LKCE16 -Upstream & Customer Kanban by Patrick Steyaert

CUSTOMER KANBAN © Patrick Steyaert, 2016 1

Success
average lead &mes have
dropped from 8 to 2 weeks
all the while reducing failure load
by improving quality
Increased delivery rate
by 40%

Local optimization
Success
Customer Business Delivery

Looking at the whole
UPSTREAM
Improve capability to beMer
meet demand 1
AnPcipate, manage and
shape the demand 2
End-to-end ﬂow from request to delivery!
DOWNSTREAM
3 Collaborate

IMPEDANCE MISMATCH
key challenge
DeliveryDemand
STOCKS
SILOS
TENSION
Flow of outgoing work Flow of incoming work

The Case
1 IT maintenance team
2 Change requests (CR) and small projects
3 Across domains of ERP, Business Intelligence (BI),
Electronic Data Interchange (EDI), ApplicaPon
development (APP)

© Patrick Steyaert, 2016 CUSTOMER KANBAN 7
Incoming versus Outgoing
Change Requests
Customer lead Pme varies between a few days and 30+ weeks.
New CR Closed CR Backlog

Points of dissatisfaction
The customer
Long
customer lead Pmes
No reliable
indicaPon
when a
request will be
fulﬁlled
Large
backlog
Lack of
transparency
Too
much
process

Points of dissatisfaction
The team
Interrupt work, mulP-
tasking
Small
projects
become
suddenly
urgent
Unclear
require-
ments
Late changes
Business not
being
available
Business
not
accepPng
in Pme

UATReady to
start
Analysis Development Test Ready for UAT Ready to deployReady to commitIdea/Request Synthesis Analysis
Kanban board visualization
Upstream
Downstream
Large WIP
(Work-In-Progress)
Blocked items (many because
of dependencies)

UATReady to start Analysis Development Test Ready for UAT Ready to deploy
10 14 5 ∞ ∞∞
System lead Pme
WIP limits
Start what you can
ﬁnish!

Kanban success

System Kanban
Idea /
Request
Ready to
prepare
Ready to
commit
Ready to
start
Ready to
accept
Ready to
deliver Delivery
System Kanban
Upstream
System lead +me
Downstream
Boundary
Boundary
Commitment
point
WIP Limit WIP Limit WIP Limit
Worker Pull
System Kanban Token
FLOW

Limits to success
0
1
2
3
4
5
6
7
8
9
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30+
Frequency of occurrence
Customer lead +me
Customer lead &me
Time between request and fulﬁllment of the request

UATReady to
start
Analysis Development Test Ready for UAT Ready to deploy
10 14 5 ∞ ∞ ∞
System lead Pme
Ready to commitIdea/Request Synthesis Analysis
End-to-end customer lead Pme
Push-pull boundaries
System Kanban boundaries
Upstream
Downstream
… and work piles
up here.
Work piles up
here …

Upstream process
Fragmented,
ambiguous, conﬂic&ng
ideas and requests are
captured
SYNTHESIS ANALYSIS
Ideas and requests are
turned in a shared,
coherent high level
concept
Concept is split in detailed
work items that can be
allocated to teams

Upstream Kanban
Visualization
Ready to commitIdea/Request Synthesis AnalysisReady to
prepare
Small, simple items skip
the synthesis step.

OPTION Selection
analysis
synthesi
s
capture
downstre
am
Commitment
point
selection
selection
ideas
selection
option
s
commitme
nts
Upstream

observations
1 Small, simple items move quickly into
“Ready to commit”
(ogen too early, ﬂooding the inventory)
2 Large, complex items move slowly into
“Ready to commit”
(ogen too late, leading to starva&on or expedi&ng)

Flooding
prepare
Small, simple items are pushed
from “Request” into “Ready to
commit” because of approval
process.

UATReady to
start
10 14 5 ∞ ∞ ∞
System lead Pme
starvation
System Kanban
Upstream
Downstream
… we may end up with
gaps in our upstream
pipeline that lead to
starvaPon later.
But, when all aMenPon goes
to downstream because of
the pressure to deliver …
Team members that
mainly work downstream
are also needed upstream
(and vice versa).

Expediting
prepare
As Pme pressure builds up,
requests are expedited
directly to downstream
without proper preparaPon.

orientation
prepare
Some items only require short
upstream lead &me, and move
too early through upstream
Other items require longer
upstream lead &me, and move
too late through upstream

Triage
We can always pull the item when needed, not much effort
is needed in preparaPon
Green
Will pass selecPon if it is given due aMenPon, Pme and effort
in preparaPon; risk of becoming red otherwise
Yellow
Needs immediate aMenPon; criPcal problem or
opportunity; immediate selecPon for downstream needed
Red
Won’t probably survive the selecPon process regardless of
what effort is put in preparaPon
Black

Order points
prepare >10
>12
>3
Green Yellow
>=1
Minimum opPons
limits act as order
points!
As long as minimum
limits are not met
appropriate acPon
must be taken.

Wait … there is more
0
50
100
150
200
250
Analysis Dev Test UAT R To D Out
Cumul.
IT Maintenance Team - Cumulative Flow Diagram
… and here.
Work piles up
here also…

UATReady to
start
10 14 5 ∞ ∞ ∞
System lead Pme
Upstream – Downstream
collaborationSystem Kanban
Upstream
Downstream
Business users need to be
involved upstream.
They are also needed
downstream.

Customer Kanban
Finish request
Start request

Pushing the boundaries
Idea /
Request
Ready to
prepare
Ready to
commit
Ready to
start
Ready to
accept
Ready to
deliver Delivery
System Kanban
Upstream “Kanban”
Customer Kanban
System lead +me
Customer lead +me
Downstream “Kanban”
Boundary
Boundary
Boundary
Boundary
Customer Pull
CONWIP
Commitment
point
Customer Kanban Token
WIP Limit WIP Limit WIP Limit
Worker Pull
System Kanban Token
FLOW

Pushing the boundaries of
Kanban
Flow of demand with customer pull
Flow unit is requests
Customer Lead Time
CONWIP & Minimal opPons limit
CollaboraPon between customer
and team in co-creaPon
System Kanban
Flow of work with worker pull
Flow unit is work items
System Lead Time
WIP limit
CollaboraPon within team to deliver
and improve service
Customer Kanban
(including Upstream Kanban)

Are we there yet?
System
kanBan

Upstrea
m
kanban

custom
er
kanban

Flow is When value is created for the
customer through meaningful WORK
It is the action, or fact, of moving along in a
steady, continuous stream

Picture: http://s117.photobucket.com/
The image of a snowmobile was oLen used by John Boyd to
illustrate the role of analysis and synthesis in innova&on
Ingenuity

Learning and change
Discovery Kanban
Reflective observation
(OODA)
Hypothesis Active experimentation
(PDCA)ObserveOrient
Abandon
Decid
e
Read
y to
Act
Plan Do Chec
k
Adjust
Observa&ons
5 4 6 5 >5 >6 >3 >8
Hypothesis
Viability
Feasibility
Desirability Abandon Experiments

business agility
Looking
at a part
Looking
at the
whole
Respondi
ng to
change
Driving
change
team network
Conformit
y
Ingenuity

Getting started
Flow needs to be
experienced
Team
flow
Cross team
flow
End-to-
end
flow
And more
hMp://www.okaloa.com/ﬂowlab

Thank you
Download article:
@PatrickSteyaert patrick.steyaert@okaloa.com
bit.ly/CustomerKanbanArPcle
Stay in touch
hMp://www.okaloa.com/ﬂowlab
Find out about Okaloa Flowlab:

LKCE16 -Upstream & Customer Kanban by Patrick Steyaert

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LKCE16 -Upstream & Customer Kanban by Patrick Steyaert