XCargo

Say goodbye to guesswork! Now it’s possible to nail down precise delivery times based on production status. Data generated from production and logistics enable simulations that help avoid risk and optimize capacities.

Customers, manufacturers, suppliers, warehousers, carriers, consignees: Running a supply chain means orchestrating smooth interactions among the various players and their IT systems. Cloud-based platforms help avoid dissonance by offering flexible options for access and integration through EDI interfaces, web services, web accounts, or mobile devices. What used to be bi directional connections become multi directional communications networks in which information is always available to the very people who need it so that they in turn can ensure smooth processes.

In this world, data provides the infrastructure for smart supply chains and the collaboration between human beings and machines. Such infrastructures are smart only when they go beyond satisfying customer needs to meet increasingly strict environmental goals. Lawmakers are not the only ones who expect polluters to pay. Port authorities are charging higher demurrage for ships that darken the skies with the emissions from the heavy fuel oils they burn. Consumers are punishing businesses that act irresponsibly. Stock prices erode when environmental scandals come to light.

When production stalls, it gets expensive. Assembly lines come to a standstill, resources remain unused, delivery deadlines slip. The chain of negative events often has far reaching and unpredictable consequences for manufacturers and their customers.

The supply chain is a delicate structure – a mosaic of relationships that link worlds. We are constantly reminded of just how vulnerable this organism is by the steady trickle of ominous new developments that threaten it: supply problems that bring semiconductor production to a standstill, a pandemic that stops supply chains in their tracks, severe weather incidents that cause regional bottlenecks, labor strikes that create traffic gridlock.

The more reliably companies are able to answer questions relating to the future and to decisions that need to be made, the more successfully they will be able to perform in the market. But how close do they really get to the ideal solution that they desire when using all of the available analysis tools? And how can this solution be implemented in real life with as few risks as possible?