Real-world stories of strategy to action: Driving change toward operational excellence

Table Of Contents

  • 1) Start small, go fast later: Phase the rollout and focus on data quality
  • 2) Win adoption on two fronts: Requesters and technicians
  • 3) Make everything a work order: Data earns budget and credibility
  • 4) Extend beyond maintenance: One source of truth builds trust across the org
  • 5) Prepare your data for AI and integrations
  • Closing thought

At the 2025 Maintenance Heroes Summit, Limble customers sat down with Kristen Drake (VP, Customer Success) to share how they moved from good intentions to measurable change. Panelists included Josh Galer (Engineering & Maintenance Manager, Island Abbey Nutritionals) and Jonathan Di Benedetto (Solutions Developer, Grove City College). Below are the five takeaways from the session that maintenance leaders can put to work now.

1) Start small, go fast later: Phase the rollout and focus on data quality

Don’t try to “do it all” on day one. Both teams phased their implementation, standing up core workflows first, then layering features (time tracking, parts, inventory, templates) once habits formed.

 “Walk before you run. Focus on the heart of the work order—clear titles, what happened, how we fixed it—then add the rest.” – Josh Galer

Tactical tips:

  • Prioritize your highest-impact assets and most frequent failure modes first.
  • Standardize work order titles and closeout notes so future you (and your AI) can learn from them.
  • Map locations progressively (e.g., building-by-building); momentum beats perfection.

2) Win adoption on two fronts: Requesters and technicians

Make it dead-simple for requesters and respectful for techs.

Grove City College added QR codes to every room so students can submit issues with zero training: “Scan, snap a photo, submit…on the requestor side, it takes no training.” Turnaround time dropped from about a month to two weeks or less. For technicians, Jonathan set expectations early, built relationships, and paced training. 

At Island Abbey Nutritionals, Josh incentivized the right behaviors (accurate time logs, complete notes) with short-term rewards until the habit stuck: “We set a 90–95% log-time goal and used gift cards for a few months. Once they saw the value in the data, it became second nature.”

 

3) Make everything a work order: Data earns budget and credibility

An asset and maintenance management platform pays for itself when you use it as the system of record. That means everything becomes a work order, so leaders can see the real cost, risk, and ROI.

After a 7-day packaging line outage caused by a missing critical part, Island Abbey secured maintenance software budget the very next day. Later, 12 months of parts and labor data justified retiring a “money-pit” machine: “In black and white, the parts alone could have bought a replacement.”

 

Grove City College automated work intake and routing, eliminating a manual role at retirement, clear ROI the business understood immediately. As Johnathon put it: “Boom. There it is. Pays for itself.”

 

4) Extend beyond maintenance: One source of truth builds trust across the org

When other teams can self-serve insights, the maintenance plaltform becomes the backbone of operations.

At Island Abbey, the Quality team now runs audits in Limble and manages instrument calibration; Engineering pulls asset history and costs to inform capital planning and process improvements; and Finance allocates labor accurately to capital projects. As Josh noted:  “Auditors now see Limble in three different rooms, not just maintenance, and they really believe in the system.”

On campus at Grove City, transparent updates, like telling other teams when a spare part will arrive, completely shifted the perception of the maintenance team as one that’s responsive, communicative, and reliable. Additionally, “other departments feel they can communicate easily… everything is tracked and organized.”

 

5) Prepare your data for AI and integrations

AI won’t turn wrenches, but it will surface patterns, speed onboarding, and cut time to resolution, if your data is clean.

What’s next:

  • Connect building automation or sensors so alerts trigger work automatically
  • Standardize closeout notes (that show the symptom, cause, and fix) so future AI and new hires learn from your history.

Closing thought

Operational excellence isn’t a single project: it’s a culture of clear data, simple workflows, and steady iteration. Start with the basics, turn every action into a work order, and invite the rest of the organization to the same source of truth. That’s how you turn strategy into action, and action into measurable uptime.

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