Making Ski Manufacturing Fit for Purpose with Lean Kanban

dja@leankanban.com @lkuceo Copyright Lean Kanban Inc.
Presents
Presenter
David J. Anderson
Stop Starting
Start Finishing
Stockholm
May 2014
Release 1.2
Making Better Decisions
understanding “fitness for purpose”,
matching capability to strategy & objectives

Blizzard Skis

Mittersil, Austria
Blizzard
Factory

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

• Since 1945
• Hand-made by craftsman
• Innovator
• Award winner

In 2007, Blizzard, effectively
bankrupt, faced closure from parent
company, Tecnica in ItalyToday Blizzard is the most
effective & efficient ski
manufacturer in the world!

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?

Orders & Deliveries of Skis
2006 winter
skis delivered
to dealers
Timeline for manufacturing, delivery and order placement for ski
industry in northern hemisphere prior to 2007
timeNov Dec Jan
2006
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan
2007
Feb Mar Apr
Start
manufacturing
2007 skis
2007 winter
skis delivered
to dealers
Start
manufacturing
2008 skis
Orders
placed for
2007 winter

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

2007 was also a warm winter as
climate change began to seriously
affect the Alps
Gun shy from 2 bad winters,
Blizzard dealers delayed
commitment on 2008 orders
until May after the ski season had
finished

In 2006 business risks appear to be low
2006 winter
skis delivered
to dealers
Changing climate conditions and its affect on ski dealers
dramatically shifts the risk profile of ski manufacturing
timeNov Dec Jan
2006
2007
Feb Mar Apr
Start
manufacturing
2007 skis
2007 winter
skis delivered
to dealers
Start
manufacturing
2008 skis
Orders
placed for
2007 winter

Previously lead time for delivery is 12 months
2006 winter
skis delivered
to dealers
Traditionally manufacturers have had a full year to make the skis
for the following winter
timeNov Dec Jan
2006
2007
Feb Mar Apr
Start
manufacturing
2007 skis
2007 winter
skis delivered
to dealers
Start
manufacturing
2008 skis
Orders
placed for
2007 winter Lead Time
to manufacture
2007 deliveries

By 2007 the risk profile has changed dramatically
2006 winter
skis 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 Jan
2006
2007
Feb Mar Apr
Start
manufacturing
2007 skis
2007 winter
skis delivered
to dealers
Start
manufacturing
2008 skis
Orders
placed for
2007 winter
Orders
placed for
2008 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!

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!

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!

By 2010 the market has a new equilibrium
2010 winter
skis delivered
to dealers
Traditionally manufacturers have had a full year to make the skis
for the following winter
timeNov Dec Jan
2010
2011
Feb Mar Apr
Start
manufacturing
2011 skis
2011 winter
skis delivered
to dealers
Start
manufacturing
2012 skis
Orders
placed for
2011 winter
Orders
placed for
2012 winter
Volume is low due
to over-stocking
of older models
Lead Time
to manufacture
2011 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!

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

Lesson 1

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
Ski craftsmen are now “idle” for 6
months per year. They use this time
to improve the factory processes

Understanding
“fitness for purpose”

What makes a pizza delivery service
“fit for purpose” ?
• Fitness criteria are metrics
that measure things
customers value when
selecting a service again &
again
• Delivery time
• Quality
• Predictability
• Safety (or conformance to
regulatory requirements)

Meet Neeta - a project manager
• Neeta’s team are working
late (again)
• Neeta needs to feed them
with pizza
• What attributes do her team
care about in a pizza delivery
service?
• 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

Neeta is also a working mom!
• Neeta gets home late.
Her kids are really
hungry and even
though she shouldn’t
she decides to order
pizza for them
• What makes a pizza
delivery service
acceptable to her kids
age 4, 6, 9 & 11 years?
• 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!

Lesson 2

To be “fit for purpose” there is a
product component & a service
delivery component
We need to offer a selection of
different recipes which are tasty
& popular. However, we must
also deliver with speed &
predictability

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

Lesson 3

Neeta has 2 identities –
Mother and Project Manager
Each of Neeta’s identities
represents a different market
segment for the pizza delivery
service

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

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?

Understanding & improving service
delivery capability with Kanban

Test
Ready
F
F
FF
F
F F
Commitment Frequency
E
I
G
D
Replenishment
Discarded
I
Pull
Ideas
Dev
Ready
5
Ongoing
Development Testing
Done
3 35
UAT
Release
Ready
∞ ∞
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!

Test
Ready
F
F
FF
F
F F
Defining Kanban System Lead Time
E
I
G
D
Pull
System Lead Time
Discarded
I
Ideas
Dev
Ready
5
Ongoing
Development Testing
Done
3 35
UAT
Release
Ready
∞ ∞
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

Test
Ready
F
F
FF
F
F F
Delivery Frequency
E
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
Ideas
Dev
Ready
5
Ongoing
Development Testing
Done
3 35
UAT
Release
Ready
∞ ∞
Frequent delivery is more
agile.
On-demand delivery is most
agile!

Service Delivery Agility
Service Agility
Commitment
frequency
Lead Time
Delivery
Frequency
LeadTime
Short
Long
Delivery
Service Agility
Commitment
Frequent
Seldom
Frequent
Seldom
More
Agile
Less
Agile
Kanban system dynamics

Understanding
Cost of Delay Risk

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
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
106
113
120
127
134
141
148
Days
CRs&Bugs
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

85% at
10 days
Mean
5 days
98% at
25 days
ChangeRequests
ProductionDefects
85% at
60 days
Mean
50 days
98% at
150 days
Mode
Median
45 days
Filter by Type or Class to get Single Modal Data

Understanding Cost of DelayRoomnights
soldperday
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 Easter
promotion for a hotel chain.

Cost of Delay for a limited shelf-life opportunity
follows an s-curve shape
Cost of delay function for a Easter marketing campaign delayed by
1 month from mid-January based on the difference of 2 integrals
on previous slide
time
impact
Total cost
of delay

When should we start something?
impact
When we
need it
85th
percentile
Ideal Start
Here
Commitment point
timeJan
10
Nov
11
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

We can study sensitivity to different start dates
impact
When we
need it
50th percentile
Later Start
Here
Commitment point
timeJan
10
Nov
25
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

What is the latest we could start?
impact
When we
need it
0th percentile
Very late
start
Commitment point
timeJan
10
Dec
19
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

To be certain of delivery without incurring any
cost of delay is expensive
impact
When we
need it
98th
percentile
Early Start
Commitment point
timeJan
10
Aug
11
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!!!

Lesson 4

Lead time is perhaps the most
important metric we gain from
kanban systems
Lead time coupled with cost of
delay sensitivity analysis is a key
enabler of deferred commitment
and consensus on when to make
commitments

What if we planned to do a series
of marketing promotions for
seasonal opportunities?
Such as, Halloween, Lucia, New
Year’s, Valentine’s,
Easter, 1st of May
& Midsummer?

How much WIP do we need?
impact
time
Halloween Lucia
New Year’s Easter
1st of May
Midsummer
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
There is only a 10% chance the
system will have 4 items in-
progress & around 50% chance of
3 items in-progress. So there will
be considerable slack time

Possible Kanban Board Design
Done
F
E
Engin-
eering
Ready
Deploy-
ment
Ready
G
1 ∞
P1
Ongoing
Development Testing
Done Verification Acceptance
2 2
Marketing
Promotions
4
4
Improvements
There is only about a 10% chance that 4
marketing promotions will be in-progress at the
same time. So we hedge the risk of idle time by
doing improvement tickets with a lower cost of
delay and a lower class of service.
Improvement tickets are marked as blocked when
team members are servicing marketing
promotions
L
M
N
D

Halloween Lucia
New Year’s Easter
1st of May
Midsummer
Valentine’s
What if we were willing to accept more risk?
impact
time
With a 50% chance of on-time
delivery it appears we only need 3
WIP.
If we wish to avoid accumulating
additional risk of late delivery then
we actually need a WIP of 4 as a
10% chance exists that 3 things will
be in-progress when we need to start
a 4th
The chance of slack time remains the
same and the board design would be
unchanged.
WIP=3???
Commitments need only be
made 45 days in advance. A
105 day gain from the risk
averse plan
WIP=4

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?

ChangeRequests
85% at
44 days
Mean
33 days
98% at
68 days
Median
26 days
Improved Service Delivery Capability
Shorter tail, much
more predictable

Halloween Lucia
New Year’s Easter
1st of May
Midsummer
Valentine’s
Now, how much WIP do we need?
impact
time
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 sufficient
WIP=3

Halloween Lucia
New Year’s Easter
1st of May
Midsummer
Valentine’s
What if we were willing to accept more risk?
impact
time
With a 50% chance of on-time
delivery we only need WIP = 2 as
there is almost no likelihood of a
3rd thing needing to be started
before an earlier one is finished.
Potentially allowing us to reduce
staff by 33%.
Commitments need only be made
26 days in advance.
WIP=2???
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.

Lesson 5

We can trade sensitivity to
cost of delay for the ability to
decide later
We must understand lead time
distribution to understand how
much WIP we need. This
determines our staffing levels and
carrying costs
A mix of work with lower cost
of delay and class of service is
needed to enable us to start
work at the ideal time with
acceptable risk

Aligning goals with capability

Go on, you can lift it!

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)
LeadTime
Short
Long
Delivery
Service Delivery Agility
Replenishment
Frequent
Seldom
Frequent
Seldom
Predictability
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?

Lesson 6

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

Conclusions

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

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

Thank you!

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.”

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

Making Ski Manufacturing Fit for Purpose with Lean Kanban

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