Case Studies > Logistics

How a Global Logistics Company Cut Track-and-Trace Data Processing from 50 Minutes to Under One with a Custom Cloud-Based TMS

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    Business Impacts

    01

    45-50 Minutes to Under 1 Minute Now!

    Time to move track-and trace data through pipeline has reduced from 45-50 mins to less than one

    02

    Easy, Efficient Forecasting

    Confluent's platform utilizes real-time and historical data for enhanced predictive analytics

    03

    Flexible Kafka Deployments

    Cloud-native Kafka solution with flexible deployment across major clouds

    Overview of Client

    Based in Arco, Italy, this global logistics leader offers extensive road, freight, air, and sea services, delivering tailored supply chain solutions worldwide. Amid fierce industry competition, they sought to enhance reporting and reduce operational latency. This case study details their transformation using Confluent Kafka, achieving substantial business improvements.

    Challenges

    The logistics provider faced several challenges that threatened its competitive edge and operational efficiency:

    Difficulty in reducing latency in data reporting.

    Complexity in normalizing diverse data formats.

    Challenges in integrating operations seamlessly into the cloud.

    Need for precise forecasting using historical and real-time data.

    Struggle to enhance operational efficiency amidst complex logistics infrastructures.

    Solutions

    To address these challenges, the logistics provider implemented a comprehensive, cloud-based transportation management system (TMS) with event-driven architecture and Confluent Kafka as the foundation. The solutions included:

    Custom-built TMS

    Cloud-native Kafka solution

    Unified data management

    Predictive analytics

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