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

Z4

X5

X3

6Series

BMW Group.Brands and Models.

Motorcycles

1 Series 3 Series 5 Series 7 Series

Source: Goudiano CSCMP 2005

BMW Group Development and Production Network

Z8Dingolfing

Munich

Leipzig

Regensburg

Spartanburg

Rosslyn

Graz (external production)

Berlin

Oxford

Goodwood

Shenyang

Source: Goudiano CSCMP 2005

Production Volume

Total: 1119.1

Production Volume

Ford’s Worldwide vehicle unit sales of cars and trucks in 2004 (in thousands):

The Americas 3,915

Ford Europe and PAG 2,476

Ford Asia Pacific and Africa 407

Total 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 mass-customized 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-OrderBuilt-to-Forecast

Sale from stock Customized vehicle

Built-to-Order vs. Built-to-Forecast

– higher level of customer satisfaction due to personalization– better inventory management – less sales incentives

Customer StorageProduction ProductionCustomer Customer

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

... leading to e.g. 1017 theoretical combinations only for the BMW 7 Series

175 InteriorEquipment Options

Source: Goudiano CSCMP 2005

500 Extra Equipment Options

90 Standard Exterior Colors

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:

6-10 weeks!!!

• Short OTD• Process/Product/Volume flexibility• Flexibility from suppliers• Flexibility from logistics operators

Current BTO Levels

1999: % BTO 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 & 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?

0102030-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

2,5

days before order freeze

Comfort seatadjustable electronically

Xenon lights

Independent vehicle heater

Navigation systems

Equipment changes in % (accumulated)

Flexibility

%

Source: Goudiano CSCMP 2005

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

Process Monitoring and Target Control

Distribution Process and Hand-over

Sales Processes andOnline Ordering

Production- Production- and Supply- and Supply- ProcessesProcesses

Dealer SalesSystem

ProductionSystem

SalesSystem

Dealer

Planning

Dealer orderPurchasingLogistics ProductionDistributionHand-over

Ord

erin

g

Del

iver

y

Sales Processes andOnline Ordering

Optimize the whole process

KOVPThe Push-Pull Interface

Production System before KOVP

Start Order AssignmentSort Sort

Early Order Assignment

Bodyshell work Paint shop Assembly

Production System with KOVP

Frozen Horizon

Sort

Late Order Assignment

Start order assignment

OSM

Bodyshell work Paint shop Assembly

Push Pull

Flexibility for Order Change

Reduction of Leadtime

Ordering/Scheduling

Production/Distribution

15 WD 28-32 WD

13-17 WD

Before KOVP: Order freeze

Process Feasibility

Supplier /Body shell work andPaint shop

Change flexibility till 6 WD

Distri-

bution

Assem-bly

Hand-over to Sales

3 WD 10 WD1 2 WD4 WD

Breakthrough target KOVP :

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 Capacity orientedProduction planningSeasonality

Source: Goudiano CSCMP 2005

Manage Supply

• Over 6000 part numbers

• 70 % option driven

• Order changes

• 40% from Europe

0

30

60

90

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101

106

Day

Dai

ly U

sag

e

Usage

Average Usage 32/day

Standard Deviation in Usage 18/day

SAME NUMBER OF CARS/DAY

Managing Supply

ForecastShipments

ArriveDecide Shipment

Quantities

Demand

Day 1 Day 10Day 40

Demand

Demand

Demand

Prepare Shipments

Challenge

• Huge number of parts: Complexity

• Order Flexibility: Variability

• Long LeadTimes: Variability

Levers for managing uncertainty

• Capacity– Capacity on Supply– Production Capacity

• Inventory

• Time – Order due date

Infinite

Constant

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

Time

Sto

ck o

n ha

nd

Reorder Point

Order placed

Lead Time

Reorder Point

Actual Lead Time Demand

Actual Lead Time Demand

Order Quantity

Actual Lead Time Demand

Actual Lead Time Demand

Order-up-to level

T L

Safety Stock Basics

• Lead time demand N(, )

• Safety stock levels– Choose z from N(0,1) to get correct

probability that lead time demand exceeds z,– Safety stock is z

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 L

• Demand per time unit has mean D, std dev D

• Assume demands in different periods are independent• Let Ddenote the standard deviation in demand per unit

time• Let Ldenote 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)D

Lead Time Variability

If Lead Times are variable• D = Average (daily) demand• D = Std. Dev. in (daily) demand• L = Average lead time (days)• L = Std. Dev. in lead time (days)• Average lead time demand

D(T+E[L])

• Std. Dev. in lead time demand(T+E[L])2

D + D2 2L

• Remember: Std. Dev. in lead time demand drives safety stock

Levers to Pull

• Std. dev in lead time demand(T+E[L])2

D + D2 2L

Reduce Lead Time

Reduce Variability

in Lead Time

Reduce Variability in Demand

Reduce Time

between orders

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