Panalpina’s new portal goes on display in Munich

Panalpina's chief commercial officer, Karl Weyeneth

Panalpina is launching its new customer portal at Transport Logistic 2019 in Munich on 3 June. It offers collaborative shipment management, fully automated instant quotation and lane risk assessment, features that make the portal unique in the industry, says the forwarder, which was recently acquired by Danish-based DSV. Customers will have the opportunity to test the customer portal in Munich before it is made available later this year.

“The customer portal enables collaborative shipment management that can be adapted to a company’s structure for ultimate customer centricity. This collaborative feature is an industry first. Customers and their external partners can work in remote teams on the platform and bring in their individual expertise at the same time,” explains chief commercial officer, Karl Weyeneth. “Our developers have created an intuitive platform in order to make shipping as easy as ordering a pair of shoes online.”

The portal allows Panalpina to provide market-proven instant quotes based on historical selling prices. Algorithms calculate prices in seconds, no matter how complex a shipment is.

Lane risk assessments based on data covering carrier capabilities, agent certifications, transport modes and warehouse facilities, allowing the forwarder’s pharma customers to more effectively qualify suppliers and assess risks during shipment planning and then choose between qualified suppliers.

The portal allows customers to explore shipment options, as well as control risks and costs even months before a shipment. When the shipment takes place, customers can see all their shipments and relevant data at a glance and in real time on the platform.

Panalpina has also integrated a new analytics function that allows customers to pull tailored reports directly from the portal.

Karl Weyeneth added: “We are already working on additional features such as machine learning for quotation, a sophisticated chatbot and big data analysis,”

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