Facility Location & Network Optimization

Too many companies choose their next warehouse or factory based on familiarity, like cities they know from business travel or regions where they want to grow. These may be reasonable starting points, but where you place your facilities is among the most strategic decisions an organization can make. A poor choice locks in excess transportation expenses, limits customer service levels, and constrains your network for years.

We take a different approach. Supply Velocity applies facility location optimization modeling to determine the best placement of warehouses, factories, and distribution centers across your network. Rather than relying on intuition, we use mathematical methods to evaluate every candidate site against your actual demand patterns and service requirements.

The Facility Location Problem: Cost Versus Service

The facility location problem is fundamentally a tradeoff between expense and service. Adding more facilities generally improves delivery speed to customers, but it also increases overhead - smaller facilities cannot allocate fixed expenses across as many units as larger ones.

This tradeoff is called the efficient frontier. A low-expense network design may sacrifice service levels, while a high-service design drives up operating spend. The worst outcome is a high-expense, low-service configuration. Without proper analysis, that is exactly where many companies end up.

Supply Velocity helps you find the right point on this frontier, where your network can minimize transportation costs and operating expenses while still meeting a delivery time constraints for every customer. We build models that solve the facility location problem (often called the FLP) mathematically, so you can make data-driven decisions instead of guessing.

How We Model the Facility Location Problem

Our approach follows a structured modeling process. We build a mixed-integer program, a type of optimization problem that evaluates candidate sites, assigns customers to facilities, and identifies the solution that maximizes profit or minimizes operating expenses. Commercial and open-source solver tools handle the computation, but the real value is in how the model is constructed.

Model Inputs

• Candidate locations — including current sites and potential new openings
• Inbound and outbound shipping expenses — based on actual carrier rates and distance
• Outbound delivery times — to calculate service level feasibility
• Operating expenses per site — rent, labor, utilities, and overhead at various capacity levels
• Inventory holding expenses — which vary by facility size and volume
• Customer demand data — order frequency, volume, and geographic distribution

Decision Variables and Outputs

The model determines which facilities to open, what size each should be, and how to assign customers to the closest facility. It can also determine which supplier locations should serve each chosen site. Each variable in the model represents a specific decision: keep or close a facility, assign a customer to a given warehouse, route inbound freight from a particular supplier.

The Objective Function

We typically frame the objective in one of two ways:

1. Maximize profit — captured revenue minus all operating, transportation, and facility expenses. This approach accounts for competitor positions and market share.
2. Minimize total expense — transportation, inventory, and cost of opening and operating each facility. This is the right formulation when market demand is fixed.

Constraints

The most important constraint is the delivery time requirement. Additional constraints may include capital investment limits for opening new facilities, capacity of each facility, and minimum volume thresholds. The capacitated facility location problem, a common variant, explicitly limits how much demand each site can handle.

What Makes Our Approach Different

Supply Velocity does not hand you a solver license and walk away. Our consultants build and run the model with your team, then translate the results into actionable recommendations.

After the initial solution, we run extensive sensitivity analyses to test how results change when transportation costs rise, demand shifts to a new region, or a candidate site construction or rental expense increases. This ensures the final recommendation is resilient across a range of plausible scenarios, not just tuned to today's assumptions.

We also integrate this analysis with broader supply chain network design. The network includes your facilities, your suppliers' operations, and your customers' locations, analyzing any one element in isolation misses the full picture.

With 190+ clients served and 900+ projects completed since 1998, we bring deep operational experience to every engagement. Our partner-led team has applied these techniques across manufacturing, distribution, retail, and food and beverage - industries where the distance between warehouse and customer directly impacts profitability.

When to Consider Facility Location Optimization

Not every company needs a full network redesign. But if any of the following describe your situation, this type of analysis can deliver measurable ROI:

• You are opening new facilities and need to identify the best site from multiple candidates
• Your distribution expenses are climbing and you suspect the current network is suboptimal
• Customer service levels are slipping because facilities are too far from key demand zones
• You have acquired or divested business units and need to consolidate or expand your network
• You are a carve-out from a bigger firm's divestiture and you will have limited access to their facilities.
• Your supply chain has grown organically without a formal inventory and network strategy

Each of these scenarios involves the same core facility location problem: where to place facilities so that total operating and logistics expense is minimized while maintaining acceptable service.

Frequently Asked Questions

What Are the Key Factors Affecting Facility Location?

Facility location decisions depend on transportation costs (both inbound and outbound), labor availability and wage rates, proximity to customers and suppliers, real estate expenses, tax incentives, and the capacity of each facility. We build all of these into the model as either inputs or constraints so the solution reflects your actual operating environment.

What Is Location Optimization?

Location optimization is a mathematical approach to selecting the best site for a warehouse, factory, or distribution center. It is a mathematical 'short-cut' through every feasible combination of candidate locations and customer assignments to find the optimal solution, the one that minimizes total expense or maximizes profit, subject to service-level and capacity constraints. Supply Velocity uses mixed-integer programming to solve these problems with precision.

What Are the 7 Keys to Facility Location?

The seven factors most commonly cited are proximity to customers, transportation infrastructure, labor supply, operating expenses, regulatory environment, proximity to suppliers, and quality of life for the workforce. In practice, the relative weight of each factor varies by industry. Our supply chain assessment process identifies which factors matter most for your specific network before we build the model.

Take the Next Step

A single facility location decision can lock in millions of dollars in operating expenses over a 10-year lease. We help you get it right the first time. Contact us to discuss how we can reduce your total network spend and improve service to your customers.