tampatra @ stock.adobe.com
A machine-learning algorithm designed to prepare the entire supply chain to ship items to geographical areas where end-users are expected to place an order. Overall, the algorithm predicts the next order and conditions the logistic framework based on previous purchasing activity. Products are usually stored closer to potential customers for faster shipping, or the final destination can be defined en route, eliminating the need for secondary storage.
The algorithm functions based on a forecasting model, real-time smart home data, and public data sources, such as product trends on social media or news stories, which predicts where an item would need to be shipped based on purchasing records. Identifying both the quantitative rise in interest in a topic and the context of that interest enables the system to make predictions about which fads could boom.