E-procurement Search Intelligence for Supplier Catalog Matching
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Solution Overview
Problem
Current E-procurement systems often fail to provide accurate and complete search results for products and services, leading to delays and additional costs for buyer systems, as they do not effectively match buyer needs with supplier catalogs, resulting in unprocured items or mismatched purchases.
Innovation Solution
The system utilizes community intelligence and enhanced search algorithms to track and analyze search queries, classify search terms, and recommend additional matches from integrated and non-integrated supplier catalogs, incorporating artificial intelligence and community data to improve procurement efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional E-procurement systems are used to search and select from supplier catalogs, then the system structure remains simple and easy to operate, but the search results are incomplete and inaccurate, leading to unprocured items or mismatched purchases
Solution Approach 1:
The patent introduces an intermediary analysis system that sits between the buyer's search query and the supplier catalogs. This intermediary component analyzes search terms, identifies potential matches across multiple catalogs, and presents refined results to the buyer, thereby improving accuracy without requiring fundamental changes to the underlying catalog systems.
Solution Approach 2:
The system implements feedback mechanisms where search results and procurement outcomes are analyzed to improve future search accuracy. The system learns from matched and unmatched items, adjusting its matching algorithms to provide progressively more accurate results while maintaining manageable complexity through iterative refinement.
2Quantity of substance
If multiple supplier catalogs are integrated into the E-procurement system, then the completeness of search results improves, but the time and computational resources required to process searches increase
Solution Approach 1:
The patent segments the large set of supplier catalogs into manageable groups or categories. Instead of searching all catalogs simultaneously, the system divides them into segments based on relevance, supplier type, or product category, processing each segment separately and combining results. This maintains comprehensive coverage while reducing overall processing time.
Solution Approach 2:
The system performs partial searching by initially focusing on the most relevant catalogs based on the search query, then progressively expanding to additional catalogs if needed. This approach provides sufficient results for most queries without the excessive time cost of searching every available catalog, balancing completeness with efficiency.
3Reliability
If the E-procurement system performs comprehensive catalog matching, then procurement accuracy improves, but the complexity of matching algorithms and data processing increases
Solution Approach 1:
The patent applies different matching strategies to different parts of the search process. For example, it uses exact matching for critical fields like product SKU, while using fuzzy matching or semantic analysis for descriptive fields. This localized application of different algorithmic qualities improves overall accuracy without requiring complex algorithms throughout the entire system.
Data Source
AI summary
A computer implemented method maintaining a database including records of one or more supplier system catalogs enabled by multiple buyer systems. The method includes tracking, by the processor, query expressions and corresponding query results generated from the database by a specific buyer system, the query results identifying matches between the query expressions and a set of records of supplier system catalogs enabled and integrated for procurement with the specific buyer system. The method further includes determining, from the query expressions and corresponding query results, the query expressions that satisfy criteria for low match rates and identifying additional matches between the query expressions and at least one unassociated supplier system catalog outside of the set of enabled and integrated supplier system catalogs, the identifying based upon an analysis of community buyer system data. A report is generated based upon the additional matches and transmitted to the specific buyer system.