Quick ROI: Pathway improved significantly the precision of container gate-out ETAs (Estimated Time of Arrival). The optimization of individual terminal operations contributed to a speed-up in handling times of containers and reduced business and environmental costs.
CMA CGM
CMA CGM is one of the largest shipping companies in the world, specializing in maritime transportation and logistics. It operates a vast network of shipping routes that connect major ports worldwide and provides comprehensive logistics solutions, including door-to-door transportation, customs clearance, warehousing, and distribution services. It also operates terminal facilities in key ports, providing efficient handling and storage solutions for cargo.
The Business Case
Pathway and CMA CGM initially started working together on a use case related to smart ports, and more specifically to container gate-out ETAs. The operational objectives were associated with improving the fluidity of gate-out containers, and truck traffic to contribute to the terminal's performance. The use case initially focused on France's leading port - Marseille Fos - which accommodates nearly 9,000 ships and handles 75 million tonnes of goods each year.
A key topic for companies like CMA CGM is to deliver the best customer experience possible. The growth of global maritime traffic has induced terminals’ saturation: with larger volumes being traded, waiting times at terminal gates have dramatically increased, and have introduced friction into the customers’ supply chains. Clients need to anticipate when to pick up their containers and they often are feeling a lack of transparency, visibility, and reliable information on the status and the estimated date for pickup of their containers, making proactive decision-making significantly harder.
Every day of delay in transit puts us in a little more trouble because we have all the resellers pushing us to always have even more stock.
It's vital for us to be able to anticipate as much as possible and iron out any kinks with our partners sufficiently in advance if we're faced with a delay.
The initial goal of the collaboration, before extending to other use cases, was thus related to visibility of supply chains for end clients of CMA CGM to enable them to anticipate changes by providing them with strategic, reliable, and real-time information, to better adapt to volatilities of transport. This was part of a larger ongoing initiative around more innovative supply chains and smart ports, integrating various technologies, such as the Internet of Things (IoT), artificial intelligence (AI), big data analytics, and automation.
The container shipping sector is a competitive industry and one of the major challenges is related to container flow optimization. Pathway was used to automatically process the data and to predict the container ETA forecasting at the container level.
- ETAs are calculated for containers, not ships
- Real-time evaluation of the chance of delay, with precision increasing during the journey
- Takes into account risks related to transshipments
- Uncovers and takes into account real-time port statistics
The ability to perform advanced data transformations, including machine learning with small latency makes it possible to unlock the massive value hidden in the logistics data. One of the key pain points of logistics tech leaders right now is the ability to align numerous event streams together to get a clear & up to date understanding of operations. When we asked some of logistics top executives "what's at stake", their answer was clear: the bottom line.