Case of use

Solistica – Planning Intelligence


With the implementation of Machine Learning models oriented to logistics operations, the allocation of vehicles for distribution was optimized. With the website you can monitor the entire operation in real time. 


Solística took between 5 and 10 hours to plan without taking into account all the variables. It is required to implement a platform that solves the problem of assigning vehicles to the demand of FEMSA, in order to deliver a list considering variables such as real-time location, occupancy status, displacement, loading/unloading point service window, capacity and traffic.


Development of a SaaS solution with a web page in which the administrative configuration, control and visualization of the operation is carried out, a mobile application for drivers, data repositories and control panels in the cloud of Google cloud that allows extracting, transforming, storing, processing and analyzing the necessary inputs to meet the requirement. 


Planning and massive assignment of vehicles in less than 1 hour in real time, replanning during the process, data repositories for the elaboration of control panels based on own metrics and indicators, fulfillment of service windows at origin and destination, decreasing by one 8% the time and Control of the execution and information of the assigned trips without calls. 

Now it is possible to inform the client (Coca Cola Femsa) and the cargo supplier (Solistica) of the current status of the operation in real time for decision making.

About the Client

Solistica is a leading company in Latin America in comprehensive logistics solutions, with extensive experience in distribution and storage services that allows us to offer a service guarantee, cost reduction and full visibility in supply chains to face the challenges and complexity of the Colombian model. and LATAM. 

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