Customs Compliance Conference Report: Data analytics for operational efficiency and cost savings

Sean Mahan, Dusseldorf

Last week SEIA GmbH took part in the Customs Compliance in Europe Conference in Düsseldorf. The event brought together senior trade compliance experts, policy specialists, and industry practitioners who are shaping how European companies respond to regulatory change. Topics ranged from the EU Customs Reform to the operational impact of rising tariffs and the future of data-driven compliance programs. The discussion was especially relevant given the speed at which regulatory expectations and geopolitical pressures now affect daily customs operations.

One recurring theme throughout the event was the tension between strategic ambition and operational reality. Panels on duty savings, EU deforestation regulation and non-preferential origin highlighted that even sophisticated companies struggle with data availability, process integration, and system alignment. Many speakers stressed that compliance functions cannot meaningfully support corporate strategy if the underlying data landscape is unreliable.

This topic was addressed in the joint presentation delivered by SEIA's Marcus Brenscheidt and Sartorius' Mathias Krug, titled “Data analytics for operational efficiency and cost savings in customs – or – Don’t fear bad data.” The presentation focused on a problem every major company knows but often finds difficult to address: data quality issues that prevent reliable customs declarations and create avoidable cost and risk. Rather than treating bad data as a technical inconvenience, the presentation framed it as a core compliance duty. Trade compliance teams must be able to demonstrate that declarations are based on accurate and consistent information, and they need the tools to verify this continuously.

The presentation outlined three key arguments:

1. First, that poor data quality is usually structural rather than accidental, stemming from decentralized material creation processes, inherited legacy systems, or acquisitions that never integrate fully.

2. Second, that the regulatory impact is real. Misclassified products, missing origin data, and valuation inconsistencies translate into operational delays, higher duty costs, and elevated audit exposure.

3. Third, that companies need practical tools that meet their data where it currently is rather than assuming ideal conditions.

   
   

SEIA showcased how its PERCEIVE assurance layer connects disparate trade, ERP, and broker data to detect gaps early. This approach enables targeted remediation while shipments are still in production rather than when goods are already at the border. A practical example illustrated how data analytics can prevent operational disruption in real export environments. The scenario focused on a company that relies on a logistics partner to consolidate multiple daily deliveries into bulk export shipments. Missing HS codes for even one product created hold-ups affecting hundreds of items, which in turn delayed departures, raised storage costs, and triggered manual rework by the compliance team. By applying early-stage risk identification, the company was able to detect missing or inconsistent customs data within one day of order intake, enabling corrective action long before goods reached the warehouse gate.

The conference made clear that the next stage of customs compliance will not be defined by new rules alone but by how companies handle the data foundations beneath their daily decisions. SEIA will continue to support organizations that want to move from reactive gap handling to structured data-driven oversight. Bad data should not be feared, but it must be measured, understood, and managed as part of core compliance work.

We hope you will join us next year in these important conversations, or look forward to seeing you at another event soon.

Check out SEIA upcoming events here.