Unlocking Landside Optimization for Road Feeder Services

AI Cargo

As European air cargo networks increasingly rely on trucking for a significant share of uplift, landside inefficiencies are no longer a minor operational nuisance, they are a structural risk to hub performance and service reliability. In this edition of our interview series "5 Questions To", Sara Van Gelder, Director of Products at Nallian, explains why landside optimization is particularly challenging for Road Feeder Services (RFS), what needs to be in place for RFS flows to become as predictable and transparent as local deliveries, and the importance of structured data, coordinated planning, and local operational flexibility.

1. Why is optimizing landside operations for RFS more difficult than for local deliveries?

RFS trucks look similar to local forwarder trucks, they use the same docks, people, and warehouse space. The difference lies in predictability and data visibility. Local forwarder pick-ups and deliveries can be scheduled, and data shared and validated upfront via a landside management system. Long-haul movements are often managed through manual scheduling, email notifications, or phone calls. Handlers frequently indicate that only around half of expected RFS cargo movements are clearly visible in their cargo management systems in advance, based on FFM or FBL data.

This lack of information introduces uncertainty into landside operations, quickly affecting queue times, turnaround times, and service reliability. In other words, RFS may look operationally similar to local deliveries, but it behaves fundamentally differently. The variability and fragmented data flows make structured planning far more complex.

"RFS may look operationally similar to local deliveries, but it behaves fundamentally differently. The variability and fragmented data flows make structured planning far more complex."

2. What are the operational consequences of this lack of predictability?

You cannot optimize what you cannot see. Ground handlers don’t have a complete picture of RFS pick up or deliveries until a truck arrives landside. That makes it difficult to prepare shipments, allocate dock doors, or balance workloads. In practice, landside teams end up reacting rather than planning - dealing with queues, last-minute changes, and inconsistent performance.

Because much information is still being shared late or incompletely, front desk staff need to spend time manually reconciling email notifications from trucking companies with attached PDF documents (such as triplists), cargo management system data (such as FFMs and FBLs), and optional slot scheduling. A single unannounced or delayed RFS arrival can ripple into missed export cut-offs, rebooked shipments, and sudden warehouse congestion. What appears to be a “truck delay” quickly becomes a network reliability issue.

"You cannot optimize what you cannot see. Ground handlers don’t have a complete picture of RFS pick up or deliveries until a truck arrives landside."

3. What is needed to optimize RFS landside operations?

Landside optimization means aligning truck arrivals, dock allocation, cargo readiness, and staffing through shared planning and reliable data. Slot booking, dock planning, and capacity management all rely on knowing who is coming, when, and with what cargo. Today, a significant share of RFS shipment information is still shared via emails or spreadsheets. That data exists, but it’s not usable for automation.

Without standardized, automated data-exchange, landside optimization simply can’t scale. So you need a consistent digital process, but one that leaves enough flexibility to reflect local realities, such as warehouse layouts, staffing models, customs constraints, or traffic delays. Optimization only works when standardized data flows are combined with local operational flexibility. The goal is not rigid centralization, but predictable coordination, enabling milestone visibility, early discrepancy detection, and exception-driven operations instead of reactive firefighting.

"Without standardized, automated data-exchange, landside optimization simply can’t scale. So you need a consistent digital process, but one that leaves enough flexibility to reflect local realities."

4. How can this be achieved?

RFS operators working across multiple airports need consistent digital processes, while handlers must still reflect local realities such as warehouse layouts, staffing models, or customs constraints. Nallian is running a pilot that brings together ground handlers, airports, airlines, and trucking companies to validate how automated slot booking and structured data exchange can work across different operational environments.

The project will pilot a standard API with several trucking companies, enabling them to request a slot booking, in an automated way between their transport management systems and landside management solutions. This will reduce reliance on manual data exchange via email. In this automated slot booking, truck flight references can be cross-checked against the FFM and FBL data in the handler’s cargo management system, and discrepancies flagged in an intuitive overview.

These are early steps. Next phases include dynamic slot updates based on traffic data, driver rest regulations, and real-time operational changes, further closing the gap between planned and actual movements. The ambition is to move from static slot reservations to synchronized truck-flight coordination.

5. What changes when RFS operations are optimized landside?

More consistent landside coordination delivers clear operational and human benefits across air cargo hubs. Better planning reduces truck idling, an important cost driver. Air Cargo Week recently cited that “European research showed that idle time can quickly add up to 65-85€ per hour when labour, fuel, and equipment are considered”. It also eases congestion and improves warehouse utilization. With improved scheduling, airlines and ground handlers can manage time-critical export flows more predictably and avoid sudden workload peaks caused by unannounced or delayed RFS arrivals.

Just as importantly, digital landside optimization shifts the focus for operational staff: instead of manually reconciling data and trying to manage stressful bottlenecks in peak time, teams gain the flexibility to concentrate on exceptions and customer interaction, while the system takes care of automatic matching, slot planning, and routine coordination. It also improves driver’s experience, reducing waiting time and making long-haul operations more efficient in a market already facing driver shortages. This balance between automation and human oversight creates more stable operations, clearer performance insights for all stakeholders, and a more resilient, sustainable landside process for RFS traffic.

"Digital landside optimization shifts the focus for operational staff: instead of manually reconciling data and trying to manage stressful bottlenecks in peak time, teams gain the flexibility to concentrate on exceptions and customer interaction, while the system takes care of automatic matching, slot planning, and routine coordination."

Conclusion

Landside optimization for RFS is no longer a theoretical ambition, it is a competitive necessity. As volumes grow and European air cargo networks increasingly depend on trucking as a structural capacity, on-the-ground predictability becomes as critical as capacity in the air. When handlers, airlines, airports, and trucking companies align around shared visibility and landside management systems support a coordinated approach while leaving room for local operational flexibility, RFS flows can be managed with the same confidence as local deliveries, benefiting operations, people, and performance across the cargo ecosystem.

The next competitive differentiator in air cargo will not only be airside capacity, but landside coordination. The hubs that master RFS predictability will master the network.

This article is inspired by input provided by Nallian to Air Cargo Week. You can read their article here.

About Sara Van Gelder

Sara Van Gelder is Director of Products at Nallian, leading the design and implementation of our digital landside and yard management solutions. Previously with the Brussels Airport Cargo team, where she led the launch of BRUcloud, and at Kuehne+Nagel, she connects day-to-day cargo operations with scalable digital innovation.