Experience Exchange: How analytics supercharge supervisor performance

In the latest episode of Experience Exchange, Tom Lewis from TTEC Digital sat down with Erica Ong, head of productivity in the public sector at AWS, to explore how data analytics is transforming the supervisor experience. From freeing supervisors from spreadsheets to using AI for actionable insights, here are the standout moments and takeaways from their conversation.

From reactive to proactive leadership

Erica set the stage by highlighting how analytics has reshaped the role of supervisors:

"Data and analytics… really hinges on shifting away from being reactive with limited information and becoming proactive and allowing supervisors to be freed up and armed with actionable insights to coach, guide, and develop their teams."

In the past, supervisors spent more time crunching numbers than leading teams. Modern analytics tools give supervisors more time to focus on what matters — coaching and developing agents to deliver better customer experiences.

Turning AI into a collaboration tool

AI-powered analytics are changing the supervisor-agent relationship for the better. Erica explained:

"It's common even today for it to be a manual process done by supervisors… literally just listening to a very small subset of recorded calls, maybe 1% of calls, maybe two if you're lucky. …And now thanks to AI, we can now monitor 100% of all calls — and that changes the dynamic completely between the supervisor and the agent..."

Instead of relying on a single, potentially biased call review, supervisors now have access to comprehensive data. This creates a coaching environment based on fairness and partnership — not guesswork or judgment.

Key metrics work together — not against each other

Tom shared his "10-pound bag of goo" analogy — how metrics like average handle time, customer satisfaction, and first-call resolution often seem at odds. Here’s how he describes it:

"Imagine you have a 10-pound bag of goo, representing the contact center. It’s an unstable mass. To keep it in balance, you add straps — metrics like average handle time, customer satisfaction, and first-call resolution. 

If you tighten one strap, say average handle time, you risk throwing the balance off and forcing the other metrics, like customer satisfaction, to loosen. If you try to control too many things at once, you end up adjusting constantly to find the right equilibrium, and this can lead to unintended consequences like agent behavior manipulation or suboptimal performance in other areas."

Erica responded with a fresh perspective, highlighting how modern data analytics can change this dynamic:

"I think now with being able to truly analyze a holistic data set — and beyond just recording data, we can do call summarizations for a whole sampling of calls — that actually means to me that average handle time, first-call resolution, and CSAT, to name a few of those key KPIs, are no longer opposing metrics. 

They can work together in harmony. Because when an agent is equipped to resolve the customer’s issue the first time, in the most efficient manner, it’s going to improve first-call resolution, increase customer satisfaction, and reduce handle time."

Instead of forcing trade-offs between metrics, the right tools and insights allow them to work together. When supervisors have access to a more complete view of performance, they can improve multiple KPIs simultaneously, leading to better outcomes across the board. By analyzing all available data, supervisors can coach agents in ways that support both efficiency and customer satisfaction, creating a more stable and balanced operation — without the constant adjustments of the past.

Smarter scheduling improves employee experience

Beyond coaching, analytics are solving another major challenge — workforce planning. Erica highlighted the value of technology in optimizing this area:

"And that's also where technology now can help so seamlessly because, as long as we have historical call volume data, we can ingest all of that in and, with the flip of a switch, showcase our predictive analytics for call volume forecasting, but also associated schedules based on the parameters you have of hours of operation, the number of agents you have, all those sorts of things."

This ability to use predictive analytics for forecasting and scheduling is a game changer. It allows supervisors to optimize staffing levels in real time, ensuring that agents are scheduled efficiently based on demand. This approach helps meet customer needs more effectively while improving the employee experience by reducing unnecessary workload and stress.

Erica also contrasted this with the challenges faced by organizations relying on outdated or fragmented systems:

"Instead of having a 'Frankenstein' contact center — with disparate technology held together with duct tape and brute force — we can now provide one packaged application with native capabilities that handle everything from performance evaluations to forecasting and scheduling. This frees up time for supervisors to focus on what matters most: their agents and customers, rather than just managing complex technology."

By streamlining technology with integrated solutions, contact centers can move away from inefficient, disjointed systems and focus on creating better outcomes for both agents and customers.

Focus on the problem, not the buzzwords

Erica offered a critical reminder for anyone adopting new technology:

"We’re living at this super exciting — but disruptive — time of adopting generative AI and figuring out the right use cases. But I would argue that sometimes generative AI is not needed for what customers are trying to do. I use the analogy: Trying to nail in a thumbtack with a sledgehammer."

She highlighted that the simplest solution is often the best one:

"It really starts with what business objectives you’re trying to solve for, and then work backward from that. Because we are living at this time where technology can almost do anything — and technology just ends up being the enabler for process changes that affect people. And that's what you always have to stay laser-focused on."

In other words, it’s not about adopting the latest flashy technology — like generative AI — but about choosing the right tools to solve real business problems.

Smarter tools, stronger teams

If the session made one thing clear, it’s that modern analytics tools are more than just technology — they’re the key to unlocking better leadership, smarter coaching, and stronger business outcomes. By freeing supervisors from manual tasks and giving them actionable insights, organizations can elevate both the employee and customer experience. Because when supervisors thrive, teams perform at a higher level — and customers feel the difference.