Supply chain integration

1. Supply chain integration • Various supply chain strategies • Push strategies • Pull strategies • Push-pull systems • Matching products or industries with supply chain strategies • Impact of the Internet on supply chain integration • Effective distribution strategies • Direct shipment • Warehousing • Cross-docking

2. Push Strategies • Production decisions based on long-term forecasts • Ordering decisions based on inventory & forecasts • What are the problems with push strategies? • Inability to meet changing demand patterns • Obsolescence • The bullwhip effect: • Excessive inventory • Excessive production variability • Poor service levels • Hard to predict production capacity or transportation capacity

3. Pull Strategies • Production is demand driven • Production and distribution coordinated with true customer demand • Firms respond to specific orders • Pull Strategies result in: • Reduced lead times (better anticipation) • Decreased inventory levels at retailers and manufacturers • Decreased system variability • Better response to changing markets • But: • Harder to leverage economies of scale • Doesn’t work in all cases

4. Pull strategies – a Kanban system Inbound buffer Outbound buffer Inbound buffer Outbound buffer Suppliers Retailers Move cards Production cards Move cards Production cards

5. Push-Pull Systems Push- Pull Boundary Push Strategy Pull Strategy End Customer Raw Materials Supply chain time line

6. Push-pull systems • A shift from a Push System... • Production decisions are based on forecast • …to a Push-Pull System • Initial portion of the supply chain is replenished based on long-term forecasts • For example, parts inventory may be replenished based on forecasts • Final supply chain stages based on actual customer demand. • For example, assembly may based on actual orders.

7. Build to Stock Forecast demand Buys components Assembles computers Observes demand and meets demand if possible. A traditional push system Build to order Forecast demand Buys components Observes demand Assembles computers Meets demand A push-pull system Consider Two PC Manufacturers:

8. Push-Pull Strategies • The push-pull system takes advantage of the rules of forecasting: • Forecasts are always wrong • The longer the forecast horizon the worse the forecast • Aggregate forecasts are more accurate • Risk Pooling impact • Delayed differentiation is another example • Consider Benetton sweater production

9. Demand uncertainty (C.V.) Pull Push H L Delivery cost Unit price L H Economies of Scale Pull Push What is the Best Strategy? I Computers II Furniture IV Books & CDs III Grocery

10. Selecting the Best SC Strategy • Higher demand uncertainty suggests pull • Higher importance of economies of scale suggests push • High uncertainty/ EOS not important such as the computer industry implies pull • Low uncertainty/ EOS important such as groceries implies push • Demand is stable • Transportation cost reduction is critical • Pull would not be appropriate here.

11. Selecting the Best SC Strategy • Low uncertainty but low value of economies of scale (high volume books and CDs) • Either push strategies or push/pull strategies might be most appropriate • High uncertainty and high value of economies of scale • For example, the furniture industry • How can production be pull but delivery push? • Is this a “pull-push” system?

12. Characteristics and Skills

13. Locating the Push-Pull Boundary • The push section: • Uncertainty is relatively low • Economies of scale important • Long lead times • Complex supply chain structures: • Thus • Management based on forecasts is appropriate • Focus is on cost minimization • Achieved by effective resource utilization – supply chain optimization • The pull section: • High uncertainty • Simple supply chain structure • Short lead times • Thus • Reacting to realized demand is important • Focus on service level • Flexible and responsive approaches

14. Locating the Push-Pull Boundary • The push section requires: • Supply chain planning • Long term strategies • The pull section requires: • Order fulfillment processes • Customer relationship management • Buffer inventory at the boundaries: • The output of the tactical planning process • The input to the order fulfillment process.

15. Locating the Push-Pull Boundary

16. Demand-driven strategies • Demand forecast: Using historical data to develop long-term estimates of expected demand • Demand shaping: Determining the impact various marketing plans such as promotions, pricing discounts, rebates, new product introductions and product withdrawal on demand forecasts • Inaccuracy of the forecast has a detrimental impact on supply chain performance: lost sales, obsolete inventory, inefficient resource utilization • Employing supply chain strategies to reduce the impacts of forecast inaccuracy • Select the push-pull boundary so that the demand is aggregated over different dimensions: products, geography, time • Use market analysis and demographic and economic trends to improve forecast • Determine the optimal assortment of products by store to reduce the impact of competing SKUs in the same market • Incorporate collaborative planning and forecasting processes with customers to better understand market demand, impact of promotions, pricing and advertising

17. Impact of Internet on SCM • What does internet change for a supply chain? • Enables a whole new business model. • Online purchasing, direct shipping, auctioning, secondary markets • Improves or enables integration between different parties of the supply chain • Enables information sharing • Enables collaboration • Reduces lead times • Reduction in order processing times • Improves product availability

18. Impact of internet • E-business: a collection of business models and processes motivated by Internet technology and focusing on improvement of extended enterprise performance • Business-to-consumer (B2C): “direct to customer”, retail activities over the internet • Business-to-business (B2B): business conducted over the internet between businesses • Impact of internet • Move from push to pull systems • Significant failures as a result • Move from pull systems to push-pull systems • Many click-and-mortar companies established. Many brick-and-mortar companies opened online stores. Some has been successful: Dell, Cisco, Amazon. Many have failed

19. Grocery Industry • Example: Peapod • Founded early 90s • Implemented a pure pull system. When an order is received, the products are picked from a nearby supermarket. Problems • Service problems: significant stock-outs • Reduced profit margins • Moved to a push-pull system. Set up a number of warehouses • Stock-out rates are lower • As compared to traditional grocers, the demand is aggregated over a larger geographical area • Transportation costs versus response time • Shipments in small batches • Response time within 12 hours • No sufficient density of customers to control transportation costs • Many failures so far: shoplink.com, streamline.com, etc

20. Book industry • Example: Amazon.com. World’s largest bookseller • Founded in 1994 • Implemented a pure pull system where it utilized Ingram Book Group to supply customer demand. Appropriate when Amazon was building its brand name. Issues became clear later when the demand increased • Ingram’s distribution capacity supports many other booksellers. Service issues for Amazon during peak demand • Amazon had to share its profit margins with Ingram • Amazon established several warehouses, where the inventory is procured using a push strategy, orders are shipped using a pull strategy • May still use a pure pull strategy for slower items • World’s largest bookseller with $3.9 Billion sales in 2002. But yet to make a profit • Response time is not as critical as grocers. May use parcel services.

21. Retail industry • Traditional retailers added online shopping component to their offering: Wal-Mart, Kmart, Target and Barnes and Noble. Advantageous over pure Internet companies • They already have the distribution and warehousing infrastructure in place • Established brand name • Easy returns and reverse logistics • Different strategies for different products • High-volume, fast-moving products stocked in stores and available online • Low-volume, slow-moving products are stocked centrally and available only online • Moving from a traditional business to internet based business may require different skills that are not present in many traditional businesses

22. Impact of internet on fulfillment

23. Spearman • Analyzes service level in pull systems • Kanban system versus a base stock policy • Kanban would not place an order for more parts if a demand had arrived when there was no stock in the outbound stock point • Kanban has a constant WIP • Stochastic ordering and Kanban systems. Two Kanban systems A and B, A has service times SA and B has service times SB. • If SA is stochastically larger than SB, then system A has worse service than system B • Two normal distributions with same variance, mA < mB • If SA is stochastically larger than SB, in the sense of increasing convex ordering, then system A has worse service than system B • Two normal distributions with same mean, sA < sB • More Kanban (WIP) leads to higher service in Kanban systems

24. Spearman - continued • The study argues that the superiority of Kanban systems is not the fact that material is pulled everywhere, but the fact that the WIP is constant • Develops a system called a constant WIP system, or CONWIP • Pulling only at the first station • Pushing on the rest of the chain using CONWIP backlog • Can utilize common setups • Consumption of item A may lead to start of the production for item B • CONWIP system outperforms Kanban system • Better service • May be more appropriate for large setup times, changing product mix.

25. Rajagopalan • Develops a model to decide whether an item should be MTO or MTS • Items that are MTO. No inventory cost. Only setup time. Orders of a same item within a bucket still shares the setup. Ship to customer within T with probability PO • Items that are MTS. Follows an (r, q) policy. Cycle stock and safety stock. Service level (type I) of PS • Decisions for items are not independent of each other. Trade-offs • Making an item MTO reduces the inventory for that item, but • Leads to more setups, thus higher capacity utilization and larger lead times • Leads to more variability in lead times • Thus larger safety and cycle stocks for MTS items, poorer service for MTO items • Decreasing the lot size for MTS similar effects

26. Rajagopalan - continued • Insights • MTO systems may be less costly but not always feasible • Medium demand items are attracted to MTS • Higher holding costs -> MTO • Higher setup costs -> MTS • Larger processing times with high demands -> MTO • Impact of priority queues (MTO orders are prioritized) • Leads to more MTO items • However leads to more cycle stocks and safety stocks for MTS items

27. Stochastic ordering m=20 s=5 m=30 s=5

28. Increasing convex stochastic ordering m=20 s=5 m=20 s=8