When every minute of downtime costs thousands and one unplanned repair can throw your operations into disarray, the maintenance strategy you choose can have a dramatic impact on your organization. Your approach to managing your assets can greatly affect (among other things) the quality of your work environment, your ability to manage risk, your customer relationships, and your bottom line. In light of all that, it's worth examining how well preventive maintenance is serving you, and whether there might be a better way.
Relying on preventive maintenance in an effort to limit unplanned downtime has become the norm across manufacturing industries. As of 2020, 88 percent of facilities followed a preventive maintenance strategy to keep their production lines running, with the average facility spending 33 hours weekly on routine maintenance.
Considering the steep costs and risks that accompany the traditional run-to-fail model, a preventive maintenance strategy is a step in the right direction. But what if you could easily increase the value of your maintenance program, spending far fewer hours managing your assets while making serious headway on your KPIs?
In this blog post, we’ll break down the real costs behind preventive maintenance and stack them against the growing benefits of predictive maintenance. Whether you’re optimizing for uptime, cost control, or equipment longevity, understanding this comparison can help you make informed decisions—and save serious money.
What Are the Downsides of Preventive Maintenance?
Preventive maintenance is a planned approach to upkeep. Teams perform maintenance tasks on a fixed schedule, regardless of asset condition. The idea is to reduce the risk of unexpected breakdowns by intervening early and often.
This strategy can sound cost-effective on paper. But in practice, the hidden costs of preventive maintenance extend to labor, materials, downtime from planned shutdowns, and replacing parts that haven’t failed. These maintenance expenditures add up—especially when they're not aligned with actual wear or equipment condition.
When maintenance tasks are based solely on time, operational efficiency takes a hit. But that's not the only drawback. Preventive maintenance routines can fail to catch issues that develop between inspections, leaving production lines at risk for costly production and revenue losses.
The Hidden Inefficiencies of Preventive Maintenance Work
"Research shows that up to 60% of our preventive maintenance tasks are adding little to no value. In other words, we're doing too much maintenance that's not necessary." — Erik Hupjé, Reliability Insights
One of the biggest drawbacks of a preventive maintenance strategy is over-servicing. Assets get pulled offline before they need repairs, and parts are replaced while still in good working condition. Rigid maintenance schedules, without regard for asset condition, can actually increase overall maintenance costs in various ways:
- Unnecessary labor hours
- Premature part replacement
- Downtime from planned stops
- Missed degradation signs between intervals
That last bullet is a mission-critical concern. According to a 2022 Annual Plant Engineering Survey, the #1 challenge to improving maintenance is aging equipment. This heightens the risk of fast-emerging issues and imminent failure—with no outward signs until it's too late—in the gaps between inspections and routine service.
Between wasted budget and the looming risk of sudden failures, preventive maintenance is becoming increasingly unsustainable as a maintenance strategy. Fortunately, thanks to next-gen remote sensor technology, advanced AI, and dedicated support from human analysts, there's better way to manage assets that costs less and delivers far more value.
What Is Predictive Maintenance, and How Does It Work?
Predictive maintenance takes a smarter, data-driven approach based on real-time views of asset health. Instead of following a calendar, this strategy enables targeted, timely responses to anomalies captured by sensors and interpreted with predictive analytics. This makes it possible for maintenance teams to identify and resolve potential issues before they escalate while optimizing resources.
Common condition monitoring techniques include:
- Vibration monitoring—a blend of continuous and route-based as needed based on asset criticality
- Oil analysis—for detecting signs of degradation and uncovering possible lubrication issues
- Temperature scanning—can reveal early-stage issues before they're picked up elsewhere
- AI-enhanced fault detection—uses historical data, expert-trained models, and machine learning algorithms to identify faults with increasing accuracy
For facilities that rely on a predictive maintenance approach, maintenance activity is triggered when equipment starts to show signs of wear—not just because it’s been six months since the last check. A proactive, condition-based maintenance approach enables teams to act when (and only when) it’s truly necessary, reducing both downtime and repair costs.
Comparing Maintenance Costs: Preventive vs. Predictive
In terms of maintenance cost implications, the gap between these two strategies is bigger than you think. Predictive maintenance offers a greater degree of visibility, precision, and control, enabling facility teams to target and eliminate equipment issues while avoiding overtime, overservicing assets, and overspending on inventory.
How can you calculate the ROI of your predictive maintenance program? Check out our recent white paper Succeeding with Predictive Maintenance: How to Justify Technology Investments and Maximize ROI. Download your copy to discover how to secure buy-in at all levels, measure progress, and drive success long term.
The Role of CMMS in Optimizing Maintenance Strategies
A Computerized Maintenance Management System (CMMS) is essential to executing any maintenance strategy efficiently. An easy, seamless integration with predictive maintenance software affords maximum efficiency, shared visibility, and ease of collaboration. This integrated system frees and empowers facility teams by:
- Prioritizing AI-driven asset alerts
- Scheduling and tracking maintenance activities
- Automating work orders
- Logging asset history, including communications with dedicated condition monitoring experts
- Integrating maintenance data from sensors
- Improving maintenance management decisions
When it comes to driving adoption of predictive maintenance technology as well as real progress on KPIs, a CMMS integration is crucial. Teams can streamline maintenance workflows, act faster, track work orders to closure, and keep comprehensive maintenance records with less manual effort.
Predictive Maintenance in Action: Real-World ROI
Here are just a few real-world examples of how predictive maintenance delivers measurable savings:
- A manufacturer using vibration analysis improved Mean Time Between Failures (MTBF) from 500 to 2,500 hours, saving $1.6 million annually by avoiding unplanned bearing failures.
- Oil analysis on 50 hydraulic presses reduced MTTR by 60%, cutting downtime from 500 to 80 hours annually and improving maintenance effectiveness.
- Temperature monitoring improved OEE from 88.9% to 97.3% by reducing performance losses and improving quality—directly contributing to enhanced operational efficiency and higher output.
These cases show how predictive analytics drive serious cost savings while reducing the risk of unexpected breakdowns.
A cement manufacturer had great success with predictive maintenance during an initial trial period, realizing over $1 million in savings in the first six months. With no CapEx required, the facility achieved 57X ROI. Read the case study here.
How to Make the Shift Toward Predictive Maintenance
Transitioning to a predictive maintenance program doesn’t happen overnight. It's a process that, when executed well, gets facility teams on board quickly and delivers value fast.
Identify High-Impact Assets
Prioritize assets with the highest repair costs or those that contribute to major equipment downtime. A criticality assessment will help determine which assets demand real-time condition monitoring and which can be maintained with route-based monitoring or even routine preventive measures.
Add Condition Monitoring Sensors
Start small, ideally with a risk-free trial with no additional costs for hardware, installation, or support. Monitor key indicators like vibration, oil quality, and temperature. Your dedicated condition monitoring support team can help you determine sensor placement, install the system, acclimate the team, and interpret the data.
Leverage Expert Guidance
With a condition monitoring engineer (CME) dedicated to your facility, you'll have CAT III+ analyst eyes on your condition monitoring data. Your CME will filter out false positives—making alert fatigue a nonissue. They'll also help prioritize maintenance needs and reach out with prescriptive recommendations when failure risks require timely interventions.
For a detailed step-by-step guide, check out our Predictive Maintenance Best Practices Checklist. You'll learn how to set the foundation for success and start driving operational gains on day one.
Key Takeaways: The Case for a Predictive Maintenance Program
- Preventive maintenance offers structure but lacks flexibility, leading to over-servicing and missed issues.
- Predictive maintenance enables smarter, real-time decisions, reducing downtime and cutting unnecessary maintenance costs.
- Predictive approaches continue to compound savings, while the ROI of preventive maintenance can flatten over time.
- CMMS integration is essential for streamlining predictive workflows.
- Predictive maintenance naturally fuels progress on KPIs, improving reliability, reducing safety risks, and supporting better planning and budgeting.
- Making the move starts small, with your most critical assets, and grows over time.
When your maintenance strategy aligns with real equipment needs—not arbitrary schedules—you don’t just save money. You gain confidence. You'll be able to count on a smooth and steady production line. Your team can enjoy their personal downtime, without having to worry about frantic callbacks. That’s the real return on investment.
When It Comes to Scoring Buy-in and Maintenance ROI, Predictive Offers Easy Wins
In the earliest days of its switch to predictive maintenance, a City of Tulsa wastewater treatment facility discovered the key to success: achieving asset saves to prove the value to reluctant teams. Our recent webinar with Noria, Navigating the Shift: City of Tulsa's Journey from Reactive to Predictive Maintenance, offers a firsthand account of a successful predictive maintenance rollout, with real ROI achieved early. Watch the on-demand replay here.
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