AI-Powered Dashboards Give Employees and Supervisors Real-Time Insight

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At the height of the COVID-19 pandemic, when most companies shifted the majority of their contact center employees to work-from-home agents, dashboards and notifications for managing contact center employees became very important. Managers could no longer walk the floor to monitor the activities of the agents under their supervision, and keeping track of their activities became a top priority.

Now that the worst of the pandemic is over, most contact center employees have returned to the office, but roughly a quarter of companies plan to keep some of their agents working remotely, providing a significant opportunity for the vendors of dashboard and notification systems.

In brick-and-mortar contact centers, dashboards are usually displayed on TVs/monitors where everyone can see them. However, they can also be web-based for use by remote and hybrid teams.

Typical dashboards—provided by dozens of vendors—present data in a number of formats, including bar charts, line charts, pie charts, heatmaps, gauges, and funnel charts.

Dashboards are widely used today to visualize live metrics, such as the total call volume, the number of calls in the queue, wait times, response times, customer satisfaction (with data culled from short post-call surveys), and a lot more. Data can be companywide or segmented by location, department, team, or individual employee.

By creating greater awareness and visibility for key metrics, dashboards make it more likely that issues will be spotted early and resolved quickly. They also provide a focal point for performance measurement, helping motivate teams to achieve their goals.

Dashboards can be focused on performance for a particular day or week or more focused on overall trends for the month. This broader perspective allows teams and team leaders to put their key metrics in context so they can improve performance in the long term. It also helps them understand how call volume is changing so they can better allocate resources.

Typical dashboards have become table stakes in contact centers, says Carmit DiAndrea, director of engineering for artificial intelligence data management at NICE. “We can show the agent stats, contacts, and queue, all of the [service-level agreement] information, the skills, the interactions, and the context.”

And while the technology to do so has been around for a while, artificial intelligence and advanced computing power are moving these dashboards beyond historical or delayed information to data presented to contact center supervisors and employees in real time.

With modern solutions, users can tell the software what to look for—everything from agent knowledge and empathy to script compliance or customer sentiment. Then, when a call breaks protocol or strays from what is required by either company or government regulations, for example, the technology immediately spots it and triggers an alert to the right people. Many also combine the power of AI with easy-to-use survey tools to create a holistic understanding of agent and team performance, bringing together automated scores, post-interaction surveys, and quality assessments, all in one place.

Additionally, contact center supervisors are examining new dashboard charts and graphs that show different cuts of data using conversational AI to better manage the contact center, says Matt Smith, vice president of analytics at LivePerson.

Contact center technology providers have updated their dashboard and notification solutions in other ways in just the past year or so, and still more innovation is planned for the near future.

NICE, for example, introduced a co-pilot for supervisors in June and has continued to add features and functionality each quarter. Conversational inquiry capabilities, introduced earlier this year, is the newest feature.

“We want to empower supervisors to prioritize their activities for maximum impact and allow them to intervene in intelligent ways,” DiAndrea says. “We’re really focused on real-time intelligent alerts. We’re providing a full summary of ongoing interactions with journey highlights. We’ve also built into our supervisory workspace conversational inquiries—or the ability for supervisors to conversationally interact with and interrogate their data so that they can intervene in the right places and in the right ways.”

A supervisor could, for example, receive a notification when one of her agents has had his third break of the day, which is 30 minutes above the team average. That indicates a need for behavioral coaching, DiAndrea says.

Another real-time alert might indicate that an agent has been on a very long call and that the customer sentiment on that call is continuing to drop, DiAndrea adds. “The reason it’s dropping is because the agent isn’t demonstrating any ownership. That is very actionable. The supervisor knows exactly how to coach this particular agent around ownership. We’re focused on providing the right alerts at the right time and providing the supervisors with enough information to make intelligent interventions.”

Intelligence is the key component of all dashboards today. The newest dashboards are much more insightful than their predecessors, says Trudy Cannon, a senior director of go-to-market strategy at Verint, which introduced a data insights bot almost a year ago.

“With the old dashboards, you would get what you asked for,” Cannon explains. “You might only get the performance of one employee rather than all of the performance happening throughout the contact center. What the data insights bot does is include additional data to provide a holistic view.

“It’s not just a static dashboard; it’s very interactive,” Cannon continues. “Instead of going in and just viewing statistics, I can just ask in natural language, in a conversational way. “

Some of these natural language queries might include “What’s my quality performance?” or “What’s the call volume across a queue?”

And with modern solutions, the supervisor receives not just the answer to that question but also any other relevant data related to that question. Drill-down capabilities enable supervisors to uncover other information, with headlines highlighting the most important things.

Dashboards and notifications have also moved from being very static to very interactive, Cannon adds. “We can just ask natural questions, then it returns not just what we asked for, but also the relative points that we need to know to make faster decisions, have better insights, and provide better coaching for the employees that we are supporting.”

Another advantage of interactive dashboards, according to Cannon, is that they pique the curiosity of the user. If the dashboard shows something out of range but not yet at a level that triggers an automated alert, the supervisor can ask a question, in conversational language, about it. The supervisor could, for example, ask why a certain employee’s average handle time is noticeably above the average and take action before it becomes a serious problem.


The newest dashboards are designed to take a lot of the guesswork out of contact center management, but experts agree that there is still plenty of room for gut instinct and intuition.

“Dashboards aren’t typically [steeped] well enough in the drivers of the problems as they occur operationally,” says Joe Bradley, senior vice president of conversational AI at LivePerson. “They mostly give you clues rather than answers.”

“The dashboards and notifications themselves are just the tools to trigger human intelligence,” agrees Smitha Baliga, CEO and chief financial officer of TeleDirect Communications.

Even with all the technology at their fingertips, supervisors still need to closely examine dashboards and notifications to discern what is prompting the alerts, according to Bradley, noting that a dashboard can notify a supervisor that the repeat call rate is on the rise, but the supervisor needs to dig through the details to determine the reason for that increase.

“The best contact center managers are really good at digging,” he says.

“You cannot ignore the value of gut intuition,” DiAndrea agrees. “It’s that gut intuition and the knowledge of how things work that really allows you to put additional context around the numbers and around all of the alerts and activities.”

This hard-earned expertise, she explains, enables supervisors to set up their own alerts and to know what to look and listen for.

The reverse is also true. “Most of the time, we see problems in the contact center not because people don’t have a good dashboard. It’s because they don’t know what their real business problem is, what to point their dashboards at, or how to interpret what those dashboards are telling them very well,” Bradley says.

Then, dashboards and alerts should be configured differently for different contact center clients, because each has different metrics, service-level agreements, call volume, staffing needs, and more, experts agree.

Though the new dashboards and notifications can provide contact center supervisors with plenty of additional, relevant data, it is important not to overload them with too much information, warns Jim Nies, vice president of product strategy for engagement management solutions at Verint.

“We have a hybrid workforce. We want to blend humans and automated capabilities. You have to have a lot of respect for the humans when you are developing the technology. You can drown people with notifications. If you don’t have the right guardrails on it, you can cross the line from annoying to unethical if you really screw up.”

So when developing alerts, companies need to be smart in setting the thresholds that result in supervisor notifications, Nies explains. Developers also need to make it easy for supervisors to move from alert screens to action screens so that when, for example, they detect that a work queue is overloaded, they can quickly move employees from a slower queue to the overloaded one.

“You have to be very careful about what reaches the level of the supervisor,” Nies says, adding that notifications shouldn’t stop with alerts but should also offer recommended next actions.

It also helps when the technology enables supervisors and employees to see the impact that requests and decisions might have on the rest of the team and on operations overall.

Verint has built that capability into its workforce management solutions so that all team members can see the larger picture when, for example, requesting time off. They could see how missing a weekend shift could put a lot of additional work on other team members, hopefully leading them to request a different day off, Nies says. “That makes for more human decision making, which is always going to be more powerful than what we can do synthetically.”


As with so many other software applications, though, generative AI is expected to become the most integral part of supervisor dashboards and notifications in the next several months, experts agree.

“One of the promises of generative AI is that you will have a much better alerting and dashboard creation process, a much more faithful one to your true customer problems, and a much more agile one than you can have today,” Bradley says.

NICE has already started introducing generative AI into its supervisor workspace, according to DiAndrea. Traditional AI, she says, “has a well-known, well-defined value proposition. But we’re going to find new ways to introduce generative AI into our supervisory workspace. We’re going to find new ways to use content from knowledge bases, along with generative AI, to more effectively guide supervisors and to find new ways to help them work smarter, be more efficient, and prioritize their workdays for maximum impact.”

LivePerson is focusing more attention on providing dashboards that help contact center supervisors see more granular information, according to Smith. “We want our dashboards to visually drive people down the page from the top line of the business down to what’s happening in the weeds and in the conversations to drive that top line. As you drill down, you basically go from 1 million conversations down to a few thousand, just for example. That becomes your dataset that you can then interrogate, and this is where the quantitative and the qualitative come together. Generative AI models allow you to then go query that set of transcripts.”

Other important innovations in the past year or so include a more unified view of data from multiple sources, such as call logs, ticketing systems, customer feedback, and CRM and contact center analytics solutions.

Data and metrics are also presented more intelligently today, with advanced systems that can group related elements, such as service-level agreement adherence, agent job performance, customer satisfaction, or agent training needs, in a single pane of glass and a much more logical sequence.

But the best dashboards, and the ones that will be most useful, have clearly defined objectives; are tailored to their audiences (C-suite executives will want more high-level insights while lower-level supervisors will want more granular details); and provide historical context to help identify trends over time, according to experts.

And finally, contact center leaders will need to regularly review and update their reports. As business needs change and goals evolve, reporting needs might also change. Regular reviews ensure that reports remain relevant and impactful for all stakeholders throughout the company. 

Phillip Britt is a freelance writer based in the Chicago area. He can be reached at spenterprises1@comcast.net.

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