Skip to content

Recently I’ve heard quality assurance programs and processes being referred to as “analytics- enabled”. What exactly does this mean?


  Printer Friendly Format    

Recently I’ve heard quality assurance programs and processes being referred to as “analytics- enabled”. What exactly does this mean?


For the past 30 years quality assurance (QA) has been performed in contact centers around the world in basically the same way. Managers search through volumes of recordings to find the 10% to 20% of calls that require attention, either because they are really bad or really good. QA is a labor-intensive function, based on an often random selection of calls, supported by technology but never truly automated. So, analytics is being injected into many contact center applications and processes to make them more actionable.

Speech analytics-enabled QA, or precision monitoring, changes the dynamics and greatly increases the value of quality assurance. It uses automation to review 100% of calls and rapidly identify calls that require attention – whether examples of excellent handling where agents should be complimented and rewarded, or calls where an agent’s performance is poor and they need to be coached. Closing the loop, the new QA solutions can evaluate the effectiveness of training and coaching programs by comparing past and current agent performance in any categories that require attention. Speech analytics can contribute to QA programs in other ways, as well. Speech analytics can be used to rapidly identify call trends in a single site or across multiple contact center sites so that organizations can more quickly fix the underlying issues that are stimulating call volume. It can also be used to assess the performance of a new group of trainees so that common training issues can be fixed right way and training programs improved.

Desktop analytics (DA) is another analytics application that is gaining ground and has strong potential to significantly contribute to an analytics-driven QA process. DA can be used to determine staff competency in using their servicing applications or whether or not they adhere to departmental policies and procedures. When agent performance trends are identified, this data can be fed into both a QA module as well as a coaching module. DA has the potential to empower agents and promote quality improvements by providing real-time guidance with the right information/offer at the right time.

The new generation of analytics-enabled QA solutions takes QA to the next level by automating many supervisory tasks. They also use a variety of analytical capabilities and technologies to improve the output from QA solutions and make the findings more targeted and actionable. These solutions automatically identify, classify and rank calls that require management attention. They also identify and classify operational issues caused by other front- and back-office departments such as sales, marketing, credit, billing, statement rendering, payment processing, manufacturing, product design, packaging, etc. With regard to QA, this means issuing alerts and creating dashboards that notify management either in real time or near-real time about any problems and their potential impact. The sooner management knows about an issue, the quicker they can get it fixed. This speed up resolution for customers already affected, and enables management to prevent the problem from impacting many others. These findings, along with links to supporting calls/emails, can be presented in customized dashboards and rapidly delivered to managers inside and outside of contact centers. They also gives QA specialists, supervisors and trainers more time to dedicate to helping agents and customers. 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.