Chapter 3: Network Planning CMB 8050 Matthew J. Liberatore

1. Chapter 3: Network Planning CMB 8050 Matthew J. Liberatore

2. 3.1 Why Network Planning? • Find the right balance between inventory, transportation and manufacturing costs, • Match supply and demand under uncertainty by positioning and managing inventory effectively, • Utilize resources effectively by sourcing products from the most appropriate manufacturing facility

3. Three Hierarchical Steps • Network design • Number, locations and size of manufacturing plants and warehouses • Assignment of retail outlets to warehouses • Major sourcing decisions • Typical planning horizon is a few years. • Inventory positioning: • Identifying stocking points • Selecting facilities that will produce to stock and thus keep inventory • Facilities that will produce to order and hence keep no inventory • Related to the inventory management strategies • Resource allocation: • Determine whether production and packaging of different products is done at the right facility • What should be the plants sourcing strategies? • How much capacity each plant should have to meet seasonal demand?

4. 3.2 Network Design • Physical configuration and infrastructure of the supply chain. • A strategic decision with long-lasting effects on the firm. • Decisions relating to plant and warehouse location as well as distribution and sourcing

5. Reevaluation of Infrastructure • Changes in: • demand patterns • product mix • production processes • sourcing strategies • cost of running facilities. • Mergers and acquisitions may mandate the integration of different logistics networks

6. Key Strategic Decisions • Determining the appropriate number of facilities such as plants and warehouses. • Determining the location of each facility. • Determining the size of each facility. • Allocating space for products in each facility. • Determining sourcing requirements. • Determining distribution strategies, i.e., the allocation of customers to warehouse

7. Objective and Trade-Offs • Objective: Design or reconfigure the logistics network in order to minimize annual system-wide cost subject to a variety of service level requirements • Increasing the number of warehouses typically yields: • An improvement in service level due to the reduction in average travel time to the customers • An increase in inventory costs due to increased safety stocks required to protect each warehouse against uncertainties in customer demands. • An increase in overhead and setup costs • A reduction in outbound transportation costs: transportation costs from the warehouses to the customers • An increase in inbound transportation costs: transportation costs from the suppliers and/or manufacturers to the warehouses.

8. Data Collection • Locations of customers, retailers, existing warehouses and distribution centers, manufacturing facilities, and suppliers. • All products, including volumes, and special transport modes (e.g., refrigerated). • Annual demand for each product by customer location. • Transportation rates by mode. • Warehousing costs, including labor, inventory carrying charges, and fixed operating costs. • Shipment sizes and frequencies for customer delivery. • Order processing costs. • Customer service requirements and goals. • Production and sourcing costs and capacities

9. Data Aggregation • Customer Zone • Aggregate using a grid network or other clustering technique for those in close proximity. • Replace all customers within a single cluster by a single customer located at the center of the cluster • Five-digit or three-digit zip code based clustering. • Product Groups • Distribution pattern • Products picked up at the same source and destined to the same customers • Logistics characteristics like weight and volume. • Product type • product models or style differing only in the type of packaging.

10. Warehouse Costs • Handling costs • Labor and utility costs • Proportional to annual flow through the warehouse. • Fixed costs • All cost components not proportional to the amount of flow • Typically proportional to warehouse size (capacity) but in a nonlinear way. • Storage costs • Inventory holding costs • Proportional to average positive inventory levels.

11. Potential Locations • Geographical and infrastructure conditions. • Natural resources and labor availability. • Local industry and tax regulations. • Public interest. • Not many will qualify based on all the above conditions

12. Service Level Requirements • Specify a maximum distance between each customer and the warehouse serving it • Proportion of customers whose distance to their assigned warehouse is no more than a given distance • 95% of customers be situated within 200 miles of the warehouses serving them • Appropriate for rural or isolated areas

13. Future Demand • Strategic decisions have to be valid for 3-5 years • Consider scenario approach and net present values to factor in expected future demand over planning horizon

14. Number of Warehouses Optimal Number of Warehouses

15. Industry Benchmarks:Number of Distribution Centers Food Companies Chemicals Pharmaceuticals Avg. # of WH 3 14 25 - High margin product - Service not important (or easy to ship express) - Inventory expensive relative to transportation - Low margin product - Service very important - Outbound transportation expensive relative to inbound

16. Model Validation • Reconstruct the existing network configuration using the model and collected data • Compare the output of the model to existing data • Compare to the company’s accounting information • Often the best way to identify errors in the data, problematic assumptions, modeling flaws. • Make local or small changes in the network configuration to see how the system estimates impact on costs and service levels. • Positing a variety of what-if questions. • Answer the following questions: • Does the model make sense? • Are the data consistent? • Can the model results be fully explained? • Did you perform sensitivity analysis?

17. Solution Techniques • Mathematical optimization techniques: 1. Exact algorithms: find optimal solutions 2. Heuristics: find “good” solutions, not necessarily optimal • Simulation models: provide a mechanism to evaluate specified design alternatives created by the designer.

18. Example • Single product • Two plants p1 and p2 • Plant p2 has an annual capacity of 60,000 units. • The two plants have the same production costs. • There are two warehouses w1 and w2 with identical warehouse handling costs. • There are three markets areas c1,c2 and c3 with demands of 50,000, 100,000 and 50,000, respectively.

19. Unit Distribution Costs

20. Heuristic #1:Choose the Cheapest Warehouse to Source Demand D = 50,000 $2 x 50,000 $5 x 140,000 D = 100,000 $1 x 100,000 $2 x 60,000 Cap = 60,000 D = 50,000 $2 x 50,000 Total Costs = $1,120,000

21. Heuristic #2:Choose the warehouse where the total delivery costs to and from the warehouse are the lowest[Consider inbound and outbound distribution costs] $0 D = 50,000 $3 P1 to WH1 $3 P1 to WH2 $7 P2 to WH1 $7 P2 to WH 2 $4 $4 $2 $5 $5 D = 100,000 P1 to WH1 $4 P1 to WH2 $6 P2 to WH1 $8 P2 to WH 2 $3 $4 $1 $2 Cap = 60,000 D = 50,000 $2 P1 to WH1 $5 P1 to WH2 $7 P2 to WH1 $9 P2 to WH 2 $4 Market #1 is served by WH1, Markets 2 and 3 are served by WH2

22. Heuristic #2:Choose the warehouse where the total delivery costs to and from the warehouse are the lowest[Consider inbound and outbound distribution costs] $0 x 50,000 D = 50,000 $3 x 50,000 Cap = 200,000 P1 to WH1 $3 P1 to WH2 $7 P2 to WH1 $7 P2 to WH 2 $4 $5 x 90,000 D = 100,000 P1 to WH1 $4 P1 to WH2 $6 P2 to WH1 $8 P2 to WH 2 $3 $1 x 100,000 $2 x 60,000 Cap = 60,000 D = 50,000 $2 x 50,000 P1 to WH1 $5 P1 to WH2 $7 P2 to WH1 $9 P2 to WH 2 $4 Total Cost = $920,000

23. The Optimization Model The problem described earlier can be framed as the following linear programming problem. Let • x(p1,w1), x(p1,w2), x(p2,w1) and x(p2,w2) be the flows from the plants to the warehouses. • x(w1,c1), x(w1,c2), x(w1,c3) be the flows from the warehouse w1 to customer zones c1, c2 and c3. • x(w2,c1), x(w2,c2), x(w2,c3) be the flows from warehouse w2 to customer zones c1, c2 and c3

24. The Optimization Model The problem we want to solve is: min 0x(p1,w1) + 5x(p1,w2) + 4x(p2,w1) + 2x(p2,w2) + 3x(w1,c1) + 4x(w1,c2) + 5x(w1,c3) + 2x(w2,c1) + 2x(w2,c3) subject to the following constraints: x(p2,w1) + x(p2,w2)  60000 x(p1,w1) + x(p2,w1) = x(w1,c1) + x(w1,c2) + x(w1,c3) x(p1,w2) + x(p2,w2) = x(w2,c1) + x(w2,c2) + x(w2,c3) x(w1,c1) + x(w2,c1) = 50000 x(w1,c2) + x(w2,c2) = 100000 x(w1,c3) + x(w2,c3) = 50000 all flows greater than or equal to zero.

25. Optimal Solution Total cost for the optimal strategy is $740,000

26. Simulation Models • Useful for a given design and a micro-level analysis. Examine: • Individual ordering pattern. • Specific inventory policies. • Inventory movements inside the warehouse. • Not an optimization model • Can only consider very few alternate models

27. Which One to Use? • Use mathematical optimization for static analysis • Use a 2-step approach when dynamics in system has to be analyzed: • Use an optimization model to generate a number of least-cost solutions at the macro level, taking into account the most important cost components. • Use a simulation model to evaluate the solutions generated in the first phase.

28. 3.3 Inventory Positioning and Logistics Coordination • Multi-facility supply chain that belongs to a single firm • Manage inventory so as to reduce system wide cost • Consider the interaction of the various facilities and the impact of this interaction on the inventory policy of each facility • Ways to manage: • Wait for specific orders to arrive before starting to manufacture them [make-to-order facility] • Otherwise, decide on where to keep safety stock? • Which facilities should produce to stock and which should produce to order?

29. Integrating Inventory Positioning and Network Design • Consider a two-tier supply chain • Items shipped from manufacturing facilities to primary warehouses • From there, they are shipped to secondary warehouses and finally to retail outlets • How to optimally position inventory in the supply chain? • Should every SKU be positioned both at the primary and secondary warehouses?, OR • Some SKU be positioned only at the primary while others only at the secondary?

30. Integrating Inventory Positioning and Network Design FIGURE 3-18: Sample plot of each SKU by volume and demand

31. Three Different Product Categories • High variability - low volume products • Low variability - high volume products, and • Low variability - low volume products.

32. Supply Chain Strategy Different for the Different Categories • High variability low volume products • Inventory risk the main challenge for • Position them mainly at the primary warehouses • demand from many retail outlets can be aggregated reducing inventory costs. • Low variability high volume products • Position close to the retail outlets at the secondary warehouses • Ship fully loaded tracks as close as possible to the customers reducing transportation costs. • Low variability low volume products • Require more analysis since other characteristics are important, such as profit margins, etc.

33. SUMMARY • Optimizing supply chain performance is difficult • conflicting objectives • demand and supply uncertainties • supply chain dynamics. • Through network planning, firms can globally optimize supply chain performance • Combines network design, inventory positioning and resource allocation • Consider the entire network • account production • Warehousing • transportation inventory costs • service level requirements.