LAScot16 - Kanban Systems for Change

SYSTEMSFORCHANGE©PatrickSteyaert,2016 1

@PatrickSteyaert

Lean Agile Scotland 2016

KANBAN systems for change


ThementalimageofasnowmobileusedbyCol.JohnBoydtoillustratetheroleofanalysisandsynthesisininnova,on.

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


Confusion

ChangeisadynamiccomplexsystemwithmanymovingpartsandinteracPons

©PatrickSteyaert,2016 SYSTEMSFORCHANGE 4

The parts Different types of change

Evolutionary change

Directed change

Retrospective change Planned

change

Convex/ExponenPalConcave/Linear


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)


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

whatneedstobedonehowithastobedone

bywhominwhatPming

Set standard Action


Unconstrained Retrospective change

Action Set standard

ThingstokeepThingstoimprove

WhathavewelearnedWhatsPllpuzzlesus

After Action Review


Creating flow

Inbound

Outbound

IdenPfyingopPonsforchange

(usingmodels,frameworks,

assessments,…)

Deliveringchange(insmall

increments)


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


What is (implicitly) expected Convex/exponential change

success

Expectedpain

Expectedgain

Changeaccumulatesinto*big*outcomes

fail


What is actually happening Concave/linear change

success

Expectedpain

Expectedgain

Outcomesarecappedandchangeini,a,vestendtostall

fail


Active experimentation The pdca loop and hypothesis-driven change

do

check

adjust

plan

Webelievethat<doingthis>

Willachieve<thisoutcome>

Hypothesis

Experiment

Results

Learning

Model


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


Experimentsneedastablecontexttogivemeaningfulresults.

Context matters

Whenthelevelofcollabora,onislowandtheprocessisunstablethen

experimenta,ondoesnotmakesense.


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


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


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.


Enabling constraints

Catalyze

Collabora,on

StableChao,c

Individual


Emerging constraints


Reflective observation The OODA loop

orient

decide

act

observe

Unfoldingevents

Implicitguidance

Implicit

guidance

Habits,experiencesanddisposiPons RaPonalchoice


Align on direction give autonomy to execution

Directed change

New target Ideal future state now

“How”isdiscovered

“Why”and“What”aredefined


Double loop Learning

ReflecPveobservaPon

AcPveexperimentaPon

ORIENT

DECIDE ACT OBSERVE

Implicitguidance

DO CHECK

ADJUST

PLAN

Feedback

Unfoldingevents

Model


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


Looking at the whole System of Change

Convexchange

Concavechange

Evolutionary change

Directed change

Retrospective change Planned

change

Enablingconstraints

Emergentconstraints

Over-constraining

Un-constraining


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


Thank you Stay in touch with us!

twiher.com/@PatrickSteyaert [email protected]

LAScot16 - Kanban Systems for Change

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