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 changeKanban

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

polarizationEvolutionary

Planned

KaizenKaikakuContinuous

Discontinuous Idealistic (true

north)Big

Small

Hypothesis-

driven


To understand the nature of changeUsing 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 timeQualityPredictability…

Search space*Iteration length

Ratio developers-testersCo-located-DistributedSpecialists-Generalists

Estimation….

To understand the effect of changeUsing fitness landscapes

Hill-climbing*

*Representative examples


Opposite ends that meetPlanned and retrospective change

ActionAfter 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 donehow it has to be done

by whomin what timing

Set

standardAction


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)


UnconstrainingRetrospective change

ActionSet

standard

Things to keepThings to improve

What have we learnedWhat still puzzles us

After Action

Review


Reflective observationThe OODA loop

orient

decide

act

observe

Unfolding events

Implicit guidance

Imp

licit g

uid

an

ce

Habits, experiences and dispositions Rational choice


jumps and exploratory walks in the landscape

Planned and retrospective

changeFitness 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 executionDirected change

New target Ideal future statenow

“How” is discovered

“Why” and “What” are defined


Governing constraintBiasing decisions with true north

Res

ou

rce

effi

cien

cy

Flow efficiency

Hig

h

High

Low

Low

True north


The Kanban MethodEvolutionary 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 constraintsWork-in-progress limits

Ideas Ready for

Dev

Development Testing Ready for

UAT

Done

ongoing done5 ∞

Abandoned

53

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 firstStable flow allows hill-climbing

Enabling constraint

Chaotic landscape

Hill-climbing


Constraints mark the transitionsCycle 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

Observations

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 youStay in touch with us!

twitter.com/@PatrickSteyaert [email protected]

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