Network Design

Design supply chains that balance cost, speed, and resilience

Supply chain networks designed by spreadsheet miss interactions between tiers, ignore capacity constraints, and cannot evaluate disruption scenarios.

16% landed cost reduction

The problem

Why this decision becomes expensive without structure

Supply chain networks designed by spreadsheet miss interactions between tiers, ignore capacity constraints, and cannot evaluate disruption scenarios.

Spreadsheets and manual planning break down when constraints interact. Generic AI tools lack the structural matching needed to produce usable, reviewable outputs. This use case needs a decision workflow that fits the problem shape, not a one-size-fits-all answer.

Typical use cases

Where this solution fits

Multi-tier sourcing and distribution optimization

Greenfield vs brownfield network design

Nearshoring and reshoring scenario analysis

Capacity allocation across production sites

Outputs you receive

Decision-ready outputs for this use case

Mongeflow packages this work into stakeholder-ready output layers and premium export formats.

Optimal network structure
Cost breakdown by tier
Disruption scenario analysis
Capacity utilization report

Benchmark context

16% landed cost reduction

Ernst et al. (2004) EJOR

Where this solution is used

Related industries

ManufacturingRetailCPGAutomotive

See this workflow inside Mongeflow

Explore how Mongeflow turns this operational problem into a structured decision path with clearer outputs, assumptions, and handoff.