Designing high-performing, modern networks


As market demands continue to shift at an unprecedented pace, businesses depend on advanced logistics network planning. This approach allows for continual digital supply network analysis and optimization to keep pace with increasing business pressures. Esri's logistics technology, enriched with artificial intelligence and machine learning, helps firms digitize end-to-end logistics tasks—from network design to distribution site planning and service-level gap analysis. Global logistics providers benefit from greater insights into network performance, higher customer service levels, and lower costs.

End-to-end logistics site and network analysis

Distribution center and warehouse siting

Analyze an integrated set of sites and dynamic market potential to see where to expand or reduce investments. Conduct advanced suitability analysis to understand demand trends and optimally site distribution centers, logistics parks, and warehouses. Identify the most suitable sites from a set of candidates, as defined with a set of individually weighted criteria.

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Logistics network planning and optimization

Design well-defined, market-specific territories that optimize processes and improve response times and customer satisfaction. Define territories based on forecast numbers, by tonnage, and by industry. Locate underperforming zones and determine why they underperform, predict how proposed changes will impact performance, and use multiple data sources to allocate the best network resources.

A graphic of a computer monitor displaying a dashboard with a colorful route map, sets of data analysis, and bar graphs

Distribution coverage area and gap analysis

Optimize fulfillment coverage by modeling demand and capacities to quickly assess service levels at any location and expose gaps automatically. Use machine learning to run forecasts and plan for business peaks at different times of the day, week, or year to gain insights that will inform customer outreach efforts before failure occurs.

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Logistics and the digital supply network

Aggregate and digitize network data for end-to-end logistics task modeling to analyze and propose improvements across the global supply chain operations. Simulate the coordination of movements using all logistics assets and influencers to visualize optimal network design and optimize processes not visible in traditional supply chain management.

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ARTICLE

Modeling the flow of dangerous goods by rail


Commodity flow maps provide an easy-to-understand visual context for complex data analyses. They analyze data spatially for safety assessment.

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