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Logistics Optimization through IoT: A Case Study of Chronopost International
Technology Category
- Application Infrastructure & Middleware - Event-Driven Application
- Sensors - GPS
Applicable Industries
- E-Commerce
- Transportation
Applicable Functions
- Logistics & Transportation
Use Cases
- Last Mile Delivery
- Transportation Simulation
The Challenge
Chronopost International, a member of the La Poste group, is a global provider of express shipping and delivery services. The company promises that all parcel deliveries in France will arrive by 1pm the following day after an order is placed. However, as demand continues to grow, especially during peak periods such as Christmas or Mother’s Day, Chronopost faced the challenge of ensuring they can always keep their promise and deliver parcels on time. The company needed a solution that would help them use and analyze historical data to optimize delivery operations and ensure delivery deadlines are met.
About The Customer
Chronopost International is a member of the La Poste group and provides express shipping and delivery services both domestically in France and internationally. In 2013, Chronopost transported 102.2 million packages in over 230 countries in Europe and worldwide. The company operates in the rapid parcel delivery industry and serves a global market. Chronopost promises that all parcel deliveries in France will arrive by 1pm the day following an order, a commitment that requires efficient and reliable logistics operations.
The Solution
Chronopost adopted DSS to create a custom application that automatically generates an ease-of-delivery rating for each address. The application takes into account historical internal delivery and retrieval data, analyzes and enriches shipping and delivery data via data aggregation by geographic location, and enables easy modeling of a rating for each delivery. The incorporation of new deliveries into the existing model allows for iteration and continuous optimization of production costs. This solution provided Chronopost with a comprehensive data analysis tool that optimized company processes and internal logistics.
Operational Impact
Quantitative Benefit
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