International Supply Case
Study
BMW
Outline
• BMW- The company
• Build-to-Order & BMW
• BMW Spartanburg Plant
– Products
– Sourcing
– Capacity
• Managing Supply
BMW History
• Founded in 1917
• Built engines for military aircraft
• 1940’s WW2: repairs, manufactured spare parts,
agricultural equipment and bicycles
• 1950’s build motorcycles
• Then the cars…
• 1970’s: South Africa Plant
• 1992: US Plant
• 1994: Purchased Rover group (Rover, Land Rover,
Mini, MG)
• 1998: Rolls Royce (2003)
• 2000: Sold Rover except Mini
BMW Business Interests
• Automobiles
– BMW
– Mini
– Rolls Royce
• Motorcycles
• Financial services
BMW
• “The BMW Group is the only
manufacturer of automobiles and
motorcycles worldwide that concentrates
entirely on premium standards and
outstanding quality for all its brands and
across all relevant segments.”
• Premium sector of the international
automobile market
BMW Group.
Brands and Models.
1 Series
3 Series
5 Series
7 Series
X5
6
Series
X3
Z4
Motorcycles
Source: Goudiano CSCMP 2005
BMW Group Development
and Production Network
Berlin
Oxford
Leipzig
Spartanburg
Goodwood
Regensburg
Munich
Graz
Z8
Dingolfing
(external production)
Rosslyn
Source: Goudiano CSCMP 2005
Shenyang
Production Volume
Total: 1119.1
Production Volume
Ford’s Worldwide vehicle unit sales of
cars and trucks in 2004 (in thousands):
The Americas
Ford Europe and PAG
Ford Asia Pacific and Africa
Total
3,915
2,476
407
6,798
Challenges
• Excess capacity => Price pressures
• Customer expectations
– Personalization
– Innovation
– Service
• Cost effective factories with flexible
manufacturing abilities
• New technologies and material
• Regulations
• ….
Build to Order
• Convert orders to products
• No finished goods inventory
• “Build-to-Order is the capability to
quickly build standard or masscustomized products upon receipt of
spontaneous orders without forecasts,
inventory, or purchasing delays.” (D.M.
Anderson)
• Demand pulls production
• WHY BTO?
Why BTO?
• LEAN!!!
• 'Lean production is aimed at the elimination of
waste in every area of production including
customer relations, product design, supplier
networks and factory management. Its goal is
to incorporate less human effort, less
inventory, less time to develop products, and
less space to become highly responsive to
customer demand while producing top quality
products in the most efficient and economical
manner possible.'
Why BTO?
• Other Alternatives
– Build to Stock/Forecast
• Assign to dealers
• Sell from available stock
Built-to-Order vs. Built-toForecast
Built-to-Forecast
Sale from stock
Production
Storage Customer
Built-to-Order
Customized vehicle
Customer Production Customer
– higher level of customer satisfaction due to personalization
– better inventory management
– less sales incentives
Increasing Product Complexity
• Product variety & Part complexity
– 1032 possible combinations of products at BMW
– 1017 possible combinations of BMW 7 series
– ~70 million configurations of the Ford Escape
– >240 configurations of Toyota Scion
Ford Escape
•
•
•
•
•
•
•
•
•
•
•
•
5 models (XLS manual, XLS automatic, XLT automatic, XLT sport, Limited automatic)
2 drive options (Front-wheel drive or four-wheel drive)
2 engine sizes (2.3L or 3.0L)
9 exterior color options (Dark Shadow Grey, Titanium Green, Redfire, Blazing Copper,
Sonic Blue, Dark Stone, Black, Silver, Oxford White)
3 interior colors (Black, Flint, Pebble)
2 transmission options (4-speed, 5-speed)
4 wheel options (15” aluminum, 15” styled, 16” aluminum, 16” Bright Machined aluminum
2 choices of tires (BSW or OWL)
4 options of electronics (AM/FM Single CD with clock, AM/FM 6-CD, AM/FM Single-CD
Cassette, Audiophile 6-CD)
4 options of seats (Cloth, Premium cloth, leather trimmed, premium leather)
5 special package options (Cargo convenience, convenience, leather comfort, safety,
towing) representing 32 different possibilities
4 different upgrades (Spare tire, moon roof, roof rack and side step) representing 16
further options.
These options lead to 70 million ~ 5x2x2x9x3x2x4x2x4x4x32x16
BMW 7 Series
350 Model
Versions
500 Extra
Equipment Options
175 Interior
Equipment Options
90 Standard
Exterior Colors
... leading to e.g. 1017 theoretical combinations
only for the BMW 7 Series
Source: Goudiano CSCMP 2005
Product Complexity
• A finite set of part numbers
• “Infinitely” many end products
BTO & Product Complexity
• BTO makes it possible to
– Address tremendous product variety
– Face the challenges of managing the
variability in component demand.
Savings through BTO
• In the U.S.
• Potential savings through BTO~ $1500/car*
• Average incentives per car sold ~$1900 in
2002*
*Miemczyk and Holweg J. Bus. Logistics, 2004
Obstacles/ Requirements
• Inability to supply customized vehicles
within “acceptable” timeframes
– Avg. Leadtime for customized vehicles: 610 weeks!!!
•
•
•
•
Short OTD
Process/Product/Volume flexibility
Flexibility from suppliers
Flexibility from logistics operators
Current BTO Levels
1999:
•
•
•
•
Avg. New
Vehicle stock in
days
U.S.:
~ 5% 60-90 days
U.K.:
~33%
64 days
Europe:
~48%
55 days
Japan (Toyota): ~60%
20 days
Source: Miemczyk and Holweg (2004)
% BTO
BTO & BMW
•
•
•
•
BMW
BMW’s operations in SC Plant
BMW’s challenges in BTO
Available levers for control
BMW USA
BMW USA
• Z4
• X5
BMW
• “Every customer receives his/her
personalized vehicle at a compulsory
date – at best at his/her preferred date”
– 100% delivery punctuality
– Flexibility for order change
Why offer
flexibility?
Flexibility
Equipment changes in % (accumulated)
2,5
Navigation systems
2,0
Xenon lights
Comfort seat
adjustable electronically
1,5
1,0
%
0,5
Independent vehicle
heater
0,0
-0,5
-1,0
30
20
10
days before order freeze
Source: Goudiano CSCMP 2005
0
BMW USA
• ~140,000 vehicles in 2004.
• KOVP (Customer-oriented production and
sales)
• Over 6000 part numbers for X5
• 70% are option driven
• Flexibility for order change
• 40% of parts from Europe
KOVP
Ordering
Optimize
the whole
process
Production
System
Sales
System
Dealer
Dealer orderPurchasingLogistics ProductionDistributionHand-over
Sales Processes and
Sales Processes and
Online Ordering
Online Ordering
Productionand SupplyProcesses
Distribution Process
and Hand-over
Process Monitoring and Target Control
Delivery
Sales
System
Planning
Dealer
KOVP
The Push-Pull Interface
Production System before KOVP
Early
Order Assignment
Start Order Assignment
Bodyshell work
Sort
Sort
Paint shop
Assembly
Production System with KOVP
Push
Frozen
Horizon
Sort
Late Pull
Order Assignment
Start order assignment
OSM
Bodyshell work
Paint shop
Assembly
Reduction of Leadtime
Flexibility for Order Change
Ordering/Scheduling
Before KOVP:
Production/Distribution
Process Feasibility
Order freeze
13-17 WD
28-32
WD
15 WD
Hand-over to
Sales
Breakthrough target KOVP :
Supplier /
Body shell
work and
Paint shop
1
4 WD
Assem
-bly
Distribution
2 WD
3 WD
Change flexibility till 6 WD
10 WD
BMW USA
• ~140,000 vehicles in 2004.
• KOVP (Customer-oriented production and
sales)
• Over 6000 part numbers for X5
• 70% are option driven
• Flexibility for order change
• 40% of parts from Europe
Sourcing
• Why source from Europe
– Relationship with suppliers
– Tooling is already there
– Social responsibility issues
Why serve global markets?
• Tooling
• Volume
• …
BMW Sourcing
Wackersdorf
•Receive, Sort, Package
•Handles >14,000 part numbers from other BMW plants and over 500 European suppliers.
•Receives ~ 160 truckloads of parts per day
•Ships ~ 75- 80 containers per day to the BMW assembly plants in Rosslyn, South Africa, Spartanburg,
South Carolina and Shenyang, China.
BMW: Capacity
• Capacity is a major investment
• Labor is highly skilled/ organized
• Production set at “takt time”
– “A vehicle every 50 seconds”
• Capacity adjustments through
adjustments to takt time,
adding/reducing shifts, shutdowns…
•
Same number of cars/day
Manage Capacity
• From day to day
– Mix of vehicles vary
– Usage of parts vary
Manage Capacity
• Mix of vehicles
Seasonality
Source: Goudiano CSCMP 2005
Capacity oriented
Production planning
Manage Supply
•
•
•
•
Over 6000 part numbers
70 % option driven
Order changes
40% from Europe
Usage
Standard
Deviation in
Usage 18/day
90
Average
Usage 32/day
Daily Usage
60
30
106
101
96
91
86
81
76
71
66
61
56
51
46
41
36
31
26
21
16
11
6
1
0
Day
SAME NUMBER OF CARS/DAY
Managing Supply
Forecast
Decide Shipment
Quantities
Prepare
Shipments
Shipments
Arrive
Demand
Demand
Demand
Demand
Day 1
Day 10
Day 40
Challenge
• Huge number of parts: Complexity
• Order Flexibility: Variability
• Long LeadTimes: Variability
Levers for managing uncertainty
• Capacity
– Capacity on Supply
– Production Capacity
Infinite
Constant
• Inventory
• Time
– Order due date
Given/Strict
Manage Inventory
• “Infinitely” many end products from
finite number of parts
• Stochastic demand
• Variable long leadtimes
• No shortages allowed:
– Production in a predetermined sequence
– Expedite
Demand Modeling
• Infinitely many end products
• Not enough data points to estimate
distribution of product demand
• Instead: Components
Challenge
•
•
•
•
Huge number of parts: Complexity
Order Flexibility: Variability
Long LeadTimes: Variability
No shortages allowed
Some Tools & Mechanisms
•
•
•
•
•
Safety Stock
Forecast Accuracy
Frequency
Global Supply process
…
Safety Stock
• Protection against variability
–
–
–
–
Variability in demand and
Variability in lead time
Typically described as days of supply
Should be described as standard deviations
in lead time demand
Traditional basics
Order-up-to level
Stock on hand
Reorder Point
Reorder Point
Actual Lead
Time Demand
Actual Lead
Time Demand
Actual Lead
Time Demand
Actual Lead
Time Demand
Order Quantity
Lead
Time
Order
placed
Time
T
L
Safety Stock Basics
• Lead time demand N(m, s)
• Safety stock levels
– Choose z from N(0,1) to get correct
probability that lead time demand exceeds z,
– Safety stock is zs
Safety Stock in Periodic Review
• Probability of stock out is the probability demand
in T+L exceed the order up to level, S
• Set a time unit, e.g., days
• T = Time between orders (fixed)
• L = Lead time, mean E[L], std dev sL
• Demand per time unit has mean D, std dev sD
• Assume demands in different periods are
independent
• Let sD denote the standard deviation in demand
per unit time
• Let sL denote the standard deviation in the lead
time.
Only Variability in Demand
• If Lead Times are reliable
– Average Lead Time Demand
(T+L) * D
– Standard Deviation in lead time demand
(T+L)sD
Lead Time Variability
If Lead Times are variable
• D = Average (daily) demand
• sD = Std. Dev. in (daily) demand
• L = Average lead time (days)
• sL = Std. Dev. in lead time (days)
• Average lead time demand
D(T+E[L])
• Std. Dev. in lead time demand
(T+E[L])s2D + D2 s2L
• Remember: Std. Dev. in lead time demand
drives safety stock
Levers to Pull
• Std. dev in lead time demand
s=(T+E[L])s2D + D2 s2L
Reduce
Time
between
orders
Reduce
Lead
Time
Reduce
Variability in
Demand
Reduce
Variability in
Lead Time
Safety Stock
• Protection against variability
–
–
–
–
•
Variability in demand and
Variability in lead time
Typically described as days of supply
Should be described as standard deviations in lead
time demand
Example: BMW safety stock
– For axles only protects against lead time variability
– For option parts protects against usage variability too