Are you ready to become “hipper” with AI in Air Freight?

A good overview of the expected arrivals of shipments is essential for inbound operations, especially in the fast-moving Air Freight business. But there is more to the arrival of a shipment than the touchdown of its flight.

Imagine this: you are on your flight to your next vacation, and you hear the stewardess saying: “Ladies and gentlemen, please return to your seats and fasten your seatbelts as we prepare for landing.”

Upon landing, it typically takes around 30-60 minutes to retrieve your luggage from the baggage claim. So, if you have a friend waiting to pick you up, they might monitor your plane’s arrival on a flight tracking service (the ARR event). They will see the status of your arrival and the time you will land, but they still need an estimate on when you get your luggage. Most likely, you would simply call your friend once you have your luggage, but let’s go back to a shipment’s journey.

The Notified (NFD) event is equivalent to calling your friend to let them know you are ready for pickup. It is information DB SCHENKER receives from the ground handling agents, the third-party companies unloading and handling the shipments after the airplane’s touchdown. While the ARR event is quite common, and for example, available via third-party providers specialized in forecasting airplane arrivals, you will not find any third-party data or predictions on the NFD events. This gap needs to be filled in to provide the import operations managers of DB SCHENKER with transparency for further processing in their hub.

That is where the “HIP project” comes into play – an AI solution called Hub Inbound Prediction (HIP).

What lies beyond the arrival?

HIP seamlessly integrates information on incoming shipments from various platforms and enriches it with predictive analytics. This transparency brings clarity and enhances overall process stability, safeguarding against uncertainties, particularly during peak periods.

Let’s say a shipment’s flight is scheduled to arrive at 8:10 a.m., and HIP’s calculations predict a ground handling duration of 3 hours and 20 minutes for this shipment. DB SCHENKER can then forecast that the shipment is ready for further processing in the hub at 11:30 a.m., enabling more transparency, streamlining operations, and enhancing workflow efficiency.

Experience the “HIP” Factor

Based on several pieces of information available for a shipment (size, origin, day, and time of arrival) and other information such as ground handling agency utilization, DB SCHENKER developed an AI-based machine learning model to predict the required ground handling time. This ground handling time is defined as the time difference between the Arrival (ARR) and Notified event (NFD).

A chart about the HIP prediction model by DB Schenker

Combining the expected or already known time of arrival with the forecasted ground handling duration, DB SCHENKER can provide the estimated time of notification:

Predicted Notified event (NFD) = expected or actual Arrival (ARR) + predicted ground handling time.

By aggregating the NFD predictions for each shipment, the DB SCHENKER in-house Hub Inbound Prediction tool provides an overview of the expected, before-predicted, short-term workload. All are specifically tailored to one or a small number of hubs/gateways. It serves as a one-stop shop for information on incoming shipments.

A laptop computer screen showing the HIP prediction model by DB Schenker — © DB SCHENKER

Flying forward with HIP

“Hub Inbound Prediction (HIP) is a great enhancement for our Air Freight import operations. Predictability and transparency are two key aspects to enable smooth operational processes. With HIP, we now have full visibility of what is coming into our hubs and gateways, and when. Internally, this helps us to plan processes and capacities better. Externally, we can provide our customers with forward-looking information and accurate predictions on when they can expect their goods.” Björn Eckbauer, SVP Global Operations & Procurement Air Freight

While there may be areas for refining NFD predictions in the future, the current implementation of HIP represents a significant leap forward with AI solutions. It is a departure from relying largely on “gut feelings,” bolstering operational efficiency.

DB SCHENKER makes the future of Air Freight more “HIP,” one prediction at a time.