As part of a wider effort to reduce unnecessary expenditure and improve quality of service in the domestic energy business for a top 6 UK energy company turned to SQS to run the struggling regression testing function. The result? Tests durations cut by 60% and costs reduced by 90%.
Resource and system inefficiencies were hitting the client’s margins, its cost to serve domestic customers spiralling. In an effort to take unnecessary spend out of the business and improve the quality of customer service, the client launched its Domestic Recovery Programme in July 2015. The two-year programme involves multiple system changes. An existing framework had been set up to run 60 regression testing scenarios but it proved manually intensive, slow, unable to run at night and prone to failure. It lacked the functionality, too. For example, it couldn’t record screenshots necessary for validation. Given the timescales involved semi-manual, unreliable regression testing simply wasn’t an option.
SQS was brought in to overhaul the testing team and revamp the struggling automated regression testing function. The SQS team also brought with it an inherent understanding of the utilities market as well as deep knowledge of the client’s processes and systems which included a heavily customised SAP implementation. Given the complexity of the client’s set up, SQS introduced a 22-day on boarding programme to get its offshore teams up to speed with core system knowledge and customisation. In an initial phase of the project, SQS corrected 30% - over 1,000 - of test cases that had previously failed to run successfully.
The results were dramatic. Within 18 months of taking over responsibility for regression testing, SQS had reduced test times by 60% and manpower costs were down by an estimated 90%. This gave the business the confidence to double the volume of regression testing it undertook as the Domestic Recovery Programme became more complex. This in turn led to two fundamental business outcomes – improved customer satisfaction and a return to profitability.