The Role of Asset Criticality in Risk-Based Maintenance Planning

Maintenance teams across asset-intensive industries face a common challenge: a growing backlog of requests with limited visibility into which tasks truly matter most. When every piece of equipment feels urgent and resources are stretched thin, the inability to prioritize effectively leads to inefficiencies, rising costs, and avoidable downtime.

This scenario is not hypothetical. According to the Society for Maintenance and Reliability Professionals (SMRP), organizations that lack structured prioritization processes often report lower maintenance effectiveness and higher reactive work ratios, impacting both asset performance and operational safety. This is where asset criticality becomes an essential planning tool.

From Reaction to Prioritization

Many organizations still rely on outdated methods such as manual scheduling, static spreadsheets, or reactive decision-making to manage growing volumes of work. In these environments, maintenance priorities are often set based on past experiences, team input, or immediate pressure from operations.

Asset criticality introduces objectivity into this process. It involves evaluating each asset based on two key factors: the likelihood of failure and the consequence of failure. The U.S. Department of Energy defines criticality analysis as a structured method for determining the probability and the impact of failure on operations, safety, environment, and compliance.

When embedded into your EAM or CMMS system, criticality scores serve as decision-making filters. This enables planners to focus preventive maintenance, inspections, and resources on assets that carry the greatest operational risk.

Putting Asset Criticality into Practice

An effective criticality model categorizes assets into tiers—typically low, medium, and high—based on a scoring framework. A high-criticality asset, for example, may be one whose failure would cause safety incidents or production loss. Conversely, a low-criticality asset may have minimal operational impact if it fails.

Modern platforms such as HxGN EAM and IBM Maximo allow maintenance teams to assign and manage these scores directly in the asset register. This enables smarter automation, such as triggering work orders or condition monitoring only for high-priority assets.

Consider the case of BASF, one of the world’s largest chemical producers. The company undertook a large-scale digital migration to modernize its asset management approach, and they reassessed asset criticality across their global operations. By integrating criticality scoring into their new HxGN EAM platform, BASF aligned maintenance frequency with real risk. The result? More focused preventive maintenance, improved uptime on essential equipment, and reduced maintenance overhead.

Criticality Must Be Dynamic

One common mistake is treating asset criticality as a one-time setup. In reality, asset conditions constantly evolve. To remain relevant, criticality frameworks must be reviewed regularly, especially during system migrations or digitalization efforts.

The best form of practice is to reassess criticality at least annually, or in response to major operational changes. This ensures that maintenance plans remain aligned with the actual risk landscape and continue to support uptime objectives.

It’s Not Just About Equipment

While most criticality models focus on individual equipment, broader system-level impacts should also be considered. For instance, a non-critical pump may support a critical cooling system. If that pump fails, the downstream impact could be significant. Certain tools help visualize these interconnections, which ultimately makes it easier to identify cascading risks across FLOCs and functional areas.

Conclusion

Asset criticality is not just a technical exercise. It is a strategic enabler for prioritizing what matters most. In complex environments where maintenance teams are tasked with doing more with less, criticality scoring helps focus resources, optimize scheduling, and support better decisions across the asset lifecycle. By embedding criticality into your maintenance planning process, you create a more reliable, data-driven path to uptime and operational efficiency.