Speech Technology Magazine

 

Analytics Revolutionizes the QA Process

Increased targeting and precision make an upgrade worthwhile.
By Donna Fluss - Posted Jan 10, 2015
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Quality assurance (QA) is a mission-critical process designed to measure how well contact center agents adhere to internal policies and procedures. When done properly and on a timely basis, it also functions as an early warning system to identify trends, issues, and opportunities for all areas of the company. All contact centers, regardless of size, number of sites, number of agents, or channels used, should perform quality assurance. For years, QA was essentially a manual activity, enabled by some technology, but the entrance of speech analytics into contact centers is changing the process for the better.

Traditional Versus Analytics-Enabled QA

Today there are two primary methods of conducting quality assurance: traditional and analytics-enabled. Traditional QA is a labor-intensive function. Supervisors and quality reviewers search hours of recordings to select a subset of them for evaluation. In some cases, QA applications can qualify calls or email/chat interactions for quality evaluation based on predefined criteria, such as call direction, call duration, interaction type (based on wrap-up, disposition, or another interaction classification mechanism), product type, program, etc. Others may use business rules to identify interactions that require attention. However, in both cases, while the QA process is facilitated and supported by technology, it is never truly automated. And because much of the process continues to be manual, only a small, statistically insignificant percentage of interactions are reviewed and evaluated. (Many contact centers receive millions of calls each week but only have the staff to evaluate 1 to 10 interactions per agent or 1 percent to 3 percent of all interactions, if they are lucky.) Although traditional QA is not ideal, for the past 30 years, it was the only way to provide some form of oversight, let agents know that they were being monitored, identify a small portion of performance issues, and surface operational, procedural, and system trends for the company.

Analytics-enabled QA is the antithesis of the traditional process. By leveraging desktop analytics, speech, and text, analytics-enabled QA solutions can automate the QA process and make it more targeted and precise. First, analytics-enabled QA solutions use speech analytics to review (and, in some cases, score) as much as 100 percent of calls to identify interactions that require attention. Speech analytics can be used to identify calls that require attention based on other key performance indicators, such as noncompliance with an established script; calls that include high emotion, talk-over, and/or positive or negative sentiment; or calls that contain/do not contain specific key words, phrases, or concepts. Speech and text analytics can also be used to identify broader enterprise trends, such as whether customer attrition is an issue, if a competitor has a new deal, or if there is a system or process that is causing high levels of customer dissatisfaction. Desktop analytics adds a new dimension to the QA process. By providing visibility into what agents do at their desktops, including the fulfillment process, it can "watch" to see if agents are delivering on their promises to customers, such as monitoring for accurate processing of monetary and nonmonetary transactions.

How to Transition to Analytics-Enabled QA

Companies that want to transition to analytics-enabled QA will need to purchase a new QA solution and typically upgrade their recording capabilities and capacity. They also have to revamp their QA best practices and policies, including their evaluation forms. As many companies are still using QA practices that were developed more than 15 years ago, all of these changes will be beneficial for the organization, its agents, and customers. DMG Consulting is a strong proponent of analytics-enabled QA; however, as is the case with most solutions, it's not as easy as the vendors make it sound, and requires different resources than were used to manage a traditional QA program. Contact center managers, supervisors, and QA specialists must be trained to use the new generation of QA-enabled systems, but it's well worth the investment.


Donna Fluss (donna.fluss@dmgconsult.com) is the president of DMG Consulting, a provider of contact center, analytics, and back-office market research and consulting.


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