Load optimization – increase utilization, reduce costs

Half-full cargo spaces are not a “minor annoyance,” but a structural cost driver: more trips, more CO₂, more hustle and bustle – and in the end, still too little capacity. In many organizations, it is not the will that is lacking, but the foundation: reliable rules, consistent data, and a process that truly supports loading decisions.

Load optimization addresses precisely this issue: it makes cargo space utilization measurable, plannable, and operationally controllable – from load planning to the decision of “does it fit or not?”.

Typical problems that load optimization solves

• Typical problems solved by load optimization
• Unclear utilization: “Feels full” replaces measurement – this creates safety reserves and empty space.
• Manual load planning: Excel, experience, and time pressure – results vary depending on shift, location, and person.
• Complex constraints: Dimensions, weights, stackability, stability, unloading sequence, load securing – everything has to fit at the same time.
• Short-term changes: Ad hoc orders, reloading, route changes – without reliable information, it becomes a gamble.
• IT disconnects: Loading planning runs “alongside” WMS/TMS/ERP instead of being integrated – this negates the effect.

What cargo space optimization means in practice

Cargo space optimization is more than just “packing better.” It is a combination of:

1. Planning logic

Loading plans are calculated algorithmically—under real constraints such as weight, stability, stackability, and unloading sequence.

2. Operational integration

Results must be usable in everyday life: roles, processes, responsibilities – and a clear process for exceptions.

3. Data on the actual status

If you want to improve reloading, ad hoc orders, or ongoing route decisions, you need information about the actual loading status—not just the plan.

4. Integration into the system landscape

Optimization only has a lasting effect if it is part of the data flows in WMS/TMS/ERP (instead of a parallel world).

PUZZLE® – Loading plans that work in everyday life

Supports algorithmic loading and packing planning: order data and restrictions are used to create reliable loading plans and packing patterns – as a basis for reproducible decisions instead of “Tetris in your head.”

CargoSight – making free capacity visible

Supports the recording of the actual loading status: photos make free cargo space or remaining volume traceable. This makes decisions on reloading, additional orders, and route adjustments much more reliable.

EfficientCargo – recording and optimizing in tandem

Supports real-time decisions: when actual data and optimization logic come together, it is possible to continuously check what still fits – including constraints such as sequence, weights, and stability.

(Details can be found on the respective product pages.)

• Utilization (volume/weight) per tour, truck, container, swap body
• Transports per order/per shipment/per ton
• Proportion of “reloading possible” vs. “not possible” (with justification)
• Planning time per loading decision (before/after)
• Damage and complaint rate (stability, load securing)