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Presents
PresenterDavid J. Anderson
Modern Management Methods
San FranciscoMay 2014
Release 1.1
Making Better Decisionsunderstanding “fitness for purpose”,matching capability to strategy & objectives
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Blizzard Skis
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Mittersil, Austria
Blizzard Factory
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Blizzard is the largest private sector employer in the Pengau Alps region of Salzburgerland,
AustriaMittersil is a factory town with over 400 people relying on the
factory either directly or indirectly for employment
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• Innovator• Award winner
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In 2007, Blizzard, effectively bankrupt, faced closure from
parent company, Tecnica in ItalyToday Blizzard is the most effective & efficient ski
manufacturer in the world!
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What went wrong at Blizzard, a proud & leading brand in alpine
ski equipment?And what enabled a remarkable turnaround, from the brink of
extinction to a return to innovation & profitability?
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Orders & Deliveries of Skis
2006 winterskis delivered
to dealers
Timeline for manufacturing, delivery and order placement for ski industry in northern hemisphere prior to 2007
timeNov Dec Jan2006
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan2007
Feb Mar Apr
Start manufacturing
2007 skis
2007 winterskis delivered
to dealers
Start manufacturing
2008 skis
Ordersplaced for 2007 winter
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2006 was a warm winter and poor snow conditions badly affected
the ski industry as people stayed home and didn’t buy new
equipment
Blizzard dealers were left holding a lot of 2006 inventory that they
would hold & later discount during the 2007 winter
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Effects of climate change in the Alps
Glacier recession is
clearly visible
1912 1933
2003
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2007 was also a warm winter as climate change began to seriously
affect the AlpsGun shy from 2 bad winters,
Blizzard dealers delayed commitment on 2008 orders until
May after the ski season had finished
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In 2006 business risks appear to be low
2006 winterskis delivered
to dealers
Changing climate conditions and its affect on ski dealers dramatically shifts the risk profile of ski manufacturing
timeNov Dec Jan2006
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan2007
Feb Mar Apr
Start manufacturing
2007 skis
2007 winterskis delivered
to dealers
Start manufacturing
2008 skis
Ordersplaced for 2007 winter
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Previously lead time for delivery is 12 months
2006 winterskis delivered
to dealers
Traditionally manufacturers have had a full year to make the skis for the following winter
timeNov Dec Jan2006
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan2007
Feb Mar Apr
Start manufacturing
2007 skis
2007 winterskis delivered
to dealers
Start manufacturing
2008 skis
Ordersplaced for 2007 winter Lead Time
to manufacture2007 deliveries
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By 2007 the risk profile has changed dramatically
2006 winterskis delivered
to dealers
Dealers still holding 2006 & 2007 inventory decide to wait until the end of the 2007 season to place reduced orders for 2008
timeNov Dec Jan2006
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan2007
Feb Mar Apr
Start manufacturing
2007 skis
2007 winterskis delivered
to dealers
Start manufacturing
2008 skis
Ordersplaced for 2007 winter
Ordersplaced for2008 winter
Volume is low due to over-stocking of older models
The period of speculative manufacturing grows from 2
months to 6 months
Time period of building to
forecast rather than against
customer orders
Blizzard fail to anticipate falling demand and over-produce 2008
skis. Bankruptcy is a serious possibility!
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Tecnica Group & Blizzard managers turn to their business school education and seek to cut
costs by consolidation & centralization
Centralizing all order processing through Tecnica HQ adds 1 month
to order times, increasing speculative build-to-forecast. As a
result costs go up!
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Cutting costs will not make Blizzard “fit for purpose” !!!
What is required to be “fit for purpose” in a period of climate
change, is to defer manufacturing until firm orders are placed!
Blizzard need to cut the lead time to build skis!
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By 2010 the market has a new equilibrium
2010 winterskis delivered
to dealers
Traditionally manufacturers have had a full year to make the skis for the following winter
timeNov Dec Jan2010
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan2011
Feb Mar Apr
Start manufacturing
2011 skis
2011 winterskis delivered
to dealers
Start manufacturing 2012 skis
Ordersplaced for 2011 winter
Ordersplaced for2012 winter
Volume is low due to over-stocking of older models
Lead Timeto manufacture2011 deliveries
Lead time to manufacture skis to order is now 6 months. No speculative build-to-forecast
To have a viable business Blizzard need a capability to make skis
twice as fast as before!
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In 2010 a Lean initiative was started in the factory. This was followed later with a Kanban
initiative in IT and Quality Assurance
Blizzard becomes the first Lean ski manufacturer in the world!
CIO, Eric-Jan Kaak wins Austrian CIO of the Year 2013
and is promoted within Tecnica Group
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Meanwhile, Major Ski Resorts Deploy Snow Cannon to Reduce Risk for Warm Winters
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Lesson 1
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Blizzard initially made a bad decision because they didn’t
understand the dynamics of their external environment
Once they realized that only manufacturing skis faster &
deferred commitment would make them “fit for purpose” did they
focus improvement efforts where they could be most effective
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Understanding“fitness for purpose”
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What makes a pizza delivery service“fit for purpose” ?
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Meet Neeta - a project manager• Delivery time =
approximately 1 hour• Non-functional quality =
tasty & hot• Functional quality (order accuracy) =
doesn’t matter if small mistakes are made, geeks will eat any flavor of pizza
• Predictability =+/- 30 minutes is acceptable
• Safety =so long as health & safety in food preparation is good, it’s fine
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Neeta is also a working mom!
• Delivery time =20 minutes
• Non-functional quality =doesn’t matter too much, it’s pizza!!!
• Functional quality (order accuracy) =it must be cheese pizza! No other flavor is acceptable! (even if you take the pepperoni off)
• Predictability =+/- 5 minutes maximum!!!
• Safety =only mommy worries about that stuff!
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Lesson 2
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To be “fit for purpose” there is a product component & a
service delivery componentWe need to offer a selection of
different recipes which are tasty & popular. However, we must also
deliver with speed & predictability
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Modern creative & knowledge worker businesses often
obsess with product definition & strategy
Operational excellence and service delivery excellence are often overlooked or treated as
inferior management skills
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Lesson 3
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Neeta has 2 identities –Mother and Project ManagerEach of Neeta’s identities
represents a different market segment for the pizza delivery
service
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We need a different set of thresholds for our fitness criteria for each market
segment
Our business needs the ability to “sense” changing customer tastes. As time goes by the
criteria & thresholds for a given market segment may change
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Our pizza delivery service can be “fitter for purpose”
by offering different classes of service for each market
segmentBut, do we have the capability to
deliver on customer expectations?
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Understanding & improving service delivery capability with Kanban
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TestReady
FF
FFF
F F
Commitment Frequency
H
E
C A
I
G
D
Replenishment
Discarded
I
Pull
IdeasDev
Ready
5Ongoing
Development Testing
Done3 35
UATReleaseReady
∞ ∞
The frequency of system replenishment should reflect
arrival rate of new information and the transaction &
coordination costs of holding a meeting
Frequent replenishment & commitment is more
agile.
On-demand commitment is most agile!
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TestReady
FF
FFF
F F
Defining Kanban System Lead Time
H
E
C A
I
G
D
Pull
System Lead Time
Discarded
I
IdeasDev
Ready
5Ongoing
Development Testing
Done3 35
UATReleaseReady
∞ ∞
The clock starts ticking when we accept the customers order, not
when it is placed!
Until then customer orders are merely available options
Kanban system lead time ends when the
item reaches
the first ∞ queue
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TestReady
FF
FFF
F F
Delivery Frequency
H
E
C A
I
G
D
Delivery
Discarded
I
Pull
The frequency of delivery should reflect the transaction &
coordination costs of deployment plus costs &
tolerance of customer to take delivery
IdeasDev
Ready
5Ongoing
Development Testing
Done3 35
UATReleaseReady
∞ ∞
Frequent delivery is more agile.
On-demand delivery is most agile!
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Service Delivery Agility
Service Agility
Commitment frequencyLead TimeDelivery
Frequency Lead T
ime
Short
Long
Deliv
ery
Service Agility
Com
mit
ment
Frequent
Seldom
Frequent
Seldom
MoreAgile
LessAgile
Kanban system dynamics
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UnderstandingCost of Delay Risk
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Data from Corbis, Seattle, April 2007
Lead times for IT system software change requests deployed during April 2007
Lead Time Distribution
0
0.5
1
1.5
2
2.5
3
3.5
Days
CR
s &
Bu
gs
This is multi-modal data!
The work is of two types: Change Requests (new
features); and Production Defects
This is multi-modal data!
The work is of two types: Change Requests (new
features); and Production Defects
Lead Time Histogram
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85% at10 days
Mean5 days
98% at25 days
Change R
equest
s
Pro
duct
ion D
efe
cts
85% at60 days
Mean 50 days
98% at150 days
Mode
Median 45 days
Filter by Type or Class to get Single Modal Data
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Understanding Cost of DelayR
oom
nig
hts
sold
per
day
Actual rooms sold
Cost of delay
Estimated additional rooms sold
When we need it When it arrived
Cost of delay is difference in integral between the two curves
timeJan Feb Mar Apr
First sketch the market payoff function for the total lifetime of the opportunity. In this example, a Spring Break promotion for a hotel chain.
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Cost of Delay for a limited shelf-life opportunity follows an s-curve shape
Cost of delay function for a Spring Break marketing campaign delayed by 1 month from mid-January based on the difference of 2 integrals on previous slide
time
impa
ct
Total costof delay
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When should we start something?
imp
act
When we need it
85th percentile
Ideal StartHere
Commitment point
timeJan10
Nov11
If we start too early, we forgo the option and opportunity to do something else that may
provide value.
If we start too late we risk incurring the cost of delay
If we pull the work into our kanban system on Nov 11 we
have a 6 out of 7 chance of on-time delivery
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We can study sensitivity to different start dates
imp
act
When we need it
50th percentile
Later StartHere
Commitment point
timeJan10
Nov25
If we start as late as November 25 we only have a 50% chance
of on-time delivery
However, the cost of delay incurred if we deliver within 60
days is relatively small. We have an 85% chance of achieving delivery with acceptable cost of delay
85th percentile
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What is the latest we could start?
imp
act
When we need it
0th percentile
Very latestart
Commitment point
timeJan10
Dec19
If we start as late as December 19 we have 0% chance of on-
time delivery
We have about a 10% chance of a total loss delivering the
promotion beyond the expiry date of the opportunity
85th percentile
total loss
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To be certain of delivery without incurring any cost of delay is expensive
imp
act
When we need it
98th percentile
Early Start
Commitment point
timeJan10
Aug11
If we are conservative and do not wish to carry any risk of late delivery or any risk of
incurring an opportunity cost of delay, then we must start as
early as August 13th.
We must commit to our Spring Break 2015 promotion during
Summer 2014!!!
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Lesson 4
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Lead time is perhaps the most important metric we gain from
kanban systemsLead time coupled with cost of
delay sensitivity analysis is a key enabler of deferred commitment and consensus on when to make
commitments
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What if we planned to do a series of marketing
promotions for seasonal opportunities?
Such as, Halloween, Thanksgiving, New Year’s,
Valentine’s,Spring Break, Cinco de Mayo
& 4th of July?
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How many service teams do we need?im
pact
time
HalloweenThanksgiving
New Year’sSpring Break
Cinco de Mayo4th of July
Valentine’s
WIP
= 4
To avoid risk of late delivery altogether, we need a WIP of at
least 4.
If current WIP >= 4 then workers will experience
significant periods of slack and utilization will be low.
Commitments must be made 150 days in advance of deliver and up to 240 days prior to the
event
Additional WIP beyond 4 must be of a lower class of service to insure that these marketing promotions can be delivered
without incurring a cost of delay
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What if we were willing to accept more risk?im
pact
time
HalloweenThanksgiving
New Year’sSpring Break
Cinco de Mayo4th of July
Valentine’s
With a 50% chance of on-time delivery we only need 3 WIP.
We can take on more lower class of service work, or we can
reduce the WIP limit and reduce staffing on the system
by as much as 25%.
Staff will still experience periods of slack if we don’t
introduce lower class of service work
Commitments need only be made 45 days in advance. A 105 day gain from the risk
averse plan
WIP
= 3
If we do reduce the WIP limit and/or adjust staffing we can
expect the lead time distribution to change – hopefully left-shifted
with a shorter tail
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What happens if we have a much more agile organization?If observed lead time capability was significantly shorter and predictability greater, what
benefits do we gain?
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Change R
equest
s
85% at44 days
Mean 33 days
98% at68 days
Median 26 days
Improved Service Delivery CapabilityShorter tail, much more predictable
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Now, how many service teams do we need?im
pact
time
HalloweenThanksgiving
New Year’sSpring Break
Cinco de Mayo4th of July
Valentine’s
To completely avoid risk of late delivery we need a WIP of 3.
If WIP >= 3 when data was collected we have capacity. There will also be slack for lower class of service work
Commitments are needed 70 days in advance.
If we were prepared to reduce demand by just 1 project, WIP
= 2 is sufficientWIP
= 3
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What if we were willing to accept more risk?im
pact
time
HalloweenThanksgiving
New Year’sSpring Break
Cinco de Mayo4th of July
Valentine’s
With a 50% chance of on-time delivery we only need WIP = 2.
Potentially allowing us to reduce staff by 33%.
As a result the lead time distribution will also be left-
shifted further improving agility.
There will still be some slack for lower class of service work.
Commitments need only be made 26 days in advance.
WIP
= 2
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Lesson 5
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We have to conclude that for a reasonably acceptable
economic outcome, we must accept some risk of late
delivery & incurred cost of delay
To guarantee on-time delivery and no lost opportunity cost due to delay, we must have 33-50% more WIP, staff to work it and
accept large amounts of idle time
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Aligning goals with capability
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Go on, you can lift it!
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Kanban system dynamics
Shelf-life(of business opportunities)
Is your service delivery fit for purpose?
Short(days, weeks,
months)
Medium(months,quarters,1-2 years)
Long(years,
decades)
Lead T
ime
Short
Long
Deliv
ery
Service Delivery Agility
Reple
nis
hm
en
t
Frequent
Seldom
Frequent
Seldom
Pre
dic
tabili
ty
High
Low
Is your service delivery
predictability & agility fit enough for
your business strategy?
If you plan to pursue short shelf-life opportunities, you must measure predictability, lead time, replenishment
& delivery frequency as fitness criteria. Does the capability exist to pursue the chosen strategy
effectively?
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Lesson 6
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Improve your capabilities before pursuing market
segments or strategies that require levels of service
delivery beyond your reach
With coaching & incremental development a child can grow to
dead lift a large bar bell. Impatience & over-reaching is
likely to end in tears!
With patience, education and a focus on evolutionary
change, your organization can grow its service delivery
capability
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Conclusions
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1. Understand your external environment before deciding what to change
2. “Fitness for Purpose” has both a product component & a service delivery component
3. Each market segment will have its own fitness criteria and threshold values
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4. Lead time coupled with cost of delay sensitivity analysis is crucial for determining start dates
5. For acceptable economic outcomes we must have a mix of work with different risks and expect some late delivery & incurred cost of delay
6. Improve your capabilities before pursuing market segments or strategies that require service delivery you currently cannot achieve
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Thank you!
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About
David Anderson is a thought leader in managing effective 21st Century businesses that employ creative people who “think for a living” . He leads a training, consulting, publishing and event planning business dedicated to developing, promoting and implementing new management thinking & methods…He has 30 years experience in the high technology industry starting with computer games in the early 1980’s. He has led software teams delivering superior productivity and quality using innovative agile methods at large companies such as Sprint and Motorola.
David is the pioneer of the Kanban Method an agile and evolutionary approach to change. His latest book, published in June 2012, is, Lessons in Agile Management – On the Road to Kanban.
David is a founder of the Lean Kanban Inc., a business dedicated to assuring quality of training in the Lean Kanban Method for managers of those who must “think for a living.”
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I’d like to thank Eric-Jan Kaak and the staff at Blizzard for providing access to produce the story of their Lean transformation.
Software maintenance lead time data courtesy of Corbis.
Acknowledgements
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