The Impact of the Internet on Supply Chain Management

1. The Impact of the Internet onSupply Chain Management Including some excerpts form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology Move the push-pull boundary to reduce costs while improving cycle times.

2. Supply Chain Management • Definition: Supply Chain Management is primarily concerned with the efficient integration of suppliers, factories, warehouses and stores so that merchandise is produced and distributed in the right quantities, to the right locations and at the right time, and so as to minimize total system cost subject to satisfying service requirements. • Notice: – Who is involved – Cost and Service Level – It is all about integration Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

3. The Business Model e- • e-Business is the process of redefining old business models, using Internet technology, so as to improve the extended enterprise performance • e-commerce is part of e-Business • Internet technology is the driver of the business change • The focus is on the extended enterprise: • Intra-organizational • Business to Consumer (B2C) • Business to Business (B2B) Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

4. 1. Purchasing • Stable volume requirements • Flexible delivery time • Little variation in mix • Large quantities 2. Manufacturing • Long run production • High quality • High productivity • Low production cost 3. Warehousing • Low inventory • Reduced transportation costs • Quick replenishment capability 4. Customers • Short order lead time • High in stock • Enormous variety of products • Low prices Conflicting Objectives in the Supply Chain Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

5. A new Supply Chain Paradigm • A shift from a Push System... • Production decisions (assembly) are based on forecast • Goods are produced, stored in retail inventory • Shocks in demand lead to stock out or unsold products • …to a Push-Pull System • Part of the production decisions (assembly) are performed on demand • Parts inventory is replenished based on forecasts • Customizing of products • Example: Dell Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

6. From Make-to-Stock Model…. Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

7. ….to Assemble-to-Order Model Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

8. Sandwiches made on demand More choice / Longer preparation time Piecework No unsold stock Sandwiches prepared in advance More limited choice No delay of preparation / faster service Cheaper production line unsold stock Pickup sandwiches

9. Choice criteria Prepared in advance On demand • Diversity of taste / willingness to satisfy heterogeneity of tastes and preferences • Added cost of piece production • Impatience of customers • Incertitude in demand. • Cost of unsold stocks

10. Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

11. Demand Forecast The three principles of all forecasting techniques: – Forecasts are always wrong –The longer the forecast horizon the worst is the forecast – Aggregate forecasts are more accurate - The Risk Pooling Concept Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

12. Risk pooling: numerical example • Many stores selling a good, • 2 consumers / store • A consumer has a chance 50-50 to desire the good. • Value of a sale=30$, cost of inventory 10$/unity • Examine of the possible inventory policies

13. Profits under full information(maximum possible profits) Expected gain = 20 $ Average gain per consumer: 10$

14. I- One unit per Store Expected gain = 12,5 $ Average gain per consumer: 6,25$

15. II- Two units per store Expected gain = 10 $ Average gain per consumer=5$

16. 4 clients / store2 units in inventory Expected gains=460/16 = 28,7$ Average gain per consumer = 7,18$ Higher average gain with 4 clients than with 2.

17. n clients / stores units in inventory Probability that x consumers wants the good Total expect profits Optimal inventory s. Marginal benefit of adding one extra unit in inventory become nil.

18. Effect of pooling risk

19. Pooling risk

20. How to pool risk • Pool consumers across time by having stocking for a longer period • Increase stocking time • Use stock as a buffer • Pool consumers geographically by having large stores serving more customers • Increase transportation costs if there are economies of scale in transportation • Greater delays for consumers • Last mile

21. How to pool risk • Delaying assembly: pool consumers across products by using the same resources for different products • Requires manufacturing flexibility • Greater delays for consumers

22. Matching Supply Chain Strategieswith Products Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

23. Locating the Push-Pull Boundary Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

24. Business models in the BookIndustry • From Push Systems... – Barnes and Noble • ...To Pull Systems – Amazon.com, 1996-1999 • And, finally to Push-Pull Systems – Amazon.com, 1999-present • 7 warehouses, 3M sq. ft., Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

25. e-Business in the Retail Industry Brick-&-Mortar companies establish Virtual retail stores • Wal-Mart, K-Mart, Barnes and Noble Use a hybrid approach in stocking • High volume/fast moving products for local storage • Low volume/slow moving products for browsing and purchase on line Channel Conflict Issues Excerpt form David Simchi-Levi Professor of Engineering Systems Massachusetts Institute of Technology

26. e-Business Opportunities e-Business Challenges • Reduce Facility Costs • Eliminate retail • distributor sites • Reduce Inventory Costs • Apply the risk-pooling concept • Centralized stocking • Postponement of product differentiation • Manage channel conflict issues • Automated fulfillment • Use and share optimally information as soon as available • Speed up assembly • Speed up delivery • Manage the “last mile”.