US 12,307,399 B1
System and method of end-to-end supply chain segmentation
Alexis Rotenberg, Egham (GB)
Assigned to Blue Yonder Group, Inc., Scottsdale, AZ (US)
Filed by JDA Software Group, Inc., Scottsdale, AZ (US)
Filed on Oct. 3, 2017, as Appl. No. 15/724,108.
Application 15/724,108 is a continuation in part of application No. 15/723,554, filed on Oct. 3, 2017.
Application 15/724,108 is a continuation in part of application No. 15/724,052, filed on Oct. 3, 2017, abandoned.
Claims priority of provisional application 62/403,576, filed on Oct. 3, 2016.
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 10/0631 (2023.01); G06Q 10/087 (2023.01)
CPC G06Q 10/06315 (2013.01) [G06Q 10/087 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A computer-implemented method for identifying supply chain segmentations from an initially non-segmented supply chain by a computer comprising a processor and a memory, comprising:
receiving a current state of items in a supply chain network comprising one or more supply chain entities, wherein an inventory of the one or more supply chain entities is used to store one or more items, and a state of the items comprises a quantity and ordered flow among the inventory of the one or more supply chain entities;
determining one or more customer-product clusters based on the size of the inventory and service expectations of the one or more supply chain entities, wherein the determining the one or more customer-product clusters is based at least in part on a Pareto analysis, wherein each customer-product cluster comprises a customer and product combination and wherein the one or more customer-product clusters are based, at least in part, on a hierarchy, and wherein the hierarchy is adjusted by defining a level of granularity between individual customers and aggregated customers;
generating one or more levers associated with one or more supply chain strategies associated with the one or more customer-product clusters, each of the one or more levers comprising one or more configuration options, wherein the one or more levers are selected from the group consisting of: forecast level, stocking strategy, demand prioritization, production rule, ATP allocation and delivery strategy;
assigning supply chain models to each of the customer-product clusters that meet requirements of the size of the inventory and service expectations of the one or more supply chain entities;
determining an inventory policy based on targets of one or more principal key process indicators that is indicative of a projected service level for an item in the inventory for one or more successive inventory planning periods; and
in response to determining the inventory policy, transporting items via robotic machinery among the one or more supply chain entities to restock the inventory of the one or more items according to the current state of items in the supply chain network.