Savi Technology (Lockheed Martin) > Case Studies > Improving In-Transit Visibility and Efficiency for a Global CPG Company

Improving In-Transit Visibility and Efficiency for a Global CPG Company

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 Improving In-Transit Visibility and Efficiency for a Global CPG Company - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Machine Learning
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Consumer Goods
  • Transportation
Applicable Functions
  • Logistics & Transportation
  • Warehouse & Inventory Management
Use Cases
  • Public Transportation Management
  • Real-Time Location System (RTLS)
  • Data Science Services
  • System Integration
The Challenge
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.
The Customer

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.
The Solution
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.
Quantitative Benefit
  • The CPG company achieved a 22% improvement in cross-docking efficiency, a 17x increase in ETA accuracy, and gained 350+ hours/week productivity per transportation lane. They were able to reduce safety stock and improve customer satisfaction through actionable insights and accurate shipment ETAs.

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