Overview
At MUFG, I led a comprehensive CMDB optimization initiative that fundamentally transformed our IT asset management and discovery processes. This project demonstrates the intersection of data governance, automation, and strategic IT operations.
The Challenge
When I joined MUFG in September 2023, the CMDB faced several critical issues:
- Data Quality: Over 7,000 critical duplicate Configuration Items (CIs)
- Database Bloat: 2.6+ million unnecessary or redundant records
- Discovery Gaps: Low coverage for servers (21 percentage points below target) and databases (40+ percentage points below target)
- Licensing Risk: 5,000+ licensable CIs creating unnecessary costs
Solution Approach
1. Duplicate Elimination Strategy
I developed a systematic approach to identify and eliminate duplicates:
- Created custom ServiceNow business rules for duplicate prevention
- Implemented automated reconciliation workflows
- Established data quality gates for new CI creation
- Built dashboards to track duplicate patterns
Result: Eliminated 7,000+ critical duplicates
2. CMDB Record Optimization
Through careful analysis and automation:
- Identified stale and obsolete records using lifecycle analysis
- Automated archival of retired CIs
- Implemented data retention policies
- Cleaned up orphaned relationships
Result: Reduced CMDB size by 2.6 million records
3. Discovery Coverage Improvement
Enhanced IT Discovery across the enterprise:
- Troubleshot and optimized ServiceNow Discovery patterns
- Collaborated with Virtualization, Network, and Database teams
- Implemented new credential management processes
- Deployed MID Server optimizations
Results:
- Server coverage increased by 21 percentage points
- Database coverage increased by 40+ percentage points
4. Cost Avoidance
Optimized ServiceNow licensing:
- Audited CI classifications
- Reclassified non-licensable items
- Implemented automated license tracking
Result: Reduced licensable CIs by 5,000+, avoiding costly package upgrade
Technologies Used
- ServiceNow: CMDB, Discovery, Business Rules, Workflows
- Python: Data analysis and automation scripts
- Power BI: Dashboards and reporting
- SQL: Data quality queries
- ITIL: Configuration Management best practices
Key Learnings
- Data Quality is Continuous: CMDB health requires ongoing monitoring and governance
- Collaboration is Critical: Success required partnership across IT teams
- Automation Scales: Manual processes don't scale; automation is essential
- Metrics Drive Decisions: Clear KPIs enabled stakeholder buy-in
Impact
The CMDB optimization project delivered measurable business value:
- Improved Compliance: Better audit readiness and reporting accuracy
- Cost Savings: Avoided licensing costs and reduced operational overhead
- Enhanced Discovery: More complete IT asset visibility
- Better Decision-Making: Trusted data for leadership decisions
- Risk Reduction: Improved security and compliance posture
Next Steps
Building on this foundation, we're now focusing on:
- CSDM (Common Service Data Model) implementation
- TBM (Technology Business Management) framework adoption
- Advanced analytics and predictive insights
- Service mapping enhancements
This project exemplifies how strategic CMDB management transforms IT operations from reactive to proactive, from chaotic to controlled, and from costly to cost-effective.