How SpinTurf Transformed Operations with UpKeep Nova

Overview

Selina Patterson, a maintenance supervisor at SpinTurf with over 20 years of hands-on experience in construction, facilities maintenance, and repair, was tasked with transitioning her facility from manual, paper-based maintenance tracking to UpKeep's CMMS system. What she discovered was that UpKeep's AI assistant, Nova, transformed not just her data entry process, but her entire approach to maintenance management.

In her own words: "My work-life balance is a lot better now."

The Challenge: "Caveman Style" Data Management

Selina describes her starting point: "We were just pen and paper, everything was just caveman style for lack of a better description."

Her initial role involved getting data into the UpKeep system. "For the first little while, all I was doing was entering data. I would ask Nova here and there for a little assistance, but I was just typing away—that's all I did."

The challenges included:

• All maintenance records on paper with no digital system
• Hours spent manually entering historical data
• Transitioning from hands-on technician work to supervisory role: "I've been turning a wrench all my life, so to move over into the supervisory role has been intricate"
• Uncertainty about what information was valuable to track
• Reactive maintenance dominating their work schedule

The Solution: Learning to Work with Nova

Taking a Two-Week Maintenance Reset

Before fully diving into UpKeep, Selina's team took a strategic approach to get ahead of reactive work:

"In order to get us to a place to where we were actually able to do the preventative maintenance task, we did a two-week shutdown, and we brought all of the equipment up and just did this huge dump of maintenance on everything."

The goal was to reduce reactive issues: "We took those two weeks and we did all of the oil changes, and we just bit the bullet and said, alright, we're gonna just handle this first, and it really cut down on a lot of the reactive issues that you would have to deal with."

The Turning Point with Nova

After weeks of manual data entry, Selina decided to test Nova's capabilities:

"I finally just bit the bullet and asked Nova one day for a little help comparing two of the lines that I had that were similar to each other. It came back with this awesome report about where there were holes in what I had entered."

That's when things changed: "Let me push the envelope a little more. I took all of our past records and the books with the items in it, and I just did this huge dump of data. I said, hey, what can you do with this, Nova?"

"It came back with a very thorough list. It was wonderful, and I haven't typed anything, really. I mean, I'll hit yes or no sometimes, but other than that, I just dump a bunch of stuff into Nova and ask Nova for help."

How Selina Uses Nova Daily

Selina describes her interaction with Nova as conversational: "I talk to Nova just like I'm talking to you. Can you make me items? Can you add this to inventory?"

For reporting: "If I need to analyze any data, I can just say, hey Nova, all of the preventative maintenance that we did over the shutdown—can you tell me what the budget was, how much of that we spent, and how much went to contractors? Nova can put it in a format where I can take it over to a Word document and print it out for a meeting."

"Literally, it's hitting the microphone button."

Key Capabilities That Made the Difference

Working with Unstructured Data

Selina emphasized how Nova handles messy data: "We started with not the best data, but just from putting everything in and the new data that it's entering—how much it's grown just from adding. Until you start building it, your data's gonna remain like that. It's really surprising just how much it has improved."

Real-Time Quality Checking

Nova helped Selina learn what data was important: "It gave me a good idea of what is valuable to keep up with. I'll say, oh, do you see any issues with what I just entered? And it'll say, oh, well, I don't see the cost of this. I'm like, oh, you're right, so I'll go and find the cost."

"AI might be training me a little. It has babysat me through the process."

Inventory Management

On inventory tracking: "The technicians have a tablet now. They say, oh, I just changed this, I used this part, and it keeps up with the inventory for us. We have highs and lows entered into it, so it lets us know what we've ordered and how much that costs."

"We don't have a parts clerk right now, but I put my minimum and my maximums in, and it'll have a little number over there notifying me, oh, we just pulled this off the shelf. Then I can ask Nova to put the data into a requisition form so I can print the requisition."

Reporting Capabilities

Before Nova: "Before Nova, I couldn't show any of that because I just didn't understand it."

After Nova: "At the touch of a button, you can ask for any financial specs, time—it keeps up with my maintenance crew and how long it takes them on a task. It literally marks every aspect of it, so no matter what corporate is asking, you can just say, hey Nova, we need a breakdown of this, and I port it over and click it into a Word document."

When asked if she could accomplish this without Nova: "I wouldn't be able to accomplish it at all."

The Results

Improved Work-Life Balance

"My work-life balance is a lot better now. I just dump a bunch of stuff into Nova, ask Nova for help, and it has changed everything."

Better Data Quality

"It's really surprising just how much it has improved. The technicians have a tablet now, and they say, oh, I just changed this, I used this part, and it keeps up with the inventory for us."

"You can find anything out about a task—it's all handled right there on one platform. It's amazing."

Shift to Preventative Maintenance

After the two-week shutdown: "We don't have as much of that reactive work cutting into it because we took those two weeks and did all of the oil changes. We're actually able to focus on the preventative maintenance more."

Enhanced Reporting and ROI Visibility

"Before Nova, I couldn't show any of that because I just didn't understand it. But now, at the touch of a button, you can ask for any financial specs, time—it keeps up with my maintenance crew and how long it takes them on a task."

On how long it would take without Nova: "Hours and hours."

Building Trust in AI

Selina was transparent about her process of learning to trust Nova:

Using the Feedback System

"There's a little reporting button underneath where you ask Nova to do things. You can give it a 1 to 5 star rating, and if you give it a 1, then you can say what the issue was that you ran into. Then they'll instantly—I think it wasn't even a day, probably the same day—they'll say, oh, this is the issue you're running into."

Maintaining Control

"There's a backup. You can actually go through everything that you've asked Nova to do, and if you want to make changes, you can ask Nova to give you a data point from before, or you can even ask Nova to notify you before it makes changes. You don't have to just throw everything in there and hope for the best."

"It gives you options on how much control you have, and I have, over time, slowly let the reins go because I gained that trust, and I know that there's a backup."

Verifying Results

When asked about trust and hallucinations, Selina explained: "You're constantly questioning it, asking it questions, and asking it to prove the data that it's showing you. You have full conversations, you can test it, you can pressure test the results of each one of the insights that it comes back with. Have it bring up actual data points that prove this or disprove that."

Advice for Other Maintenance Managers

When asked what she'd tell someone who hasn't started with AI yet, Selina said:

"I would tell them to pick one process. For us, it was preventative maintenance. We just decided to start uploading all of the preventative maintenance, and I would tell them to pick one point that they wanted and try it out. Just see what happens, and they'll get hooked, I know, beyond a doubt."

"No matter what you decide to use it for first, whether it be your stock, your inventory, even just reorder stuff—just try one part, and you'll be hooked. It will change everything."

"And if you already have it and you're not using it yet, it won't take long."

On waiting for perfect data: "Until you start building it, your data's gonna remain like that, so just see what happens and they'll get hooked."

Conclusion

Selina's experience shows that AI adoption doesn't require perfect data or extensive technical expertise. By starting with one process (preventative maintenance), using Nova conversationally, and gradually building trust through the feedback system, she transformed her maintenance operations and improved her work-life balance.

Her final advice: "Just try one part, and you'll be hooked. It will change everything."