Herb Shear

At the 2025 Gartner Supply Chain Planning Summit in Denver, Scott Luton caught up with Justin Siefert, a familiar face in the supply chain community and a leader at John Galt Solutions, a global provider of end-to-end supply chain planning software. From demand and supply planning to inventory and S&OP, John Galt supports organizations across industries with the holistic capabilities needed to thrive in an increasingly unpredictable landscape.   A Company Investing in the Next Generation Before diving into industry trends, Siefert shared an update on one of the programs that sets John Galt apart: its supply chain scholarship program, which awards $10,000 to students pursuing supply chain degrees. This year’s cycle brought in a record number of nominations, with new winners set to be announced in January. It’s an initiative Siefert is proud of—and one that reflects John Galt’s belief in cultivating tomorrow’s leaders.   Old Problems, New Pressures: Planning in a World of Uncertainty When asked about the biggest challenges facing planners today, Siefert didn’t hesitate: uncertainty. While the forms of disruption change—pandemics, geopolitical shifts, demand shocks, evolving portfolios—the underlying challenge remains the same. Planners must anticipate what’s next and respond quickly, often in real time. “No day…

Special Guest Blog Post written by Chris Cunnane with InterSystems   Demand sensing and demand forecasting are both crucial aspects of optimizing supply chains, but they do have slightly different functions in their approach and focus. Demand sensing uses real-time data and analytics to identify and respond to immediate demand fluctuations, while demand forecasting uses historical data to predict future demand over a longer period (months or years). Different methods, such as statistical modeling and machine learning, are used to enhance the accuracy and adaptability of these processes. Both areas are crucial for companies when it comes to projecting sales, managing inventory, and coordinating replenishment. In the end, the goal is to accurately predict customer demand by using predictive models to forecast future demand. InterSystems surveyed 450 senior supply chain practitioners and stakeholders to examine key supply chain technology challenges, trends, and decision-making strategies across five key use cases: fulfillment optimization; demand sensing and forecasting; supply chain orchestration; production planning optimization; and environmental, social, and governance (ESG). This blog focuses on demand sensing and forecasting.   Current State of Demand Sensing and Forecasting According to the survey results, when asked how they currently forecast demand, 36% of respondents indicated that…