KLM: AI Cargo

After participating in a Design Sprint with colleagues from the Cargo department of KLM, workload prediction system has been created. The artificial intelligence team developed a model, which is based on historical data, that can predict the incoming cargo to Schiphol Airport.

Some attendees in the Design Sprint were also end users. They thought it had a lot of potential, but they admitted that they were not that tech savvy. In other words, we want a simple application where I can fill in my interests and a simple result will pop out.

Therefore, I created a first prototype to this case. Users can fill in their wishes, such as their unit, day of operation (deadline for shipping) and a time window. When that is filled in, the user receives a graph where the prediction model does its work. The graph’s look and feel is still work in progress, this is a raw output from the prediction tool.