From booking estimate to loaded truck: why better shipment data beats extra fleet capacity in construction logistics.

Construction consolidation centres (CCCs) collect deliveries from many suppliers at an off-site hub and send them to the building site in fuller, coordinated truckloads. Pilots across Europe report far fewer site arrivals, but they assume the hub knows exactly what it is shipping. In practice suppliers book their delivery slots months ahead, while drawings are still changing, so the declared volume and weight of each load is an estimate. When the real load turns out larger than booked, a truck leaves overloaded or an unscheduled vehicle has to be sent, which undoes the savings the hub was meant to deliver.

The EaSiCon project develops a digital twin that gives a real-time virtual representation of construction processes and their connected supply chains, supporting tactical and operational planning to improve efficiency and sustainability. This article presents research into truck planning between a consolidation centre and its construction sites, which examines how uncertain shipment volumes and weights cause overloads and which measures absorb them best. A route planning model was combined with a simulation that replays each plan thousands of times with realistic deviations, using a delivery scenario developed with logistics specialists at VolkerWessels.

Full trucks leave no room for error

Planning software fills every truck as close to its limit as possible, so that as few vehicles as possible are needed. Once real loads replace the booked estimates, a plan without margin turns fragile. Trucks planned right up to capacity regularly leave overloaded, and on most days at least one back-up vehicle is needed. Routes that keep even a little spare capacity almost never fail.

Weight is the limit that breaks first. Axle limits are usually reached well before deck space runs out, and weight overloads are the hardest to remove.

City sites are more exposed than rural ones

The same ten-house delivery was planned for an inner-city site and for a set of rural projects in Groningen. Both plans use the same number of trucks, yet the city schedule overloads more often and needs about twice as many unscheduled vehicles. The cause is not geography itself but how full the trucks are. When all material goes to one site, every truck can be packed to its limit. In the rural case loads fan out across several villages, so trucks are grouped by location, and that leaves small pockets of unused space. Those pockets make rural plans more forgiving before any buffer is added.

A few routes and one product family carry the risk

Overloads are highly concentrated. Two or three routes per plan cause most of them, while lightly loaded trucks practically never fail. Prefabricated elements such as concrete wall panels, precast stairs and timber façade cassettes account for most of the excess weight, followed at a distance by scaffolding and finishing materials. Fleet-wide measures therefore spend most of their effort where little risk exists.

Better data beats bigger buffers

A small capacity buffer, leaving one or two percent of each truck deliberately unfilled, removes nearly all volume overloads. Weight is less forgiving. A very small weight buffer can even increase overloads by letting the planner reshuffle heavy loads onto one truck.

The strongest lever is data quality. When the uncertainty in booked volumes and weights is narrowed, overloads drop sharply and excess weight all but disappears, without a single extra truck. Larger or smaller trucks change how many vehicles are dispatched, not how likely a route is to overload. Splitting the day into separate delivery slots lowers overloads only by adding trucks and kilometres in advance.

Conclusion and recommendations

A consolidation centre delivers its benefits only if the plan still holds once the real load is on the dock. Practitioners can reduce overload risk most effectively through:

• tighter volume and weight declarations from suppliers
• a one to two percent capacity buffer on every truck
• a higher buffer and load balancing for prefab-heavy trucks
• weight checks before departure on known high-risk routes
• more conservative buffers at urban hubs than at rural ones

These results tie directly to the aim of a construction digital twin. The more accurately shipment data flows from supplier to hub, the less spare capacity planners need to hold back, and the closer a consolidation centre comes to its promise of fewer trucks and fewer empty miles.

For more information, please contact:

Ragnar Klabbers

Ivo Agricola

Kees Jan Roodbergen

Michael Dienstknecht

Jeroen Laarman