Case study

Transforming Cloud Operations with Scalable ServiceNow Workflow Automation for an ICT Provider

APAC Market

  • Team size: 8 people
  • Development time: Ongoing, since 2024


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Background

By 2025-2026, enterprises are moving beyond isolated automation efforts and toward scalable, workflow-level transformation. McKinsey 2026 AI transformation article states that leading companies create value by reshaping products, services, and core business processes, not just by adopting new tools. Deloitte’s 2026 ServiceNow report highlights a move away from piecemeal automation toward end-to-end outcomes. In other words, operational excellence increasingly depends on how well organizations standardize, automate, and govern their processes through ServiceNow workflow automation. For a system integrator working across complex ICT environments, this shift is especially important. When service delivery involves multiple systems, multiple stakeholders, and frequent change requests, success depends on clear governance, automation, and a delivery model that can reduce risk without slowing execution.
Our client, a prominent ICT and system integration company that designs, builds, and maintains mission-critical ICT environments through a multi-vendor approach, engaged with us to improve their cloud environments management efficiency.
ICT provider: standard quality control

Challenges

Before implementation:
Our client needed a more efficient way to manage hundreds of distinct cloud environments for different customers. Each new tenant required a bespoke manual setup, which created operational overhead and made scaling increasingly difficult. The team also had to manage high-risk network changes such as firewall rules and routing, where even a small mistake could trigger a serious outage. On top of that, critical information was spread across multiple databases, forcing engineers to switch between systems to resolve a single incident. The lack of standardized ServiceNow workflow automation also made it difficult to scale operations consistently across environments.
During delivery:
Our experts also faced implementation challenges. Some customer requests required special handling that could conflict with ServiceNow best practices, while post-upgrade issues had to be tested and fixed after instance changes. Communication between the ServiceNow consultants and the customer was limited, and unclear naming conventions for tables and columns created additional confusion across teams. To align stakeholders and reduce ambiguity, our specialists also introduced our client’s native language learning for the whole team, developed a unified naming standard, and applied a high-fidelity solution design approach to clarify requirements before implementation.
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ICT provider: Engineering team doing brainstorming in server hub, using AI powered tech
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Solution 

GEM first analyzed the client’s existing processes, identified operational bottlenecks, and assessed risks in managing cloud environments at scale. Based on this, the team designed a structured solution using Service Catalog and Flow Designer.

A “New Tenant” request was designed as a ServiceNow workflow automation, triggering provisioning across AWS, Azure, and private cloud systems., replacing manual setup with a standardized workflow. The solution emphasized reusability and scalability, allowing new services to be introduced with minimal rework.

To ensure quality and reliability, GEM integrated ServiceNow workflow automation with ATF (Automated Test Framework), enabling faster validation cycles and reducing manual testing effort. This enabled faster validation cycles and reduced dependency on manual testing.

At the integration layer, GEM leveraged IntegrationHub, Scripted REST APIs, and data transformation capabilities to connect ServiceNow with multiple legacy systems. Authentication, data exchange, and reconciliation processes were standardized to ensure consistency across environments.

In parallel, governance was strengthened through unified naming conventions, structured documentation, and a high-fidelity solution design methodology, ensuring that requirements were clearly defined and consistently implemented.

Tech stack

  • Service Catalog (Angular JS)
  • Flow Designer
  • ATF
  • IntegrationHub
  • Scripted REST API
  • JSON/XML
  • OAuth 2.0
  • IRE
  • CMDB

Output 

  • Designed standardized and automated workflows for tenant provisioning across multi-cloud environments
  • Built a reusable Service Catalog and workflow architecture to support scalable service delivery
  • Established integration frameworks connecting ServiceNow with cloud platforms and legacy systems
  • Developed automated testing capabilities to support continuous validation
  • Improved Service Portal usability for a more streamlined request experience
  • Defined unified naming conventions and governance standards across teams
  • Delivered structured documentation and high-fidelity solution design for consistent implementation

Impacts 

The results were both measurable and operationally significant. The delivery team scaled by 60% (from 2 to 5 consultants) within the first year, while maintaining 99% requirement delivery with zero defects, demonstrating strong execution quality and platform stability.

Testing efficiency improved dramatically. A regression test cycle that previously required 5 people working for one week can now be executed in under 2 hours using ATF. The automated framework enables the execution of hundreds of test cases across forms, server-side logic, and UI, helping detect 95% of defects in the development stage and significantly reducing defect leakage into production.

The platform also achieved a high level of scalability and reuse. The team developed and maintained 40+ catalog items and 45+ flows and sub-flows, enabling standardized service delivery across environments. In parallel, 20+ integrations were implemented to connect ServiceNow with cloud platforms and legacy systems, supporting authentication, data exchange, and reconciliation processes at scale.

Operational efficiency improved as manual provisioning was replaced by automated workflows, reducing setup effort and minimizing the risk of configuration errors. The reusable architecture also allowed new services to be introduced faster and more consistently, supporting the client’s ability to scale cloud operations while maintaining control.

In addition, ATF created an automated audit trail for every test run, supporting country-specific regulatory compliance and providing clear evidence of system readiness and control. These improvements were driven by the adoption of ServiceNow workflow automation, which enabled faster execution, higher quality, and scalable operations.


Closing remarks

This case shows how GEM helped the client strengthen service delivery through automation, standardization, and disciplined ServiceNow implementation. By reducing manual work, improving testing efficiency, and enabling scalable workflow design, GEM supported the delivery of a more stable and adaptable platform for crucial ICT operations.


Explore a relevant ServiceNow case here: Modernizing Global Aerospace Service Operations with ServiceNow Managed Services