CMMS Gap Analysis & Planned Maintenance Optimisation Study

Why we were contracted

The client was facing the following challenges:

• Absence of quality asset register data
• The CMMS was not set up adequately to allow for an optimised planned maintenance schedule
• No packaging, nesting or routing of maintenance was built into the planned maintenance regime
• Inability to prioritise maintenance due to poor criticality assignment

Our approach

An initial data analysis was performed to identify any gaps, inconsistencies and recommendations for improvement in the data provided by the client.

This scope of work focused on the review and analysis of the CMMS data content, structure and associated maintenance. The study conducted by ABL benchmarked the data and maintenance against industry best practice standards, as well as ABL experience derived from projects with similar assets, with the intent to identify opportunities for optimisation.

The review covered:

• The structure and contents of the functional location hierarchy
• A sense check of the assigned criticality and classification of equipment types
• Frequency of the PM’s
• PM work order descriptions

What we did

• Data collection and review
• Workshop to agree key assumptions with the asset stakeholders
• CMMS Gap Analysis
• Planned Maintenance Benchmarking Study
• Delivery of results and prioritised implementation plan based on risk, return on investment and criticality

Initial findings

• 86% of tags had zero maintenance assigned to them
• 383 tags of these tags were assigned as “high criticality” yet had no maintenance assigned to them
• 32% of the data analysed had no estimated hours or labour allocation, making it difficult to plan and schedule maintenance
• $148,000 was being spent per year to manually schedule and prepare planned maintenance that could be automated through optimised foundational data and utilisation of the CMMS
• 5,733 annualised man hours of maintenance could be removed following optimisation

Benefits & deliverables

• $456,000 of annual savings were identified by optimising the frequency of existing maintenance activities and time spent on manually scheduling planned maintenance
• Over 10,000 hours planned maintenance man-hours could be saved through the implementation of the optimisation recommendations provided by ABL
• 7 days per month saved on admin time that was previously spent manually scheduling maintenance by unlocking efficiencies in the CMMS functionality