Why Your CMMS is a Roadblock to Data-led Operations and Maintenance

Computerized Maintenance Management Software (CMMS) plays a very crucial role in asset-intensive industries. It performs a range of critical functions, including work order management, preventive maintenance, inventory management, and the assignment and tracking of all maintenance tasks.

However, at the core of any CMMS lies its data. The data collected and managed by the CMMS serves as the backbone of your operations and maintenance. But can you be absolutely certain that the data generated by your current CMMS is both accurate and genuinely helpful in making well-informed decisions?

Regardless of how modern and advanced your CMMS system may be, it is not exempt from challenges that can impact the quality and consistency of data.

What happens when CMMS data is low-quality or inaccurate?

Data quality issues occur because of inadequate system design. Let’s dive deeper and understand why your current CMMS data is inaccurate and how inadequate system design affects CMMS data.?

1. No Data Quality Checks

The lack of thorough data quality checks is one of the primary issues with the legacy as well as modern CMMS systems. These systems often rely on basic yes/no checklist questions to assess equipment conditions. While these binary questions can offer a basic understanding, they lack the depth of quantitative measurements and qualitative insights required for comprehensive asset management. This data can pose significant limitations, acting as a roadblock to fully data-led operations and maintenance.

1. Insufficient insight into asset performance

The over-reliance on simplistic checklists can be counterproductive. These questions could pinpoint obvious issues, but they fail to capture specifics and details that can impact asset performance. For instance, when a technician reviews an asset's maintenance history, they can determine how many times repairs were performed on the asset. However, the absence of context means they cannot determine the specific issues that occurred, understand why the previous technician made specific decisions, or assess the extent to which the asset was compromised. Without the capacity to keep track of more detailed data, your CMMS may lack the crucial information necessary for data-driven operations.

1. Can't Build a Reliable Knowledge Base?

In existing CMMS systems, technicians are limited in their ability to provide qualitative observations and explanations for their actions and decisions. This limitation makes it difficult for the generation of valuable insights that can drive efficient maintenance strategies and inform future decision-making.?

The decision-making process is based solely on experience rather than reliable data. In this case, the current workforce has irreplaceable knowledge and experience. This future workforce will fall short in such experience. Hence, the decision-making process cannot solely rely on the experience of the technician but rather on data. With the present generation rapidly retiring also known as the Great Retirement , organizations will struggle to retain workforce knowledge . Hence, it becomes necessary to establish a knowledge repository for the future workforce to rely on.

Poor CMMS data quality can hamper your Digital Transformation initiatives

Poor data quality might potentially have a significant and wide-ranging impact on all of your maintenance and operations. Furthermore, it's important to understand that the effects of this poor data quality extend beyond simple constraints and result in an extensive number of untapped opportunities that might be extremely advantageous to asset owners.

To remain competitive in the digital age, organizations need to embrace digital transformation. The lack of data depth and quality checks can impede digital transformation efforts. Since data is essential to decision-making, CMMS systems won’t offer the granularity and quality of data required for operations to be data-led.?

Planned maintenance regimes and the data gathered by CMMS are even more important for facilities without Building Management Systems (BMS) or IoT data. These maintenance routines are the main source of data, and without the ability to obtain rich quantitative and qualitative information, it becomes difficult to build a historical performance record and make informed decisions in the absence of real-time sensor data.

Looking ahead, it is becoming absolutely essential to upskill your workforce and make them future-ready. In the era of digital advancements, adapting to change is imperative; any delay or denial will lead to a poorly trained workforce. Hence, it is important to train your O&M teams to work in a data-first environment . Starting with data-led operations will help them get acquainted with a new status quo.

What this means for Asset Owners and Asset Managers

There are major consequences of data quality issues that are faced by different stakeholders be it facility managers, O&M teams, or asset owners.

1. Making decisions without quantitative and qualitative data leads to subpar asset management and maintenance, which increases the Total cost of ownership (TCO) , and lowers the investment value and return for asset owners.?

1. High-quality data is crucial for planned preventive maintenance strategies which can save maintenance costs by two to five times when compared to a reactive approach. These strategies prevent unexpected equipment failures and minimize downtime, which is critical for both asset owners and facility managers responsible for keeping operations running smoothly and avoiding unexpected maintenance expenses.

1. Frequent and unexpected downtime can overburden facility managers and experienced technicians. Furthermore, technicians may have to spend up to 30% to 40% of their day finding and verifying the information they need to perform their tasks if they don't trust the accuracy of their CMMS data. Managing crises as they occur becomes the norm, creating a stressful and reactive work environment.?

1. Poor CMMS data quality can highly affect service performances and outcomes leading to lower customer satisfaction. It is important for Facility Managers to maintain good service quality which will result in greater customer satisfaction and, therefore will increase customer retention and loyalty.?

Your current CMMS may have served you well in the past, but it's essential to recognize its limitations, especially in terms of data quality and relevance. In order to excel in data-led operations and maintenance, these issues need to be addressed at the point of origin. This becomes important if you not only want to protect your assets but also don't want to miss out on new opportunities for efficiency, cost savings, and growth in the digital age.

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