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Perfecting Distribution Channels
Software gives businesses ability to adapt to market changes
By Michael Watson and Jim Morton
Taken from Perfecting Distribution Channels, Parcel Shipping & Distribution Magazine, April 2000 - Revised December 2003
Many organizations today face a dynamic business environment. This situation requires a robust supply chain strategy and the ability to rapidly respond to market changes. Strategic supply chain planning through the use of decision support software tools is the most effective way to respond to this need.
Today’s supply chain modeling is done predominately with PC based software tools. The purpose of the modeling effort is to consider a wide variety of what-if scenarios to determine the optimal supply chain configuration and to offer decision support to help management meet its stated business objectives.
The standard process is for the business analyst to "model" the current supply chain using decision support modeling software. The analyst first builds a baseline model that establishes a basis of comparison to the alternative what-if scenarios. By comparing the baseline to a wide variety of optimized alternative scenarios, the analyst is able to evaluate the relative cost/benefit ratio for each strategy and offer the appropriate recommendations.
To design the best network, one must consider all relevant costs and service-level constraints. Relevant costs include inbound and outbound transportation, fixed and variable warehouse costs, inventory carrying and producing or sourcing from different locations. Complex trade-offs make these costs difficult to analyze. For example, as the number of warehouse locations increase, transportation cost will decrease, but inventory cost will increase. Moreover, costs are often dependent on the location and capacity of plants or vendors, as well as the location and demand characteristics of customers.
Fortunately, commercially available software can make network redesign a manageable task. Several companies make network design software that can model your supply chain and compute the optimum network configuration. Among other things, this software allows you to input facility locations, product information and relevant cost data as mentioned above. To use these models successfully, you must consider all factors that drive your supply chain.
Figure 1: Product flow and ground service levels for current network. 
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Using software to design networks
The following case study uses network design software to optimize network performance. LogicNet Plus®, PC-based software from LogicTools, Inc., is used for the analysis. The case study examines how logistics costs and service criteria impact design of an optimal network. In addition, the example shows how to design a network that meets a desired customer service level by integrating carrier time-in-transit data into the logistics model.
This case study is a compilation of several projects. "BuyPC, Inc." is a fictitious company that sells computers via the Internet. BuyPC, Inc. emphasizes next-day delivery of its products so its distribution network must feature high availability and one-day transit time. It ships customer orders using a small package carrier. A network of 15 warehouses located throughout the US provides next-day ground service to most customers. A factory in Asia ships replenishment stock to the port of Los Angeles. From there, products are shipped in truckload quantities to the warehouses.
Figure 2: Logistics costs versus number of warehouses for an optimum network.
Cost Trade-Off for BuyPC, Inc. 
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Figure 1 illustrates product flow and service levels within the existing network. In this example, map colors are based on UPS time-in-transit for ground service, with the assumption that each customer is served from the warehouse location that provides fastest service. The pie chart reflects the percent of orders that can be delivered relative to ground transit time. BuyPC, Inc. ships about 90% of customer orders (customers within red areas) inexpensively via ground service. The company upgrades the remaining 10% of orders (customers within blue or orange areas) to one-day air service in order to meet the next-day delivery commitment.
Table 1 summarizes annual logistics costs. Transportation costs are $3.8 million. Average total inventory is approximately $50 million, sufficient to ensure high product availability. Management estimates the inventory carrying cost (ICC) is 25% of the value of the inventory. This estimate includes the cost of capital, depreciation, obsolescence, damage and also shrinkage. Therefore, annual inventory carrying costs are about $13 million. Warehouse fixed costs, including leases, utilities, security and also staffing, are about $1.8 million. Total logistics cost is $18.9 million.
Table 1: Summary of current logistics costs.
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Port to Warehouse Shipping Cost
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$850,984
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Warehouse to Customer Shipping Cost
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$2,929,853
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Inventory Carrying Cost
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$13,291,150
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Warehouse Fixed Cost
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$1,875,000
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TOTAL COST
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$18,946,987
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Management wants to reduce total logistics cost by reducing the number of warehouses. Consolidating the network should reduce inventory, ICC expense and brick and mortar expense. Unfortunately, having fewer sites will also increase transportation cost because more orders will be fulfilled via one-day air service. So, what network configuration will achieve the ideal balance between warehouse cost and transportation cost? A single warehouse? Ten warehouses? Where should the warehouses be located? And what financial impact is expected?
Logistics problems such as this one are complex because there are so many possible combinations of the underlying variables. It is virtually impossible to find the optimal solution without the aid of network design software. Optimization-based software models use a mixed-integer programming (MIP) algorithm that intelligently sorts the myriad of possible combinations to find the minimum-cost network. However, in our example, BuyPC, Inc. must minimize total cost and satisfy the service constraint — one-day delivery to all customers. Consequently, it is necessary to set up the model such that it meets both goals simultaneously.
Figure 3: Product flow and ground service levels for new network. 
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Setting rates
Among other things, LogicNet Plus requires carrier rates for every possible warehouse-to-customer lane. For the model to consider both cost and service levels, the rate assigned to each lane must reflect the carrier service level required for one-day delivery. For example, consider Chicago as a warehouse location. Using ground service, Chicago can reach Milwaukee customers in one day. Consequently, the rate for the Chicago to Milwaukee lane is set to the ground service rate. However, Chicago requires two days to reach Atlanta customers via ground service. The warehouse must upgrade these customers to one-day air service to meet the service goal. The rate for the Chicago to Atlanta lane is set to the one-day air rate. Each lane is assigned an appropriate rate in this manner.
BuyPC, Inc. needs a rate structure that guarantees next-day service. Using the above approach, one can design mixed mode networks to meet different customer service levels. For example, an optimum two-day network consists of a blend of ground service and two-day air service. An optimum three-day network consists of a blend of ground service and a guaranteed three-day service. In each case, the rate assigned to a lane reflects the carrier service level required to meet the desired customer service level. Integrating carrier time-in-transit information using the rate structure enables the software to examine the complex trade-off between the number and location of distribution centers and the proper mix of ground and premium services.
Optimizing the distribution network
Once all data has been entered into the model, the optimizer is run. In general, LogicNet Plus determines the best set of warehouse locations from a list of potential locations. BuyPC, Inc. wants to consolidate its network by selectively eliminating warehouse locations. Consequently, LogicNet Plus will consider only existing warehouse locations as potential locations in the redesigned network.
Figure 2 depicts optimization results for BuyPC, Inc.. This graph shows how total logistics cost varies with the number of warehouse locations. It clearly illustrates the trade-off between warehouse related costs and transportation cost. The consequence of having just one or two warehouses is excessive transportation cost. Too many orders are shipped using one-day air service. Conversely, having much more than five warehouses results in excessive inventory and brick-and-mortar costs. A five-warehouse network represents a good compromise and minimizes total logistics cost.
Figure 3 shows the optimum five-warehouse network, including product flow and ground service time-in-transit. This new network costs $15 million annually, a savings of $4 million (about 20%) from the original network. Table 2 shows the source of the savings. With fewer warehouse locations, transportation cost increases by $2.9 million. However, warehouse fixed costs and inventory carrying costs decrease by a combined $6.9 million. Clearly, the savings in warehouse costs more than compensates for the increase in transportation costs. BuyPC, Inc. will now ship about 44% of orders using air service.
Table 2: Summary of revised logistics costs.
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Port to Warehouse Shipping Cost
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$783,328
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Warehouse to Customer Shipping Cost
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$5,899,685
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Warehouse to Customer Variable/Holding Cost
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$7,679,331
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Warehouse Fixed Cost
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$625,000
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TOTAL COST
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$14,987,344
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Decreasing ground transportation costs
Note that the Los Angeles warehouse has a particularly large service area. Los Angeles serves some customers, including locations in the Dakotas, which are actually closer to the Chicago warehouse. This may not make sense unless one considers inbound transportation costs. Intuitively, it is more costly to ship a one-day air package to Sioux Falls from Los Angeles than from Chicago. However, the inbound line haul cost to Los Angeles is much less expensive than the line haul cost to Chicago. With regards to total transportation cost, Los Angeles is the better choice for serving customers such as those in Sioux Falls.
Putting it all together
Network design software is a valuable tool in the design of optimal distribution networks. In our example, BuyPC, Inc. can redesign its network, substantially reducing logistics costs while maintaining a one-day service level. Software models allow you to incorporate all costs relevant to your supply chain. Typically, these models seek to minimize total logistics cost. However, by integrating carrier time-in-transit data with carrier rates, a model can minimize cost while meeting a desired service level, such as next-day delivery. Properly configured, the model is able to find the ideal number and location of warehouses and determine the proper mix of ground and premium services.
Companies striving to create a world-class supply chain are incorporating strategic supply chain planning into their core competencies. Those companies that continually analyze the structure of their network outperform their peers. BuyPC, Inc. should continually evaluate their network as the market, their products, and their customers change.
Michael S. Watson, Ph.D.: Vice President of Business Development. He has consulted on numerous network design projects in many different industries. This experience ranges from completing network design projects to teaching consulting firms how to build a network design practice. He is co-author of the article "Defining Perfect Distribution Channels" published in the April 2000 issue of Parcel Shipping & Distribution magazine.
He completed his Ph.D. at Northwestern University in Industrial Engineering and Management Sciences, specializing in production and supply chain management. He has worked for IBM as a management consultant in their Logistics Practice. He is adjunct professor at Northwestern University in the Master of Engineering Management program.
E-mail contact: Michael Watson
Jim Morton is a Manager within Cap Gemini Ernst & Young's supply chain consulting practice and is based in Atlanta. He has managed numerous projects that include operational assessment, business process reengineering, and technology implementation. His advice helps clients reduce cost, improve working and fixed capital efficiency, and achieve profitable growth. Within CGE&Y, Jim serves as the solution leader for Distribution Network Design for the Americas Region. He has a broad range of industry experience, encompassing supply chain operations, software development, and engineering R&D. His ten years of experience with United Parcel Service qualify him as an authority on motor and air freight. Jim holds both a Bachelors and Masters degree in electrical engineering and has been awarded three U.S. patents for developing technology that improves supply chain operations.
Contact Info: Jim Morton or 404-541-7278
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