Abstract: A system can maintain an adaptive stock-keeping unit (SKU) associated with a type of procedure, where the adaptive SKU can include a combination SKU having a plurality of SKUs for the type of procedure and a plurality of parameters. The adaptive SKU can be represented by an adaptive SKU data structure having a schema including a membership field storing an ordered list of identifiers for the plurality of SKUs, a dependency field storing quantity relationship entries that define propagation rules, and a rule field storing executable rules for permitted membership modifications. The system can establish connections to systems of an entity, receive one or more operational constraints and store the operational constraints in association with the adaptive SKU data structure, receive an update message identifying a change event for a first SKU, determine an action with respect to the adaptive SKU, and communicate the action.

Abstract: A system can receive procedure data from a plurality of heterogeneous source systems, store a mapping data structure that maps procedure identifiers and stock-keeping unit (SKU) identifiers to canonical identifiers, and transform the procedure data into a procedure record associated with a canonical procedure identifier. The system can store a combination SKU record having a membership field, a quantity-range field, a rule field, and a dependency field. The system can receive factor-based data and preference data associated with at least one site identifier. The system can generate candidate combination SKU record identifiers and corresponding score values based on the procedure record, the factor-based data, inventory data, and the preference data, select a target combination SKU record identifier, compute quantities for constituent SKUs using dynamic quantity ranges and propagation rules, and perform an incremental recomputation operation that updates quantities for an affected subset of constituent SKUs.

Abstract: A system can maintain an adaptive stock-keeping unit (SKU) associated with a type of procedure, where the adaptive SKU can include a combination SKU having a plurality of SKUs for the type of procedure and a plurality of parameters. The adaptive SKU can be represented by an adaptive SKU data structure having a schema including a procedure-key field storing a procedure identifier, a membership field storing an ordered list of identifiers for the SKUs, a dependency field storing quantity relationship entries defining, for at least one pair of identifiers, a propagation rule mapping a quantity change of a first SKU to a quantity change of a second SKU, and a rule field storing executable membership rules defining permitted membership modifications. The system can establish interfaces to systems of an entity and receive customer parameters for storage in association with the adaptive SKU data structure.

Abstract: Systems and methods for using adaptive stock-keeping unit (SKU) data structures are provided. A system can store an adaptive SKU data structure having a schema comprising a procedure-key field storing a procedure identifier, a membership field storing an ordered list of underlying SKU identifiers, a dependency field storing quantity relationship entries that define propagation rules, and a rule field storing executable membership rules. The system can receive an update message identifying a change event for a first underlying SKU identifier. The system can update the membership field by executing at least one executable membership rule selected based on the change event. The system can perform an incremental recomputation operation that updates quantities for a subset of underlying SKU identifiers affected by the membership modification. The system can store the updated quantities in association with the adaptive SKU data structure.

Abstract: A system can store an adaptive stock-keeping unit (SKU) data structure having a schema including an adaptive SKU identifier, a procedure-key field storing a procedure identifier for a type of procedure, and a membership field storing an ordered list of underlying SKU identifiers for a combination SKU associated with the type of procedure. An ingestion engine can receive procedure data associated with the procedure identifier and factor-based data including operational parameter values for a given time period and can transform the procedure data and the factor-based data into a canonical feature representation that includes a feature vector. A forecasting engine can execute a machine learning model to generate an initial quantity estimate. An integration manager can receive distributor data identifying delivery dates for an underlying SKU identifier. The forecasting engine can refine the initial quantity estimate and store the refined quantity in association with the adaptive SKU identifier.

Abstract: A method and system for providing order placement and inventory control, integrating customers and suppliers and using both real-time and historical data to provide an automated process for the management of inventory. Various embodiments of this invention can include such features as automatic order placement, usage factor analysis, waste factor analysis, inventory analysis and reconciling of inventory data.

Abstract: A method and system for providing order placement and inventory control, integrating customers and suppliers and using both real-time and historical data to provide an automated process for the management of inventory. Various embodiments of this invention can include such features as automatic order placement, usage factor analysis, waste factor analysis, inventory analysis and reconciling of inventory data.