Caitlin Roberson

At the Gartner Supply Chain Planning Summit in Denver, Scott Luton sat down with Caglar Ozdag, a supply chain leader at ZS. Known for its deep analytics and technology expertise across industries such as life sciences, airlines, consumer goods, and agriculture, ZS has become a trusted partner for organizations looking to elevate their planning and manufacturing performance. Ozdag leads the firm’s supply chain practice with a focus on planning from detailed forecasting through detailed scheduling. As a former practitioner himself—having led planning operations at large global enterprises—he brings a grounded, real-world perspective to the challenges facing today’s supply chain leaders.   Old Problems Persist—and New Ones Are Emerging When asked about classic and emerging challenges in planning, Ozdag didn’t hesitate: firefighting isn’t going away. From supply planning disruptions to last-minute schedule changes, firefighting remains a daily reality. “Life happens,” Ozdag noted. Plans rarely match reality, and organizations must constantly adjust. But today, a new layer has been added: AI uncertainty. Everywhere he goes, leaders are asking the same questions: “Is AI the right investment?” “Will the ROI materialize?” “Are we adopting the right tools, or just chasing hype?” This blend of enduring complexity and emerging skepticism has become a defining…

Special Guest Blog Post written by Matt McKinney, Co-Founder and CEO of Loop   I spend most of my time with supply chain and innovation leaders at major enterprises who are sitting on significant AI budgets but struggling to show measurable business impact in an increasingly complex and volatile supply chain environment.   These conversations have evolved dramatically. A year ago, executives were asking basic questions about AI feasibility. Today, the questions have shifted to strategic implementation at enterprise scale.   Based on hundreds of these discussions, three questions consistently emerge that separate companies making transformational progress from those stuck in pilot purgatory.   How do we move from AI experiments to enterprise-scale impact?   Most organizations have yet to see organization-wide, bottom-line impact from AI use. This is the strategic challenge keeping C-suite leaders awake at night.   The problem isn’t the technology. It’s the application of the technology. Too many enterprises are trying to treat AI like a magic wand they can bolt onto existing systems. But garbage in, garbage out. If your underlying data is fragmented and inconsistent, AI won’t solve your problems; in fact they’ll get worse.   At its core, anything automated is powered by…