Work Order
What is a Work Order?
A work order is a formal instruction to perform a specific task on an asset — a repair, a scheduled service, an inspection, an installation. It captures everything about that task: what needs to be done, which asset it involves, who's responsible, what parts are needed, when it's due, and what actually happened when the work was completed.
Think of a work order as a contract between the person requesting work and the person doing it. Without work orders, maintenance happens informally: someone tells a technician "hey, the pump is acting up," the technician fixes it (or doesn't), and there's no record of what was wrong, what was done, how long it took, or what parts were used. When that pump fails again in three months, nobody remembers the previous issue.
Work orders turn maintenance from an invisible activity into a documented, trackable, optimizable process. They're the foundation of every serious maintenance operation — and the primary source of data for metrics like MTTR, MTBF, and maintenance cost per asset.
Types of Work Orders
Corrective (Reactive) Work Orders
Created in response to a breakdown or reported problem. The asset has already failed or is malfunctioning and needs repair.
Characteristics:
- Triggered by: failure event, user report, alarm
- Priority: usually medium to emergency
- Timeline: ASAP or within defined SLA
- Cost: typically higher than planned work (emergency parts, overtime, rush shipping)
Example: A warehouse forklift won't start Monday morning. The operator creates a work order: "Forklift FLT-07 — won't start, battery indicator shows full charge, clicking sound when key is turned." Maintenance diagnoses a starter motor failure and replaces it.
Preventive Maintenance (PM) Work Orders
Scheduled in advance based on time intervals, usage milestones, or calendar dates. Generated automatically by the maintenance system as part of a preventive maintenance program.
Characteristics:
- Triggered by: schedule (every 90 days, every 500 hours, every January)
- Priority: planned, usually medium
- Timeline: within scheduled maintenance window
- Cost: predictable and budgetable
Example: Every 250 operating hours, the system generates a work order for CNC machine oil change and filter replacement. The work order includes the checklist, required parts (2L oil, 1 filter), estimated time (45 min), and assigned technician.
Predictive Work Orders
Triggered by condition monitoring data — IoT sensors, vibration analysis, thermal imaging, oil analysis — that indicates a developing problem before it causes a failure.
Characteristics:
- Triggered by: sensor alerts, trend analysis, inspection findings
- Priority: medium to high (failure hasn't happened yet, but it's coming)
- Timeline: planned but time-sensitive (days to weeks)
- Cost: lower than reactive (planned parts, no emergency premium)
Example: Vibration sensors on a motor show increasing amplitude over two weeks — a pattern that historically precedes bearing failure. A predictive work order is created: "Replace bearings on Motor M-12 — vibration trending above threshold, predicted failure within 2–3 weeks."
Emergency Work Orders
High-priority work orders for situations involving immediate safety risks, environmental hazards, or critical operational impact. These skip the normal queue.
Characteristics:
- Triggered by: safety event, critical equipment failure, environmental risk
- Priority: emergency (top of queue)
- Timeline: immediate response
- Cost: highest (overtime, emergency suppliers, production losses)
Example: A gas leak is detected near a boiler. Emergency work order: "Isolate and repair gas line in Building C boiler room — gas detector alarm activated." All other maintenance is deprioritized until this is resolved.
Inspection Work Orders
Routine assessments to evaluate asset condition without necessarily performing repairs. Findings may generate follow-up corrective or predictive work orders.
Characteristics:
- Triggered by: schedule, regulatory requirement, pre-purchase evaluation
- Priority: planned, usually low to medium
- Timeline: scheduled
- Output: condition report, follow-up work orders if issues found
Example: Quarterly inspection of all fire extinguishers: check pressure gauge, verify seal integrity, confirm signage visibility, update inspection tag. If any unit fails, a corrective work order is automatically generated.
Work Order Lifecycle
A work order moves through defined stages from creation to closure:
| Stage | What Happens | Key Actions |
|---|---|---|
| 1. Request | Someone identifies a need | Submit request with asset ID, description, urgency |
| 2. Review & Approve | Supervisor evaluates and prioritizes | Confirm validity, set priority, estimate resources |
| 3. Plan | Schedule resources and materials | Assign technician, reserve parts, set due date |
| 4. Assign | Technician receives the work order | Notification sent, work order appears in queue |
| 5. In Progress | Work is being performed | Technician executes, logs time and materials |
| 6. On Hold (if needed) | Work is paused | Waiting for parts, approval, or access |
| 7. Complete | Work is finished | Technician records what was done, parts used, time spent |
| 8. Review & Close | Supervisor verifies completion | Quality check, cost review, close work order |
Average cycle times (benchmarks):
- Preventive: 1–3 days from generation to completion
- Corrective (non-emergency): 1–5 days
- Emergency: hours
- Inspection: same day
What a Work Order Should Contain
A complete work order captures both the plan and the result:
Before Work Starts
- Asset identification — Asset ID, name, serial number, location
- Problem description — Clear, specific description of what's wrong or what needs to be done
- Priority level — Emergency, high, medium, low
- Work type — Corrective, preventive, predictive, inspection
- Assigned technician — Who will perform the work
- Due date — When the work must be completed
- Required parts and materials — What's needed (with part numbers)
- Estimated labor hours — How long the work should take
- Safety requirements — PPE, lockout/tagout, permits needed
- Reference documents — Manuals, diagrams, previous work order history
After Work Is Completed
- Actual work performed — What was done (may differ from the plan)
- Root cause (for corrective work) — Why the asset failed
- Parts actually used — With quantities and part numbers
- Actual labor hours — Total time from start to finish
- Downtime duration — How long the asset was out of service
- Condition assessment — Current state of the asset after work
- Follow-up recommendations — Any additional work needed
- Photos/evidence — Before and after documentation
Key Metrics from Work Orders
Work orders generate the data that powers maintenance metrics:
| Metric | Formula | What It Tells You |
|---|---|---|
| Work order completion rate | Completed WOs / Total WOs × 100% | How much planned work actually gets done |
| PM compliance rate | Completed PM WOs / Scheduled PM WOs × 100% | Whether you're keeping up with preventive schedules |
| Reactive vs. planned ratio | Reactive WOs / Total WOs × 100% | How much of your work is firefighting vs. planned |
| Average completion time | Total time (open → close) / Number of WOs | How quickly work gets done |
| Backlog | Open WOs × average hours per WO | How many hours of work are waiting |
| Cost per work order | Total maintenance cost / Number of WOs | Average cost of each intervention |
Benchmarks
| Metric | World-Class | Average | Needs Improvement |
|---|---|---|---|
| PM compliance | > 95% | 80–90% | < 75% |
| Reactive/planned ratio | < 20% reactive | 30–50% reactive | > 60% reactive |
| Work order completion rate | > 95% | 80–90% | < 75% |
| Maintenance backlog | < 2 weeks | 2–4 weeks | > 6 weeks |
Real-World Examples
Example 1: From Chaos to Control
A mid-sized manufacturing company (180 employees, 400+ assets) had no formal work order system. Maintenance was managed through:
- Verbal requests ("Hey Mike, the press is jamming again")
- Email chains ("Can someone look at the HVAC unit in Building B?")
- Sticky notes on the maintenance office door
- WhatsApp group messages
Problems:
- No maintenance history — when an asset failed, nobody knew if it had been serviced before
- Duplicate work — two technicians sometimes showed up for the same job while other jobs went unassigned
- No cost tracking — maintenance budget was one big number with no breakdown per asset or category
- Compliance gaps — inspectors asked for maintenance records, and the team scrambled to reconstruct them from memory
- Reactive ratio: estimated 75%+ (nobody tracked it, but most work was emergency responses)
After implementing a work order system:
- All requests go through a single channel with required fields (asset, description, urgency)
- Automatic PM work orders generated for 120 critical assets on schedule
- Every work order tracks time, parts, and cost
Results after 12 months:
- Reactive ratio: dropped from ~75% to 38%
- PM compliance: rose from ~40% (estimated) to 91%
- Maintenance costs per asset: visible for the first time — revealing that 12 assets accounted for 45% of total maintenance spending
- MTTR improved by 28% (technicians had repair history and procedures available)
- Audit time for compliance reviews: reduced from 3 days to 4 hours
Example 2: Work Order Prioritization Impact
A hospital facilities team managed 2,800 assets with an average of 120 open work orders at any time. Everything was treated as "high priority" because the system had no meaningful prioritization.
The problem: When everything is urgent, nothing is urgent. Critical repairs (patient-area HVAC, medical gas systems) waited in the same queue as non-critical requests (broken office chair, scuffed paint). Average completion time: 6.8 days for all work orders.
The fix: Implemented a 4-tier priority system:
| Priority | Response Time | Examples | % of Work Orders |
|---|---|---|---|
| Emergency | < 1 hour | Medical gas, fire safety, patient-area failures | ~5% |
| High | < 24 hours | Patient comfort (HVAC, lighting), kitchen equipment | ~15% |
| Medium | < 5 days | Non-patient-area repairs, aesthetic issues | ~50% |
| Low | < 15 days | Cosmetic, non-functional, wish-list items | ~30% |
Results:
- Emergency response time: 6.8 days → 42 minutes
- High-priority completion: 6.8 days → 18 hours
- Overall average completion: 6.8 days → 5.2 days (improved despite adding more structure)
- Patient-area equipment uptime: improved by 22%
- Staff satisfaction with facilities: 2.8/5 → 4.1/5
Common Mistakes
- Not closing work orders. The most common issue. Work gets done, but nobody updates the work order. Result: inflated backlog numbers, inaccurate cost tracking, and a system nobody trusts.
- Vague descriptions. "Machine broken" is useless. "Conveyor C-3 — belt slipping under load, squealing noise from drive roller, noticed during second shift" gives the technician a running start.
- No completion notes. Knowing what was done is just as important as knowing what was requested. Future technicians will refer to this history. "Fixed it" is not a completion note.
- Skipping the parts record. If you don't track which parts were used, you can't calculate true maintenance costs, and your spare parts inventory will always be wrong.
- Using work orders only for reactive work. If your PM tasks and inspections aren't tracked through work orders, you're only documenting half your maintenance activity — and the less important half.
- Over-engineering the process. A work order that requires 15 fields to fill in before submission will be avoided. Start with the essentials (asset, description, priority, assignee) and add detail over time.
Best Practices
- Make it easy to create work orders. If submitting a work order takes 10 minutes of form-filling, people will use the phone, email, or sticky notes instead. Mobile scanning, voice notes, and minimal required fields lower the barrier.
- Auto-generate PM work orders. Preventive maintenance should never depend on someone remembering to create a work order. Let the system generate them automatically based on schedules and usage triggers.
- Require completion data. The value of a work order comes from the completion notes: what was done, how long it took, what parts were used, what condition was found. Make these fields required before a work order can be closed.
- Review backlog weekly. An unmanaged backlog grows silently. Weekly reviews ensure old work orders are either completed, rescheduled, or canceled — keeping the system clean and trusted.
- Link work orders to assets. Every work order should be tied to a specific asset. This builds the maintenance history that drives MTBF, MTTR, and replacement decisions.
- Track reactive vs. planned ratio. This single metric tells you more about your maintenance maturity than almost anything else. If more than 40% of your work orders are reactive, you need more preventive and predictive maintenance.
- Use photos. Before and after photos attached to work orders provide evidence for warranty claims, compliance audits, and training new technicians. A photo of the failed component is worth a thousand words in the description field.
Related Terms
- Mean Time To Repair (MTTR) — Calculated from work order timestamps; measures repair speed
- Mean Time Between Failures (MTBF) — Work order failure records feed MTBF calculations
- Preventive Maintenance — Generates scheduled work orders automatically
- Predictive Maintenance — Sensor data triggers condition-based work orders
- Compliance Tracking — Work orders provide documented evidence of regulatory maintenance compliance
- Stock Replenishment — Parts used in work orders drive inventory consumption and reorder triggers
- Check-in/Check-out — Work orders may require tools or equipment to be checked out for the job
Conclusion
Work orders are the operational backbone of maintenance management. Every repair, every scheduled service, every inspection — if it's not documented in a work order, it might as well not have happened. The data from work orders feeds every important maintenance metric, supports every compliance audit, and informs every repair-vs-replace decision. Organizations that take work orders seriously don't just maintain equipment better — they build an institutional memory that makes every future maintenance decision smarter.
Work Orders with UNIO24
UNIO24 lets you create, assign, and track work orders for any asset — from a mobile device or desktop. Set priorities, attach photos, assign team members, add checklists, and monitor progress from request to completion. Every closed work order adds to that asset's maintenance history, building the data foundation for smarter decisions about maintenance strategy, parts stocking, and asset replacement. Auto-generated PM work orders ensure scheduled maintenance never gets forgotten, and real-time dashboards show your team's workload, backlog, and completion rates at a glance.
