When it comes to habits, Do you begin each day with a cup of coffee (or two)? What about screen time? If you were to calculate your habits and categorize them as “good” or “bad,” which grouping would be bigger?
Habits are good if the contribute to consistent positive behaviors. But in the workplace, they can have a negative impact on business outcomes. Resistance to change can cause your company to fall behind competitors that react more quickly and invest in operational improvements. Sometimes “business as usual” in a contact center can cause challenges in quality management and stifle progress toward organizational goals.
As a contact center professional, you can appreciate that our industry has long been an incubator of innovation. A case in point is customer relationship management (CRM) software. Every contact center has a form of contact management software, but it wasn’t until 1993 that CRM was even invented. Now it is the world’s largest selling category of enterprise software.
CRM is just one of the many examples where innovation has sparked positive change in the contact center market. However, quality monitoring (QM) has remained largely unchanged for many years. Since the advent of the modern call center in the mid-1970s, quality management professionals have manually monitored and evaluated call quality. They’ve listened to real-time conversations or recorded interactions remotely. They’ve then applied a standardized form and rated agents based on various quantitative and qualitative measures.
Because the manual QM process is labor-intensive and the average call volume is high, it’s been estimated that most contact centers evaluate only 1%-2% of the calls they receive. That means QM professionals are forced to leave a vast majority of interactions untouched. It also means most contact centers aren’t assessing enough calls to produce a statistically significant sample size.
While it’s clear that measuring the quality of agent-customer interactions is critical to contact center success, it’s increasingly difficult to do so via manual monitoring. It’s quickly becoming an outdated process due to the prevalence of remote and hybrid work and increased customer interactions via multiple communication channels.
As consumer expectations rise and more channels emerge, quality management has never been more important. Gone are the days in which manually spot-checking calls is good enough. As digital experiences and automation become increasingly prevalent, contact centers must adopt modern approaches for identifying quality management issues.
The traditional way of manually reviewing individual agent interactions is slow, costly and often ineffectual in accomplishing its main objective: improving the customer experience. It’s a particular source of frustration for contact center directors and analytics/BI specialists. They want access to near real-time data so they can identify challenges in quality management and issues shortly after they occur.
For quality management professionals, manual monitoring often leads to negative impacts such as:
For analytics or BI specialists, manual QM presents issues like:
As manual QM continues to fall behind, automated quality management (AQM) systems are gaining traction as an effective alternative, or least a supplement, to traditional monitoring methods.
Automated, predictive, analytics-fueled QM takes the time, and potential biases, out of the quality management process. AQM software uses advanced speech analytics to sift through all agent interactions during the defined time span and automatically score each interaction based on a user-defined scorecard. Reports show results by individual and by team, and QM professionals can track performance over time.
Additionally, AQM software can automatically categorize interactions, regardless of channel, and run predictive scoring on 100% of customer interactions. This is a major improvement from the average 2% of interactions that manual QM methods can address.
Using advanced speech analytics, AQM can also capture, categorize and quantify answers to open-ended questions. This helps eliminate some of the existing challenges in quality management associated with manual monitoring. Now that the technology has matured, major vendors such as Calabrio are stepping into the arena with their own offerings.
There’s really no comparison between a traditional, labor-centric quality management system and new, automated solutions. Let’s home in on the AQM advantages I believe are the most important.
Over the years, Pelorus Associates has authored several papers and articles that touch on the issue of employee retention. There are several causes for employee turnover. Rather surprisingly, we learned that an important factor was perceived supervisor bias. Agents believed that some employees were favored over others and, therefore, got higher ratings. There is an adage in the industry, “Agents don’t leave companies, they leave supervisors.”
Furthermore, agent attrition resulted from concerns about the way quality evaluations were conducted. The process was thought unfair because the calls reviewed were not (in the agents’ opinion) representative of typical calls.
Automated quality management systems directly address both concerns. First, all calls are reviewed, not just a small sample. Second, the ratings are administered automatically without human intervention using pre-defined scorecards.
Compliance is a very high priority in C-level suites. The contact center is perceived as a point of vulnerability because of the sheer volume of interactions and the reality that freshly trained agents may not be aware of the most critical rules that govern our industry. For example, compliance issues can surface when well-meaning agents request protected personal information (PPI) from customers, misstate warranty and return policies or fail to disclose required transactional information.
For these reasons and others, automated QM software with speech analytics provide greater security than manual monitoring. Speech analytics can help monitor compliance and reduce liability risks. AQM searches for keywords that may signal a compliance issue. Then, quality management supervisors can review those interactions on an ad-hoc basis.
Contact centers perform quality monitoring evaluations for a basic reason: ensuring a consistently positive customer experience. As evidenced by research, positive customer experiences result in improved customer loyalty. They consequently drive sales and profit growth too.
AQM can pinpoint areas where agents need help. This leads to targeted coaching that addresses the specific needs of individuals. It can also establish better hiring criteria and training policies for agents based on historical data.
In countries with highly dynamic economies, situations can rapidly change. Examples include new products, price increases, new competition, product recalls, staff shortages, senior management changes or relocation of a plant or headquarters office. Negative or positive information can impact quality scores, given the speed with which news travels through social media.
Brands increasingly expect contact centers to contribute to business intelligence. Management may ask you for consumer reactions to recent initiatives. With AQM, you can quickly change the scorecard or probe for answers to open-ended questions. The application records replies and analyzes them using speech analytics. Consumer response is almost immediate.
Traditional quality management is a highly labor-intensive process. Based on reasonable assumptions, we estimate that the annual labor cost for supervisors alone is $129,000 for a 350-agent contact center. Perhaps more importantly, we estimate that supervisors and quality analysts spend an average of 19 hours per month conducting agent evaluations. This estimation is based on several assumptions:
Contrastingly, AQM frees up supervisors to spend more time teaching, coaching and motivating rather than dealing with paperwork. This is not to say that AQM will render supervisor monitoring obsolete. What it does have the potential to do is make supervisors more effective with personalized coaching and training. Since AQM applications can surface complex and problematic calls, supervisors can focus on those rather than reviewing routine calls.
While virtually every other activity performed by contact centers has benefited from artificial intelligence, natural language understanding, advanced analytics, sentiment analysis or robotic process automation, the quality monitoring process is an exception. It remains largely untouched by these recent advances in technology, resulting in persistent, yet avoidable, challenges in quality management. Automated quality management presents a viable alternative that addresses the many weaknesses associated with manual quality monitoring.
Considering the cost of supervisor labor and the impact of quality monitoring on shaping the customer experience, we advise forward-looking contact centers to explore the state of automated quality monitoring at this time and evaluate how it could contribute to improved performance in their contact centers.