The typical strategic logistics network design problem considers the number of warehouses required, customer service delivery requirements, the inventory investment required under alternative network configurations, inbound and outbound freight costs, and facility (i.e., warehouse) costs. Facility costs include labor, land, construction, taxes, and other regional location variables.
Developing the optimal network design strategy and configuration requires that a firm evaluate appropriate trade-offs between all pertinent cost and service variables. For example, the number and location of warehouses in a network (e.g., a domestic U.S. network) will impact the cost of inbound freight versus outbound freight. Typically, a network with many warehouses will have lower outbound customer delivery freight costs than will a network with one or a few warehouses.
On the other hand, inbound freight costs from plants and other supply points to warehouses may be higher in a network with many customer-facing DCs than in a network with one or two DCs located in close proximity to the major supply points. A good network study and strategy must examine these and all other trade-offs.
One key trade-off in logistics network studies and strategies that frequently does not receive enough scrutiny concerns the level of technology and automation planned in warehouse operations. The authors’ experience over several decades in logistics management suggests that too frequently firms approach a logistics study with either a “pre-determined” view of the type of warehouse to be employed in the network, or alternatively just a general concept of the capacity planned for a new warehouse.
The Pre-Determined Approach
The size of existing distribution centers and the technologies used in existing centers often shape this “pre-determined” view. Logistics planners first determine the basic facility layout, capacity and technology that represent their “standard” configuration for each DC in their network, i.e., a basic template or model for their DCs. Naturally, some variations in facility size and other variables will be allowed. However, the firm will establish a basic design and technology configuration for DCs in the firm’s network.
With this determination complete, logistics planners then turn their attention to the optimal number and locations of warehouses for their network. In this second stage of the network design problem, the firm conducts the standard trade-off analyses between freight costs, warehouse location costs (e.g., taxes and labor costs), finished goods inventory investment and carrying costs (as a function of the number of locations), target service levels, and so on.
Network Study Approach
When a firm designs its warehouse(s) after conducting a logistics network study, the opposite sequence occurs. First the firm performs its evaluation of freight, warehouse location and other logistics costs, and then the warehouse layout, technology and automation planning take place.
In either case, this two-stage, non-integrated network design approach can result in a sub-optimal overall network strategy. This happens because the cost, productivity and capacity implications that alternative warehouse technologies may offer are not integrated into the logistics network analysis. Instead, the one-time investment costs associated with different levels and types of technologies employed in a warehouse, and the differences in productivity levels and annual operating costs associated with different technologies and levels of automation, must be integrated into the network design stage. Only a fully integrated analytic methodology can correctly evaluate all the trade-offs and identify the optimal level of warehouse technology and automation for a logistics network, as well the optimal number of locations, capacities and service levels.
The Correct Approach: Strategic
What’s needed is an iterative, integrated approach to planning. Let’s assume a firm is just initiating a logistics network study. The study team consists of two sub-teams:
(a) A network design team and
(b) A warehouse design team.
The planning process proceeds as follows:
The network design team performs an initial evaluation of warehouse locations and warehouse roles based on the traditional factors previously cited.
Concurrently, the warehouse design team explores a range of warehouse layouts, technologies and capacities. Factors such as the type and configuration of storage systems versus labor requirements, height of storage systems versus warehouse floor space required, type of manually supported material handling equipment (e.g., lift trucks) versus more automated storage solutions, and manual versus automated picking and conveyance systems are evaluated.
The network design team then incorporates the warehouse design team’s results as inputs to a second round of network design evaluations. The network design team will simultaneously consider both potential warehouse locations and potential alternative warehouse designs and capacities. For example, multiple types of warehouses (more manual versus more automated) with multiple storage and picking capacity levels may be evaluated for one potential location in this phase. Scenarios with different numbers of warehouses and different technologies will also be considered.
The evaluation continues with as many iterations that may be required between the warehouse design team and the network design team until the teams identify the optimal, aligned network and warehouse designs.
Full Integration
In a fully integrated logistics network analysis, the opportunity to create a strategic advantage through improved service and reduced cost is much more likely, as the exogenous variables, such as labor rates, utility rates, taxes and freight costs, are balanced with the opportunity to use technology to control variable rates, such as the amount of labor and utilities required within the warehouse. This approach enables a holistic view and balances total logistic network annual operating costs, investment costs and service levels.
The integrated evaluation of all these variables yields solutions that can provide a strategic advantage for a firm and value for its customers.
Tan Miller is director of the Global Supply Chain Program at the Rider University College of Business Administration, and a member of MH&L’s Editorial Advisory Board. Steve Smith, PE, is engineering manager at Johnson & Johnson Sales & Logistics Company, LLC.
