Dave Wheeler

At the 2025 Gartner Supply Chain Planning Summit in Denver, Scott Luton sat down with Fred Baumann, Senior Industry Principal at Kinaxis, one of the world’s most recognized leaders in supply chain planning and orchestration. Kinaxis has spent over four decades shaping the planning landscape and has been named to the Gartner Leaders Quadrant an extraordinary 11 consecutive times—a testament to its execution strength and long-term vision. Baumann’s role at Kinaxis centers on helping chief supply chain officers and senior leaders shape their strategic transformation roadmaps, quantify value, and build the business cases necessary to achieve breakthrough outcomes.   From Episodic Disruptions to Continuous Turbulence When asked about old and new challenges facing supply chain planning teams, Baumann observed a major shift: disruption is no longer episodic—it’s continuous. Historically, companies faced major disruptions every few years. Today, volatility and constraint-related challenges—whether driven by tariffs, sourcing changes, geopolitical shifts, or supply shortages—are unfolding weekly or even daily. This environment demands a new way of working. The speed of global business is accelerating, and uncertainty is at historic highs. As Baumann noted, organizations must now adjust their supply chains “much faster than they had to even last year.” The shift isn’t only…

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…