Advanced analytics are enabling contact centers to deliver by making the most of the combination of human and artificial intelligence-driven automation.
The implementation and impact of advanced analytics in contact center operations were explored by leading global consulting firm McKinsey at an event organized by Enterprise Ireland, the trade and innovation agency.
Customer Experience (CX) centers use data analytics to improve productivity, profitability and customer satisfaction.
Right now, the sector is undergoing significant change, with automation quickly moving to take on relatively advanced tasks, said Julian Raabe, who heads up McKinsey’s customer experience practice for EMEA.
Finding the right fit for automation
Raabe used a major US bank as a case in point. It has stripped 360,000 lawyer hours from its overhead by using automated processes to parse contracts to highlight only those that needed further – human – analysis.
Some 50% of all tasks done at work today could potentially be automated, although it may not make sense to do so in terms of value, said Raabe, who reckoned that, in fact, just 5% of jobs are likely fully automatable. Despite the rapid technological advancements of the past half-century, the only job that has disappeared completely is that of ‘lift boy’, he suggested.
What contact centers are ripe for is not automation to remove jobs, but automation to strip out non-value adding elements of a job, enabling agents to be more efficient and freeing them up to add more value to their role.
The power of predictive analytics
From Robotic Process Automation (RPA) to guided workflows and advanced analytics, right up to artificial intelligence, the opportunity to transform daily tasks in contact centers is, therefore, growing rapidly, with data collection and processing at the core.
One of the biggest transformations is the growth in proactivity, whereby businesses will increasingly use the data they have available about customers to predict why those customers might contact them, to try and resolve the issue in advance, he said, using a utility firm facing an outage as a case in point.
“Predictive maintenance is already there. They can fix a lot of these things before the customer even realizes it has happened. And if it’s not resolvable, at least when the customer calls, they can say, ‘Look, are you calling because of this particular issue?’ with successful prediction rates of over 70%.”
CX journeys are increasingly digital
CX journeys are increasingly starting in digital channels. In the service space, between 30% and 60% of issues that start digital are resolved there – and growing, he said.
Where digital-only is not sufficient, the move to omnichannel options is significant. “Customers increasingly expect companies to offer multiple channels,” he said, pointing to a two-year-old McKinsey survey, which found that 75% of people want to contact a company through at least two channels, and 25% want at least three.
The rise in social media should be of particular interest to the CX sector because not alone do customers like it, but – schooled by their experience in personal networks – they don’t expect an immediate response. This stands in contrast to a customer on the phone, who wants an answer now.
A second advantage is that social media enables both the customer and the contact center agent to have a full history of the conversation, enabling an agent to get up to speed quickly. What’s more, in social media, the person you are talking to is identified.
It’s why social media is something companies are now accelerating, said Raabe, “and it’s a little bit of a myth that the adoption of a channel depends only on your customers. It’s a combination of what your customers want and what you drive as primary channels.”
Frontline robotics will grow, helped by the increased success rate of interactive voice response (IVR) in resolving issues. The issue-resolution rate with IVR, without recourse to an agent, is as high as 65% among some McKinsey clients, without any drop in customer satisfaction.
Chatbots work well too, helped by the fact that people write shorter and more clearly than they speak, and accents are not an issue. Simply by automating those parts of a contact center call where a customer identifies themselves, and their issue can save up to 30% of a human conversation.
How analytics are impacting recruitment and retention
The result is a shift in the type of people being hired by contact centers. More investment is going into attracting and retaining the right people. This is important because while automation can boost efficiency, it is the human that provides the ‘X factor’, he said.
New technologies increasingly play a part in upskilling agents, including solutions that use speech analytics to monitor non-contextual elements, such as energy and empathy in an agent’s voice, to guide them to better performance – in real-time.
Next-best-action engines, driven by analytics, are growing in use too, helping the agent to fulfill requests more quickly. All of these initiatives are reducing dropped calls and transfers, empowering agents to resolve more issues themselves.
At the front end, it’s about prediction; at the backend, it’s about agent enablement, he said.
Advanced analytics can also help from a macro-management perspective, for example enabling employers to see which agents are most likely to leave in the next three months, and to optimize shift combinations, said Vinay Gupta from McKinsey Boston, a technical expert in data analytics. Employee analytics can also help you to select the right candidate profile for your call center.
Increasingly, McKinsey sees that organizations are starting to try and capture the employee life cycle value, increasing the productivity as well as the length of time employees stay.
It is enabling this by transforming the way training and development are conducted, resulting in a move away from one-to-one coaching towards peer learning. Equally, it is unearthing the real satisfaction drivers for employees, as opposed to those simply assumed by management.
An agile move beyond metrics
Advanced data analytics is facilitating a move beyond dashboards – which simply report metrics – to ‘action boards’.
The move to agile work practices, a concept traditionally held not to work in call centers, is, in fact, helping boost customer satisfaction by enabling more customers to have issues resolved in the first contact, rather than having them routed through the organization.
Regrouping personnel into clusters ensures greater agent identification with clients, delegates heard. It also incentivizes earlier resolution because agents know if a problem is simply passed on and not resolved somewhere else, it will come back to them.
Moreover, metrics are shifting from per-call costs to the total-customer cost, in line with agile principles such as empowerment, transparency, and responsibility.
Agile is often thought of as an “innovation engine” but Raabe sees it as an “execution engine”, which changes how people think and behave in call centers. By putting all these elements together “we can help to deliver a completely different customer experience,” he said.