How to Identify Bad Maintenance Data (and how to FIX it!)

Learn how to spot bad maintenance data and fix it to improve efficiency, reduce costs, and streamline your operations. Get tips for cleaner, more reliable data!
The FieldEx Team
July 9, 2025
Header image

In the world of maintenance, good data is like gold. It helps you stay organized, make informed decisions, and keep everything running smoothly. But bad maintenance data? Well, it can feel like a ticking time bomb, costing you time, money and maybe even your sanity.

If your maintenance data is less than stellar, you're not alone. Whether it's wrong stock levels, missed maintenance schedules, or outdated asset records, bad data can sneak in from all sorts of places. The good news? With a little effort and the right tools, you can fix it.

In this guide, we’ll break down where bad maintenance data comes from and give you simple steps to clean it up. Ready to get started? Let’s dive in!

The Real Cost of Bad Maintenance Data

Before we get into how to fix it, let’s talk about why bad data is such a big deal. Bad maintenance data can impact your operations in several ways:

  • Unplanned Downtime: Imagine your team is working hard, but then a machine breaks down unexpectedly. Guess what? Poor data, like outdated maintenance schedules or faulty inventory logs, can cause these unplanned disruptions. These downtimes are costly; each minute of downtime can cost a company thousands of dollars in lost productivity.
  • Compliance Risks: If your maintenance logs aren't accurate, you could be violating industry regulations without even knowing it. This can lead to hefty fines or even legal trouble. In industries like manufacturing and construction, staying compliant is a must.
  • Higher Maintenance Costs: When your data’s wrong, you end up doing unnecessary work, ordering the wrong parts, or scheduling maintenance that isn’t needed. This wastes resources and leads to inflated costs.
  • Bad Decision-Making: Poor data means poor insights. If you're making decisions based on inaccurate reports, you could be setting your team up for failure. Bad data leads to inefficient maintenance strategies and delays.

Where Bad Maintenance Data Comes From

Now that we know why bad maintenance data is such a headache, let’s explore where it comes from in the first place.

Manual Data Entry Errors

It’s no surprise that manual entry is a big culprit here. Whether it's a technician miswriting a serial number or missing a decimal point, these small mistakes can add up quickly. And let’s face it, handwritten logs are often hard to read, leaving room for error.

Lack of Standardized Data Collection

If your team is using different naming conventions or inconsistent units of measurement, it’s like trying to fit square pegs into round holes. One technician might log “Pump-1,” while another calls it “Pump_01.” These discrepancies make it difficult to track your assets or parts accurately.

Outdated or Incomplete Records

Sometimes, the data you're working with is just plain old or incomplete. Maybe your system is using outdated records from a few years ago, or you’ve got gaps in your maintenance history. Either way, your maintenance decisions are only as good as the data you're feeding into the system.

Siloed Data & Poor Integration

Data that lives in multiple places (eg spreadsheets, emails, legacy systems) becomes disjointed. Without a unified platform, like a CMMS (Computerized Maintenance Management System), you end up with a scattered mess of information that’s tough to analyze. It’s a classic case of "too much data, too little insight." 

Sensor & IoT Data Failures

With the rise of smart technology and IoT (Internet of Things) devices, you’d think data accuracy would improve. Unfortunately, faulty sensors, misconfigured devices, or even a bad internet connection can lead to incorrect data readings. These errors might not be obvious right away but can cause problems in the long run.

Lack of Technician Training & Engagement

Sometimes, the issue isn’t the software but the people using it. If your technicians aren’t properly trained or don’t fully understand how to log data correctly, mistakes happen. A lack of engagement with the system can lead to incomplete or skipped entries.

Missing Preventive Maintenance Schedules

Regular maintenance is key to avoiding bigger problems down the road. When preventive maintenance (PM) schedules are ignored or missed, data can get out of sync, leading to equipment failure and other avoidable issues.

How to Fix Bad Maintenance Data

Fixing bad maintenance data isn’t as hard as it sounds, IF you break it down into manageable steps. Here’s what you can do:

Step 1: Implement Data Standardization

Start by establishing clear guidelines for naming conventions, units of measurement, and asset categories. When everyone follows the same format, you’ll avoid confusion.

A little consistency goes a long way. For example, always write "Pump-01" and avoid variations like “Pump 1” or “Pump_1.”

Step 2: Automate Data Collection & Entry

Automation is your friend here. By using tools like RFID scanners, barcodes, and IoT sensors, you can reduce manual data entry mistakes.

Real-time tracking through your CMMS helps ensure that data is accurate and up-to-date, minimizing human error.

Step 3: Improve Technician Training & User Adoption

Provide regular training for your technicians on how to use your maintenance system correctly.

Also, encourage them to actively engage with the system. If the software is easy to use and provides value, your team will be more likely to log accurate data.

Step 4: Conduct Regular Data Audits

Regular audits help catch errors before they become bigger problems. Review your data periodically and make sure everything is consistent and accurate.

You can even set up automated validation checks within your CMMS to flag any discrepancies in real time.

Step 5: Integrate All Maintenance Data Sources

Siloed data is a major issue. Make sure that your CMMS is integrated with other systems like ERP software, inventory management, and IoT devices.

This will give you a unified view of your maintenance operations, allowing for more accurate and timely decision-making.

Step 6: Optimize Preventive & Predictive Maintenance

Instead of waiting for equipment to fail, use predictive maintenance to stay ahead of problems.

Analyze trends and patterns to identify when equipment is likely to fail, and schedule maintenance accordingly. This keeps your data fresh and accurate.

In Conclusion

Bad maintenance data doesn’t just mess up your operations, it costs you money and time. But with the right strategies in place, you can fix the root causes of bad data and streamline your maintenance processes.

By standardizing your data, automating where possible, and improving your technician training, you can ensure your maintenance data is always accurate and ready for action.

If you’re looking to streamline your maintenance data, FieldEx can help. Our CMMS solution makes it easy to automate data entry, integrate with other systems, and conduct regular audits. Plus, with real-time updates and predictive analytics, you can keep your data on point without breaking a sweat. FieldEx helps eliminate errors caused by manual data entry and ensures your maintenance records are always reliable.

Want to see FieldEx in action? Book a free demo today, or reach out with any questions you may have. We’re here to help.

Frequently Asked Questions: Bad Maintenance Data

1. What exactly is “bad” maintenance data?

Bad maintenance data refers to inaccurate, outdated, inconsistent, or incomplete records in your maintenance system. This includes everything from mislabeled assets and incorrect inventory levels to missing work order details. If your data leads to poor decisions or operational delays, it’s bad.

2. Why is bad maintenance data such a big deal?

Because it costs you, big time. Bad data can lead to unplanned downtime, unnecessary maintenance, incorrect part orders, compliance violations and wasted labor. 

You can’t manage what you can’t measure, and faulty data means faulty strategies.

3. Where does bad maintenance data usually come from?

Common culprits include:

  • Manual entry mistakes
  • Inconsistent naming conventions
  • Siloed or disconnected systems
  • Faulty IoT/sensor readings
  • Lack of technician training
  • Missed preventive maintenance logs

4. How can manual data entry impact my maintenance operations?

Even tiny manual entry errors (like wrong serial numbers or skipped work order fields) can snowball into major issues, like ordering the wrong parts, duplicating records or missing scheduled maintenance entirely. It’s the fastest route to chaos.

5. What’s the first step to fixing bad maintenance data?

Start with data standardization. Create clear naming rules, use consistent units of measurement, and make sure your team sticks to them. 

Consistent data is the foundation for any maintenance strategy that actually works.

6. Can technology help reduce bad data?

Absolutely. Tools like barcodes, RFID tags, and IoT sensors can automate data collection and minimize human error. And when integrated into a smart CMMS like FieldEx, they give you real-time visibility and accuracy.

7. How do I know if my data is “clean” or not?

Run a quick audit. Ask:

  • Are asset names and categories consistent?
  • Are there missing fields in your work orders?
  • Are maintenance records outdated or duplicated?

If the answer is yes to any of these, your data could use a cleanup.

8. What role does technician training play in improving data quality?

A huge one. Even the best system can’t help if your team doesn’t know how to use it. Regular training ensures technicians understand how and why to log accurate data. And it boosts system adoption too.

9. How often should I audit my maintenance data?

Ideally, schedule audits quarterly or biannually. Regular checkups help catch small errors before they grow into expensive problems. 

Bonus: You can also set up automated alerts in your CMMS to flag inconsistent data in real time.

10. How does FieldEx help fix bad maintenance data?

FieldEx takes the mess out of maintenance. It automates data entry with mobile-friendly forms, integrates with your existing systems (ERP, inventory, sensors), and even offers built-in validation checks. 

Plus, our real-time dashboards and predictive analytics ensure your data stays clean, accurate and actionable, so you can focus on running things, not cleaning up after them.

11. Is FieldEx affordable for small teams or startups?

Yes! FieldEx offers flexible pricing plans, including a free tier for small teams to help you get started without breaking the budget. You only pay for what you need, and scale when you're ready. Check out our pricing page to learn more!

12. Is FieldEx easy to use for non-technical teams?

More than easy! FieldEx is designed for real-world users, not just tech pros.

It’s clean, intuitive and mobile-friendly, so your team can log jobs, track tasks and access asset info from the field with zero headaches.

13. Can FieldEx integrate with my existing systems?

Yup, FieldEx connects easily with tools you’re already using like CRMs, calendars and inventory systems. You won’t have to start from scratch or juggle multiple platforms.

14. How do I get started with FieldEx?

Simply schedule a free demo, and see how FieldEx helps you reduce downtime, automate maintenance and stay in control. Or reach out with any questions you may have. We’re here to help.

Related reads:

  1. The Complete Guide to Work Order Data Analytics (2025 Edition)
  2. FieldEx CMMS: Ultimate Guide
  3. What to Consider Before Buying a CMMS Software
  4. What is RFID Equipment?
  5. What are CMMS KPIs and How to Track Key Metrics
  6. ‍FRACAS 101: How to Leverage Failure for Maximum Output

About the Author

Dashboard mockup

The FieldEx Team

FieldEx is a B2B field service management software designed to streamline operations, scheduling, and tracking for industries like equipment rental, facilities management, and EV charging, helping businesses improve efficiency and service delivery.

Complex operations simplified with one software.

No paperwork. No spreadsheets. No blindspots. Just one solution that simplifies your field service operations.
Header image