ServiceNow holds high-signal operational data—requests, approvals, incidents, changes, assets, identities. Treat it as a first-class data product. Define a shared data model: normalize key entities (user, service, offering, CI, vendor), apply consistent keys (employee IDs, asset tags), and enforce data quality with stewardship workflows. Use CMDB not as a dumping ground but as the federated truth for service context; integrate authoritative sources for hardware, software, SaaS, and relationships. Publish curated data products (e.g., “Service Health,” “Fulfillment Flow,” “Knowledge Effectiveness”) to analytics platforms for cross-domain insight. Establish data contracts for integrations to avoid brittle point-to-point links; version APIs, document schemas, and manage changes via release notes. Implement PII and sensitive data handling policies with masking/encryption and access controls based on role and purpose. Measure data quality with completeness, validity, timeliness, and reconciliation rates; show scores on operational dashboards. When ServiceNow data is modeled and governed, it powers predictive staffing, cost transparency, and risk analytics—elevating conversations from tickets to trends and decisions.
