A Practical Framework for Better Maintenance Decisions in Facility Operations

In a previous article, we looked at why many CMMS implementation projects fall short of expectations, even when organizations invest significant time, effort, and budget. We also discussed some of the key reasons behind these challenges and how organizations typically try to address them.

But a more important question remains:

How can these challenges be avoided from the beginning—and how can implementation start in a more effective way?

In many organizations, a significant amount of time and money is spent on selecting and implementing maintenance systems. However, in practice, the expected return on investment (ROI) is often not achieved, and there is usually a clear gap between what was expected and what actually happens.

Based on real project experience, many of these challenges are not caused by the system itself, but by conditions that exist before the system is even selected or implemented.

This article focuses on a practical way to approach this problem—one that organizations can use before making decisions about system selection or defining their maintenance strategy. This approach helps create better conditions for implementation and supports better and more reliable decisions.

Without this preparation, even good systems fail to make a real difference. But when these conditions are in place, organizations move forward with greater clarity and a much higher chance of success.

The Real Problem: It Starts Before Implementation

In most organizations, maintenance challenges are not hidden.

Managers and operations teams usually know what is going on. They know there is no clear way of managing maintenance. They are familiar with the equipment that keeps causing problems. In many cases, there is little or no reliable history to refer to.

Even so, there is often an expectation that once a CMMS is put in place, these issues will be resolved.

This is where things begin to go wrong—before implementation even starts.

In many cases, organizations move forward with selecting and introducing a system without a clear direction. It is not clear where to begin, what should be done first, what needs to be prepared, or how progress should be tracked.

As a result, the system is introduced, but there is no clear link between the system and real operational improvement.

This is where the real issue begins:

Not in the system itself, but in not having a clear way to guide decisions before implementation.

This raises an important question: how can an organization know if it is ready to make the right maintenance decisions?

Introducing the Decision Readiness Framework

To close the gap between system implementation and real results, a different way of thinking is needed—one that looks at how ready an organization is to make maintenance decisions before moving forward.

The framework presented here is based on hands-on experience from real projects. Its idea is simple: to help organizations understand how well they can make decisions in maintenance.

It focuses on four key aspects. Together, they show how decisions are made, what kind of information is available, how well teams understand their work, and how actions are followed up.

1. Decision Structure

This part looks at how decisions are made.

Is there a clear way of making maintenance decisions, or do they mostly depend on individuals and personal judgment?

In many organizations, even experienced teams do not always produce consistent results, simply because there is no clear way of making decisions that everyone follows.

2. Quality of Information

The quality of decisions depends directly on the quality of information.

Here, the focus is on how data is recorded and used:

• Is asset information recorded in a structured and consistent way?
• Is the data complete and reliable enough to support decisions?
• Or is information spread across different sources, incomplete, and dependent on individuals?

When the data cannot be trusted, even the best teams find it difficult to make the right decisions.

3. Technical Knowledge

Technical knowledge plays a key role in maintenance decisions.

This part looks at whether the people involved—both those making decisions and those doing the work—have the right level of understanding.

In many cases, the issue is not the lack of data, but how the data is understood and used. That is why continuous development of technical knowledge is so important.

As knowledge improves, decisions become more accurate, actions become more focused, and equipment performance becomes more stable.

4. Execution and Feedback

Good decisions only create value when they are properly put into action and reviewed.

This part looks at how decisions are translated into work, and whether there is a way to learn from what happens afterward.

In many organizations, there is no clear way to track what actually happened, review the results, and improve future decisions. As a result, the same issues repeat, and progress remains limited.

A simple flow of decision, action, and review is essential for continuous improvement.

Diagnostic Questions

To understand what is really happening in an organization, it is not enough to check if processes are in place. What matters is how decisions are made in daily work.

For this reason, a set of focused questions is used to examine how maintenance decisions are made, how information is used, and how results are followed.

These questions are not limited to simple yes or no answers. They help show how work is actually done, not just how it is described.

In many cases, answering these questions leads to a very different understanding of the organization.

The responses can be scored, and the results are summarized in a way that is easy to understand.

This typically includes:

• A clear picture of the current situation (for example, using a radar chart)
• Identification of key gaps
• Prioritization of improvement actions
• A time-based plan for next steps

Based on this, a maintenance improvement roadmap can be prepared. This roadmap gives managers a clear view of where they stand, what needs attention first, and what steps should follow—along with timing and coordination between teams.

To give a clearer sense of how this evaluation works, a few key topics are listed below:

Equipment Data and Classification

This part looks at how assets are identified, categorized, and documented.

The focus is on whether equipment information is organized in a way that supports analysis and decision-making.

Safety and Emergency Preparedness

This part reviews safety systems, emergency readiness, and preventive actions.

The goal is to make sure that people, assets, and operations remain protected, and that risks are kept under control.

Documentation and Compliance

Here, the focus is on technical records, maintenance history, and alignment with regulations and standards.

Reliable and up-to-date documentation is essential for making sound decisions.

Maintenance Maturity and Overall Performance

This part looks at the overall approach to maintenance across the organization.

It includes goals, planning, use of data in decision-making, and how teams work together.

It shows whether maintenance is managed in a structured way or handled in a more reactive manner.

Conclusion

Organizations that take time to review where they are before implementing a system usually move forward with much more clarity.

They know where they stand, what needs to be done first, and what comes next. This makes it easier to plan budgets, assign resources, and manage timelines without facing unexpected issues along the way.

A clear roadmap also helps reduce many of the problems that often appear during implementation and later in daily use. Issues such as incorrect data entry, unreliable reports, and decisions based on incomplete or inaccurate information can be greatly reduced.

In many cases, when this step is skipped, CMMS ends up being used mainly as a data entry tool, instead of supporting better decisions and improving equipment performance.

In the end, CMMS should not be the starting point. It should be the result of an organization being ready to make better maintenance decisions.