Toyo Tires Cut Overtime By 30% By Fixing Attendance

THE SHIFT START PROBLEM

6:47 a.m. Your incoming supervisor just walked on the floor.

They don’t know yet that two operators called out overnight. They don’t know that the voicemail box employees were supposed to call filled up before their message went through. They don’t know that the line has been short-staffed for three hours already.

They find out the same way they always do: when the line falls short.

At Toyo Tires’ manufacturing plant in White, Georgia, this wasn’t an exception. It was every shift. 1,500 employees running 24 hours a day, 7 days a week. And the only way to call out was a plant landline that might not get answered and a voicemail box that was chronically full.

For the plant manager, this created a problem that doesn’t show up in the ERP at least not with an explanation attached. The line ran short. Overtime spiked. Cost per unit climbed. And the Monday morning report showed a variance that no dashboard could fully explain.

That variance had a name. It was the shift change. And it was happening every single day.

THE MATH PROBLEM

Mia Williams had been in HR for nearly 30 years.

She’d started her career as a production supervisor at Ford Motor Company and she carried that lens into every HR role that followed. When she arrived at Toyo Tires and saw the attendance system, her instinct was immediate.

She wasn’t looking for a way to make HR more efficient. She was looking for a way to give the operation back its visibility.

She implemented TeamSense. Not as a people-management tool. As an operational data layer. And what happened next wasn’t primarily an HR transformation it was a shift intelligence transformation.

HOW ATTENDANCE BECAME OPERATIONS DATA

When employees can report absences via text — no landlines, no voicemail boxes — the signal arrives before the shift.

Supervisors had crew visibility before the line started. And that data didn’t stay in HR. It traveled exactly the way Mia had always believed it should.

For plant managers, this is the signal that was always missing. The ERP shows what happened. It doesn’t show why. It shows the line ran short, it doesn’t show that three operators called out at 5 am, and the supervisor had no way to know before the shift started.

TeamSense closed that gap. And the numbers followed.

THE RESULTS

The department with the highest overtime burden cut those hours by 30%.

That’s not an HR metric. That’s a per-unit cost metric. It’s a production planning metric. It’s the number that shows up on the Monday morning report as variance recovered rather than variance explained away.

The overtime reduction didn’t just reduce cost. It triggered something Mia hadn’t initially anticipated: a gain share payout to the entire hourly workforce.

When your floor workers receive a share of the gains your operation recovered because supervisors finally had the visibility to run the shift correctly, that’s the moment you understand that attendance isn’t an HR problem. It’s an ops problem with an HR entry point.

WHAT THE DATA REVEALED BEYOND THE NUMBERS

The most powerful thing about operational data is what it surfaces that you weren’t looking for.

When Toyo’s team started analyzing call-off patterns, really digging into the data, department by department, they found something they hadn’t gone looking for.

A spike in back pain in one department. Investigation revealed that tenured workers had been standing on concrete floors with no ergonomic mats, possibly since the plant opened. Mats were installed. Workers’ comp cases dropped.

The same data showed pattern after pattern of family emergency, transportation crisis, and childcare gap. And the COO saw the numbers. He didn’t file them under HR. He created a dedicated Community Resource Coordinator a full-time position whose entire mandate is connecting Toyo employees with United Way, food banks, housing subsidies, childcare assistance ($200/month per employee), and vehicle purchase programs. A bus service to bring workers to the plant is in the works.

The COO didn’t fund this from an HR budget. He funded it because the data made the business case. Fewer terminations means lower replacement costs, fewer training gaps, more experienced operators on the floor, and a workforce that trusts the company enough to show up.

That’s the shift from HR tool to operational intelligence layer.

WHAT TOYO PROVED — AND WHAT’S COMING NEXT

Mia Williams built something remarkable with the foundation TeamSense provided.

A production intelligence system where attendance data flows upstream to inform scheduling, forecast overtime, and drive cost per unit decisions. She built it manually through daily calibrations, morning production reports, and a relentless belief that every people problem is a math problem.

What TeamSense is building in 2026 is that same intelligence layer, as a product. So the next plant doesn’t have to start from scratch.

Toyo Tires ran ahead of the roadmap. What their HR leader built manually the ops-HR data bridge, the production forecasting loop, the cost per unit connection is what TeamSense is now building into the product.

The thesis is proven. The system is being built. The question for every plant manager is the same one Mia Williams asked in 2024: What would it look like if you treated this like a math problem?