Dr. Lisa Williams

Inside the reverse logistics education gap and the economic blind spot keeping it invisible Special Guest Blog Post written by Deborah Dull   Tony Sciarrotta has been asking the same question at industry conferences for years. As the Senior Director of Circularity and Reverse Logistics at the National Retail Federation, he knows what answer he’s going to get. But he keeps asking anyway. “Anybody in here go to school for returns management, reverse logistics, circularity? Any degrees in those fields the room?” It’s rare that anyone raises their hand. “That’s what’s wrong with our industry,” Sciarrotta told me at NRF Rev this January, the first conference under NRF’s new reverse logistics banner. “We still need to fix it.”   The Numbers That Should Make Headlines Here’s what makes reverse logistics so fascinating: the scale is staggering, but the infrastructure to support it needs to be stronger. According to the National Retail Federation, American retailers processed approximately $890 billion in returns in 2024 which is roughly 17% of all retail sales – and it’s higher for ecommerce. But that number almost certainly understates reality. “We have a fragmented industry,” Sciarrotta explained. “Where are all those returns going? It has to be…

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…