Maintenance Performance Analytics & Decision Making

Maintenance teams generate large amounts of information through work orders, equipment history, failure records, downtime, labor hours, backlog, maintenance costs, and schedule performance. Yet having more data does not automatically lead to better maintenance. Organizations may track numerous indicators without understanding which ones reveal reliability problems, resource constraints, planning weaknesses, or opportunities for improvement. The real value of maintenance analytics lies in connecting performance signals with the decisions that need to be made.
 

Boost Consulting & Training offers this course to develop a practical, decision-focused approach to maintenance performance analytics. The program explores how maintenance data can be structured, interpreted, and connected across reliability, work management, cost, and resource performance.

Participants learn to select meaningful measures, investigate performance deviations, identify patterns and relationships, and communicate insights that support maintenance priorities and management action.
 

The main concept of this course is to move beyond reporting maintenance numbers and use performance data to understand what is happening, why it is happening, and what decision should follow.

• Identify maintenance data that provides meaningful performance insight.
• Distinguish operational measures from indicators that support management decisions.
• Interpret reliability measures such as failure frequency, MTBF, MTTR, and equipment availability.
• Analyze backlog, planned work, schedule performance, and maintenance execution trends.
• Connect maintenance cost and resource data with asset performance.
• Investigate performance deviations and identify underlying patterns.
• Design focused maintenance performance views for different decision needs.
• Translate analytical findings into clear maintenance priorities and improvement actions.