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Closed Incidents – With Proper Data for Reporting

Sep 22, 2025

Problem

When incidents are closed without complete or accurate information, reporting becomes unreliable and trend analysis is compromised. This issue is especially critical for operational reviews, SLA tracking, and executive dashboards. Missing links to services, configuration items, or assignment details can hide systemic issues and prevent continuous improvement. This blueprint ensures that all closed incidents (from the last 30 days) are properly documented, enabling high-quality reporting and audit readiness.

What the Blueprint Includes

This blueprint validates that closed incidents are linked to the right supporting entities:

  1. Incident – the root, restricted to incidents closed in the last 7 days.
  2. User – verifies the caller and manager details.
  3. Group – ensures an active assignment group is captured.
  4. Company – ensures caller’s company is recorded.
  5. Service Offering – confirms which service offering was impacted.
  6. Service – records both the impacted business service and the linked service context.
  7. Configuration Item – validates both directly assigned CIs and those linked through “CIs affected.”

Considerations

  • Timing: Only incidents closed within the last 7 days are included, supporting both operational and weekly reporting cycles. You should change the timing based on ticket volumes and follow up frequency.
  • Completeness: All critical links (caller, assignment, service, CI) must be filled for the incident to qualify as properly documented.
  • Active references: Assignment groups and user records must still be active at the time of closure.
  • Service hierarchy: The model enforces service-to-service offering relationships, ensuring clarity in impact analysis.
  • Consistency: Closing workflows should prevent incidents from being finalized without these mandatory fields populated.

Benefits

  • Reliable reporting: Dashboards and SLA reports reflect a complete and accurate picture of closed incidents.
  • Audit compliance: Proper traceability of callers, services, and configuration items supports regulatory and internal audits.
  • Improved problem analysis: With consistent data, trend reporting highlights recurring issues more effectively.
  • Operational excellence: Ensures both ticket handling (while active) and data integrity (when closed) are maintained.

Find more blueprint templates related to Activity data, such as tasks, requests, and projects.

Read more about the Two Million Euro Incident that could have been prevented with proper Server modeling.

How to Get This Blueprint?

If you’re already a Data Content Manager Customer, you can download the Blueprint from the Knowledge Base. You will need your login credentials to access the blueprint download page.

My complex Blueprint was up and running in 10 minutes, and I got audit results immediately. It would have taken months to complete without DCM.

Enterprise Architect
Global Healthcare Company

DCM has been central in federating our dependency mapping to technical teams, and that momentum is building. It’s been a successful first year, and we’re extending use with additional blueprints.

Product Manager - Service Catalog
U.K. Public Sector

DCM has delivered incredible value to our business by drastically accelerating application rationalization. What would have taken years to complete was achieved in just months. Its intuitive, well-designed GUI makes navigation seamless for both users and administrators. Most importantly, DCM has significantly matured our CMDB, bringing clarity and structure. We highly recommend both the product and the outstanding team at Qualdatrix.

Banner Health

With CSDM providing a prescriptive data model and DCM providing a view of our data in a consumable manner, we are able to drive the necessary changes across the bank in a non-obtrusive way, which is seen to add value to our business, not be viewed as an operational overhead.

Craig Alexander
SVP, Danske Bank

The CMDB Data Quality Playbook

A Practical Guide for Improving ServiceNow Data Quality, Governance and AI-Readiness.

  • A practical way to establish ownership and roles
  • The 5-step model for data quality improvement
  • Best practices for engaging data providers
  • Five common pitfalls in CMDB data quality and how to avoid

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