Logistics today faces more than one cost-related challenge. Fuel costs, fleet maintenance and a shortage of drivers are compounded by unstable demand. In the fourth quarter of 2025, European contract rates for road transport rose by 3.1 per cent year-on-year, although spot rates fell by 3.3 per cent. At the same time, there was a shortage of around 444,000 lorry drivers across Europe. For Poland, the stakes are particularly high. In 2024, domestic hauliers accounted for almost one-fifth of the total freight volume across the European Union. In this situation, technology only makes sense if it reduces the cost of uncertainty. A delayed delivery means more than just extra kilometres. It also means downtime, overtime, unused warehouse slots, safety stock and poorer customer service.
The problem does not end on the road. The World Bank’s latest Logistics Performance Indicators model, based on real-world shipment data, shows that high unpredictability is concentrated, amongst other places, in ports, transhipment points, at borders and inland checkpoints. More important than yet another system
Order and cargo details have the greatest impact on cost. Weight, dimensions, number of pallets, temperature requirements, exact addresses and delivery windows determine the choice of vehicle, consolidation, route and handling time. An error in a single field can result in the wrong vehicle being dispatched, an empty run or a redelivery attempt.
It is no coincidence that Eurostat’s transport statistics include load weight, distance, kilometres travelled with and without a load, fuel consumption and space utilisation. These figures are directly linked to fleet productivity. Additionally, there are event-based data: the actual times of collection, departure, arrival, start of unloading and completion of delivery. Equally important is the reason for any deviation from the plan. It is this information that reveals where the delay is actually occurring.
The GS1 EPCIS standard describes supply chain visibility through several fundamental questions: what, when, where, why and in what condition. The truck’s location alone will not explain whether the driver is waiting for a loading bay, a document, an inspection or for the goods to be prepared. The group combines telematics with external data. A vehicle’s location and speed must be cross-referenced with traffic volume, accidents, weather, road restrictions and queues at borders. Research into journey time forecasting shows that data on incidents, demand, precipitation, visibility and wind improve predictions compared with using speed alone. There is also data on the availability of drivers, vehicles, loading bays, warehouse space and stock. This data not only helps to identify a problem, but also enables decisions to be adjusted – such as rescheduling a load, selecting a different warehouse, combining orders or booking a new delivery slot.
Where technology saves time
The greatest impact is felt before departure. Integrating data from order, warehouse and transport systems allows for better utilisation of load capacity, reduces empty runs and enables realistic route planning.
During transit, dynamic estimated time of arrival forecasts and automatic exception handling provide real value. The system should not merely display a delay; it should trigger an action: a route change, a change of loading bay or early notification of the consignee.
A third area concerns data transfers between companies and public authorities. The EU’s eFTI Regulation is set to replace some paper documentation with standardised electronic information. From January 2026, platforms and service providers can begin preparing for implementation. Full implementation of the regulations will begin on 9 July 2027. The European Commission estimates the sector’s potential operational and administrative savings at €1 billion per year. ek
In logistics, it is not all data that is valuable, but rather the data linked to decision-making. First, you need to organise the load parameters, addresses and time slots. Next, record actual events, stops and exceptions. Only on this basis can artificial intelligence, route optimisation and predictive forecasting reduce costs.
In the face of mounting pressure, the advantage lies not in the most impressive app, but in the smallest difference between planned and actual delivery times. Technology streamlines logistics when it changes operational responses, rather than simply creating yet another screen with a map.
