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Transitioning from Old QA to New Analytics-Enabled Quality Assurance (Whitepaper)

Transitioning from Old QA to New Analytics-Enabled Quality Assurance

By Donna Fluss



Contact centers have performed quality assurance (QA) the same way for the past 30 years with little change in their approach to continuous improvement. They record, assess and evaluate a sample of agent calls (and possibly emails) so that they can identify training opportunities and use this information to coach their staff. Some contact centers also ask their QA specialists to identify trends and challenges that may interest or impact managers in other parts of the enterprise. Over time, recording and QA solutions, known as workforce optimization (WFO) suites, were introduced to facilitate the selection of calls (and emails) and to partially automate the agent evaluation process. However, this remains a highly labor-intensive exercise in most companies, where QA specialists still need to listen to a large number of recorded calls to find the interactions that provide agent coaching or recognition opportunities. But now there is a better, more effective way to use the QA process to improve agent productivity, quality and the customer experience.

In the last few years, WFO vendors have introduced a new generation of QA solutions that use workflow automation and analytics to eliminate many of the manual steps previously required for QA. These new solutions can find specific calls or emails that require supervisory attention with 60% to 80% less manual effort. They can also automate the process of tracking agent training needs, assign targeted coaching sessions, and identify, analyze and report on contact center and enterprise inquiry trends, empowering the organization to be more proactive. However, while the new generation of analytics-enabled QA applications makes the QA process and specialists substantially more effective and productive, they do not eliminate the need to listen to calls. The literal voice of the customer (VOC) will still be heard.

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