The Bottom Line
Run-to-Failure
~$1,000,000 / event
2–7 days downtime. Emergency callout. Parts at premium pricing. Collateral damage. Safety risk.
Predictive Maintenance
~$144,000 / event
4–8 hours scheduled downtime. Standard pricing. No collateral damage. Minimal safety risk.
86% cost reduction per event
Full Cost Breakdown
| Cost Component | Run-to-Failure | Predictive | Savings |
|---|---|---|---|
| Emergency repair parts | $250K–$500K | $50K–$80K | ~80% |
| Deferred production | $500K–$700K | $40K–$60K | ~91% |
| Crew mobilization | $50K–$100K | $10K–$20K | ~80% |
| Secondary damage | $50K–$200K | ~$0 | 100% |
| Downtime duration | 2–7 days | 4–8 hours | ~92% |
| Safety incident risk | High | Low | — |
| Total per event | ~$1,000,000 | ~$144,000 | 86% |
Annual ROI Calculation
For a facility with 12 unplanned failures per year at $1M each:
Break-even at 5% detection: The system only needs to prevent 1 in 20 failures to cover its deployment cost. The validated detection rate far exceeds this threshold. Everything above 5% is pure savings.
Why Run-to-Failure Persists
If predictive maintenance is so clearly better, why do most facilities still run-to-failure? The answer is in how costs are accounted:
- Emergency costs are invisible until they happen. They don't appear in the maintenance budget as a line item. They're scattered across repair invoices, production reports, and overtime.
- Predictive maintenance requires upfront investment. Sensors, software, and integration cost money before any savings are realized. Run-to-failure costs nothing until the failure — then costs everything.
- Cultural inertia. "We've always done it this way" is the most common maintenance strategy in the world.
- Skill gap. Maintenance teams are trained in mechanical repair, not data science. The transition requires new capabilities.
Calculate Your Facility's Savings
Enter your failure frequency and cost per event to see your estimated annual savings with predictive maintenance.