Charles Chase is the executive industry consultant and trusted advisor for the SAS Retail/CPG global practice. He is the author of Next Generation Demand Management: People, Process, Analytics and Technology, author of Demand-Driven Forecasting: A Structured Approach to Forecasting, and co-author of Bricks Matter: The Role of Supply Chains in Building Market-Driven Differentiation, as well as over 50 articles in several business journals on demand forecasting and planning, supply chain management, and market response modeling. His latest book is Consumption-Based Forecasting and Planning: Predicting Changing Demand Patterns in the New Digital Economy. To learn more, please see his Author page.
Almost everyone enjoys a good glass of wine after a long day, but did you ever stop to wonder how the exact bottle you're looking for makes its way to the grocery store shelf? Analytics has a lot to do with it, as SAS demonstrated to attendees at the National
How do you explain flat-line forecasts to senior management? Or, do you just make manual overrides to adjust the forecast? When there is no detectable trend or seasonality associated with your demand history, or something has disrupted the trend and/or seasonality, simple time series methods (i.e. naïve and simple
There's been a lot of hype regarding using machine learning (ML) for demand forecasting, and rightfully so, given the advancements in data collection, storage, and processing along with improvements in technology. There's no reason why machine learning can't be utilized as another forecasting method among the collection of forecasting methods
