Tech Isn’t Enough: How to Improve Predictive Maintenance Adoption Across Maintenance Teams

Predictive maintenance has the potential to transform reliability, but technology alone doesn’t create lasting results. The real test comes after alerts surface: Who owns them? Who responds? How does the team follow through?

You build the culture, process, and ownership needed to act.

AssetWatch hosted an insight-packed session on Tech Isn’t Enough: Building a Culture of Reliability Success, featuring AssetWatch experts and a customer leader who has helped put these principles into practice:

• Josh Pinnau (Customer Success Manager Team Lead, AssetWatch)

• Benjamin Keel (Condition Monitoring Application Engineer, AssetWatch)

• Cindy Barnett (Preventive Maintenance Reliability Supervisor, Tyler Union)

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Predictive Maintenance Adoption Isn’t Just a Technology Problem

Maintenance teams aren’t short on tools, data, or alerts. But many predictive maintenance programs still fall short because the gap isn’t always technical; it’s operational.

Common challenges include:

• Poor data quality — if sensors are placed incorrectly or baselines can’t be trusted, teams won’t trust the program

• False alarms — noisy or inaccurate alerts can quickly create alert fatigue

• Complex recommendations — if insights aren’t clear, technicians may not know what action to take

• Unclear ownership — when no one owns the alert, follow-through stalls

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Three Moves That Help Build Predictive Maintenance Reliability Culture

Successful predictive maintenance programs require clear roles, repeatable workflows, and internal champions who sustain momentum.

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1. Define Ownership Early

At Tyler Union, Cindy became the internal facilitator for alerts. Every alert came through her first, then moved to the right person for inspection, action, and follow-up.

That single point of ownership helped make sure nothing sat unresolved.

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2. Turn Alerts Into Action

More than just flag problems, AssetWatch alerts helped the Tyler Union team understand what to inspect, what to fix, and how to close the loop.

That process helped the team move from “What does this mean?” to “We know what to do next.”

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3. Make Wins Visible

Trust in a predictive maintenance program happens when teams see compounding results. Tyler Union started small with critical baghouse fans, then expanded to more than 400 monitoring points across 102 assets.  

In one example, a high-temperature alert helped the team identify a blown gearbox seal on a critical demuller. By acting early, they added oil, switched to a backup unit, and avoided costly unplanned downtime.

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The Bigger Opportunity

The most successful predictive maintenance programs are built around partnership. Technology matters, but the people and process around it determine whether insights lead to action.

The bottom line? Teams that build ownership, response paths, and internal champions around predictive maintenance are more likely to achieve lasting reliability, not just another tool in the stack.