What is Quality Management?
Quality Management (QM) is the process of continuous improvement based on setting goals, identifying deviations from these goals, and adjusting processes and behaviors accordingly.
Quality Management is the combination of QA and process improvement, making it a critical component of successful contact center operations. Potentially a customer’s first point of contact, the contact center presents a unique opportunity for an organization to directly and often permanently impact a customer’s experience and overall perception of the company. For example, a representative who fails to disclose a privacy statement or who is rude to a customer could inadvertently land the organization in legal trouble, elicit bad press, or both.
QM programs improve contact center performance by clearly defining desired representative behaviors, identifying interactions that miss the mark, and providing mentorship based on these “coachable moments.” A mature QM program not only improves customer perceptions of an organization, but also empowers representatives to become and remain effective frontline drivers of both positive CX and consistent regulatory compliance.
What do current approaches to Quality Management look like?
While there is a spectrum of maturity for QM programs, most follow these core processes:
Traditional rubrics or scorecards often evaluate performance by examining the presence of desired behaviors, some of which may be easier to consistently measure than others. For example, a rubric might evaluate the presence of a required disclosure statement or whether a representative showed soft skills like empathy. While a disclosure statement is relatively straightforward to both communicate and identify, soft skills requirements are often fuzzier and leave much up to the subjective interpretation of both the auditors and the representatives themselves, leading to inconsistent scoring.
Contact centers evaluate a percentage of their representatives’ calls. Auditors evaluate adherence to expected behaviors; however, manual quality management processes introduce the potential for subjective variation and human error. Extreme sampling can also make it harder to find significant trends that inform smart coaching.
Coach on Behaviors:
Coaches review representatives’ performance to reinforce organizational standards and expectations. However, coaches are limited by the number of audited calls, hours in a day, and the audit timeframe. Coaches may not give feedback to an agent until a month after a call, thereby making it very difficult for the agent to remember the interaction and learn from the situation, Additionally, a lack of historical records makes it challenging for agents and supervisors to track improvement over time.
QM programs build on QA processes by uncovering macro-level trends across contact center interactions and incorporating these discoveries into operation-wide improvements. However, if an organization only considers a sample of interactions, the insights it finds may be misleading or inaccurate.
Clarabridge’s approach to Quality Management:
Clarabridge’s QM solution is specifically designed for contact center professionals and harnesses the power of our entire product suite. Move from manual sampling to automatically evaluating 100% of contact center interactions by leveraging powerful rubrics and targeted coaching opportunities that cater to every member of your organization. With Clarabridge QM, every member of the contact center – from supervisors to representatives to speech analysts – is involved in a humanistic cycle of improvement.
Looking for more Quality Management tricks and tidbits? Download our eBook, Quality Management Reimagined: A Professional’s Guide to Optimizing Contact Center Operations.
Debunking Natural Language Processing
We’re on a mission to demystify a complex term: Natural Language Processing. Natural Language Processing (NLP) is a field of study that focuses on a computer’s ability to interpret human language in order to process, analyze, and extract meaning from large volumes of natural language text data.Download Now