Air Cargo Vision

Space saving experts set up air cargo unit

Revenue-optimisation specialist Wiremind has launched a dedicated air cargo business unit, aimed at helping operators get the best use out of their capacity.

The software and data-science company, which was established in 2014 with a focus on optimising systems mainly for the transport and logistics industries, launched its SkyPallet solution in 2017. The ULD and flight optimisation system that aims to address the imbalance in essential operational knowledge across air cargo teams, the lack of continuity between sales and operations processes, and the fact that airline pricing strategies often overlook the volume factor despite its critical impact on margins.

The software as a service (SaaS) solution offers a 3D planning view and manages capacity through advanced heuristics – in other words, a custom function that selects the best solution on a given dataset, applying rule-based logic. Unique algorithms take into account the respective regulations for special products, carry out weight and density checks for heavy cargo, and ensure smart capacity optimisation to minimise space loss.

With the Covid pandemic putting unprecedented pressure on available air cargo capacity, its efficient use is more crucial than ever. However, capacity management is not easy given that shipments come in all shapes, sizes, and commodities, and travel in varying aircraft types. Bookings do not always match what is actually delivered to the airline, and space wastage, as well as the risk of having to leave shipments behind, is inevitable.

Wiremind says that it now has over 1200 SkyPallet users in 100 countries and has been adopted by operators such as Emirates, Atlas Air, United, Qantas, ECS Group, and Chapman Freeborn.

Chief commercial officer, Nathanaël de Tarade, said: “There is huge potential for further digitalisation in air cargo, yet the industry currently lacks data science expertise at the right level. We know that it can certainly benefit from similar technology, such as deep learning models, for example, that we have successfully deployed on large-scale projects in several industries. Therefore, we have already doubled the size of our air cargo team, and aim at tripling it within the coming months.”

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