lascot16 - kanban systems for change

SYSTEMSFORCHANGE©PatrickSteyaert,2016 1

@PatrickSteyaert

Lean Agile Scotland 2016

KANBAN systems for change

SYSTEMSFORCHANGE©PatrickSteyaert,2016 2

ThementalimageofasnowmobileusedbyCol.JohnBoydtoillustratetheroleofanalysisandsynthesisininnova,on.

Picture: http://s117.photobucket.com/

SYSTEMSFORCHANGE©PatrickSteyaert,2016 3

Confusion

ChangeisadynamiccomplexsystemwithmanymovingpartsandinteracPons

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The parts Different types of change

Evolutionary change

Directed change

Retrospective change Planned

change

Convex/ExponenPalConcave/Linear

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The whole

Constraints* and regime changes

Enablingconstraints

Emergentconstraints

Over-constrained

Un-constrained

*InspiredbybothA.Juarrero’sDynamicsinAc9onandE.Goldrath’sTheoryofConstraints

(Individual,nosystem)

(Emergentteam,system)

(“Individual”,rigidrules)

(Team,system)

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Opposite ends that meet Planned and retrospective change

Action After Action

Review Set standard

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By separating the thinking from the doing the system of work becomes over-constrained

Planned change

After Action Review

whatneedstobedonehowithastobedone

bywhominwhatPming

Set standard Action

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Unconstrained Retrospective change

Action Set standard

ThingstokeepThingstoimprove

WhathavewelearnedWhatsPllpuzzlesus

After Action Review

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Creating flow

Inbound

Outbound

IdenPfyingopPonsforchange

(usingmodels,frameworks,

assessments,…)

Deliveringchange(insmall

increments)

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Kanban system for change Planned and retrospective change

upstream inventory downstream suggestion Evaluation consolidation Ready to

impl ready Initiate

change Guide

change Validate Adoption

TechniquesPrac,cesProcedures

5 4 65>7 >5 >38

Inventory

TechniquesPrac,cesProcedures

Storymapping Visual

mngt

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What is (implicitly) expected Convex/exponential change

success

Expectedpain

Expectedgain

Changeaccumulatesinto*big*outcomes

fail

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What is actually happening Concave/linear change

success

Expectedpain

Expectedgain

Outcomesarecappedandchangeini,a,vestendtostall

fail

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Active experimentation The pdca loop and hypothesis-driven change

do

check

adjust

plan

Webelievethat<doingthis>

Willachieve<thisoutcome>

Hypothesis

Experiment

Results

Learning

Model

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Evolutionary change

Start where you are now

STEP #1

Implement a safe-to-fail change

STEP #2

Evaluate fitness against fitness-for-

purpose criteria

Ø  ifposiPvereinforceØ  ifnegaPverollback

STEP #3

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Experimentsneedastablecontexttogivemeaningfulresults.

Context matters

Whenthelevelofcollabora,onislowandtheprocessisunstablethen

experimenta,ondoesnotmakesense.

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Too unstable to experiment in What turns this …

Ideas Ready for Dev Development TesTIng Ready for UAT Done

ongoing done

Abandoned

A user story

A user story

A user story

A user story

A user story

A user story

A user

story A user story

A user story

A user story

A user story

A user story

A user story

A user story A user

story A user story

A user story

A user story

A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

A user story

A user story A user

story A user story

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Into this? Ideas Ready for Dev Development TesTIng Ready for UAT Done

ongoing done

Abandoned

A user story

A user story

A user story

A user story

A user story

A user story

A user

story A user story

A user story

A user story

A user story

A user story

A user story

A user story A user

story A user story

A user story

A user story

A user story

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Kanban Ideas Ready for Dev Development TesTIng Ready for UAT Done

ongoing done 5 ∞

Abandoned

5

3

A user story

A user story

A user story

A user story

A user story

A user story

A user

story A user story

A user story

A user story

A user story

A user story

A user story

A user story A user

story A user story

A user story

A user story

A user story ItisnotaboutvisualizaPon;itisabout

theeffectofWIPlimitsasaconstraintthatenablesnovelbehavior.

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Enabling constraints

Catalyze

Collabora,on

StableChao,c

Individual

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Emerging constraints

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Reflective observation The OODA loop

orient

decide

act

observe

Unfoldingevents

Implicitguidance

Implicit

guidance

Habits,experiencesanddisposiPons RaPonalchoice

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Align on direction give autonomy to execution

Directed change

New target Ideal future state now

“How”isdiscovered

“Why”and“What”aredefined

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Double loop Learning

ReflecPveobservaPon

AcPveexperimentaPon

ORIENT

DECIDE ACT OBSERVE

Implicitguidance

DO CHECK

ADJUST

PLAN

Feedback

Unfoldingevents

Model

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Kanban system for change Reflective observation + Active experimentation

Decision making (OODA) Hypothesis Learning (PDCA) Observe Orient

Abandon

Decide Act Plan Do Check Adjust

Observa,ons

5 4 655 6 88

Hypothesis

AbandonExperiments

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Looking at the whole System of Change

Convexchange

Concavechange

Evolutionary change

Directed change

Retrospective change Planned

change

Enablingconstraints

Emergentconstraints

Over-constraining

Un-constraining

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System of change

Changing the way of change

Planned change is often the starting point – It can mobilize for change

Keep a watch on emergent constraints to realize measurable results

Look for constraints that enable collaboration and experimentation

Retrospective change is your eyes and ears in the organization

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Thank you Stay in touch with us!

twiher.com/@PatrickSteyaert patrick.steyaert@okaloa.com