Supply Chain Network Optimization
Supply chain network optimization becomes more important as companies add facilities, products, customers, suppliers, and geographic markets. Without an enterprise-wide approach to allocating demand and capacity, organizations can experience imbalanced plant utilization, excess transportation costs, extended lead times, capacity constraints, and inconsistent service.
Implementation Engineers designs and implements supply chain network optimization solutions that determine how demand, production, capacity, inventory, and transportation should be balanced across the network. We work with client teams to translate network strategy into practical planning rules, decision-support tools, and operating processes that improve service while reducing cost-to-serve.
What We Implement
Production Network & Demand Allocation
Determine where products and customer orders should be produced across the network.
IE develops demand-allocation models that evaluate production capabilities, capacity, tooling, customer requirements, geographic considerations, and other operating constraints.
We implement processes that allow organizations to allocate demand across facilities based on enterprise objectives rather than individual plant priorities.
Capacity & Constraint Optimization
Balance demand with the actual capabilities of the production network.
IE evaluates available and required capacity across plants, production lines, equipment, labor, and other critical resources to identify bottlenecks and underutilized assets.
We help organizations understand where capacity exists, where constraints will limit performance, and how production can be redistributed to improve overall network utilization through capacity optimization.
Cost-to-Serve Optimization
Understand the true operational and logistics cost of serving customers.
Production cost alone does not determine the most profitable location for fulfilling demand. IE incorporates transportation, capacity, operating efficiency, service requirements, and other relevant costs into network decisions.
This allows organizations to evaluate trade-offs between production locations and establish allocation strategies that balance cost, capacity, and customer service through cost-to-serve optimization.
Scenario Modeling & Decision Support
Evaluate alternatives before changing the network.
IE develops models and decision-support tools that allow planners and leadership teams to evaluate different demand, capacity, production, and network scenarios.
What-if analysis can help determine the operational and financial impact of shifting production, changing demand patterns, adding or removing capacity, or responding to supply chain disruptions through supply chain scenario modeling.
Network Planning Integration
Turn network optimization into an ongoing planning capability.
Network optimization should not exist as a standalone analysis. IE integrates network allocation and capacity decisions into the organization’s broader planning processes, including SIOP, production planning, capacity planning, and inventory management.
We establish the roles, decision rules, data requirements, and planning routines required for teams to continue making enterprise-wide network decisions after implementation. This can include multi-plant production planning and distribution network planning where required.
Why Supply Chain Network Optimization Matters
The Closest Plant Isn’t Always the Best Plant
As manufacturing networks grow, production decisions are often influenced by historical assignments, local plant priorities, available capacity, or proximity to the customer.
Individually, those decisions can appear reasonable. Across an entire network, however, they can create significant inefficiency.
One plant may operate near its capacity limit while another has available resources. Products may be manufactured at facilities with higher production costs. Orders may travel farther than necessary. Capacity constraints can create longer lead times and service problems while available assets elsewhere in the network remain underutilized.
Supply chain network optimization creates an enterprise-wide view of demand, capacity, cost, constraints, and service requirements.
Instead of optimizing individual facilities, organizations can determine how the entire production network should operate to achieve the best overall business outcome.
The result is better utilization of existing assets, more informed capacity decisions, lower cost-to-serve, improved delivery performance, and a network better positioned to respond as demand and operating conditions change.
IX® in Action | Global Manufacturing
Optimizing Production Across a Five-Plant Network
A global manufacturer serving aerospace, electric vehicle, infrastructure, and networking markets operated five production plants with overlapping capabilities. Despite significant capacity across the network, there was no structured process for allocating demand to the optimal facility.
Orders were assigned based primarily on local decisions rather than enterprise-wide optimization. The result was imbalanced plant loading, extended lead times, unnecessary freight costs, and lost profitability.
Implementation Engineers implemented a production network optimization solution to determine how demand should be allocated across the company’s five plants to minimize cost, maximize throughput, and improve customer service.
Implementation included:
- An enterprise demand-allocation model to determine the optimal production location for each order.
- Capacity, tooling, and production-constraint integration.
- Identification of bottlenecks and underutilized assets across the network.
- Plant-level overload prevention.
- Outbound freight and cost-to-serve analysis.
- Evaluation of production-efficiency and delivery-performance trade-offs.
- Scenario modeling and what-if analysis.
- Integration of network decisions into the organization's standard SIOP process.
- Planner training to support ongoing data-driven allocation decisions.
Balanced
Plant Utilization
Lower
Cost-to-Serve
More Predictable
Delivery Performance
The implemented solution gave planners and leadership a structured way to make production-allocation decisions across the enterprise rather than optimizing facilities independently. By connecting demand with capacity, constraints, cost, and service requirements, the manufacturer established a more disciplined approach to utilizing its existing network and making ongoing production decisions.
Frequently Asked Questions
What is supply chain network optimization?
Supply chain network optimization evaluates demand, production, capacity, inventory, transportation, costs, and service requirements across facilities to determine how the overall network should operate.
How does network optimization reduce supply chain costs?
Network optimization helps identify the right production locations, reduce unnecessary transportation, improve capacity utilization, and balance production and service requirements to lower overall cost-to-serve.
Which factors are included in a supply chain network model?
A supply chain network model can include customer demand, production capabilities, capacity, labor, tooling, inventory, transportation, geographic factors, production costs, service requirements, and operating constraints.
How should demand and production be allocated across multiple plants?
Demand and production should be allocated based on enterprise-wide objectives, considering capacity, production capabilities, customer requirements, cost, transportation, constraints, and service needs rather than optimizing individual plant priorities.
What is cost-to-serve optimization?
Cost-to-serve optimization evaluates the total operational and logistics costs involved in serving customers, including production, transportation, capacity, operating efficiency, and service requirements.
How often should a supply chain network be reevaluated?
A supply chain network should be reevaluated when there are significant changes in demand, capacity, customers, facilities, products, suppliers, transportation costs, or geographic markets. Regular scenario reviews can also help organizations anticipate future network changes.