One of the world’s largest insurance companies had been running its service management on i3S, a legacy platform that had grown fragmented and difficult to trust. Configuration data was spread across i3S, team spreadsheets, network tooling and vulnerability scanners. Each held part of the picture, none held all of it, and the versions did not agree.
The business driver was a strategic cloud migration. Before infrastructure could be safely moved to the cloud, the client needed an accurate, current and well-structured picture of what actually existed across its estate — spanning fifteen data centres across the Americas, EMEA and APAC. That picture did not exist in a single reliable place, which made the CMDB the critical dependency for the entire transformation.
The engagement was technically and organisationally complex across several dimensions.
The existing CMDB contained very large volumes of duplicate and orphaned records — over 127,000 network adapter entries and tens of thousands of duplicated compute template and disk records, all of which had to be reconciled rather than simply copied across. Configuration data had to be brought together from i3S, network team spreadsheets, Tenable vulnerability data and live discovery, each in a different format with inconsistent IP range data full of duplicates.
Global scale added further complexity. Fifteen data centres had to be discovered, each with different network bandwidth limits, credentials and firewall rules, from Munich at 10Gb down to sites of 10Mb. Windows, Linux and SNMP access varied site by site, with missing credentials, SUDO permission errors and firewall restrictions reducing coverage and requiring systematic resolution.
Identification and reconciliation rules had to be defined at field level so that records from different sources resolved to a single trusted configuration item. And the target CMDB had to be structured to the Common Service Data Model (CSDM) so that discovery, service mapping and future capabilities would populate the right classes and relationships from the outset.
Hikon led the work through six clearly defined stages: Discovery, Assessment, Gap Analysis, Implementation, Training and Handover. The technical build ran as a series of proof-of-concept iterations to prove the approach before scaling it across the full estate.
Fifteen MID Servers were deployed on dedicated Azure virtual machines, one aligned to each data centre, with an additional MID Server for Service Mapping. Beneath the six stages, parallel workstreams covered Discovery and Service Mapping, CMDB and CSDM, Incident and Change, Service Catalogue and Knowledge, SLA and Reporting, GRC and Vulnerability, and Identity and Access.
ServiceNow was established as the client’s single ITSM and configuration platform, replacing i3S and providing a trusted, current and governed view of the global estate. The CMDB was rebuilt to the Common Service Data Model, with field-level identification and reconciliation rules ensuring that records arriving from discovery, i3S, Tenable and network sources resolved to a single configuration item, ending the cycle of duplication that had undermined the legacy data.
Large-scale deduplication was applied to the inherited CMDB, and IP range data from multiple inconsistent spreadsheets was extracted, normalised and deduplicated through purpose-built automation before being used to drive discovery. Discovery, Service Mapping, Tenable and Azure sources were connected to feed and validate the CMDB, while incident, change, catalogue, knowledge and SLA data were migrated from i3S into ServiceNow.
This engagement shows how a complex, global service management estate can be moved off a fragmented legacy platform onto ServiceNow without simply carrying the old problems across. The combination of automated discovery, disciplined data cleansing, field-level reconciliation and CSDM alignment turns a distrusted inventory into a dependable asset — and makes subsequent transformation programmes possible rather than merely aspirational.
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