Safetrack QA Project
Highlight
Luvina Software supported a major Japanese railway operator in validating their upgraded in-house ERP system. The goal was to ensure system stability, data integrity, and functional correctness following updates to both the application’s source code and deployment environment.
Our team provided comprehensive manual testing services, focusing on real-world business scenarios and regression testing to identify any inconsistencies between the legacy and upgraded systems.
Country: Japan
Industry: Transportation – Railway
Scope: Focus Area: ERP (Warehouse & Inventory Management)
Project Duration:
– Phase 1: July to September 2024 (35 MM)
– Phase 2: October to December 2024 (16 MM)
Service Type: Full-scope Manual Testing
CLIENT BACKGROUND & CHALLENGES
The client operates a mission-critical ERP system that has been in use since the early 2000s to manage inventory and warehouse operations across its railway network. To meet evolving business needs and technical standards, the system underwent a significant upgrade, involving:
- – Migration to a new Windows Server environment
- – Updates to core technical libraries and application source code
- – Enhancement of existing business features
CHALLENGES
Due to the system’s long lifespan and complexity, the client faced significant risks:
- – Potential incompatibility between legacy functions and new infrastructure
- – High dependency on existing business workflows
- – Increased likelihood of hidden errors after the upgrade
- – To address these risks, a thorough testing process was critical.
LUVINA’S SOLUTIONS
To ensure the quality and timely delivery of the ERP upgrade testing project, Luvina applied a strategic and process-driven QA approach tailored to the client’s specific challenges:
1. Optimized Testing Strategy for Complex ERP Systems
Drawing on extensive experience with large-scale ERP systems like GRANDIT, our team:
- – Analyzed the interdependencies between business modules
- – Developed a Master Test Schedule to allocate resources efficiently
- – Maintained delivery timelines as committed to the end client
2. Agile Resource Coordination and Transparent Delivery
- – Maintained weekly visibility into testing output to help the System Integrator (SI) adjust their review schedule in real time
- – Reserved internal backup resources to scale up quickly when delivery acceleration was needed
3. Standardized Process to Align Stakeholder Expectations
- – To avoid misunderstandings and ensure consistency across teams, we:
- – Executed a pilot trial phase to validate the testing process
- – Standardized Test Evidence (TE) reporting format and secured approval from the SI
- – Rolled out the approved process and reporting standard across the entire QA team
All testing activities followed strict CMMI-compliant procedures, and were carried out by highly skilled QA professionals, ensuring that Luvina’s deliverables met the highest quality standards and minimized the workload for the SI.
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Seamless Post-Upgrade System Operation
- – The ERP system remained fully operational immediately after go-live, with no downtime or disruption reported
- – Over 800 screens and batch processes were thoroughly tested across two phases
- – Achieved 100% functional stability for all core business operations
High Data Integrity
- – Achieved a >99.95% data consistency rate between the legacy and upgraded systems
- – Ensured accurate report exports, receipt generation, and batch processing, minimizing operational risk
Exceptionally Low Post-QA Defect Rate
- – Post-QA bugs reported by the end user were less than 0.35 bugs per 100 test cases, outperforming the industry benchmark (~0.5 bugs/100 TCs)
- – Bug count in Phase 2 was reduced by nearly 50% compared to Phase 1, thanks to process refinements
Long-Term Maintenance Cost Savings
- – Comprehensive testing, covering logic, performance, and UI, significantly reduced post-deployment issues
- – Estimated to help the client save 15–20% in maintenance costs within the first 12 months post-upgrade, compared to typical ERP projects of similar scale
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