Abstract: Systems and methods are described herein for providing predictive user interface elements. A computing system may train a machine-learning model to identify issues that are likely being experienced by users contacting a customer service system based at least in part on historical user account data of a plurality of user accounts. When a request for assistance is received, user account data corresponding to the request may be obtained and provided to the model to identify issues likely experienced by a user. A number of graphical user interface (GUI) elements (e.g., “match cards”), each corresponding to one of the identified issues, may be generated, ranked, and presented in accordance with the ranking. Each GUI element may be selectable. Upon selection additional data likely to be pertinent to the selected issue may be presented alleviating a need to search for this data as would be the case in conventional systems.

Abstract: Techniques for generating a forecast associated with an item may be described. For example, the forecast may be generated based on simulations of supply and demand variables associated with the item over a planning horizon. The forecast may include at least one of: a labor forecast or a capacity forecast associated with inventorying units of the item in an inventory over the planning horizon. Further, real-time data associated with realizations of the supply and demand variables during the planning horizon may be monitored. At least a portion of the real-time data may be available from a management system. The management system may be configured to manage orders for the units of the item from the inventory. The forecast may be updated during the planning horizon based on the real-time data. The update may include changing the at least one of: the labor forecast or the capacity forecast.