A globally-recognized telecommunications provider was facing several challenges in its migration to a cloud-based framework: error management, defect detection and timeline maintenance.

HCL’s Intelligent Sustenance Engineering (ISE) helped streamline the data management process, driving efficiency, responsiveness and cost-effectiveness.

HCL’s 3-stage solution utilized analytics and machine learning to prevent defect duplication and enhance Defect Removal Efficiency (DRE). The component processes were:

• Perform code analysis to provide actionable metrics on three aspects: namely complexity of code, number of defects per file and files which were frequently changed.
• Achieve error segmentation in order to isolate error-prone segments and map out trends in defect occurrence.
• Perform test sufficiency analysis to highlight most-failed test cases, and throw visibility on DRE.

HCL’s tripartite solution actioned ISE’s unique features helping to reduce ticket production by 9%, defect backlog by 23% and DRE improvement by 6-7%.

To learn more about how a high-volume communication provider optimized its migration pathway and minimized its defect ratios, using HCL’s ISE optimized solution, please read our detailed case-study.