Savi Technology (Lockheed Martin) > Case Studies > Global 50 Consumer Packaged Goods (CPG)

Global 50 Consumer Packaged Goods (CPG)

Savi Technology (Lockheed Martin) Logo
 Global 50 Consumer Packaged Goods (CPG) - IoT ONE Case Study
Technology Category
  • Functional Applications - Transportation Management Systems (TMS)
Applicable Industries
  • Food & Beverage
Applicable Functions
  • Business Operation
Use Cases
  • Inventory Management
  • System Integration
The Challenge

A Global 50 Consumer Packaged Goods (CPG) company averaged 25,000 North American truck shipments per month. Because there was no system in place for real-time monitoring of inventory in transit, operation team members were unaware of real-time disruptions, rendering them unable to avoid or mitigate late or non-delivery for their customers.

A new strategic cross-docking network was unable to realize high-efficiency targets because the inbound Estimated Time of Arrivals (ETAs) was inaccurate ─ reducing the number of goods that could be cross-docked. The Transportation Management System (TMS) and Enterprise Resource Planning (ERP) systems did not receive real-time information and rarely received shipment plan updates.

The Customer

Consumer Packaged Goods (CPG)

About The Customer

Consumer packaged goods, or CPG, refer to the space within an industry that features goods that consumers use in everyday life. These goods are produced on a large scale and generally have a short lifespan. CPG companies sell their goods to retailers, which in turn sell to consumers.

The Solution

Savi worked with this customer to implement Savi Visibility, our live streaming in-transit tracking, and ETA solution. The CPG company asked their truck carriers to send Electronic Data Interchange (EDI) and telematics feeds to Savi, while Savi set up an automated feed from and to the CPG’s Transportation Management System (TMS) to log planned shipments.

After ingesting the data from the carriers and the TMS, Savi’s massively scalable machine learning platform began to use Artificial Intelligence (AI) to build algorithms to much more accurately predict both inbound and outbound ETAs. The Savi Visibility user interface provides map, list, and reporting views of the real-time status of all shipments.

Predictive alerts, such as “Trending Late” and “Trending Early,” were determined using customer-specific thresholds of time, distance, and amount predicted late. Predictive ETAs and alerts were sent to users and the Enterprise Resource Planning (ERP) system, enabling synchronization between TMS, Warehouse Management System (WMS), and yard management operations.

Operational Impact
  • [Efficiency Improvement - Operation]

    Planners were able to focus on mitigating or avoiding disruptions of shipments that would otherwise have arrived late.

  • [Efficiency Improvement - Production]

    With a continuous live streaming view of all shipments in transit and real-time alerts for the 5-10% of shipments that required attention, the burden on operations diminished dramatically, making far fewer check calls necessary.

Quantitative Benefit
    • 22% improvement in cross-docking efficiency and orchestration
    • 17x increase in ETA accuracy
    • 350+ hours/week productivity gained per transportation lane

Case Study missing?

Start adding your own!

Register with your work email and create a new case study profile for your business.

Add New Record

Related Case Studies.

Contact us

Let's talk!
* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.

Thank you for your message!
We will contact you soon.