NLQ is enhanced through configurable synonyms and semantic shortcuts, which translate natural language terms into accurate database queries. For instance, synonyms like "vendor" map to the Supplier column, and semantic conditions refine searches, such as identifying closed contracts by specifying active=false.

Key Features

• Natural Language Query (NLQ): Converts user questions into database queries to fetch precise procurement data.
• Configurable Synonyms: Enables flexibility by mapping multiple search terms to relevant database fields (e.g., "vendor" for Supplier).
• Semantic Conditions: Improves search accuracy by applying conditions to synonyms, such as filtering open or closed records.
• Predefined Supported Questions: Provides a variety of sample queries across procurement processes, including purchase requisitions, sourcing requests, negotiations, purchase lines, purchase orders, milestones, receipt tasks, and procurement cases.
• Graphical Results: Search results may be visually represented depending on the query parameters.
• Search Improvement Guidance: Offers tips to refine questions if initial search results are unsatisfactory.

Practical Usage Tips

• Specify exact table names as they appear in the database when forming queries.
• Include relevant keywords such as status (e.g., open, closed) or type (e.g., standard, blanket) to narrow down results.
• Leverage synonyms and semantic conditions to enhance search precision.
• Use the “How can I improve my results?” option for assistance in refining queries.

Key Outcomes

By utilizing the Source-to-Pay Workspace Analytics Center, ServiceNow customers can quickly and intuitively explore procurement data, monitor current performance, and analyze trends over time. This capability supports informed decision-making and efficient management of procurement activities within the platform.