Maximo KPI Guide: Work Order Aging

Most organizations that try to measure Work Order Aging end up with a number on a dashboard that nobody trusts and nobody acts on. The average says 30 days, but half the backlog is under a week old and the other half has been sitting untouched since last fiscal year. Leadership asks "what's our aging?" and the planner gives a number that hides more than it reveals. The aging report becomes wallpaper.

What You Get

This guide changes that. It gives you everything you need to implement Work Order Aging as a live operational control in IBM Maximo, not just a number on a screen. You get verified Maximo field mappings (REPORTDATE, STATUS, WORKTYPE, and every supporting field), a step-by-step KPI Manager configuration walkthrough, a Cognos Analytics report design guide for the aging distribution histogram, five annotated SQL queries ready to run against your database (with DB2, Oracle, and SQL Server platform notes), a Green/Yellow/Red threshold framework with specific action triggers for each band, seven root cause playbooks that map aging patterns to their causes and tell you exactly which Maximo query to run for diagnosis, and a quick setup checklist you can hand to your Maximo administrator and say "do this Monday morning."

Who This Is For

This guide is for maintenance managers who need to report this metric to leadership with confidence. For reliability engineers who need to know which assets have aging corrective work sitting unaddressed. For planners and schedulers who own the weekly backlog grooming meeting and need to know what to do with a work order that has been open for 90 days. For Maximo administrators who need to configure the KPI Manager, Start Center portlets, escalation rules, and conditional validation to protect the data. And for consultants implementing Maximo who are tired of searching for KPI configuration guidance that is actually specific to the product.

Not a 5-Page PDF

This is not a 5-page PDF with a formula and a bar chart. It is an 86-page operational control guide with two calculation versions (the distribution you should report and the average you should trend), status and date logic explained in detail (including why REPORTDATE is the right entry date and why STATUSDATE is not), rules for what counts and what gets excluded, an ownership model with a RACI table, data quality triggers that tell you when to stop trusting the number and fix the data first, and process controls to sustain the measurement over time. It takes you from "I need to measure this" to "I have ownership, thresholds, escalation rules, and a Monday morning review process."