As an example, a server may receive and/or retrieve news items and process the news items using natural language processing to identify news related to entities (e.g., people, locations, and organizations) extracted from an enterprise resource planning system. A term frequency-inverse document frequency algorithm may be used to identify critical news items that may impact one or more supply chains associated with at least one product that is to be manufactured. A long short-term memory artificial recurrent neural network may be used to determine a confidence score for each critical news item. The confidence scores of the critical news items may be used to adjust replenishment planning and a master build plan that includes a plan to build the at least one product. In this way, news items may be used to automatically (e.g., without human interaction) adjust the master build plan.