Abstract: Examples relate to managing node inventory levels are disclosed. An example may involve: obtaining historical data of items at a node in a network for a past time period; generating a supply chain lead time variability for an item at the node based on the historical data; generating a demand variability for the item at the node based on the historical data and the supply chain lead time variability; generating, based on the supply chain lead time variability and the demand variability, a recommended inventory level of the item in the node for a future time period; and transmitting the recommended inventory level to a computing device associated with the node for inventory arrangement in the future time period.

Abstract: Systems and methods for inventory placement and demand allocation of items in a retail fulfillment network are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, a recommendation request regarding a plurality of nodes in a retail fulfillment network; obtaining feature data based on the recommendation request; computing, using at least one machine learning model, recommendation data based on the feature data, wherein the recommendation data indicates at least one recommendation regarding inventory placement and demand allocation among the nodes in the retail fulfillment network; and transmitting, in response to the recommendation request, the recommendation data to the computing device.

Abstract: Systems and methods for predicting buffer values are discussed. A quantity data value is retrieved from a database for a receiving location associated with a processing location. A lower buffer value and a higher buffer value are predicted for a period of time based on received lower and higher confidence values and an effective lead time. The effective lead time is determined from the total processing time and a delivery time from the processing location to the receiving location. The lower and higher buffer values indicate a quantity in addition to the present quantity data value to meet variations in the demand value. A buffer data value is received that is more than the lower buffer value and less than the higher buffer value, and an order request is automatically generated and processed for supplying the buffer data value to the processing location.