Hi @ashokakumar
It’s great to see you leveraging NLU (Natural Language Understanding) for access-related use cases. Integrating NLU with Flow Designer is a modern, scalable way to handle service desk automation.
Here is a breakdown of your approach, best practices for accuracy, and potential alternatives to ensure a robust solution.
1. Is this the recommended approach?
Yes, using NLU to drive Flow Designer is the standard "Pro-Code/Low-Code" approach in ServiceNow for intelligent routing. It shifts the burden of manual categorization from the user to the platform.
- The Benefit: It reduces "Mean Time to Repair" (MTTR) by bypassing the general service desk and landing the ticket immediately with the team that handles ID validation.
- The Caveat: NLU is only as good as its training data. For "Access Issues," the model needs to distinguish between "I forgot my ID" (Password Reset) and "My ID isn't working for App X" (Access Validation).
2. Improving Intent Recognition Accuracy
To ensure your NLU model doesn't misfire, consider these best practices:
- Diverse Utterances: Provide at least 15–20 varied utterances per intent. Instead of just "ID validation," include "Can't log in with my credentials," "User ID blocked," or "Verify my system access."
- Use Entities: Don't just identify the Intent; identify the Entity. If the user says "Access issue with SAP," the Intent is Access Issue and the Entity is SAP. This allows your Flow to be more specific.
- Vocabulary Sources: Add company-specific jargon or acronyms to the NLU Vocabulary so the model understands internal system names.
- Conflict Resolution: Regularly use the NLU Workbench to check for "conflicting utterances" where two different intents look too similar to the model.
3. Alternative & Complementary Approaches
While NLU is powerful, combining it with other ServiceNow features can make the process even more effective:
A. Virtual Agent (VA) Integration
Instead of just analyzing a Short Description after a ticket is created, use a Virtual Agent conversation.
- The VA can use NLU to start the topic.
- It can then ask clarifying questions (e.g., "Which system are you trying to access?") before the Flow Designer even triggers. This ensures the data passed to the validation flow is 100% clean.
B. Predictive Intelligence (Task Intelligence)
If you find NLU configuration too manual, look into Task Intelligence.
- It uses machine learning to look at historical data and automatically categorize/assign incidents based on the Short Description without you having to manually define "intents" and "utterances."
C. Catalog Item with "Auto-Submit"
If the validation logic is very rigid, sometimes a well-designed Service Catalog Item with a few mandatory fields is more reliable than a free-text Short Description. You can use NLU to redirect a user from a general search to this specific Catalog Item.
