What are System Performance metrics? Crafting the perfect System Performance metrics can feel overwhelming, particularly when you're juggling daily responsibilities. That's why we've put together a collection of examples to spark your inspiration.
Copy these examples into your preferred app, or you can also use Tability to keep yourself accountable.
Find System Performance metrics with AI While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.
Examples of System Performance metrics and KPIs 1. Mean Time to Detect (MTTD) The average time taken to identify a security threat or performance issue.
What good looks like for this metric: Typically less than 24 hours
Ideas to improve this metric Implement continuous monitoring systems Use automated alert systems Regularly update threat intelligence Train staff for rapid response Conduct regular security audits 2. Mean Time to Recovery (MTTR) The average time needed to recover from a security breach or system performance issue.
What good looks like for this metric: Often less than 5 hours
Ideas to improve this metric Develop a comprehensive incident response plan Invest in reliable backup solutions Conduct disaster recovery drills Enhance system redundancy Use AI-driven analytics for faster issue resolution 3. System Uptime Percentage The percentage of time the system is operational and available.
What good looks like for this metric: Above 99.9%
Ideas to improve this metric Regular system maintenance Implement failover strategies Use load balancing Monitor server health continuously Upgrade hardware periodically 4. Incident Rate The number of security or performance incidents detected within a specified period.
What good looks like for this metric: Fewer than 5 per month
Ideas to improve this metric Strengthen access control policies Adopt advanced security software Enhance employee training programs Regularly test for vulnerabilities Improve system configurations 5. Vulnerability Remediation Time The time taken to fix identified vulnerabilities in the system.
What good looks like for this metric: Under 30 days
Ideas to improve this metric Prioritise vulnerability patches Automate patch management Regularly update software Establish a dedicated security team Use vulnerability scanning tools continuously
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1. Time to Detect Issues The duration it takes to identify technical issues from the moment they arise
What good looks like for this metric: Less than 1 minute
Ideas to improve this metric Implement real-time monitoring tools Set up automated alerts Regularly update system documentation Conduct routine system audits Train staff on quick issue identification 2. System Availability Coverage The extent to which systems are monitored for availability and functionality
What good looks like for this metric: Coverage for all critical systems
Ideas to improve this metric Expand monitoring tools to cover more systems Integrate with third-party monitoring solutions Define critical systems and prioritise them Ensure redundancy for critical systems Regularly review and update system coverage 3. Data Refresh Rate The frequency at which system data is updated to reflect the latest information
What good looks like for this metric: Refresh every 10 seconds or less
Ideas to improve this metric Optimise data processing algorithms Utilise caching strategies effectively Upgrade hardware for better performance Ensure efficient data querying Regularly test data refresh processes 4. Incident Resolution Time The time taken to resolve issues once they are detected
What good looks like for this metric: Within 1 hour
Ideas to improve this metric Streamline incident response processes Improve inter-department communication Conduct regular incident response training Have a clear escalation path Invest in advanced diagnostic tools 5. User Satisfaction Score A feedback metric showing user satisfaction with system performance and uptime
What good looks like for this metric: Above 85%
Ideas to improve this metric Conduct regular user feedback surveys Improve user interface and experience Regularly update users on system status Address user complaints swiftly Provide clear user support channels
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1. Annual Sales Volume The total quantity of plastic products sold within a year
What good looks like for this metric: 10,000 MT in 2025, increasing to 50,000 MT by 2035
Ideas to improve this metric Expand market reach through marketing Increase product quality to boost sales Enhance sales team training and incentives Identify and target key industries needing plastic Collaborate with international partners 2. Production Yield The percentage of produced items that meet quality standards
What good looks like for this metric: 95% in 2025, aiming for 99% by 2035
Ideas to improve this metric Implement quality checks at each production phase Invest in modern machinery and technology Train employees on quality control processes Conduct regular maintenance on equipment Incorporate lean manufacturing practices 3. Customer Retention Rate The percentage of customers who continue to buy over time
What good looks like for this metric: 80% in 2025, increasing to 95% by 2035
Ideas to improve this metric Enhance customer service and support Implement a loyalty program Regularly seek customer feedback for improvements Offer personalized deals and discounts Ensure high product quality and consistency 4. Cost per Metric Tonne (MT) The cost incurred to produce one metric tonne of plastic
What good looks like for this metric: 10% reduction by 2026, aiming for 20% reduction by 2035
Ideas to improve this metric Streamline procurement processes Negotiate better deals with suppliers Optimize production scheduling for efficiency Minimize waste during production Utilize energy-efficient machinery 5. Training Hours per Employee The average number of hours each employee spends in training annually
What good looks like for this metric: 20 hours in 2025, increasing to 60 hours by 2035
Ideas to improve this metric Develop a comprehensive training calendar Encourage online and external training sessions Introduce mentorship programs Link training to career development plans Utilize technology for training modules
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1. Incident Response Time The average time taken by the team to respond to reported incidents
What good looks like for this metric: Less than 30 minutes
Ideas to improve this metric Implement automated alert systems Conduct regular training on incident management Set clear response time goals Prioritise incidents based on severity Review and analyse past response times for improvement 2. System Uptime The percentage of time systems are operational and available
What good looks like for this metric: 99.9% or above
Ideas to improve this metric Conduct regular system maintenance Implement redundancy solutions Perform load testing to understand capacity Monitor system health in real-time Establish a disaster recovery plan 3. User Satisfaction Score Survey score given by users based on their satisfaction with team support
What good looks like for this metric: 8 out of 10 or higher
Ideas to improve this metric Regularly survey users to gather feedback Implement a user-friendly ticketing system Ensure timely updates to users Provide training in customer service skills Analyse feedback and address common issues 4. Ticket Resolution Rate The percentage of tickets resolved within the agreed service level agreement (SLA)
What good looks like for this metric: 95% or higher
Ideas to improve this metric Establish clear SLAs for ticket resolution Use ticketing software to prioritise workload Encourage team collaboration on complex issues Track pending tickets and address bottlenecks Hold regular reviews on ticket performance 5. Change Success Rate The percentage of system changes that are successfully implemented without causing incidents
What good looks like for this metric: 90% or higher
Ideas to improve this metric Establish a change management process Conduct risk assessments before changes Communicate changes to all stakeholders Provide training on implementing changes Review and learn from failed changes
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1. Incident Response Time The average time it takes for the IT department to respond to an incident after it is reported.
What good looks like for this metric: 30 minutes to 1 hour
Ideas to improve this metric Implement automated alert systems Conduct regular training sessions Set up a 24/7 support team Streamline incident escalation processes Utilise incident management tools 2. First Contact Resolution Rate The percentage of IT issues resolved during the first contact with the user.
What good looks like for this metric: 70% to 80%
Ideas to improve this metric Enhance self-service tools and resources Improve knowledge base quality Conduct specialised training for support staff Implement a feedback loop for continuous improvement Use advanced diagnostic tools 3. System Uptime The percentage of time that IT systems are operational and available for use.
What good looks like for this metric: 99% to 99.9%
Ideas to improve this metric Regularly update and patch systems Implement high availability solutions Conduct regular system monitoring Perform routine maintenance checks Use redundant systems 4. User Satisfaction Score The average satisfaction rating given by users after IT services are provided.
What good looks like for this metric: 4.0 to 4.5 out of 5
Ideas to improve this metric Offer regular customer service training Obtain user feedback and act on it Enhance communication channels Implement a user-friendly ticketing system Provide regular updates to users 5. Mean Time to Repair (MTTR) The average time taken to fully repair an IT issue after it is reported.
What good looks like for this metric: 2 to 4 hours
Ideas to improve this metric Improve diagnostic procedures Use automated repair tools Maintain an updated inventory of spare parts Enhance collaboration between IT teams Conduct thorough post-incident reviews
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1. Response Time The time taken for a system to respond to a request, typically measured in milliseconds.
What good looks like for this metric: 100-200 ms
Ideas to improve this metric Optimise database queries Use efficient algorithms Implement caching strategies Scale infrastructure Minimise network latency 2. Error Rate The percentage of requests that result in errors, such as 4xx or 5xx HTTP status codes.
What good looks like for this metric: Less than 1%
Ideas to improve this metric Improve input validation Conduct thorough testing Use error monitoring tools Implement robust exception handling Optimize API endpoints 3. Request Per Second (RPS) The number of requests the server can handle per second.
What good looks like for this metric: 1000-5000 RPS
Ideas to improve this metric Use load balancing Optimise server performance Increase concurrency Implement rate limiting Scale vertically and horizontally 4. CPU Utilisation The percentage of CPU resources used by the backend server.
What good looks like for this metric: 50-70%
Ideas to improve this metric Profile and optimise code Distribute workloads evenly Scale infrastructure Use efficient data structures Reduce computational complexity 5. Memory Usage The amount of memory consumed by the backend server.
What good looks like for this metric: Less than 85% of total memory
Ideas to improve this metric Identify and fix memory leaks Optimise data storage Use garbage collection Implement memory caching Scale infrastructure
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1. Data Processing Throughput Measures the amount of data processed successfully within a given time frame, typically in gigabytes per second (GB/s)
What good looks like for this metric: Varies by system but often >1 GB/s for high-performing systems
Ideas to improve this metric Increase hardware capabilities Optimise software algorithms Implement data compression techniques Use parallel processing Upgrade network infrastructure 2. Latency Time taken from input to desired data processing action, measured in milliseconds (ms)
What good looks like for this metric: <100 ms for high-performing systems
Ideas to improve this metric Enhance server response time Minimise data travel distance Optimise application code Utilise content delivery networks Implement load balancers 3. Error Rate Percentage of errors during data processing compared to total operations, measured as a %
What good looks like for this metric: <5% for acceptable performance
Ideas to improve this metric Implement error-handling codes Train systems with more robust datasets Regularly update software Conduct thorough system testing Improve data input validity checks 4. Disk I/O Rate Measures read and write operations per second on storage devices, expressed in IOPS (input/output operations per second)
What good looks like for this metric: >10,000 IOPS for SSDs, lower for HDDs
Ideas to improve this metric Upgrade to faster storage solutions Redistribute data loads Increase cache sizes Use faster file systems Optimise database queries 5. Resource Utilisation Percentage of CPU, memory, and network bandwidth being used, expressed as a %
What good looks like for this metric: 75-85% for efficient resource use
Ideas to improve this metric Perform regular system monitoring Distribute workloads more evenly Implement scalable cloud solutions Prioritise critical processes Utilise virtualisation
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Tracking your System Performance metrics Having a plan is one thing, sticking to it is another.
Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.
A tool like Tability can also help you by combining AI and goal-setting to keep you on track.
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Planning resources OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:
Tability's check-ins will save you hours and increase transparency
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