Logistics firms hit by messy data

Logistics companies are finding that artificial intelligence projects often stop at the same place: messy records that machines cannot reliably read. (elmercantil.com) At a logistics event on Tuesday, April 14, in DFactory Barcelona, executives from DHL Supply Chain, Linde Material Handling and Damm said they had to standardize data before they could use artificial intelligence in real operations. DFactory is a 17,000-square-meter Industry 4.0 hub in Barcelona’s Zona Franca. (elmercantil.com) (zfbarcelona.es) The problem is basic: if one system writes an address, product code or transaction one way and another system writes it differently, an artificial intelligence model reads them as different things. Damm’s Fernando Gordo said the brewer had to standardize all its data, do extensive manual work and build data infrastructure “from scratch” to run these projects. (elmercantil.com) That cleanup work sits behind the flashier uses of artificial intelligence in logistics, such as route planning, demand forecasting and warehouse control. Boston Consulting Group said on March 27 that logistics providers are focusing on operational use cases, but only 10% report measurable financial impact so far. (bcg.com) Recent industry surveys put data quality near the top of the obstacle list. Trimble’s Transportation Pulse Report 2026, based on more than 230 responses in the United States and Europe, said poor data quality was the biggest barrier for 57% of carriers and for more than half of shippers. (transportation.trimble.com) The issue is not only inside one company. Víctor García of Kion Group said many obstacles come from data governance, because logistics moves through multiple companies, systems and handoffs that all record the same shipment differently. (elmercantil.com) That is why logistics groups keep talking about “visibility” and “intelligence” in the same breath. FedEx said in its 2026 Future of Logistics Intelligence Report that teams often use three or more systems to manage shipments, while disconnected systems and manual workarounds slow decisions and create backlog. (fedex.com) Large operators are still investing. DHL Group said in its 2025 annual report that digitalization, automation and standardization are key levers, and that artificial intelligence is increasingly being used in customer service, customs clearance, fulfillment and service logistics. (group.dhl.com) Kion has been building out that push in Barcelona. The German group said its Digital Hub at DFactory is its first center outside Germany and is meant to develop sensing, connectivity and artificial intelligence tools for intralogistics. (zfbarcelona.es) For logistics companies, the first artificial intelligence project is often not a model or a chatbot. It is the slower job of getting every location, item and shipment record to mean the same thing everywhere. (elmercantil.com)