The role of supervision in the call centre has always been multifaceted, serving to ensure good management of resources both human and technological, and to provide live monitoring of conversations with the brands customers.
For many years this role has been performed technologically to a significant extent, but in the centralised call centre operations we were all accustomed to until earlier this year, there was always a visual component as well — the reading of the body language of the agent, to discern all sorts of feedback, from stress to slacking. But when a single manager is overseeing a large shift of agents, whether they are co-located or working from their own homes, the manager only has one set of ears and eyes, and there can often be an element of luck involved in which conversations get supervised or not.
100% supervision and support
Enghouse’s real-time speech analytics listens to the whole conversation, and applies an AI interface to ensure optimal use of the supervisor attention. As Jeremy Payne, Group VP of Marketing & Alliances, explained, as well as listening to the content and specific words delivered, it is also sensitive to much more nuanced aspects of the conversation:
“There are more than 20 measurements within it, including things like, I am interrupting you each time you try and speak? Do I talk over the top of you? Am I talking more loudly than you? It also monitors use of inappropriate language, words or phrases that either break compliance with regulatory polices (like the wording of a legal disclaimer), or signify escalating stress in either party”.
As well as triggering automated guidance and warnings to the agent on their screen, alerts can prompt a supervisor to listen live to any call, where they’ll have the ability to either support the agent discreetly via ‘whisper’ mode, or in the most extreme event take over the call themselves.
A listening ear on every call
The bot can also render assistance that is far lower in the emotional stakes of course, such as by retrieving the most useful articles from a large knowledge base, so the agent appears to be an instant expert in whatever complex difficulty the caller is discussing, and the software was originally designed to support regulatory compliance. But the real change with home-based working is the ability to pick up on the less tangible, human reactions and responses which enables a smart contact centre software suite to stand out against more basic tools, because right now frontline call centre workers are having to absorb not only higher volumes of enquiries which might previously have resolved face-to-face, they are dealing with high levels of frustration and distress from many callers.
“The technology piece was actually pretty straightforward,” Payne explained. “The technologies [for distributed call centre operation] were already there, they could be scaled up pretty rapidly. But it’s the people and the culture that matter. What’s the right outcome for the customer? For the employee?”
“Most organisations still have a framework that’s based on measuring tasks, and quantitative indicators, and that won’t necessarily tell you whether you got the right outcome for the customer and the business”
So, if companies and their teams want to continue to benefit from all the upsides of the remote revolution, such as reduced commuting and energy and time-wasting, they’ll need to find new and smarter ways to support their teams effectively — ensuring their public-facing colleagues are empowered to do their best work in an appropriate cultural context, wherever they’re doing it from.
Natural language processing and real-time speech analytics are the solution to continuity, connectedness, and control, in the distributed contact centre of the present and future.
