Chris Turlica is the CEO of MaintainX — a leading CMMS and EAM platform for maintenance and reliability teams.
Reliability doesn’t come cheap: U.S. manufacturers spend over $57 billion annually repairing and maintaining machinery. But that’s nothing compared to how much industrial organizations lose when machinery isn’t well maintained: Related losses, including downtime and product defects, cost the industry as much as $222 billion per year.
This means that well-run maintenance operations more than pay for themselves in terms of unplanned downtime reductions and other avoided losses. Sloppy maintenance, on the other hand, costs companies millions of dollars, over and above direct costs such as labor and parts.
Given the stakes, it’s surprising so many organizations still fly blind when it comes to maintenance, repair and operations (MRO). For other mission-critical functions, executives pay close attention to a long list of KPIs, but remarkably few leaders take a similarly data-driven approach to measuring and optimizing their organization’s maintenance success.
That’s a big deal, because the research linked above shows that effectively managed maintenance delivers significant benefits. Well-run maintenance operations can reduce unplanned downtime by over half while slashing product defects by 87%. Other studies show that effectively managed maintenance delivers savings of up to 30% of total operating costs, dwarfing the ROI on most other industrial functions.
What To Measure
The path to data-driven maintenance starts with identifying the right metrics to track. When maintenance is done right, it proves to be a smart investment. And like any other high-priority investment, it needs to be measured, quantified and managed effectively to deliver real ROI.
What should leaders track to optimize the return on maintenance investments? The must-track metrics fall into four categories.
Equipment Reliability
For many manufacturers, this becomes a defining question: Are machines up and running when they’re needed? The critical KPI is overall equipment effectiveness (OEE), which fuses equipment availability, speed and quality into a single unified metric. The point is that these datapoints only make sense when taken together. If you have zero downtime but your equipment is running at half-speed and your products are defective, you still have a big problem on your hands.
Another key reliability metric, mean time between failures (MTBF), tracks periods between equipment outages. That’s important because it shows how effectively teams are addressing problems before they happen: A reactive approach won’t do much for your MTBF, but a proactive strategy can head off potential outages and keep equipment online for longer.
Cost Efficiency
To maximize bottom-line returns, organizations must track how much maintenance actually costs them. The simplest metric is the maintenance cost per unit—a calculation of total maintenance costs divided by the units produced. Remember, the goal isn’t necessarily to minimize MCU; instead, it’s to ensure unit costs are proportional to the benefits (such as increased OEE) that maintenance delivers.
It’s also important to watch your planned versus unplanned work ratio—a measure of scheduled and unscheduled downtime. A focus on planned work can cut total maintenance costs by as much as 40%, with some individual repairs costing over 15 times more when managed reactively, so maximizing planned work (and, when necessary, planned downtime) is a smart way to keep maintenance costs low without sacrificing overall operational effectiveness.
Workforce Productivity
Every manufacturer wants to reduce mean time to repair (MTTR), but repairs are carried out by people, so the best way to improve MTTR is often to track underlying metrics that help technicians work more efficiently. Monitoring wrench time—and how long technicians spend on tasks that don’t drive value—is critical. One study found that 15% of assigned tasks don’t create value, and that eliminating busywork, standardizing workflows and streamlining task management could boost wrench time by as much as 100%.
Modern CMMS and EAM platforms have made tracking these workforce metrics significantly easier, automatically calculating wrench time and providing real-time visibility into technician efficiency. The key is ensuring these systems are configured to capture meaningful data rather than just generating reports.
Leaders should also keep tabs on their team’s first-time fix rate (FTFR)—a widely used metric for field technicians in consumer categories, but also a powerful measure of efficiency for industrial maintenance. If technicians consistently need to order parts, fetch specialized tools or dig up additional documentation to get machinery working again, there are likely significant internal bottlenecks that require attention.
Predictive Analytics
Predictive maintenance is transforming maintenance and turning operational data into a driver of bottom-line benefits. To maximize the benefits, organizations should track forecast accuracy and measure how effectively predictive tools do their jobs. One study, for instance, found that AI-powered fault prediction in automotive systems ranged in accuracy from 63% to 100%—a significant range if you’re shutting down production lines or replacing expensive parts based on the algorithm’s forecasts.
It may also be worth tracking data quality, with low-quality data estimated to erode up to 12% of organizational revenues. That might mean checking that sensors are properly calibrated, working to ensure that human error doesn’t pollute key datasets or conducting periodic audits to ensure that relevant insights (including qualitative data from human technicians) are properly passed through to your predictive tools.
Of course, these suggestions just scratch the surface of the maintenance data available to modern manufacturers. The goal, however, shouldn’t be to track every metric but rather to track the right metrics—the ones that boost performance and build bottom-line value for your organization.
Consider, for instance, the U.S. Air Force. They created an entire handbook to help maintenance leaders use metrics more effectively. But they also dedicated a big portion of that handbook to warning leaders against an overreliance on KPIs. “Chasing metrics for metrics’ sake is a bad thing,” the report cautions. “Metrics are not just charts and numbers to be looked at. They are tools for fixing problems.”
The point is that metrics are useful not because they quantify performance, but because they can help augment performance. When you measure the right things, you can turn maintenance into a force multiplier for your entire organization. The key is to track the maintenance metrics that align with your business goals—and then use those insights effectively to drive performance improvements and cost savings across your organization.
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