- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
- Consumer Goods
- Logistics & Transportation
- Warehouse & Inventory Management
- Public Transportation Management
- Real-Time Location System (RTLS)
- Data Science Services
- System Integration
A Global 50 Consumer Packaged Goods (CPG) company had no system in place for real-time monitoring of inventory in-transit, leading to late or non-delivery for customers. Inaccurate Estimated Time of Arrivals (ETAs) reduced cross-docking efficiency. Manual check calls to carriers, drivers, and customers were time-consuming and error-prone.
Consumer Packaged Goods (CPG)
About The Customer
The customer is a Global 50 Consumer Packaged Goods (CPG) company that averaged 25,000 North American truck shipments per month. They had a new cross-docking network but struggled with inaccurate ETAs and lack of real-time information.
Savi implemented Savi Visibility™, an in-transit tracking and ETA solution. Electronic Data Interchange (EDI) and telematics feeds were collected from truck carriers, and a feed was set up with the CPG's Transportation Management System (TMS). Savi's machine learning platform used AI to predict ETAs accurately. The Savi Visibility user interface provided real-time status and predictive alerts. ETAs and alerts were sent to users and the ERP system for synchronization.
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