Monica Truelsch

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…

Last month, we launched Between the Lines, our Supply Chain Now book club, with a simple idea: the best leaders don’t just consume headlines, they read deeply, think critically, and stay curious. The response to our first edition reminded us how powerful shared learning can be! This month, we’re building on that momentum with fresh selections designed to challenge perspectives, spark new ideas, and strengthen the way we think, innovate, and navigate an ever-evolving global landscape.   Check out a few of the selections the Supply Chain Now team recommends from February 2026:   Scott Luton: The 2028 Global Intelligence Crisis from Citrini Research Imagine a short-term future where the very technology we hail as humanity’s next great productivity engine becomes essentially the source of a global economic crisis. “The 2028 Global Intelligence Crisis” from Citrini Research is a thought experiment that projects just such a scenario: by 2028, rapid and widespread AI adoption has supercharged productivity yet hollowed out the consumer economy, driving unemployment above 10% and triggering a deep market downturn as traditional spending collapses despite booming output. In this speculative, but unsettling, framework, AI doesn’t fail, it succeeds so overwhelmingly that the economy it was meant to…