MentisCell – MTTR (Mean Time to Repair)

Summary

MTTR (Mean Time to Repair) is a key reliability and performance metric that measures the average time required to diagnose, fix, and restore a failed system or component to full functionality. It reflects the efficiency of maintenance and incident response processes.

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MentisCell – MTTR

Content

Mean Time to Repair (MTTR) is widely used in IT operations, engineering, and service management to evaluate how quickly systems can recover from failures.
It is calculated by dividing the total downtime caused by repairs by the number of incidents over a given period.

Main functions

Performance measurement: assess the effectiveness of repair and recovery processes.
Reliability indicator: shorter MTTR values indicate higher resilience and operational efficiency.
Decision support: guide investments in automation, redundancy, and preventive maintenance.
Compliance: demonstrate adherence to service-level agreements (SLAs) and reliability standards.
Continuous improvement: identify bottlenecks in incident response and optimize workflows.

Formula

M T T R = \frac{Total Repair Time}{Number of Repairs}

Use cases

Measuring IT service desk efficiency in resolving incidents.
Evaluating hardware maintenance performance in data centers.
Tracking recovery times for cloud services and SaaS platforms.
Supporting SLA negotiations with customers and partners.
Benchmarking operational resilience across teams or vendors.

Essence

Average time to restore functionality after a failure.
Critical metric for reliability, resilience, and SLA compliance.
Supports operational efficiency and continuous improvement.
Directly impacts customer satisfaction and trust.

Interconnections

ITOM — MTTR is a key metric in IT operations monitoring and incident management.
ITSM — MTTR supports SLA tracking and service performance evaluation.
KPI — MTTR is often defined as a KPI for operational efficiency.
OKR — MTTR reduction can be set as a measurable key result.

Contributors

Created with the support of Microsoft Copilot on 2025-11-10.
Validation and editorial direction by Jorge Godoy.