CMMS ROI Calculator
Quantify your downtime costs and calculate the ROI of implementing Dovient's AI-powered CMMS. See how much you can save on downtime, MTTR, and knowledge retention.
Downtime Cost Quantification
Annual Downtime Cost
$ 1.20 M
Cost per Incident
$ 80.0 K
Your Operations
Your Potential Savings
Estimated Annual Savings
$ 394.8 K
ROI Multiple
20.7x
Payback Period
1 mo
Downtime Hours/Month
MTTR (Mean Time To Repair)
Downtime Cost Reduction Waterfall
3-Year Cost vs Savings
What-If Scenarios
Explore how operational improvements would boost your ROI.
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How to Calculate the Cost of Manufacturing Downtime
Manufacturing downtime cost is calculated by multiplying downtime hours by the cost per hour of downtime. Total cost per hour typically includes: lost production revenue (the largest component), idle labor costs, emergency repair labor and parts, missed delivery penalties, and wasted materials from stoppages. For example, if your plant experiences 20 hours of unplanned downtime per month at $5,000/hour, your annual downtime cost is $1,200,000.
Siemens' True Cost of Downtime report (2024), which acquired Senseye, estimates that unplanned downtime costs Fortune Global 500 industrial companies approximately $1.4 trillion annually, or 11% of their yearly revenues. According to this same research, the average cost of unplanned downtime ranges from $39,000 to over $2 million per hour depending on the sector, with automotive and oil & gas at the highest end. Capital-intensive, continuous-process industries like steel and energy face the highest per-hour costs.
What Is a Good ROI for CMMS Software?
A well-implemented CMMS typically delivers significant positive ROI within the first year. Plant Engineering's 2023 Maintenance Survey found that organizations implementing CMMS software see 10-40% reduction in maintenance costs, 20-50% reduction in equipment downtime, and 5-20% improvement in asset lifespan. Industry benchmarks consistently show best-in-class manufacturers using CMMS achieve payback periods of 3-6 months.
AI-powered CMMS platforms like Dovient often achieve higher ROI through additional MTTR reduction via knowledge management, predictive failure detection, and automated workflows. McKinsey (2025) notes that AI-augmented maintenance platforms are delivering measurably better outcomes than traditional CMMS implementations due to faster diagnostics and proactive failure prevention. Use our calculator above to model your exact scenario.
Understanding MTTR and Its Impact on Manufacturing Costs
MTTR (Mean Time To Repair) is the average time required to diagnose and fix an equipment failure, as defined by IEC 60050-192 and the Society for Maintenance & Reliability Professionals (SMRP). It directly impacts downtime costs - every hour saved in repair time saves one hour of production capacity. According to Plant Engineering's 2023 Maintenance Survey, the average manufacturing MTTR ranges from 2 to 8 hours, with a significant portion of repair time spent on diagnosis rather than actual repair work.
Key strategies to reduce MTTR include: digital SOPs for faster troubleshooting, predictive diagnostics, spare parts availability, and capturing tribal knowledge. IDC (2024) research shows maintenance teams spend 30-40% of their time searching for information rather than performing repairs, making knowledge management a high-impact lever. Dovient's AI agents automate knowledge capture and delivery, cutting MTTR by 20-50% across plants - aligning with findings from Deloitte's 2025 Manufacturing Industry Outlook.
How Predictive Maintenance Reduces Downtime Costs
Predictive maintenance uses sensor data, AI, and historical patterns to detect equipment anomalies before they cause failures. McKinsey's widely cited research on predictive maintenance estimates it can reduce machine downtime by 30-50% and increase machine life by 20-40%. Deloitte's Predictive Maintenance and the Smart Factory report similarly found up to 40% reduction in maintenance costs.
The U.S. Department of Energy (DOE) estimates that predictive maintenance delivers 8-12% cost savings over preventive maintenance alone, while also reducing breakdowns by 70-75% and eliminating 35-45% of downtime. The ROI is highest in capital-intensive industries like energy, steel, and automotive. Learn more about how Dovient's maintenance modules enable predictive strategies.
Building a CMMS Business Case
According to Gartner's 2024 Market Guide for Enterprise Asset Management, a comprehensive CMMS business case should quantify: (1) Current downtime costs (hours × cost per hour), (2) MTTR improvement potential - industry benchmarks show 20-40% MTTR reduction is achievable with modern CMMS, (3) Labor efficiency gains - IDC (2024) research indicates maintenance teams spend 30-40% of time searching for information, (4) Reduced repeat failures from knowledge capture, (5) Inventory optimization savings - Deloitte reports 10-20% reduction in spare parts inventory with CMMS, (6) Compliance and audit cost reduction, (7) Software costs, and (8) Expected payback period.
This calculator focuses on the highest-impact items: downtime reduction and MTTR improvement, which account for 60-80% of total CMMS value according to Plant Engineering (2023). For a complete picture of how production costs break down, try our Manufacturing Cost Estimator, or measure your equipment effectiveness with the OEE Calculator.
Average Cost of Unplanned Downtime by Industry
Based on data from Siemens/Senseye's True Cost of Downtime report (2024), downtime costs vary significantly by industry. Average cost per hour of unplanned downtime: Automotive ($2.3 million) and Oil & Gas ($220,000+) at the highest end per Siemens data, Pharmaceuticals ($25,000-$50,000) per ISPE data, Food & Beverage ($8,000-$30,000), Steel & Metals ($20,000-$40,000) per the World Steel Association, and General Manufacturing ($39,000+ average) per the Siemens/Senseye benchmark.
Siemens' (2024) analysis found that the average Fortune Global 500 manufacturer experiences approximately 320 hours of unplanned downtime per year (down from historical estimates of 800 hours), costing between $4 million and $40 million annually depending on industry. Use our industry selector above to load realistic benchmarks sourced from published industry research.