Ryan Schreiber

Special Guest Blog Post written by Philip Vervloesem   If your supply chain planning still runs on a monthly cycle, 2026 will be uncomfortable. We are operating in a polycrisis where change is constant, and responses need to be fast enough to keep up. From customer conversations, industry research, and leadership discussions at the Gartner supply chain conferences, a clear pattern has emerged: the organizations pulling ahead are not planning more often. They are embedding agility, intelligence, and speed into the way they make decisions. Here are five predictions shaping supply chain excellence in 2026 – our “bingo card” for what’s now table stakes.   1. Continuous, always-on planning is a must Monthly or quarterly cycles are no longer enough. The organizations that outperform treat planning as a continuous capability embedded in daily operations, and make it part of their governance and operational excellence. Imagine this: a sudden surge in demand hits or a supplier flags a delay. Instead of waiting for the next planning cycle, teams immediately evaluate options, share insights across functions, and adjust course. Planning stops being a calendar exercise and starts shaping real-time decisions.   “By shifting from process-centric to decision-centric planning, we now run hundreds…

At Gartner Supply Chain Symposium/Xpo 2026 in Orlando, some of the sharpest minds in supply chain gathered to tackle one central question: what does the next operating model for supply chain actually look like? In a special livestream conversation, Scott Luton sat down with Mike Griswold, VP Analyst at Gartner, alongside fellow Supply Chain Now hosts Karin Bursa and Jake Barr, to unpack the biggest themes emerging from this year’s symposium. The consensus? Supply chain leaders are moving beyond AI fascination and toward something much bigger: redesigning how decisions, workflows, and organizations operate.   AI Is No Longer the Story. Outcomes Are One of the strongest themes from the event was a more mature, pragmatic approach to AI adoption. According to Mike Griswold, many organizations are finally moving past the “shock and awe” phase that dominated conversations a year ago. “People need to figure out exactly what problem or problems AI is going to solve for them,” Griswold explains. That may sound simple, but it represents a significant shift. Instead of experimenting with AI for AI’s sake, companies are becoming more disciplined about identifying operational value and measurable business outcomes. Griswold also warns against a familiar trap: creating “highly efficient…