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According to a new white paper from VPI, Quality Assurance 2.0, The Rebirth of Contact Center QA, traditionally QA involved random recording or the selection of a random sample from all recorded calls from which to periodically evaluate and score a small number of calls for each agent. The objective was to confirm that agents exhibit desirable behaviors, without deviating from prescribed internal rules, scripts and policies. The outcome of the evaluation was then reflected in the agents‘ compensation.
The three major shortcomings of traditional QA are:
Primary Focus on the Agent – Most recordings of customer-agent interactions carry relatively low business value. Consequently, most random samples of recordings are likely to provide low-value information.
Manual, Time Consuming Workflow – Traditional QA often involves many manual, tedious, arbitrary tasks that do not take attributes of different types of calls into consideration.
Therefore it is not surprising that many contact center managers operate with irrelevant quality statistics and do not achieve business objectives – they‘re too busy taking ineffective actions aimed at attacking the symptoms of deficiencies rather than their root causes.
Difficult to Assess Effectiveness –There are many cases when QA evaluations are performed in bulk at the end of the month. Feedback and coaching is then given to the agents at month-end when they have already forgotten about the interaction and can no longer make a connection. Plus, most businesses have found themselves stuck in the rut of adding new QA components to an already hefty QA form as the industry, market, and business focus changes, rather than reworking the QA template and process entirely.
Siloed from Other Important Systems – Traditional QA systems and reports were siloed from other contact center performance management systems. There was no easy way to coordinate delivery of agent training assignments that were based on a combination of QA scores and Key Performance Indicators (KPIs). And, there was no way to report on how improvements in QA skills impacted other contact center performance metrics, such as whether customer satisfaction was improved or sales increased.