1. International Supply Case Study BMW

2. Outline BMW- The company Build-to-Order & BMW BMW Spartanburg Plant –Products –Sourcing –Capacity Managing Supply

3. 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

4. BMW Business Interests Automobiles –BMW –Mini –Rolls Royce Motorcycles Financial services

5. 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

6. Z4 X5 X3 6 Series BMW Group. Brands and Models. Motorcycles 1 Series3 Series5 Series7 Series Source: Goudiano CSCMP 2005

7. BMW Group Development and Production Network

8. Z8 Dingolfing Munich Leipzig Regensburg Spartanburg Rosslyn Graz (external production) Berlin Oxford Goodwood Shenyang Source: Goudiano CSCMP 2005

9. Production Volume Total: 1119.1

10. 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

11. Challenges Excess capacity => Price pressures Customer expectations –Personalization –Innovation –Service Cost effective factories with flexible manufacturing abilities New technologies and material Regulations ….

12. 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?

13. 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.'

14. Why BTO? Other Alternatives –Build to Stock/Forecast Assign to dealers Sell from available stock

15. 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 Customer

16. Increasing Product Complexity Product variety & Part complexity –10 32 possible combinations of products at BMW –10 17 possible combinations of BMW 7 series –~70 million configurations of the Ford Escape –>2 40 configurations of Toyota Scion

17. 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

18. BMW 7 Series 350 Model Versions... leading to e.g. 10 17 theoretical combinations only for the BMW 7 Series 175 Interior Equipment Options Source: Goudiano CSCMP 2005 500 Extra Equipment Options 90 Standard Exterior Colors

19. Product Complexity A finite set of part numbers “Infinitely” many end products

20. BTO & Product Complexity BTO makes it possible to –Address tremendous product variety –Face the challenges of managing the variability in component demand.

21. 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

22. 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

23. 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)

24. BTO & BMW BMW BMW’s operations in SC Plant BMW’s challenges in BTO Available levers for control

25. BMW USA

26. Z4 X5

27. 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?

28. Equipment changes in % (accumulated) Flexibility % Source: Goudiano CSCMP 2005

29. 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

30. KOVP Process Monitoring and Target Control Distribution Process and Hand-over Sales Processes and Online Ordering Production- and Supply- Processes Dealer Sales System Production System Sales System Dealer Planning Dealer orderPurchasingLogisticsProductionDistributionHand-over Ordering Delivery Sales Processes and Online Ordering Optimize the whole process

31. KOVP The Push-Pull Interface Production System before KOVP Start Order Assignment Sort Early Order Assignment Bodyshell workPaint shop Assembly Production System with KOVP Frozen Horizon Sort Late Order Assignment Start order assignment OSM Bodyshell workPaint shop Assembly Push Pull

32. Flexibility for Order Change Reduction of Leadtime Ordering/SchedulingProduction/Distribution 15 WD 28-32 WD 13-17 WD Before KOVP: Order freeze Process Feasibility Supplier / Body shell work and Paint shop Change flexibility till 6 WD Distri- bution Assem -bly Hand-over to Sales 3 WD 10 WD 12 WD4 WD Breakthrough target KOVP :

33. 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

34. Sourcing Why source from Europe –Relationship with suppliers –Tooling is already there –Social responsibility issues

35. Why serve global markets? Tooling Volume …

36. 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.

37. 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

38. Manage Capacity From day to day –Mix of vehicles vary –Usage of parts vary

39. Manage Capacity Mix of vehicles Capacity oriented Production planning Seasonality Source: Goudiano CSCMP 2005

40. Manage Supply Over 6000 part numbers 70 % option driven Order changes 40% from Europe

41. Usage Average Usage 32/day Standard Deviation in Usage 18/day SAME NUMBER OF CARS/DAY

42. Managing Supply Forecast Shipments Arrive Decide Shipment Quantities Demand Day 1 Day 10 Day 40 Demand Prepare Shipments

43. Challenge Huge number of parts: Complexity Order Flexibility: Variability Long LeadTimes: Variability

44. Levers for managing uncertainty Capacity –Capacity on Supply –Production Capacity Inventory Time –Order due date Infinite Constant Given/Strict

45. 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

46. Demand Modeling Infinitely many end products Not enough data points to estimate distribution of product demand Instead: Components

47. Challenge Huge number of parts: Complexity Order Flexibility: Variability Long LeadTimes: Variability No shortages allowed

48. Some Tools & Mechanisms Safety Stock Forecast Accuracy Frequency Global Supply process …

49. 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

50. Traditional basics Time Stock on hand Reorder Point Order placed Lead Time Reorder Point Actual Lead Time Demand Order Quantity Actual Lead Time Demand Order-up-to level TL

51. 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 

52. 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  D  denote the standard deviation in demand per unit time Let  L  denote the standard deviation in the lead time.

53. 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

54. 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 + D 2  2 L Remember: Std. Dev. in lead time demand drives safety stock

55. Levers to Pull Std. dev in lead time demand  (T+E[L])  2 D + D 2  2 L Reduce Lead Time Reduce Variability in Lead Time Reduce Variability in Demand Reduce Time between orders

56. 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