LLKD16 Improvement Kanban

IMPROVEMENT KANBAN© Patrick Steyaert, 2016 1
LONDON APRIL 2016
london Lean kanban day 2016
Improvement
KANBAN

© Patrick Steyaert, 2016 IMPROVEMENT KANBAN 2
A method for change
Kanban
What you see: FLOW
What you don’t see: CHANGE

CHANGE: kanban for change
FLOW: kanban for work
Improvement Kanban
Agree
urgency
Negotiate
change
Verify
performan
ce
Validate
adoption
Ready to
commit
Elaborat
e
ReadyDevelop &
Test

Ambiguity, misconception and
polarization
Evolutionary
Planned
Kaizen
KaikakuContinuous
Discontinuous Idealistic (true
north)
BigSmall
Hypothesis-
driven

To understand the nature of change
Using constraints
Convex
change
Concave
change
Evolutionary
change
Directed
change
Retrospectiv
e change Planned
change
Enabling
constraints
Governing
constraints
Over-
constraining
Un-
constraining

Fitness for purpose*
Delivery time
Quality
Predictability
…
Search space*
Iteration length
Ratio developers-testers
Co-located-Distributed
Specialists-Generalists
Estimation
….
To understand the effect of change
Using fitness landscapes
Hill-climbing*
*Representative examples

Opposite ends that meet
Planned and retrospective change
Action
After Action
Review
Set
standard

By separating the thinking from the doing the
system of work
becomes over-constrained
Planned change
After Action
Review
what needs to be done
how it has to be done
by whom
in what timing
Set
standard
Action

Example – Ford’s Flow productionDeliver the highest possible quality at the lowest possible cost
Flow production based on division of labor,
interchangeable parts and standard work
Planned change – thinking
largely separated from doing
Cost/Benefit, Return on
investment (ROI)

Unconstraining
Retrospective change
Action
Set
standard
Things to keep
Things to improve
What have we learned
What still puzzles us
After Action
Review

Reflective observationThe OODA loop
orient
decide
act
observe
Unfolding
events
Implicit
guidance
Implicit
guidance
Habits, experiences and dispositions Rational choice

jumps and exploratory walks in the landscape
Planned and retrospective
change
Fitness
for purpose
Jumps have a big effect but
it is like teleportation: it is
hard to know upfront what
the landscape will look like.
Jumps

Concave changeCapped expected gain
success
Expected
pain
Expected
gain

CONVEX changeSmall changes accumulate into
*big* outcomes
success
Expected
pain
Expected
gain

Active experimentationThe pdca loop
do
check
adjust
plan
We believe that
<doing this>
Will achieve
<this outcome>
Hypothesis
Experiment
Results
Learning
Model

Example – Toyota’s continuous flowDeliver what the customer wants when the customer wants it
Continuous flow integrating people in teams
and integrating value adding steps in value
streams
A cultivated habit of change based
on active experimentation (PDCA)
True north – e.g. one-piece
flow, zero defects

Align on direction give autonomy to execution
Directed change
New target Ideal future statenow
“How” is discovered
“Why” and “What” are defined

Governing constraint
Biasing decisions with true north
Resourceefficiency
Flow efficiency
High
High
Low
Low
True north

The Kanban Method
Evolutionary change
Start where you
are now
STEP #1
Implement a
safe-to-fail
change
STEP #2
Evaluate fitness
against fitness-
for-purpose
criteria
 if positive reinforce
 if negative roll back
STEP #3

Enabling constraints
Work-in-progress limits
Ideas Ready for
Dev
Development Testing Ready for
UAT
Done
ongoing done
5 ∞
Abandoned
5
3
WIP limits are enabling
constraints.
Work-In-Progress (WIP)
limits enable novel
collaborative behavior.

Enabling constraintsprepare the fitness landscape for hill-climbing
Unstable flow needs to be stabilized first
Stable flow allows hill-climbing
Enabling
constraint
Chaotic landscape
Hill-climbing

Constraints mark the transitions
Cycle of Change
Convex
change
Concave
change
Evolutionary
change
Directed
change
Retrospectiv
e change Planned
change
Enabling
constraints
Governing
constraints
Over-
constraining
Un-
constraining

Change change
Fitness
for purpose
Jump
Hill-climbing
Shift
Towards A more ecological approach

both
A polarity to manage
+ Alignment
+ Synergies
+ Governance
- Conformance
- Cargo cult
- Disengagement
- Resistance to change
+ Fitness-for-purpose
+ Engagement
+ Learning
- Isolation
- Not Invented Here
- Drift

Learning
Reflective
observation
Active
experimentation
ORIENT
DECIDEACTOBSERVE
Implicit
guidance
DOCHECK
ADJUST
PLAN
Feedback
Unfolding
events
Model

DoingExploring and implementing practices
Inbound
Outbound
Create options
for change
Committing to
change

Kanban for learningReflective observation + Active experimentation
Decision making
(OODA)
Hypothesis Learning (PDCA)
ObserveOrient
Abandon
Decid
e
Act Plan Do Chec
k
Adjust
Observation
s
5 4 655 6 88
Hypothesis
AbandonExperiments

Kanban for doingExploring and implementing practices
upstream inventory downstream
suggestionEvaluationconsolidat
ion
Ready
to impl
ready Initiat
e
chan
ge
Guid
e
chan
ge
Validat
e
Adopti
on
Techniques
Practices
Procedures
5 4 65>7 >5 >38
Inventory
Techniques
Practices
Procedures

Improvement
Kanban
Changing the way organizations change
Use constraints to understand
change
Use Kanban for change
Manage polarities
Take a more ecological
approach

Thank you
Stay in touch with us!
twitter.com/@PatrickSteyaert patrick.steyaert@okaloa.com

LLKD16 Improvement Kanban

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