meetings
dja@djaa.com, @djaa_dja
37. Improvement Kata
A mentor-mentee relationship
Usually (but not always) between a superior and a sub-ordinate
A focused discussion about system capability
Definition of target conditions or desired outcomes
Agreement upon counter-measures – actions taken to improve
capability – resulting in process evolution
dja@djaa.com, @djaa_dja
38. Operations Review
Monthly meeting
Disciplined review of
demand and capability
for each kanban system
Provides system of
systems view and
understanding
Kanban system design
changes & process
evolution suggested by
attendees
dja@djaa.com, @djaa_dja
39. 6 Practices for Evolutionary DNA
The More Specific Version
Visualize work, workflow & business
risks
(using large physical or electronic boards in communal
spaces)
Implement Virtual Kanban Systems
Manage Flow
Make Policies Explicit
Implement Kanban Kata
Educate your workforce to enable
collaborative evolution of policies & ways of
working
dja@djaa.com, @djaa_dja
44. Scaling Kanban
Each Kanban System is designed from
first principles around a specific
service
Scale out in a service-oriented fashion
Do not attempt to design a grand
solution at enterprise scale
The Kanban Kata are essential!
Allow a better system of systems to
emerge over time. Let evolution work!
dja@djaa.com, @djaa_dja
45. Scaling up and down
(big projects, portfolios & personal work)
dja@djaa.com, @djaa_dja
47. Collaboration Benefits
Shared language for improved
collaboration
Shared understanding of dynamics of
flow
Emotional engagement through
visualization and tactile nature of boards
Greater empowerment (without loss of
control)
dja@djaa.com, @djaa_dja
48. Tangible Business Benefits
Improved predictability of lead time and
delivery rate
Reduced rework
Improved risk management
Improved agility
Improved governance
dja@djaa.com, @djaa_dja
49. Organizational Benefits
Improved trust and organizational social
capital
Improved organizational maturity
Emergence of systems thinking
Management focused on system capability
through policy definition
Organizational Adaptability
(to shifts in demand and business risks under management)
dja@djaa.com, @djaa_dja
50. Change Management Benefits
Significantly reduced resistance to change
Processes uniquely tailored to business
environment and risk under management
Evolutionary changes reduce impact
during change and lower risk of failure
Change led from the middle and enacted
by the workforce. Reduced need for
coaching and process specialists
dja@djaa.com, @djaa_dja
51. Kanban Improves Agility
• Lead times gradually reduce
• Predictability of delivery gradually improves
• Organizational social capital improves
• Governance, risk management are improved
• Empowerment without loss of control
• Improves are often dramatic!
• 700% increase in delivery rate at BBC
• On-time delivery often greater than 90%
• Delivery times often reduced by up to 90%
dja@djaa.com, @djaa_dja
52. Learn More
http://leankanbanuniversity.com
• For best results, work with an accredited trainer (AKT) or
credentialed Kanban Coaching Professional (KCP)
http://www.leankanban.com
• Part of a global conference series promoting Kanban
and related concepts for improved business performance
dja@djaa.com, @djaa_dja
54. About
David Anderson is a thought
leader in managing effective
software teams. He leads a
consulting, training and
publishing and event planning
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 the pioneer of the Kanban Method an agile and
evolutionary approach to change. His latest
book, published in June 2012, is, Lessons in Agile Management
– On the Road to Kanban.
David is a founder of the Lean-Kanban University Inc., a
business dedicated to assuring quality of training in Lean
and Kanban for knowledge workers throughout the world.
dja@djaa.com, @djaa_dja
55. Acknowledgements
Hakan Forss of Avega Group in Stockholm has been instrumental in
defining the Kanban Kata and evangelizing its importance as part of a
Kaizen culture.
Real options & the optimal exercise point as an improvement over
“last responsible moment” emerged from discussions with Chris
Matts, Olav Maassen and Julian Everett around 2009.
The inherent need for evolutionary capability that enables
organizational adaptation was inspired by the work of Dave
Snowden.
dja@djaa.com, @djaa_dja