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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

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

Easy, Efficient Forecasting

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

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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