Abstract: Features related to systems and methods for predictive estimation for network inventory planning for items for distribution through a multi-echelon network are disclosed. The problem may be modeled to account for demand for an item that may be satisfied by fulfillment centers within the network. The model considers benefits to ensuring adequate inventory to meet expected demand streams along with any savings accruing from a lower transfer and salvage costs.

Abstract: Embodiments herein are directed to determining an expected demand for an item. The specialized computer system can model an impact to an expected demand for the item between a current planning horizon and a next planning horizon, including an estimated leftover demand to be fulfilled during the next planning horizon. As calculated, this leftover demand may be less than an unfulfilled demand from the current planning horizon and may be estimated based at least in part on the unfulfilled demand and on historical leftover demand between planning horizons.

Abstract: Techniques for generating a decision to store units of an item may be provided. The units of the item may be offered from a network-based resource. For example, a first ordering channel and a second ordering channel may be provided to facilitate orders of the item from the network-based resource. The first and second ordering channels may allow random orders and deterministic orders of the item, respectively. Additionally, a value of a look ahead window associated with the second ordering channel may be accessed. The value may shift a time for an automatic generation of a deterministic order. Further, a first loss and a second loss may be computed based on the value. The first and second losses may be associated with losing a random order and losing the deterministic order, respectively. The decision may be generated based at least in part on the first loss and the second loss.