Abhishek Gupta

At the Gartner Supply Chain Planning Summit in Denver, Scott Luton caught up with Rob Haddock, a seasoned supply chain practitioner and advisor with Demand Chain AI, to discuss the persistent planning challenges organizations face—and why maturity, discipline, and optimization still matter more than buzzwords. Demand Chain AI blends consulting services with advanced supply chain technologies, focusing on optimization across trade promotion management, demand sensing, supply planning, and detailed production scheduling. Haddock’s role centers on helping organizations strengthen business processes—particularly sales and operations planning (S&OP), performance reporting, and the practical application of technology to improve execution on both the demand and supply sides.   A Practitioner’s Perspective on Planning Gaps Haddock’s perspective is shaped by decades spent inside large, sophisticated supply chain organizations. Early in his career, he worked within an iconic, global beverage company where advanced planning environments were already in place—though, in hindsight, he admits those tools were sometimes underutilized. Today, Haddock spends much of his time working with small and mid-sized organizations that haven’t been as fortunate. In many of these environments, planning maturity is still low, foundational practices are missing, and—unsurprisingly—Excel remains the primary planning tool. “Basic business practices that have been around since the 1990s…

Special Guest Blog Post written by Deborah Dull   Imagine it’s launch season in your supply chain, and a team of AI agents is hard at work: coordinating shipments with suppliers, allocating inventory, and handling a missed delivery. It’s hard to go a day without hearing about the latest AI headlines: new LLMs, new applications, new use cases. These discussions are part of my every day. Business leaders and IT teams are eager to explore – and they have a lot of questions… and apprehension. In these discussions, we have found one framework that lands consistently: consider AI agents like new hires, not new software.   Step 1: Hire Like You Mean It Just like hiring humans, this step is about defining what you need. The first decision is the purpose of the role: what problems are you trying to solve? Where are your people overwhelmed? Where is your business growing in coming months? From here, the next decision is to build the business case just like you would for a new headcount. For example, consider the ROI of having a digital employee who can process supplier performance data 24/7. Now, decide on the type of agent that will join…