Unique Identifier Generation for Supply Chain Entity Resolution
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Solution Overview
Problem
Supply chain data analysis is hindered by the complexity of identifying unique entities amidst multiple 'doing business as' (DBA) names and the sheer volume of data from various sources, making it difficult to detect potential risks and disruptions in a timely manner.
Innovation Solution
A computer-implemented method generates a unique identifier for each unique entity, including its DBA names, by analyzing supply chain data from multiple sources, using a hash based on entity information and URLs, to consolidate and enrich data, enabling efficient risk analysis and mitigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If supply chain data from multiple sources is analyzed to identify unique entities and DBA names, then data completeness and accuracy are improved, but data complexity and processing difficulty increase
Solution Approach 1:
The patent segments the complex entity identification process into distinct components: generating unique identifiers from entity information, separately managing DBA name associations, and systematically linking multiple data attributes. This segmentation transforms the overwhelming task of analyzing multi-source supply chain data into manageable modular operations, resolving the contradiction between identification accuracy and processing complexity
Solution Approach 2:
The patent introduces unique identifiers as intermediary elements that mediate between raw entity information and the complex web of DBA names and data attributes. These identifiers act as stable reference points that simplify the association process, enabling accurate entity identification without directly confronting the full complexity of multi-source data
2Reliability
If multiple data attributes are linked across multiple dimensions, then risk detection capability is improved, but data processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-generating unique identifiers and pre-establishing DBA name associations before risk analysis begins. This preliminary structuring of data attributes and relationships enables rapid risk detection without requiring time-consuming data processing during actual risk assessment, resolving the contradiction between detection capability and processing time
3Productivity
If unique identifiers are generated and associated with entities and DBA names, then data consolidation efficiency is improved, but computational resources required increase
Solution Approach 1:
The patent transforms entity information into unique identifiers through hash functions, changing the parameter representation from complex textual entity descriptions to compact fixed-length hash values. This parameter transformation dramatically improves data consolidation efficiency by enabling rapid comparison and matching, while the one-way nature of hashing provides computational efficiency compared to maintaining and comparing full entity attribute sets
Data Source
AI summary
Examples described herein provide entity resolution and consolidation using a unique identifier for data with complex relationships gathered across a computer network from a plurality of sources. According to an aspect, a computer-implemented method includes receiving, by a processing device, supply chain data. The method also includes analyzing, by the processing device, the supply chain data to identify a unique entity and a doing business as (DBA) name associated with the unique entity. The method further includes generating, by the processing device, the unique identifier for the unique entity. The method additionally includes associating, by the processing device, the unique identifier with the unique entity and the DBA name associated with the unique entity and updating, by the processing device, the supply chain data to include the unique identifier for the unique entity and the DBA name associated with the unique entity.