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Real-Time Shipment Tracking Implementation at Magnus Logistics
Technology Category
- Analytics & Modeling - Machine Learning
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Transportation
Applicable Functions
- Logistics & Transportation
- Sales & Marketing
Use Cases
- Supply Chain Visibility
- Transportation Simulation
Services
- Data Science Services
The Challenge
Magnus Logistics, a leading logistics service provider in the Baltics, was facing a significant challenge in their operations. With customer expectations constantly evolving in the supply chain and logistics world, Magnus recognized an opportunity to further digitalize operations to improve the level of service offered. A visibility gap existed across their transport operations, for own fleet as well as sub-contracted services. This made it difficult to anticipate delays and impossible to warn customers in advance. Without this information, customer satisfaction could be jeopardized and financial penalties incurred. Furthermore, many large scale customers required shipment tracking of some kind within RFPs, creating an opportunity cost associated with lack of visibility.
About The Customer
Established in 2007, Magnus Logistics is a leading logistics service provider in the Baltics and currently manages a fleet of 1000+ trucks delivering over 200 loads per day and operating throughout the entire European Union. In 2015, the Lithuania-based company also expanded operations into Poland, opening a subdivision in Warsaw. The company made more than €50m in sales revenue in 2020 with a freight volume of 61,000 units. Magnus’s management systems have been awarded international accreditations in ISO9001, ISO14001 and AEO, SQAS and are trusted by some of the world’s most recognizable brands. The logistics provider has also been ranked in the top 6% of companies in Lithuania for reliability and economic stability.
The Solution
To address this challenge, Magnus Logistics implemented a real-time transport visibility platform, Shippeo’s platform. This platform offered Magnus a way to fill the visibility gap and lift overall capabilities to the next level. Real-time location data collected gives Magnus full visibility across their transport operations, including sub-contractors, eliminating the need to manually chase deliveries. This automated freight control process is therefore also much more cost-effective. The platform analyzes the location data collected and uses sophisticated machine learning algorithms, created by an in-house data science team, to provide predictive ETAs with market-leading accuracy and reliability. These are shared automatically with customers in Magnus-branded notifications, ensuring they remain up-to-date with the latest information on their deliveries.
Operational Impact
Quantitative Benefit
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