Supported by Blue Yonder, Traxion Leads in Speed and Service
Company Size
1,000+
Region
- America
Country
- Canada
- Mexico
- United States
Product
- Blue Yonder transportation management
- Luminate Control Tower
Tech Stack
- Artificial Intelligence
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
- Platform as a Service (PaaS) - Connectivity Platforms
Applicable Functions
- Logistics & Transportation
Use Cases
- Predictive Maintenance
- Real-Time Location System (RTLS)
- Supply Chain Visibility
Services
- System Integration
About The Customer
Traxion is Mexico's largest logistics provider, with a fleet of 8,000 vehicles and over 1,000 customers. The company has grown 28-fold since it was founded in 2011, making it three times the size of its nearest competitor. Traxion operates in a rapidly growing market, with the Mexican third-party logistics market growing up to 25% per year even before the pandemic. The growth was further accelerated by the pandemic, with e-commerce in Mexico doubling in 2020, compressing three years of logistics demand into just one year. Traxion's customer base is growing, and with it, the requirements of the customers. The company needs to maximize its speed and responsiveness, while also controlling costs and ensuring profitability.
The Challenge
Traxion, Mexico's largest logistics provider, has experienced a 28-fold growth since its inception in 2011. With a fleet of 8,000 vehicles and over 1,000 customers, Traxion is three times the size of its nearest competitor. As Traxion's customer base grows, so do customer requirements. The company needs to maximize its speed and responsiveness, while also controlling costs and ensuring profitability. The Mexican third-party logistics market was growing up to 25% per year before 2020. The pandemic dramatically accelerated that growth, with e-commerce in Mexico doubling in 2020, compressing three years of logistics demand into just one year.
The Solution
Traxion partnered with Blue Yonder to implement its transportation management solution, as well as Luminate Control Tower, to gain real-time visibility across the internal supply chain and the extended partner network. The Blue Yonder’s transportation management solution enables Traxion to quantify savings and opportunities, balance service-level and cost tradeoffs, and prioritize execution. Traxion can evaluate network-wide performance, as well as troubleshoot disruptions, to drive reliability and savings. In its daily operations, Traxion benefits from Blue Yonder’s advanced routing, mode, container and service-level optimization with inventory awareness across the supply chain. Supported by artificial intelligence, the transportation management solution automates both execution and re-planning as conditions change. Luminate Control Tower provides Traxion with a unified view of events across its partner network. Critical alerts help planners anticipate disruptions in real-time and predict the impacts on inventory, production capacity and sales.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Remote Temperature Monitoring of Perishable Goods Saves Money
RMONI was facing temperature monitoring challenges in a cold chain business. A cold chain must be established and maintained to ensure goods have been properly refrigerated during every step of the process, making temperature monitoring a critical business function. Manual registration practice can be very costly, labor intensive and prone to mistakes.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Leading Tools Manufacturer Transforms Operations with IoT
Stanley Black & Decker required transparency of real-time overall equipment effectiveness and line productivity to reduce production line change over time.The goal was to to improve production to schedule, reduce actual labor costs and understanding the effects of shift changes and resource shifts from line to line.
