Peggy Gulick

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…

written by Chris Cunnane with InterSystems   Supply chains have never been more complex or more exposed to disruption. From geopolitical instability and extreme weather to labor shortages and shifting demand, organizations are operating in a constant state of uncertainty. In this environment, basic visibility is no longer enough. Companies need the ability to monitor products in motion, understand their history, and act quickly on reliable data. That is where track and trace becomes essential. Track and trace technology enables organizations to follow products across the supply chain in real time and trace their full history from origin to destination. It connects data from barcodes, RFID tags, IoT sensors, telematics systems, and enterprise applications into a unified view. When supported by a modern data platform, this information becomes more than operational detail. It becomes a foundation for smarter decisions.   Move from Visibility to Action Many organizations have invested in visibility tools, but visibility alone does not solve problems. Knowing that a shipment is delayed is useful; knowing how that delay will affect downstream production, customer commitments, and inventory levels is far more valuable. Track and trace capabilities, when paired with analytics and decision intelligence, help companies shift from reactive…