Quality Management and the Power of AI

The quality management process is a strategic component of a contact center’s daily activities. Because it’s a pillar for enhancing performance, ensuring compliance and driving customer experience, you need to find the right tools to support and enhance its benefits.

Quality assurance depends on human factors, specifically agent performance. Managers know that generating clear guidelines and training while adequately monitoring employees is key to achieving optimal performance. However, many managers often feel immersed in a series of disconnected processes.

  • Redundant manual processes: Managers and evaluators need to navigate and collect necessary information that’s often spread throughout — or hidden in — disparate systems. This prevents them from having all the necessary information at hand to effectively compare and efficiently analyze data.
  • Low analysis range: On average, only 2% – 3% of interactions executed monthly are analyzed. In turn, reports are generated based on data that could have a high margin of error, which can have counterproductive effects on business.
  • Inadequate quality feedback: Because feedback can be subjective due to the small segment of interactions analyzed, the findings provided don’t cover the entire spectrum of potential outputs. In addition, this could decrease the effectiveness in decision-making while degrading the ability to provide suitable training for agents and develop generic training programs.

These methods are outdated and no longer offer companies a path to address quality processes. Each company has a unique way of approaching clients and a variety of compliance policies on which they must focus — limiting the quality process to a subsequent random evaluation of interactions won’t give you enough data to make appropriate corrections. The quality assurance process needs to be seen from the perspective of not only the quality teams but also training teams, supervisors and agents.

Looking to the Future of Quality Management

If we take into consideration that 83% of companies say artificial intelligence (AI) is a strategic priority for them, and that AI solutions increase productivity, it’s time to consider how AI-powered tools can boost productivity and give companies the flexibility to adapt to an ever-changing environment.

Many companies have started incorporating tools to automate scoring and monitoring, and execute sentiment analysis through all interactions. Some tools will personalize training and coaching and provide immediate feedback through real-time error identification.

AI will become a key piece of the quality management process as it becomes deeply rooted in essential tools. With that, it will drive more:

  • Analytics-based decision-making
  • Accuracy
  • Automation
  • Intelligent training and coaching

Having intuitive platforms that recognize and select which interactions to evaluate will optimize repetitive tasks with a large workload. Resulting data and insights will drive the decision-making process.

AI-powered tools use sentiment analysis to examine all interactions that take place, reducing manual input, automating scoring processes and quickly identifying interactions that show both low performance and exceptional execution.

By mixing intuitive platforms with machine learning capabilities, transcription processes can enable 100% quality assurance monitoring through all interactions. This will be critical to improving performance evaluations and generating personalized KPIs using agent and customer sentiments as well as compliance requirements. And this will improve the overall user experience.

These tools also empower supervisors and managers to work more efficiently and strategically, reducing the time it takes to navigate through interactions and determine which ones to evaluate. With AI, high- and low-performance interactions are marked for evaluation, reducing agent subjectivity and bias. Ultimately, this allows managers to identify knowledge gaps and generate more relevant training programs for employees.

AI is driving a sea change within quality management. With a mix of the tools that can integrate speech and text analytics, sentiment analysis, predictive coaching and assistance, the quality assurance and compliance field will see a boost in results. These tools will also increase how efficiently tasks are executed, enabling supervisors and managers to empower their teams and execute more strategic business decisions.

Read why Frost & Sullivan recognized Genesys in the 2020 North American Workforce Optimization Innovation Excellence Frost Radar Award. And read on to find out why Gartner named Genesys as a Visionary in Workforce Engagement Management.