Blog

5 Data mistakes that lead to downtime

4 minutes

Spoiler alert: Many M&O executives get asset health analytics wrong

How well do you know the quality of your data?

For many M&O executives, piecing together data from paper-based maintenance systems or software not specifically designed for M&O isn’t cutting it. Without intelligent, data-driven decisions guiding maintenance operations, there might be some problems.

It can add up quickly if you're relying on reactive maintenance to manage assets.

Here’s a quick primer on five mistakes executives make with analytics that can impact asset health and maintenance operations.

1. Data (mis)interpretation

Managing and improving M&O requires reporting from quality data. Insufficient data is more common than you think.

According to a recent ServiceMax report, 75% of executives admit to having asset ignorance (i.e., experiencing equipment failures due to insufficient reporting.). That same report also found that 32% of executives could not service or support equipment and assets, while 37% claimed losses in production time of a critical asset — all the result of insufficient data.

2. Not seeing the big picture

Smarter doesn’t have to mean harder. While that ServiceMax report found that 88% of executives believe they can improve equipment and asset health, many don’t know where to start.

Marc Evans, Brightly’s Vice President of Government Solutions, uses smart cities as an example of how executives often use a “buy first, plan later” approach to technology without investing in how to use it.

“There’s a history of unintelligent spending by smart city planners due to an impulse to buy the most technology their budgets will allow,” Evans argues. “But as we’ve seen with many of these smart cities, that mindset has led to siloed approaches, a lack of focus on overall goals of the project and technology that quickly becomes irrelevant.”

Whether it’s a smart city or a manufacturing facility, if you can capture data, you can make more informed investment decisions.

3. Thinking error-free means correct

Skipping preventive maintenance can shorten asset life. While reactive-focused maintenance approaches may work for some, many M&O professionals (and their larger organizations) will face serious financial consequences with equipment and asset health.

Preventive maintenance is not just an investment into the long-term availability of assets, but it ensures that M&O is not just an expense but a profit center.

For example, an IBM survey found that preventive maintenance from EAM software can improve asset health by 20%. That ServiceMax report we mentioned earlier showed the value of extended asset life, noting that “stock-outs” cost $260,000 per hour in unplanned downtime from production delays.

When implemented correctly, a preventive maintenance approach with EAM systems results in savings over time as assets last longer, use less energy, and cause fewer interruptions to your processes.

4. [04] Unknown error

A lack of data quality or understanding of root causes can lead to equipment failure. Recent data from Senseye reveals that large facilities across all industries spend roughly $532,000 per month on unplanned downtime due to machine and equipment failures. That’s no small chunk of change.

The total economic impact of not capturing data from EAM systems can be hundreds of thousands of dollars for organizations just to maintain productivity.

5. Paralysis by analysis

Large amounts of unstructured data have no impact on asset health. Incomplete and inaccurate data can lead to increased overtime and time spent due to missing parts, reduced productivity, incorrect usage of M&O staff and equipment parts replacement.

Analytics are only as valuable as their relevance.

Your data should cover specific criteria to optimize maintenance staff, extend equipment lifespan, and ultimately save money while boosting productivity. A Deloitte report found that structured and narrowed criteria create actionable data from EAM systems that have proven to increase equipment uptime by 20%.

How to avoid those data mistakes

Data accuracy and integrity is critical. By harnessing analytics in one EAM system, all of this information is accurate and available at your fingertips, and data-backed decision-making becomes standard practice.

A robust EAM system will help your organization drive productivity, efficiency and clear visibility into maintenance work:

  • Maintaining assets throughout the life cycle
  • Keeping accurate inventory
  • Using data to recommend proactive maintenance
  • Increasing worker safety

Proven to achieve an 89% reduction in corrective work order hours and a 63% decrease in maintenance spend, Asset Essentials™ and EAM tools may be your solution.

Need a visual? Check out our infographic on the 5 Mistakes Execs Make with Data.

Schedule a demo to see why 12,000 organizations have trusted Brightly for over 20 years.