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Predictive Maintenance Success Story: Achieving Team Buy-in With Early ROI

February 14, 2025

Are predictive maintenance services worth the investment? Here’s how one facility got team buy-in and paid for two years of service with its first asset win.

If you’re fed up with the chaos, stress, and costs of putting out fires as assets suddenly fail (aka the reactive “cycle of doom”), predictive maintenance is likely on your radar.

A growing number of manufacturers and municipalities are discovering the immense value of detecting and resolving equipment issues early via vibration monitoring, oil analysis, and other condition monitoring techniques. It’s not just about money saved due to avoiding costly repairs and extending asset lifespan; predictive maintenance is also key to achieving a calmer, more productive, more sustainable operation.

That said, the prospect of adopting predictive maintenance technologies can seem daunting to facility teams. Many wonder:

• Does this technology actually work?

• Will adoption be painful, in terms of implementing and learning the system?

• How will artificial intelligence impact the workforce?

As the City of Tulsa’s wastewater treatment facility was preparing to transition from preventive maintenance to a predictive maintenance strategy, some members of the team were a bit skeptical at first. They questioned the value that predictive maintenance technologies could bring.

Fortunately, a quick and sizable savings delivered during an initial trial period eased those concerns and doubts.

Predictive Maintenance Costs vs. Benefits: Understanding What’s at Stake

Having to put out fires with every sudden equipment failure at the wastewater treatment facility came at a high cost for the City of Tulsa. The maintenance team would have to rush order parts they didn’t have on hand as well as bring in contract labor to help manage the situation.

Even worse, if the facility ever found itself relying on backup systems and lacking the right parts inventory, planning, or scheduling—a major risk without the benefit of early detection and resolution of issues—an unexpected breakdown could mean big trouble.

As Maintenance Reliability Coordinator Scott Furman put it, “They say when it’s wastewater, if it fails, it really rolls downhill.”

Because he understood the potential of predictive technologies, Scott provided the team with documentation and research showing the value of having a predictive maintenance program in place. He got the team on board, but some were still skeptical.

“We had already transitioned a little bit more into preventive, and then we were rolling towards predictive and implementing that in a more structured manner. Everybody wondered if the technology was actually going to work. After we received a few results, it definitely started to . . . and buy-in for it, too.”

— Scott Furman, Maintenance Reliability Coordinator, City of Tulsa

Facility’s $45,000 Savings During Trial Period Pays for First 2 Years of Predictive Maintenance

The City of Tulsa began a six-month trial of AssetWatch’s end-to-end condition monitoring solution—including Vero® remote vibration sensors, predictive analytics software, and dedicated CAT III+ analyst support—at 50 locations.

The team chose to go with AssetWatch’s subscription service, rather than building and maintaining a condition monitoring system in house, partly because the team lacked the qualifications and training needed to interpret the vibration data coming in. By partnering with AssetWatch, the team could get up to speed while working toward certifications of their own.

“It was actually a pretty smooth transition,” Scott said. “When AssetWatch came in and did the six-month trial with us, they took us through it step by step to show what they were going to produce for us and what type of service they were going to provide. I thought it was very interactive and they were very thorough in how they explained what their process was.”

During this trial period, AssetWatch detected an anomaly caused by a minute manufacturer defect on a blower bearing. Because the defect was caught and resolved early, the facility saved about $45,000 in repair costs—with this savings alone paying for the first two years of service.

“The monitoring service showed us what it could provide us,” Scott said, “and it also showed us justification of going forward with the process and the predictive maintenance technology.”

Asked for any advice he might give other maintenance and reliability teams considering predictive maintenance or which provider to choose, Scott had this to say: “Keep an eye on the predictive technologies. Dig into the companies very deeply. Make sure you know what you’re getting into, and know what they provide. Dial it in before you decide you’re going to pull the trigger.”

“I know there’s some hesitancy towards the artificial intelligence type of programs, but honestly . . . it’s a technology that’s going to save you money, it’s going to save you time, it’s going to save you maintenance time and maintenance work labor hours as well.”

— Scott Furman, Maintenance Reliability Coordinator, City of Tulsa

Learn More About the City of Tulsa’s Successful Transition to Predictive Maintenance

There’s much more to this predictive maintenance success story. To learn more about how the City of Tulsa overcame initial challenges and how their predictive maintenance program has continued to evolve, watch the replay of the recent Noria webinar Navigating the Shift: One Plant’s Journey from Reactive to Predictive Maintenance.

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