Unreliable data causing instability and frustrating efforts to plan change.
View PDFView VideoRead MoreRead More"Many thanks for all the efforts from CSX, a great set of outcomes achieved. I look forward to continuing to work with you in the future!"
Head of Group IT Service Management
CSX were approached to help with a large cloud migration programme. However the lack of a reliable data to underpin analysis was flagged as a major impediment to planning. When we looked for good data, we found more:
· Frequent outages due to inability to accurately monitor/manage/change services
· Multiple overlapping tools being used by different teams to provide data and reports
· A lack of consistent baseline across the estate
· People pulling data from different repositories and editing / enriching it for their own purpose.
CSX recommended a factory approach to provide a reliable and trusted Single Point of Truth (SPOT) for service data and to coordinate efforts for improving configuration management and the CMDB.
CSX delivered a proof of concept (“POC”) for SPOT data to cover a set of critical business applications with effective service-to-app-to-infrastructure mapping.
Remaining 550 handed over to BaU.
Major Global Insurance Provider - Multi-billion turnover - Tightly Regulated - 54 managed locations
14,000 users
25 countries
No single point of truth for IT configuration data - Non-standard ways of working - Data spread across three ticketing systems and a variety of non-standard sources - Fragmented ownership of applications and infrastructure
- Workshops - Service Mapping - Enrich the Data - Codify the Rules - Populate the CMDB - Verify & Iterate Outputs: - SPOT Principles (e.g. “Automate discovery & verification where possible”) - Mapping of critical business applications - Impact Assessment - Process flow - BI / Reporting capabilities - Audit procedures - Health Dashboards / KPIs - Single tooling framework - Monitoring and alerting integration - Governance model - Gamified Certification - Automated interfaces - Data usage guides - Data modelling