Semantic Solution Segment Indexing for Enterprise Sales
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Solution Overview
Problem
Current approaches for enterprise solution management in sales and pre-sales processes rely on limited keyword searches, leading to non-targeted recommendations and inefficiencies, especially in multi-vendor bid preparations, resulting in low precision, long cycle times, and reduced win rates due to unstructured information and lack of traceability.
Innovation Solution
A computer-implemented method for identifying and ranking solution segments based on semantic associations, using a database to provide context-based content recommendations by aggregating, segmenting, and annotating work-products, and indexing documents with keywords for precise matching and relevance scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If keyword search is used to search for solution information, then the search process is simple and fast, but the precision and relevance of recommendations deteriorate
Solution Approach 1:
The patent segments solution documents into atomic segments based on solutioning concepts, allowing fine-grained semantic matching. Each segment can be independently matched against query concepts, enabling precise recommendations while maintaining search efficiency through indexed segment retrieval.
Solution Approach 2:
The patent changes the search parameter from simple keywords to semantic concepts with associated metadata. By transforming unstructured text into structured concept segments with metadata tags, the system achieves precise semantic matching while maintaining fast search performance through indexed retrieval.
2Quantity of substance
If unstructured information is stored and shared via informal channels, then information availability is high, but traceability and integration quality deteriorate
Solution Approach 1:
The patent segments unstructured solutioning information into structured atomic segments associated with solutioning concepts. Each segment maintains traceability through concept links and metadata, enabling full audit trails while preserving the richness of unstructured information.
Solution Approach 2:
The patent introduces solutioning concepts as intermediary entities that mediate between raw unstructured information and structured knowledge representation. Concepts serve as the glue that connects informal communications, documents, and data, providing traceability and integration without losing information richness.
3Measurement precision
If multi-vendor bid preparation is performed with individual units working independently, then each unit can offer precision in sales configurations, but integration quality and overall solution precision deteriorate
Solution Approach 1:
The patent creates a universal solutioning concept framework that serves all multi-vendor units. This common taxonomy and concept model enables consistent integration across vendors while preserving each vendor's configuration precision through specialized solution segments.
Solution Approach 2:
The patent segments the overall solution into vendor-specific atomic segments that can be independently created with high precision, then integrated through common concept references. This allows each vendor to optimize their configurations while ensuring overall solution consistency through shared concept taxonomy.
Data Source
AI summary
Techniques, a system and an article of manufacture for designing integrated enterprise solutions. A method includes aggregating multiple work-products pertaining to solutions submitted in response to one or more previous solution requests, segmenting the multiple work-products into multiple segments based on content category, annotating each of the multiple segments with a tag based on one or more semantic associations with the content of each of the segments, adding each of the segments and each of the tags into a database, performing a search in the database to identify a set of one or more of the segments with at least one tag that corresponds to content of a current solution request, and ranking each of the segments in the set based on a degree of semantic matching with one or more parts of the current solution request.