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Wednesday, January 17, 2018

WHY AUTOMATED QM IS THE NEXT STEP IN IMPROVED CUSTOMER ENGAGEMENT

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Ovum believes the major benefit of Automated Quality Management is the freeing up of valuable supervisory time from scoring to be used for coaching and other agent support efforts.

In today’s customer care environments, a strong quality management (QM) system is crucial to moving customer engagement interactions to the next level of performance excellence. For many years, companies have used QM software and techniques to optimize their customer service operations. These tools have been essential to agents and supervisors in performing their daily operational duties as they strive to optimize the customer experience and ensure agents perform at high levels and deliver a high level of competitive differentiation.

A core necessity of strong QM is the recording of agent/customer interactions to allow supervisors to review agent performance across a broad range of situations and businesses to measure, train, and correct agent performance as required over time. In most organizations, recorded conversations are periodically sampled and reviewed by the supervisor or member of a dedicated quality team in time for monthly, quarterly or annual agent evaluations.

Biases are inadvertently introduced into this process because the sampling could be made unfair by the selection and evaluation of calls that may have been recorded at a less than desirable time, such as when an agent was having a bad day or feeling ill. In addition, agents’ perceptions that the QM process is biased could undermine the effectiveness of the observations, their response to the scoring of call evaluations, and the subsequent review with their supervisor or quality coach.

Modern technology allows for an Automated Quality Management (AQM) process that provides more fairness for agents and is more useful to supervisors. If every call is recorded and used to automatically feed pertinent information to supervisors, the bias can be eliminated, giving the supervisor access to all of an agent’s calls, as well as the ability to measure all agents immediately, and do their evaluations “on a level playing field.” Automating the review process and the automated reporting of quality scores, or the highlighting of important KPIs that are missed, can free supervisors from these very repetitive tasks and allow them to devote more time to important face-to-face agent coaching.

Since agents would have the ability to self-monitor based on automatic feedback and system transparency, they can implement improvement processes themselves in real time. However, even with automated notification by which agents can self-monitor and take corrective action based on feedback, many are unlikely to do so unless transparency into performance gaps is accompanied by additional coaching or supervisory assistance. In fact, Ovum believes the major benefit of AQM is the freeing up of valuable supervisory time from scoring to be used for coaching and other agent support and improvement efforts.

In practice, an effective AQM system has the ability to issue alerts to the agent if certain performance thresholds are missed, which can prompt the automatic scheduling of coaching or the pushing of e-learning sessions to drive improvements. When automation of the QM process is handled properly, management can eliminate the issue of depersonalization of the agent/supervisor relationship, which can become an issue with some QM systems.

The bottom line is that AQM provides the ideal method of fairly and consistently measuring an agent’s performance, enabling organizations to quickly implement changes in methodology, train agents when needed, and optimize customer interactions, ultimately leading to improved satisfaction and greater employee engagement.

 

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