What are Quality Assurance metrics?
Finding the right Quality Assurance metrics can be daunting, especially when you're busy working on your day-to-day tasks. This is why we've curated a list of examples for your inspiration.
You can copy these examples into your preferred app, or alternatively, use Tability to stay accountable.
Find Quality Assurance 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 Quality Assurance metrics and KPIs
Metrics for Quality Assurance in Finance
1. Defect Rate
The percentage of products or services that have defects relative to the total produced, often calculated by dividing the number of defective units by the total number of units produced.
What good looks like for this metric: Typically less than 1%
Ideas to improve this metric- Implement stricter quality control processes
- Enhance staff training initiatives
- Conduct regular audits and inspections
- Utilise root cause analysis tools
- Increase customer feedback collection
2. First Pass Yield (FPY)
The percentage of products manufactured correctly and to specification the first time through the process without using rework.
What good looks like for this metric: 85%-95%
Ideas to improve this metric- Improve process documentation
- Increase equipment maintenance frequency
- Optimise employee onboarding and training
- Reduce process variability
- Incorporate automated quality checks
3. Customer Complaint Rate
The number of customer complaints received over a specific period divided by the number of transactions within that period.
What good looks like for this metric: Less than 5 per 1,000 transactions
Ideas to improve this metric- Improve after-sales support
- Analyse customer feedback for trends
- Maintain open communication channels
- Enhance product/service quality
- Regularly revise protocols based on feedback
4. Audit Compliance Rate
The percentage of audits that pass compliance checks relative to the total number of audits conducted.
What good looks like for this metric: Above 95%
Ideas to improve this metric- Regularly update compliance training for staff
- Automate compliance tracking
- Engage third-party compliance experts
- Conduct more frequent internal audits
- Develop corrective action plans for identified issues
5. Corrective Action Effectiveness
Measures the success of implemented corrective actions, determined by the reduction in defects and issues post implementation.
What good looks like for this metric: Reduction in issues by at least 75%
Ideas to improve this metric- Utilise a robust change management process
- Track and measure results of actions
- Ensure clear communication of changes to all stakeholders
- Perform regular follow-up checks
- Encourage continuous improvement culture
Metrics for Support Role Performance
1. Customer Satisfaction (CSAT)
Measures customer satisfaction with the service provided, usually through post-interaction surveys
What good looks like for this metric: 75% to 85% satisfaction rate
Ideas to improve this metric- Provide personalised responses
- Ensure timely follow-ups
- Offer multi-channel support options
- Use clear and concise language
- Continuously train staff on customer service
2. Quality Assurance (QA) Score
Evaluates the quality of support interactions based on predefined criteria
What good looks like for this metric: 85% to 95% QA score
Ideas to improve this metric- Regularly update QA criteria
- Conduct team workshops
- Implement a feedback loop for staff
- Use role-playing scenarios
- Review and analyse call recordings
3. Average Handle Time (AHT)
Tracks the average duration of handling a customer request from start to finish
What good looks like for this metric: 4 to 8 minutes
Ideas to improve this metric- Implement time-saving tools
- Provide comprehensive training
- Streamline internal processes
- Utilise call scripts effectively
- Regularly review AHT goals
4. Tickets Handled Per Hour
Measures the number of tickets resolved by a support agent in an hour
What good looks like for this metric: 8 to 12 tickets per hour
Ideas to improve this metric- Use ticket management systems
- Prioritise tasks effectively
- Encourage team collaboration
- Automate repetitive tasks
- Regularly assess ticket assignment
5. First Call Resolution (FCR)
Indicates the percentage of calls resolved without the need for follow-up
What good looks like for this metric: 70% to 85% FCR rate
Ideas to improve this metric- Provide extensive product training
- Empower agents to make decisions
- Enhance access to information
- Use customer feedback effectively
- Address common issues promptly
Metrics for Assessing software quality
1. defect density
Defect density measures the number of defects per unit of software size, usually per thousand lines of code (KLOC)
What good looks like for this metric: 1-5 defects per KLOC
Ideas to improve this metric- Improve code reviews
- Implement automated testing
- Enhance developer training
- Increase test coverage
- Use static code analysis
2. code coverage
Code coverage measures the percentage of code that is executed by automated tests
What good looks like for this metric: 70-80%
Ideas to improve this metric- Write more unit tests
- Implement integration testing
- Use better testing tools
- Collaborate closely with QA team
- Regularly refactor code for testability
3. mean time to resolve (MTTR)
MTTR measures the average time taken to resolve a defect once it has been identified
What good looks like for this metric: Less than 8 hours
Ideas to improve this metric- Streamline incident management process
- Automate triage tasks
- Improve defect prioritization
- Enhance developer expertise
- Implement rapid feedback loops
4. customer-reported defects
This metric counts the number of defects reported by end users or customers
What good looks like for this metric: Less than 1 defect per month
Ideas to improve this metric- Implement thorough user acceptance testing
- Conduct regular beta tests
- Enhance support and issue tracking
- Improve customer feedback channels
- Use user personas in development
5. code churn
Code churn measures the amount of code changes over a period of time, indicating stability and code quality
What good looks like for this metric: 10-20%
Ideas to improve this metric- Encourage smaller, iterative changes
- Implement continuous integration
- Use version control effectively
- Conduct regular code reviews
- Enhance change management processes
Metrics for Increase Fermentation Of Cacao
1. Fermentation Duration
This measures the time period for which cacao beans are fermented, typically calculated by the number of days the beans are kept at a controlled temperature and humidity.
What good looks like for this metric: 6 to 7 days
Ideas to improve this metric- Ensure an even distribution of heat during fermentation
- Monitor and control humidity levels diligently
- Turn the beans regularly to aerate
- Use a thermometer to achieve optimal temperature
- Adjust fermenting period based on observed results
2. Temperature Control
This measures the consistency of temperature maintained during cacao bean fermentation, which affects the flavour and quality of the final product.
What good looks like for this metric: 45°C to 50°C
Ideas to improve this metric- Install thermal insulators around the fermentation setup
- Use thermostatic controllers to maintain steady temperature
- Regularly check for hot spots inside the fermenting boxes
- Utilise temperature logs to detect anomalies
- Consider environmental impact on temperatures and adjust accordingly
3. pH Levels
Monitoring the acidity levels of fermenting beans helps in assessing proper fermentation, calculated by taking pH readings at intervals.
What good looks like for this metric: 4.5 to 5.5
Ideas to improve this metric- Use a reliable pH meter for accurate readings
- Sample beans from different sections of the fermentation mass
- Evaluate pH at regular intervals
- Adjust fermenting circumstances to reach desired pH
- Apply organic acids if necessary to modulate pH
4. Moisture Content
The proportion of water present in the fermenting beans, affecting final texture and processing requirements.
What good looks like for this metric: 53% to 60% during fermentation
Ideas to improve this metric- Weigh batch before and after fermentation to determine moisture loss
- Use moisture meters for precise measurements
- Adjust ventilation to control evaporation rate
- Add water incrementally if moisture drops too low
- Monitor climate conditions to understand moisture variation
5. Aeration Frequency
Frequency with which cacao beans are stirred or turned during fermentation to increase exposure to oxygen for consistent fermentation.
What good looks like for this metric: Every 48 hours
Ideas to improve this metric- Use mechanical turners for uniform aeration
- Implement a consistent aeration schedule
- Observe changes in aroma to gauge when turning is needed
- Document each aeration session for review
- Collaborate with fermented food experts
Metrics for Tracking Quality of Code
1. Code Coverage
Measures the percentage of your code that is covered by automated tests
What good looks like for this metric: 70%-90%
Ideas to improve this metric- Increase unit tests
- Use code coverage tools
- Refactor complex code
- Implement test-driven development
- Conduct code reviews frequently
2. Code Complexity
Assesses the complexity of the code using metrics like Cyclomatic Complexity
What good looks like for this metric: 1-10 (Lower is better)
Ideas to improve this metric- Simplify conditional statements
- Refactor to smaller functions
- Reduce nested loops
- Use design patterns appropriately
- Perform regular code reviews
3. Technical Debt
Measures the cost of additional work caused by choosing easy solutions now instead of better approaches
What good looks like for this metric: Less than 5%
Ideas to improve this metric- Refactor code regularly
- Avoid quick fixes
- Ensure high-quality code reviews
- Update and follow coding standards
- Use static code analysis tools
4. Defect Density
Calculates the number of defects per 1000 lines of code
What good looks like for this metric: Less than 1 defect/KLOC
Ideas to improve this metric- Implement thorough testing
- Increase peer code reviews
- Enhance developer training
- Use static analysis tools
- Adopt continuous integration
5. Code Churn
Measures the amount of code that is added, modified, or deleted over time
What good looks like for this metric: 10-20%
Ideas to improve this metric- Stabilise project requirements
- Improve initial code quality
- Adopt pair programming
- Reduce unnecessary refactoring
- Enhance documentation
Metrics for Process Improvement
1. Cycle Time
The total time from the beginning to the end of your process, as defined by you and your customer.
What good looks like for this metric: Varies widely by industry
Ideas to improve this metric- Identify and eliminate bottlenecks
- Automate repetitive tasks
- Streamline workflow with software
- Implement continuous feedback loop
- Enhance staff training and skills
2. First Pass Yield
The percentage of products that are manufactured correctly and to specifications the first time without any rework.
What good looks like for this metric: 80-95%
Ideas to improve this metric- Improve employee training programs
- Regularly maintain and calibrate equipment
- Implement quality checks at every stage
- Analyse defect patterns
- Develop clear manufacturing protocols
3. Cost Per Unit
The total expenditure to produce one item or serve one customer, including both fixed and variable costs.
What good looks like for this metric: Industry-specific, varies
Ideas to improve this metric- Negotiate better rates with suppliers
- Optimise production scheduling
- Reduce material waste
- Adopt energy-saving practices
- Invest in more efficient technology
4. Process Efficiency
The percentage of time spent producing value-added work versus non-value-added work.
What good looks like for this metric: 60-80%
Ideas to improve this metric- Use lean methodology
- Map and analyse the process steps
- Reduce waiting times between process steps
- Simplify complex processes
- Train employees in efficiency techniques
5. Customer Satisfaction Rate
Measures how satisfied customers are with a company's products, services, and capabilities.
What good looks like for this metric: 70-80%
Ideas to improve this metric- Solicit regular customer feedback
- Improve customer-facing processes
- Accelerate response time to queries
- Enhance product or service quality
- Personalise customer interactions
Metrics for Improving workflows and safety
1. Infection Rate Reduction
The measure of reduction in infection cases reported in the facility after renovations
What good looks like for this metric: A typical benchmark is a 20% reduction in infection rates
Ideas to improve this metric- Conduct regular infection audits
- Ensure proper sanitisation of equipment
- Implement staff training on infection control
- Enhance air filtration systems
- Utilise antimicrobial surfaces
2. Patient Safety Incident Count
Number of safety-related incidents reported per 1,000 patient days
What good looks like for this metric: Aim for fewer than 10 incidents per 1,000 patient days
Ideas to improve this metric- Standardise safety protocols
- Improve staff communication channels
- Introduce safety drills and training
- Enhance surveillance systems
- Regularly update safety guidelines
3. Workflow Efficiency Percentage
Percentage of processes completed within the expected time frame
What good looks like for this metric: Achieving at least 85% on-time process completion
Ideas to improve this metric- Optimise staffing schedules
- Implement workflow management software
- Regularly review and adjust processes
- Conduct time management training
- Utilise feedback to streamline operations
4. Patient Satisfaction Scores
Patients' average satisfaction rating post-renovation
What good looks like for this metric: A target of at least 90% satisfaction
Ideas to improve this metric- Enhance waiting area conditions
- Provide clear communication about changes
- Solicit frequent patient feedback
- Ensure staff are attentive and responsive
- Provide patient education on safety improvements
5. Staff Compliance Rate with Protocols
Percentage of staff compliance with updated infection control protocols
What good looks like for this metric: Aim for at least 95% compliance
Ideas to improve this metric- Incentivise adherence to protocols
- Conduct regular staff assessments
- Provide ongoing training sessions
- Utilise visual reminders and aids
- Implement a peer review system
Metrics for Quality and Reliability
1. Defect Density
Measures the number of defects per unit size of the software, usually per thousand lines of code
What good looks like for this metric: 1-10 defects per KLOC
Ideas to improve this metric- Implement code reviews
- Increase automated testing
- Enhance developer training
- Use static code analysis tools
- Adopt Test-Driven Development (TDD)
2. Mean Time to Failure (MTTF)
Measures the average time between failures for a system or component during operation
What good looks like for this metric: Varies widely by industry and system type, generally higher is better
Ideas to improve this metric- Conduct regular maintenance routines
- Implement rigorous testing cycles
- Enhance monitoring and alerting systems
- Utilise redundancy and failover mechanisms
- Improve codebase documentation
3. Customer-Reported Incidents
Counts the number of issues or bugs reported by customers within a given period
What good looks like for this metric: Varies depending on product and customer base, generally lower is better
Ideas to improve this metric- Engage in proactive customer support
- Release regular updates and patches
- Conduct user feedback sessions
- Improve user documentation
- Monitor and analyse incident trends
4. Code Coverage
Indicates the percentage of the source code covered by automated tests
What good looks like for this metric: 70-90% code coverage
Ideas to improve this metric- Increase unit testing
- Use automated testing tools
- Adopt continuous integration practices
- Refactor legacy code
- Integrate end-to-end testing
5. Release Frequency
Measures how often new releases are deployed to production
What good looks like for this metric: Depends on product and development cycle; frequently updated software is often more reliable
Ideas to improve this metric- Adopt continuous delivery
- Automate deployment processes
- Improve release planning
- Reduce deployment complexity
- Engage in regular sprint retrospectives
Metrics for Backend Developer Performance
1. Code Quality
Measures the standards of the code written by the developer using metrics like cyclomatic complexity, code churn, and code maintainability index
What good looks like for this metric: Maintainability index above 70
Ideas to improve this metric- Conduct regular code reviews
- Utilise static code analysis tools
- Adopt coding standards and guidelines
- Refactor code regularly to reduce complexity
- Invest in continuous learning and training
2. Deployment Frequency
Evaluates the frequency at which a developer releases code changes to production
What good looks like for this metric: Multiple releases per week
Ideas to improve this metric- Automate deployment processes
- Use continuous integration and delivery pipelines
- Schedule regular release sessions
- Encourage modular code development
- Enhance collaboration with DevOps teams
3. Lead Time for Changes
Measures the time taken from code commit to deployment in production, reflecting efficiency in development and delivery
What good looks like for this metric: Less than one day
Ideas to improve this metric- Streamline the code review process
- Optimise testing procedures
- Improve communication across teams
- Automate build and testing workflows
- Implement parallel development tracks
4. Change Failure Rate
Represents the proportion of deployments that result in a failure requiring a rollback or hotfix
What good looks like for this metric: Less than 15%
Ideas to improve this metric- Implement thorough testing before deployment
- Decrease batch size of code changes
- Conduct post-implementation reviews
- Improve error monitoring and logging
- Enhance rollback procedures
5. System Downtime
Assesses the total time that applications are non-operational due to code changes or failures attributed to backend systems
What good looks like for this metric: Less than 0.1% downtime
Ideas to improve this metric- Invest in high availability infrastructure
- Enhance real-time monitoring systems
- Regularly test system resilience
- Implement effective incident response plans
- Improve software redundancy mechanisms
Metrics for Halal Accreditation Compliance
1. Non-Conformance Rate
The frequency of non-conformances in Halal standards detected during audits or inspections
What good looks like for this metric: Less than 10 incidents annually
Ideas to improve this metric- Implement regular internal audits
- Provide comprehensive staff training
- Use checklists for routine checks
- Engage external experts for consultation
- Establish a corrective action plan
2. Audit Pass Rate
The percentage of successfully passed Halal compliance audits out of total audits conducted
What good looks like for this metric: Above 90%
Ideas to improve this metric- Conduct mock audits
- Ensure up-to-date documentation
- Set clear compliance instructions
- Regular management reviews
- Invest in audit management software
3. Supplier Halal Compliance Rate
The percentage of suppliers that are compliant with Halal standards out of the total suppliers
What good looks like for this metric: Above 95%
Ideas to improve this metric- Establish strict supplier guidelines
- Require supplier certification
- Conduct supplier audits/reviews
- Communicate regularly with suppliers
- Establish supplier improvement programs
4. Corrective Action Implementation Time
The average time taken to implement corrective actions after a non-conformance is identified
What good looks like for this metric: Within 30 days
Ideas to improve this metric- Prioritise action steps
- Assign dedicated resources
- Monitor progress weekly
- Automate reminders and follow-ups
- Create specific action deadlines
5. Training Completion Rate
The percentage of employees that have completed Halal compliance training out of total employees
What good looks like for this metric: 100%
Ideas to improve this metric- Schedule mandatory training sessions
- Offer e-learning modules
- Incentivise training completion
- Track training progress
- Regularly update training content
Metrics for Backend Developer Performance
1. Code Quality
Measures the frequency and severity of bugs detected in the codebase.
What good looks like for this metric: Less than 10 bugs per 1000 lines of code
Ideas to improve this metric- Implement regular code reviews
- Use static code analysis tools
- Provide training on best coding practices
- Encourage test-driven development
- Adopt a peer programming strategy
2. Deployment Frequency
Tracks how often code changes are successfully deployed to production.
What good looks like for this metric: Deploy at least once a day
Ideas to improve this metric- Automate the deployment pipeline
- Reduce bottlenecks in the process
- Regularly publish small, manageable changes
- Incentivise swift yet comprehensive testing
- Improve team communication and collaboration
3. Mean Time to Recovery (MTTR)
Measures the average time taken to recover from a service failure.
What good looks like for this metric: Less than 1 hour
Ideas to improve this metric- Develop a robust incident response plan
- Streamline rollback and recovery processes
- Use monitoring tools to detect issues early
- Conduct post-mortems and learn from failures
- Enhance system redundancy and fault tolerance
4. Test Coverage
Represents the percentage of code which is tested by automated tests.
What good looks like for this metric: 70% to 90%
Ideas to improve this metric- Implement continuous integration with testing
- Educate developers on writing effective tests
- Regularly update and refactor out-of-date tests
- Encourage a culture of writing tests
- Utilise behaviour-driven development techniques
5. API Response Time
Measures the time taken for an API to respond to a request.
What good looks like for this metric: Less than 200ms
Ideas to improve this metric- Optimize database queries
- Utilise caching effectively
- Reduce payload size
- Use load balancing techniques
- Profile and identify performance bottlenecks
Metrics for AI in Assignment Rubrics
1. Time Saved Creating Rubrics
The amount of time saved when using AI compared to traditional methods for creating assignment and grading rubrics
What good looks like for this metric: 20-30% time reduction
Ideas to improve this metric- Automate repetitive tasks
- Utilise AI suggestions for common criteria
- Implement AI feedback loops
- Train staff on AI tools
- Streamline rubric creation processes
2. Consistency of Grading
The uniformity in applying grading standards when using AI-generated rubrics across different assignments and graders
What good looks like for this metric: 90-95% consistency
Ideas to improve this metric- Use AI for grading calibration
- Standardise rubric templates
- Provide grader training sessions
- Incorporate peer reviews
- Regularly update rubrics
3. Accuracy of AI Suggestions
The correctness and relevance of AI-generated rubric elements compared to expert-generated criteria
What good looks like for this metric: 85-95% accuracy
Ideas to improve this metric- Customise AI settings
- Review AI outputs with experts
- Incorporate machine learning feedback
- Regularly update AI models
- Collect user feedback
4. User Satisfaction With Rubrics
The level of satisfaction among educators and students with AI-created rubrics in terms of clarity and usefulness
What good looks like for this metric: 70-80% satisfaction rate
Ideas to improve this metric- Conduct satisfaction surveys
- Gather and implement feedback
- Offer training on rubric interpretation
- Enhance user interface
- Continuously update rubric features
5. Overall Cost of Rubric Creation
Total expenses saved by using AI tools over traditional methods for creating and managing rubrics
What good looks like for this metric: 10-15% cost reduction
Ideas to improve this metric- Analyse cost-benefit regularly
- Leverage cloud-based AI solutions
- Negotiate better software licensing
- Train in-house AI experts
- Integrate AI with existing systems
Metrics for Reliability of Legal Content
1. Accuracy Rate
Percentage of content free from errors or inaccuracies
What good looks like for this metric: 98% accuracy
Ideas to improve this metric- Conduct regular content audits
- Implement a strict review process
- Provide training for content creators
- Use advanced grammar and spell-check tools
- Automate accuracy checks with AI tools
2. Timeliness of Updates
Frequency with which content is updated to reflect the latest legal standards and practices
What good looks like for this metric: Monthly updates
Ideas to improve this metric- Create a content refresh calendar
- Track changes in legal practices regularly
- Hire researchers to monitor legal developments
- Implement automated update alerts
- Schedule regular content revision sessions
3. Source Verification Rate
Proportion of content that is backed by verified and reputable sources
What good looks like for this metric: 100% verified sources
Ideas to improve this metric- Build a list of trusted sources
- Verify all references in content
- Utilise a peer review process
- Cross-check with external experts
- Maintain a source validation checklist
4. User Feedback Score
Average rating given by users regarding the helpfulness and trustworthiness of the content
What good looks like for this metric: 4.5 out of 5
Ideas to improve this metric- Collect regular feedback through surveys
- Implement a feedback loop for improvements
- Enhance user engagement with content
- Monitor social media mentions
- Hold focus groups for direct feedback
5. Content Comprehensiveness
Degree to which content covers all necessary aspects and scenarios in the legal field
What good looks like for this metric: 90% completeness
Ideas to improve this metric- Perform gap analysis on current content
- Incorporate user case studies and scenarios
- Regularly benchmark against competitors
- Enlist domain experts for content creation
- Utilise AI to identify under-represented areas
Metrics for Steriliser Load Compliance
1. Load Cycle Completion Rate
The percentage of steriliser load cycles that are completed without interruption or error
What good looks like for this metric: Typically above 95%
Ideas to improve this metric- Ensure regular equipment maintenance
- Train staff on proper loading procedures
- Implement a checklist for pre-cycle checks
- Schedule regular audits of steriliser operations
- Use automated alerts for cycle failures
2. Cycle Documentation Accuracy Rate
The percentage of steriliser cycles with complete and accurate documentation
What good looks like for this metric: 90% or higher
Ideas to improve this metric- Introduce digital documentation systems
- Conduct regular staff training on documentation standards
- Implement peer reviews of documentation records
- Streamline the documentation process
- Use templates to standardise documentation
3. Chemical Indicator Compliance Rate
The percentage of loads that correctly use chemical indicators according to protocol
What good looks like for this metric: 95% usage compliance
Ideas to improve this metric- Ensure ample supply of chemical indicators
- Provide refresher training on chemical indicator usage
- Implement a monitoring system for indicator application
- Conduct regular spot checks
- Review procedures and update protocols regularly
4. Load Turnaround Time
The average time taken from loading the steriliser to load completion
What good looks like for this metric: Less than 2 hours
Ideas to improve this metric- Optimise scheduling to minimise downtime
- Invest in faster sterilisation technologies
- Review workflow for bottlenecks
- Provide timely maintenance to prevent delays
- Balance load to enhance efficiency
5. Equipment Malfunction Incident Rate
The number of incidents due to equipment malfunction per 100 load cycles
What good looks like for this metric: Fewer than 5 incidents per 100 cycles
Ideas to improve this metric- Conduct regular preventative maintenance checks
- Replace old or obsolete equipment
- Keep a detailed maintenance log
- Train operators on troubleshooting procedures
- Schedule regular reviews with equipment manufacturers
Metrics for Evaluating Test Performance
1. Test Coverage
Measures the percentage of the codebase tested by automated tests, calculated as (number of lines or code paths tested / total lines or code paths) * 100
What good looks like for this metric: 70%-90% for well-tested code
Ideas to improve this metric- Increase automation in testing
- Refactor complex code to simplify testing
- Utilise test-driven development
- Regularly update and review test cases
- Incorporate pair programming
2. Defect Density
Calculates the number of confirmed defects divided by the size of the software entity being measured, typically measured as defects per thousand lines of code
What good looks like for this metric: Less than 1 bug per 1,000 lines
Ideas to improve this metric- Conduct thorough code reviews
- Implement static code analysis
- Improve developer training
- Use standard coding practices
- Perform regular software audits
3. Test Execution Time
The duration taken to execute all test cases, calculated by summing up the time taken for all tests
What good looks like for this metric: Shorter is better; aim for less than 30 minutes
Ideas to improve this metric- Optimise test scripts
- Use parallel testing
- Remove redundant tests
- Upgrade testing tools or infrastructure
- Automate test environment setup
4. Code Churn Rate
Measures the amount of code change within a given period, calculated as the number of lines of code added, modified, or deleted
What good looks like for this metric: 5%-10% considered manageable
Ideas to improve this metric- Emphasise on quality over quantity in changes
- Increase peer code reviews
- Ensure clear and precise project scopes
- Monitor team workload to avoid burnout
- Provide comprehensive documentation
5. User Reported Defects
Counts the number of defects reported by users post-release, provides insights into the software's real-world performance
What good looks like for this metric: Strive for zero, but less than 5% of total defects
Ideas to improve this metric- Enhance pre-release testing
- Gather detailed user feedback
- Offer user training and resources
- Implement beta testing
- Regularly update with patches and fixes
Tracking your Quality Assurance metrics
Having a plan is one thing, sticking to it is another.
Setting good strategies is only the first challenge. The hard part is to avoid distractions and make sure that you commit to the plan. A simple weekly ritual will greatly increase the chances of success.
A tool like Tability can also help you by combining AI and goal-setting to keep you on track.
Tability's check-ins will save you hours and increase transparencyMore metrics recently published
We have more examples to help you below.
The best metrics for Steriliser Load Compliance- The best metrics for Team Manager and ASM performance
- The best metrics for Compliance with road standards
- The best metrics for Reliability of Legal Content
- The best metrics for Improving matching for counselling
- The best metrics for Referral Implementation in Education
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:
- To learn: What are OKRs? The complete 2024 guide
- Blog posts: ODT Blog
- Success metrics: KPIs examples