Cheep, a global provider of supply chain solutions, is now focusing on the digital transformation of its business, which includes improving its pallet recovery processes and its call center operations in Lisbon, Portugal. Outside Europe, the company is running similar projects in the United States and Brazil.
Madrid. As Alfonso Martin, Director of Asset Productivity at Cheap Europe, explained: “A year ago we launched the Predict project as a first step in adopting a data-driven asset recovery approach. Using machine learning technology, in combination with data from our manufacturers, carriers and retail customers, we have developed algorithms that generate weekly tasks for our call center agents.
“The tool manages collection at more than 100,000 locations and in the last year alone has contributed to increasing pallet recovery to 500,000 units, improving supply chain efficiencies and promoting sustainability,” says Martin.
Chepe’s relaunch of Pooling Systems aims to improve upon a global pooling solution that is already a leader in the sector, while developing new capabilities across the company and identifying new opportunities to generate value for its customers. does. It all hinges on a digital transformation that will harness the power of data and digital capabilities. By combining all this with fundamental business principles such as reuse, resilience and regeneration, Cheep is once again leading the way as a pioneer for the supply chains of the future.
Christian Carrasco, Director of Asset Productivity Process Transformation, Global, explained that “We are developing a detailed process map of all activities handled by the call center, which allows us to identify areas of improvement that serve as the basis for transformation Will Work” .
“The transformation of the call center is based on three pillars: the first is improving customer satisfaction. All our customers, whether internal or external, expect the same level of service. And the third is to achieve efficiency, which includes optimizing processes and speeding up problem resolution”, Carrasco elaborated.
