About the client 

A large enterprise IT organization (identity and sector withheld) that had run ServiceNow for many years. Its hardware estate spanned end-user computing, servers, storage, network gear and data-center equipment, distributed across many physical sites and stockrooms. Over time the platform had accumulated custom asset management: duplicate hardware models, custom fields shadowing standard ones, retirement processes that differed by device type, and inventory records that had drifted from the physical world. 

The organization engaged ValueCentrix to replace that customization with licensed ServiceNow Hardware Asset Management Pro capability. The program ran 16 capability streams in parallel across 20 two-week sprints and 15 production releases over roughly eight months, absorbed a platform upgrade mid-program without breaking cadence, and delivered 100% of committed scope into production. 

The situation 

The platform carried substantial customization across its asset and configuration tables. No one could say with confidence which custom fields were still load-bearing, which model categories sat outside licensed parents, or which scheduled jobs depended on fields the new product would replace. Switching on HAM Pro against that foundation would have meant discovering those dependencies in production, one incident at a time. 

What we did 

• Ran a structured assessment of the core platform tables (location, company and user) to establish what HAM Pro would rely on and where existing data would not support it. 

• Audited every custom field on the asset and hardware model tables, cataloguing offline substates, asset function values and duplicate asset data. 

• Reviewed every custom model category to confirm it sat beneath a licensed parent, a prerequisite for normalization to work. 

• Checked whether display-name concatenation and other core behaviors had drifted from product standard. 

• Converted every finding into a costed remediation story, linked as a dependency to the assessment that produced it, so nothing could be silently dropped. 

  
  

Outcomes 

• Every finding was in the backlog, estimated and dependency-linked, before enablement began, rather than surfacing as unplanned work mid-delivery. 

• A data-quality dashboard built during assessment was promoted into production, so the issues discovery surfaced stay monitorable instead of disappearing at the next environment refresh. 

• Assessment artifacts were retained as documentation records, giving the client a durable account of what was found and why each decision was taken.