Network Optimization: Choosing the Best Location for Your Facility

Network optimization in supply chain management is all about strategically selecting the best location for warehouses, distribution centers, or manufacturing plants. The goal? Minimize costs, maximize efficiency, and improve service levels.

It’s a balancing act—factoring in transportation, inventory, production, and customer demand, all while navigating constraints like labor availability, regulations, and supplier proximity.

Key Factors in Facility Location Selection

1. Cost Considerations

  • Land & Real Estate: Purchase vs. lease costs
  • Labor Costs: Availability and wage rates
  • Taxes & Incentives: State and country tax structures, government incentives
  • Utility Costs: Power, water, internet connectivity

2. Transportation & Logistics

  • Proximity to Suppliers: Reduces inbound freight costs
  • Proximity to Customers: Lowers outbound shipping costs and lead times
  • Infrastructure: Access to highways, rail, ports, and airports

3. Market & Demand

  • Customer Locations: How quickly can you serve key markets?
  • Demand Patterns: Seasonal demand fluctuations, future growth potential

4. Operational Efficiency

  • Access to Skilled Labor: Availability of the right workforce
  • Technology & Automation: Can local infrastructure support advanced operations?
  • Supply Chain Resilience: Risks like geopolitical issues, natural disasters, or supplier dependencies

5. Regulatory & Environmental Factors

  • Zoning Laws & Permits: Government restrictions on land usage
  • Trade Agreements & Tariffs: Impact on import/export costs
  • Sustainability & ESG Goals: Carbon footprint, renewable energy sources

Approaches to Network Optimization

1. Center of Gravity (CoG) Analysis

Finds the optimal location by weighing customer and supplier locations based on demand volume.

Example: If 70% of your customers are on the East Coast, a facility in Pennsylvania might be more efficient than one in Texas.

2. Total Cost Modeling

Models fixed and variable costs—transportation, labor, inventory holding—to pinpoint the most cost-effective location.

3. Simulation & Scenario Analysis

Uses advanced tools like linear programming, machine learning, or supply chain simulation to test different location scenarios.

Example: What happens to costs if fuel prices rise by 20%?

4. Network Design Software

Top tools include Llamasoft (Coupa), AnyLogic, IBM ILOG CPLEX, and even custom-built Excel models. These help optimize facility locations, route efficiencies, and cost trade-offs.


Key Takeaways

  • Data-Driven Decisions: Avoid gut-feeling choices; use data models.
  • Balance Costs & Service: The lowest cost option isn’t always best if it slows deliveries.
  • Future-Proofing: Consider long-term trends like labor shifts and automation.
  • Leverage Technology: Use network optimization software for precise analysis.

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