System and method for scenario-driven optimization of sourcing cost

A system, comprising:

• a memory storing instructions;
• one or more communication interfaces;
• and
• one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to:
• receive an input request from one or more entities;
• query a parts repository based on the input request to identify a plurality of parts;
• apply a Jaccard similarity for each pair of parts from the plurality of parts by calculating a similarity score between each set of parts from the plurality of parts to obtain one or more combinations of a set of similar parts;
• identify, based on the similarity score, at least one corresponding supplier from a suppliers repository and tag the at least one corresponding supplier to each of the one or more combinations of the set of similar parts;
• perform a comparison between the similarity score and a threshold;
• identify based on the comparison, one or more target suppliers from the one or more combinations of the set of similar parts and the at least one supplier;
• determine a sourcing cost for each set of similar parts corresponding to the one or more identified target suppliers based on one or more pre-defined scenarios;
• and
• optimize a total sourcing cost derived from the sourcing cost for each set of similar parts based on one or more constraints.

One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause a method for bundling of parts, selecting corresponding supplier, and optimizing an overall sourcing cost, the method comprising:

• receiving, via the one or more hardware processors, an input request from one or more entities;
• querying, via the one or more hardware processors, a parts repository based on the input request to identify a plurality of parts;
• applying, via the one or more hardware processors, a Jaccard similarity for each pair of parts from the plurality of parts by calculating a similarity score between each set of parts from the plurality of parts to obtain one or more combinations of a set of similar parts;
• identifying, based on the similarity score, at least one corresponding supplier from a suppliers repository and tagging the at least one corresponding supplier to each of the one or more combinations of the set of similar parts;
• performing, via the one or more hardware processors, a comparison between the similarity score and a threshold;
• identifying, via the one or more hardware processors, based on the comparison, one or more target suppliers from the one or more combinations of the set of similar parts and the at least one supplier;
• determining, via the one or more hardware processors, a sourcing cost for each set of similar parts corresponding to the one or more identified target suppliers based on one or more pre-defined scenarios;
• and
• optimizing, via the one or more hardware processors, a total sourcing cost derived from the sourcing cost for each set of similar parts based on one or more constraints.