Alex Pradhan

In a rapidly evolving global supply chain landscape, SAP’s David Vallejo believes the most exciting innovations are happening in planning—and that the industry is entering a fundamentally new era. At the Gartner Supply Chain Planning Summit 2025 in Denver, Vallejo, who leads global product marketing for SAP’s supply chain portfolio, joined Scott Luton to discuss how planning is transforming, why data now sits at the center of competitiveness, and what SAP is doing to help organizations make faster, more confident decisions.   A Shift From ERP-Centric to Data-Centric Vallejo described his team’s role as one that constantly scans the market—identifying trends, customer expectations, and the problems companies will need to solve next. Those insights help shape new innovations across the SAP ecosystem. He noted that SAP has moved decisively from an ERP-centric worldview to a data-centric one. This shift is essential, he argued, because the biggest advantage in modern planning lies in having the right data—clean, connected, contextualized, and ready to drive decisions. As Vallejo put it, “It’s all about the data that I need to make better planning decisions.”   Planning Models Are No Longer Static Reflecting on how planning has evolved since he entered the field two decades…

Special Guest Blog Post written by Dr. Johannes Hangl with e2open   AI is no longer an experiment in global trade compliance. It’s already being applied in product classification, document-to-declaration workflows, risk targeting, and sanctions screening. At the same time, regulators and customs authorities are adopting AI themselves. This is raising expectations for data quality, transparency, and governance across the entire trade ecosystem. With the EU AI Act set to apply from August 2026, companies that have not yet implemented human-in-the-loop controls, drift monitoring, and defensible audit trails are running out of time to close the gap.   Where AI is already adding real value today: HS and ECN classification   Product classification has become one of the most practical AI use cases. Modern tools can now suggest harmonized system (HS/ HTS) and export control (ECCN) codes, explain the rationale, and attach confidence scores and audit metadata to each decision. This direction mirrors what customs authorities are doing. Administrations such as German Customs have discussed using machine learning to improve targeting and risk detection. It appears both sides of the border are moving toward data-driven decision support. AI does not remove accountability. It changes how accountability is exercised.   Practical…