I’m about to say something that’ll make half the ops leaders reading this immediately hit delete: Average Handle Time (AHT) is a garbage metric. There, I said it.
Look, I get it. I’ve spent years watching AHT dominate every dashboard, every coaching session, every QA form. I’ve sat in countless budget meetings where reducing AHT by 30 seconds was treated like finding the Holy Grail, complete with PowerPoint animations and everything. I’ve seen entire operations strategies built around shaving time off calls like we’re preparing for the Olympics of customer service. And you know what I’ve learned? We’ve been optimizing ourselves straight into mediocrity.
It’s like we all collectively decided that the best customer experience is the fastest one. By that logic, the best restaurant would be the one that throws food at you while you’re still in the parking lot.
The AHT Trap We All Fell Into
Here’s how it happens. Finance needs to justify headcount. Leadership wants efficiency gains. Your WFM team needs predictable intervals. So AHT becomes the golden child, the favorite metric that can do no wrong, the valedictorian of your KPI family while Customer Satisfaction is out back on another extended break.
Before you know it, every decision flows through this single lens: “Will this increase or decrease handle time?” It’s like asking “will this make us taller?” for every business decision. Sometimes the answer doesn’t actually matter.
Agents learn the game fast. They rush through interactions like they’re speed dating. They develop clever ways to get customers off the phone without actually solving anything, mastering what I call the “polite ejection seat” technique. They become transfer artists, moving problems around like a shell game at a carnival. Your quality team catches some of it, but they’re drowning in volume too, listening to calls while silently screaming into the void. Meanwhile, your CSAT scores are bleeding, your repeat contact rate is climbing, and nobody can figure out why.
I can tell you why. Because we told everyone that speed matters more than outcomes. We essentially gave everyone a participation trophy for showing up quickly.
What Actually Happens When You Worship Speed
Let me paint you a picture. Mid-sized BPO, about 800 seats, handling tech support for a major consumer electronics brand. Their AHT target was 8 minutes. Sounds reasonable, right? They were hitting it consistently. Leadership was thrilled. Efficiency was through the roof. The wall of green dashboards was so beautiful it could make a grown CFO weep.
Then we dug into the data, because I’m that guy who ruins everyone’s party by actually asking questions. Their first contact resolution was 61%. Think about that. Nearly 4 out of 10 customers were calling back. When we tracked those repeat contacts, the real handle time for actually resolving issues averaged 23 minutes spread across multiple interactions. But hey, each individual call hit the 8-minute target, so everyone got their bonuses and probably high-fived about it.
It was like watching someone brag about their time in a relay race while conveniently forgetting they dropped the baton twice.
The customer experience was trash. Agent morale was worse. They knew they were playing a shell game, shuttling problems down the line instead of solving them. The good agents burned out. The ones who stayed were the ones comfortable with mediocrity, or as I like to call them, “the survivors of the efficiency apocalypse.”
That’s what AHT optimization gives you: a beautifully efficient operation that doesn’t actually work. It’s the business equivalent of running really fast in the wrong direction.
The Metrics That Actually Tell You Something
So what do you measure instead? I’m not saying handle time is completely irrelevant, but it needs to be part of a constellation of metrics that actually reflect outcomes.
- Start with First Contact Resolution. Not the made-up version where you survey 8% of customers. Real FCR based on interaction tracking. If a customer contacts you about the same issue within 7 days, you didn’t resolve it the first time. Period. This metric alone will change how your team approaches every interaction.
- Customer Effort Score matters more than CSAT. How hard did we make this for the customer? Did they have to explain their issue three times? Did we transfer them twice? Did we solve it, or just document it? CES correlates with loyalty better than any satisfaction metric I’ve seen.
- Resolution Time across channels. In 2025, customers don’t have “a call” with you. They have a journey that might include chat, email, a callback, and an app interaction. What’s the time from initial contact to actual resolution? That’s your real efficiency metric.
- Agent utilization, not occupancy. I want to know if my agents are productively engaged, not just if they’re on a call. An agent spending 6 minutes researching a complex issue is adding more value than one who’s been on back-to-back calls but solving nothing.
- Quality calibrated to outcomes. Stop scoring on whether the agent said the right words. Score on whether the issue was resolved, the customer was satisfied, and we didn’t create more work downstream. Correlation is your friend here.
The Business Case for Slowing Down
Here’s where I usually lose the CFO crowd, and I can see their eyes glaze over like I just suggested we switch to a four-day work week and free massages. They hear “stop optimizing handle time” and they see costs spiraling out of control, probably with little cartoon dollar signs flying away.
So let’s talk dollars, because that’s the only language that matters when you’re trying to change peoples mindset.
That operation I mentioned earlier? We ran a pilot where we gave 50 agents permission to take the time needed to actually resolve issues. No AHT targets for 90 days. Just solve the problem. We tracked everything else, but handle time became advisory, not punitive. Basically, we told them “you can’t get in trouble for doing your job right,” which apparently was a revolutionary concept.
Average handle time went up 2.3 minutes per contact. Finance nearly had a stroke. I’m pretty sure someone printed out the report just so they could crumple it up dramatically. But FCR jumped from 61% to 84%. Repeat contacts dropped 35%. CSAT climbed 18 points. And here’s the kicker that made everyone shut up: when we modeled the total cost including repeat contacts, transfers, and escalations, we were 14% more efficient than before.
Turns out, doing it right the first time is cheaper than doing it fast three times. Who knew? Well, apparently not the last several years of contact center conventional wisdom.
What This Looks Like Operationally
Making this shift isn’t just about changing metrics. It requires rewiring how your operation thinks. I’ve done this enough times to know where the landmines are.
- First, your coaching model needs to flip. Stop coaching to time. Start coaching to outcomes. When you review interactions, the question isn’t “could this have been faster?” It’s “did we solve this completely?” That’s a fundamental mindset shift, and your frontline leaders will resist it because it’s harder to measure and easier to debate.
- Second, your knowledge management becomes critical. If you’re asking agents to resolve issues thoroughly, they need tools that actually work. Most knowledge bases are optimized for speed too, giving agents just enough information to sound credible but not enough to actually fix anything. You need deep, comprehensive content that enables real resolution.
- Third, your workforce management model has to evolve. Traditional forecasting assumes consistent handle times. When you shift to outcome-based operations, your AHT becomes more variable. Your WFM team will hate this initially, but it forces them to build in appropriate buffers and plan for complexity, which is more realistic anyway.
- Fourth, you need executive air cover. The first month your AHT ticks up, someone’s going to panic. You need leadership that understands you’re playing a longer game. Track your pilot metrics religiously and communicate them constantly. Show the total cost picture, not just the handle time snapshot.
The AI Dimension Nobody’s Discussing
Here’s where this gets really interesting in 2025. Everyone’s throwing AI at their contact centers, and most are measuring success by how much AI reduces handle time.
Wrong game entirely.
AI should be handling the simple stuff, which means your agents are getting a higher concentration of complex issues. If your AHT isn’t going UP after AI implementation, you’re probably not routing intelligently. You’re just making humans clean up AI’s messes faster.
If you’re using AI just to make humans faster, you’re missing the entire point of the technology.
Making the Shift
If you’re reading this and thinking “this sounds great but impossible,” I get it. You’ve got entrenched systems, vendor contracts built around AHT, compensation plans tied to speed, and a decade of operational muscle memory to overcome.
Start small. Pick a team, a client, a product line. Run a pilot where you change the metrics and see what happens. Track everything. Build your business case with real data. Then scale what works.
The contact center industry has been on autopilot with AHT for too long. We’ve optimized for a metric that doesn’t actually correlate with business outcomes. It’s time to wake up and measure what matters.
Your customers don’t care about your handle time. They care about whether you solved their problem. Maybe it’s time we cared about the same thing.
Your Move
So here we are. I just spent 2,000 words telling you that the metric you’ve built your entire operation around is fundamentally flawed. You’re probably either nodding your head thinking “finally, someone said it,” or you’re mentally composing an angry email about why I’m completely wrong. Good. Do it. I mean it.
Here’s what I want from you: tell me I’m an idiot. Tell me why AHT still matters. Show me your operation where speed and quality somehow coexist in perfect harmony like some kind of contact center unicorn. I’ll wait. Better yet, I’ll engage, because I’ve been wrong before (my wife has a long list), and I’m always open to data that challenges my thinking.
Or maybe you’ve lived this nightmare. Maybe you’re the ops leader who’s been screaming into the void about FCR while everyone around you obsesses over handle time. Maybe you ran a similar pilot and got similar results. Share your story. Let’s build a case study collection that’s actually useful instead of the sanitized vendor garbage we usually get.
And if you’re sitting there thinking “oh my god, this is exactly what’s happening to us right now,” do me a favor. Forward this to your leadership team. Better yet, accidentally CC your CFO on it. Print it out and leave it on the conference room table before your next operations review. Blame it on me. Tell them some VP with too much time on his hands wrote something that made you think.
Consider this your permission slip to try something different. Run a pilot. Change the metrics for one team. Track what actually happens instead of what you think will happen. The worst case scenario? You prove me wrong and get to write a strongly worded LinkedIn comment about it. The best case? You fix something that’s been broken for years and actually improve your operation.
I’m genuinely curious where you land on this. Are you team “AHT is dead” or team “you’ll pry my handle time targets from my cold, dead hands”? Hit me in the comments, send me a message, or write your own counter-argument. I read everything, and I actually respond.
And if this resonated with you, subscribe to The Operational Edge. Every edition tackles something the industry accepts without question. Sometimes I’m right. Sometimes I’m spectacularly wrong. But it’s never boring, and I promise you’ll never read another paragraph about “synergistic optimization frameworks” or whatever consultant-speak is trending this week.
Fair warning: next edition might be about why your quality program is secretly teaching agents to fail. Or why your AI vendor is lying about their accuracy metrics. Haven’t decided yet. Depends on what makes more people mad.
Let’s make contact center operations interesting again. Or at least honest.
This blog was first published on LinkedIn
