AI models can process thousands of factors simultaneously, including demand signals across multiple items, macroeconomic ...

The landscape of demand forecasting, data science and machine learning is rapidly evolving, as companies seek innovative approaches to handle the intricate intersection between technology and consumer ...

While demand planning accuracy currently hovers around 60%, DLA officials aim to push that baseline figure to 85% with the help of AI and ML tools. Improved forecasting will ensure the services have ...

Michael Amori is CEO and cofounder of Virtualitics. A data scientist and entrepreneur with a background in finance and physics. Accurate demand forecasting is the linchpin of effective inventory, cost ...

Researchers at Institute of Science Tokyo have developed a novel Group Encoding method that accurately forecasts electricity demand using only On/Off device data from building energy systems. Tested ...

What do the stock market and weather forecasting have in common? Here’s a clue: stocks are valued based on trend projections, whereas changes in weather are tracked using prevailing atmospheric ...

The Energy Systems Integration Group (ESIG) has released a report examining how utilities and planners forecast long-term electricity demand and distributed energy resources (DERs) in an era of rapid ...

The requirements for retail success don’t get much more basic than the ability to accurately forecast customer demand. Even a mom-and-pop bodega has to have a pretty good sense of how many people will ...