Matt Harding

Warehousing historically hasn’t been a particularly exciting topic. But times have changed. Thanks to technological innovations, warehouse automation has made the receiving, housing, and distributing of goods truly fascinating stuff. At Supply Chain Now, we spotlight companies doing exciting things throughout the industry. In modern warehousing, the innovations garnering attention include systems integrations involving robotics, automation, and artificial intelligence (AI); the use of optical character recognition (OCR) technology in yard management; an “elegant” automated storage and retrieval system (AS/RS); and a solution called Chuck. Warehousing at a Crossroads: Innovation for Efficiency “The warehousing industry is experiencing a technological revolution, with advancements in automation, robotics, IoT, AI, and data analytics transforming operations and driving efficiency. These innovations are not just enhancing operational capabilities but are also paving the way for smarter, more connected, and efficient warehouse environments,” an October report by Taiwan-based logistics property developer ALP said. ALP said AS/RSs, automated guided vehicles (AGVs), and robotics “are at the forefront of the smart warehousing revolution. These systems enhance efficiency, reduce labor costs, and improve accuracy.” AI and Robotics: A New Frontier for Modern Warehousing A Forbes Council post in November said that “one of the most visible impacts of AI and…

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…