Share:

Federico Gomez

More

August 28, 2020

This Week on Supply Chain Now: August 24th – 28th

What a week at Supply Chain Now! If you missed an episode, get a quick summary and listen here. On Monday, we published an excellent episode with Jon Gold, the VP of supply chain and customs policy at the National Retail Federation. Supply Chain Now · “The Voice of Retail: Jon Gold with the National Retail Federation”   On Tuesday, Scott & Greg welcomed two APICS legends to the podcast, Anthony “Z” Zampello & Fred Tolbert, for a lesson in S&OP fundamentals and best practices.   Supply Chain Now · “S&OP Fundamentals & Best Practices: Anthony “Z” Zampello & Fred Tolbert”   On Wednesday, we published this week’s Supply Chain Buzz, with an update on Hurricane Laura from Riskpulse Chief Meteorologist Jon Davis, and then covered the top news in supply chain with Kara Brown and Will Haraway with Lead Coverage.   Supply Chain Now · “The Supply Chain Buzz for August 24th Featuring Jon Davis, Kara Brown, & Will Haraway”   On Thursday, Greg welcomed Flourish CEO Colton Griffin to the TECHquila Sunrise podcast for a great conversation on the ins and outs of founding a tech company, the start-up life, and the cannabis industry.   Supply Chain Now…
global supply chain
February 3, 2026

The Value of a Data-Driven Approach to Demand Sensing and Forecasting

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…