Chapter 3 Network Planning

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? 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

3.2 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

Key Strategic Decisions Number of facilities. Location of each facility. Size of each facility. Allocating space for products. Sourcing requirements. Determining distribution strategies 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. Objective: Design or reconfigure the logistics network in order to minimize annual system-wide cost subject to a variety of service level requirements

Data Collection & Aggregation 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 Technology exists to solve the logistics network design problem with the original data Data aggregation still useful because forecast demand is significantly more accurate at the aggregated level Aggregating customers into about 150-200 zones usually results in no more than a 1 percent error in the estimation of total transportation costs GENERAL RULES FOR AGGREGATION Aggregate demand points into at least 200 zones Holds for cases where customers are classified into classes according to their service levels or frequency of delivery Make sure each zone has approximately an equal amount of total demand Zones may be of different geographic sizes. Place aggregated points at the center of the zone Aggregate products into 20 to 50 product groups Customer Zones & Product Groups

Transportation Rates Rates linear with distance but not volume Internal TL - Zone-to-zone costs provides cost per mile per truckload between any two zones. LTL – Class, Exception & Commodity Rates Mileage estimation INTERNAL Data Required: Annual costs per truck Annual mileage per truck Annual amount delivered Truck’s effective capacity Calculate cost per mile per SKU. Class rates standard rates for almost all products or commodities shipped. Classification tariff system that gives each shipment a rating or a class. Factors involved in determining a product’s specific class include: product density, ease or difficulty of handling and transporting, and liability for damage. After establishing rating, identify rate basis number. Approximate distance between the load’s origin and destination. With the two, determine the specific rate per hundred pounds (hundred weight, or cwt) from a carrier tariff table (i.e., a freight rate table). Exception rates provides less expensive rates Commodity rates are specialized commodity-specific rates

Warehouse Costs Handling costs Fixed costs Storage 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.

Warehouse Capacity Estimation of actual space required Average inventory level = Annual flow through warehouse/Inventory turnover ratio Space requirement for item = 2*Average Inventory Level Multiply by factor to account for access and handling aisles, picking, sorting and processing facilities AGVs Typical factor value = 3

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

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

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

Number of Warehouses Optimal Number of Warehouses

Sexy 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.

Unit Distribution Costs Facility warehouse p1 p2 c1 c2 c3 w1 4 3 5 w2 2 1 Two heuristics and an optimization technique: Choose the cheapest warehouse to source demand Choose the warehouse where the total delivery costs to and from the warehouse are the lowest LP

Heuristic #1: Choose the Cheapest Warehouse to Source Demand $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

Market #1 is served by WH1, Markets 2 and 3 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 $2 D = 50,000 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

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 $2 x 50,000 D = 50,000 P1 to WH1 $5 P1 to WH2 $7 P2 to WH1 $9 P2 to WH 2 $4 Total Cost = $920,000

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

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.

Optimal Solution Facility warehouse p1 p2 c1 c2 c3 w1 140,000 50,000 50,000 40,000 0* w2 60,000 50,000* Total cost for the optimal strategy is $740,000 *Your text has the w2c3 and w1c3 numbers reversed

DSS for Network Design Flexibility to incorporate a large set of preexisting network characteristics Other Factors: Customer-specific service level requirements. Existing warehouses kept open Expansion of existing warehouses. Specific flow patterns maintained Warehouse-to-warehouse flow possible Production and Bill of materials details may be important Robustness Relative quality of the solution independent of specific environment, data variability or specific settings

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?

Single Product, Single Facility Periodic Review Inventory Model Assume - SI: amount of time between when an order is placed until the facility receives a shipment (Incoming Service Time) S: Committed Service Time made by the facility to its own customers. T: Processing Time at the facility. Net Lead Time = SI + T - S Safety stock at the facility:

2-Stage System Overall objective is to choose: Reducing committed service time from facility 2 to facility 1 impacts required inventory at both facilities Inventory at facility 1 is reduced Inventory at facility 2 is increased Overall objective is to choose: the committed service time at each facility the location and amount of inventory minimize total or system wide safety stock cost.

ElecComp Case Large contract manufacturer of circuit boards and other high tech parts. About 27,000 high value products with short life cycles Fierce competition => Low customer promise times < Manufacturing Lead Times High inventory of SKUs based on long-term forecasts => Classic PUSH STRATEGY High shortages Huge risk PULL STRATEGY not feasible because of long lead times

New Supply Chain Strategy OBJECTIVES: Reduce inventory and financial risks Provide customers with competitive response times. ACHIEVE THE FOLLOWING: Determining the optimal location of inventory across the various stages Calculating the optimal quantity of safety stock for each component at each stage Hybrid strategy of Push and Pull Push Stages produce to stock where the company keeps safety stock Pull stages keep no stock at all. Challenge: Identify the location where the strategy switched from Push-based to Pull-based Identify the Push-Pull boundary Benefits: For same lead times, safety stock reduced by 40 to 60% Company could cut lead times to customers by 50% and still reduce safety stocks by 30%

Notations Used FIGURE 3-11: How to read the diagrams

Trade-Offs If Montgomery facility reduces committed lead time to 13 days assembly facility does not need any inventory of finished goods Any customer order will trigger an order for parts 2 and 3. Part 2 will be available immediately, since it is held in inventory Part 3 will be available in 15 days 13 days committed response time by the manufacturing facility 2 days transportation lead time. Another 15 days to process the order at the assembly facility Order is delivered within the committed service time. Assembly facility produces to order, i.e., a Pull based strategy Montgomery facility keeps inventory and hence is managed with a Push or Make-to-Stock strategy.

Current Safety Stock Location FIGURE 3-12: Current safety stock location

Optimized Safety Stock Location FIGURE 3-13: Optimized safety stock

Current Safety Stock with Lesser Lead Time FIGURE 3-14: Optimized safety stock with reduced lead time

Supply Chain with More Complex Product Structure FIGURE 3-15: Current supply chain

Optimized Supply Chain with More Complex Product Structure FIGURE 3-16: Optimized supply chain

Key Points Identifying the Push-Pull boundary Taking advantage of the risk pooling concept Demand for components used by a number of finished products has smaller variability and uncertainty than that of the finished goods. Replacing traditional supply chain strategies that are typically referred to as sequential, or local, optimization by a globally optimized supply chain strategy.

Local vs. Global Optimization FIGURE 3-17: Trade-off between quoted lead time and safety stock

Global Optimization For the same lead time, cost is reduced significantly For the same cost, lead time is reduced significantly Trade-off curve has jumps in various places Represents situations in which the location of the Push-Pull boundary changes Significant cost savings are achieved.

Problems with Local Optimization Prevalent strategy for many companies: try to keep as much inventory close to the customers hold some inventory at every location hold as much raw material as possible. This typically yields leads to: Low inventory turns Inconsistent service levels across locations and products, and The need to expedite shipments, with resulting increased transportation costs

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?

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

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

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.