What are Quality Assurance Team metrics?
Finding the right Quality Assurance Team 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 Team 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 Team metrics and KPIs
Metrics for Quality Assurance Team Effectiveness
1. Defect Detection Rate
The percentage of defects found by the QA team compared to the total defects found post-development
What good looks like for this metric: 80% or higher
Ideas to improve this metric- Increase test coverage
- Enhance tester training programmes
- Implement automated testing tools
- Conduct regular code reviews
- Encourage collaboration between developers and testers
2. Time to Detected Defects Fix
Average time it takes to fix defects once they are detected
What good looks like for this metric: 24 to 48 hours
Ideas to improve this metric- Prioritise defect fixing in sprint planning
- Improve communication between QA and developers
- Automate regression testing
- Use defect tracking tools
- Provide comprehensive defect reports
3. Test Coverage
Percentage of code or functionalities tested by the QA team
What good looks like for this metric: 95% or higher
Ideas to improve this metric- Automate repeated test cases
- Perform regular gap analysis
- Involve QA early in the development process
- Invest in robust testing tools
- Schedule frequent test plan reviews
4. Technical Debt Identified
Amount of potential rework or improvements identified that could prevent future defects
What good looks like for this metric: Issue-free code
Ideas to improve this metric- Regularly refactor code
- Use static code analysis tools
- Document known tech debt
- Incorporate tech debt discussion in retrospectives
- Allocate time for tech debt resolution
5. Customer-reported Defects
Number of defects reported by customers after release compared to defects found internally
What good looks like for this metric: Less than 10% of total defects
Ideas to improve this metric- Conduct thorough user acceptance testing
- Enhance early-stage testing processes
- Foster a customer feedback loop
- Strengthen pre-release testing cycles
- Improve real-time monitoring post-release
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 Packaging Operations Metrics
1. Production Output Rate
The production output rate measures the number of units produced per hour in the production area
What good looks like for this metric: Typical benchmark values range from 80-95 units per hour
Ideas to improve this metric- Increase machine efficiency
- Minimise downtime through regular maintenance
- Optimise worker shifts for maximum coverage
- Implement process automation
- Ensure raw material availability
2. First Pass Yield
First pass yield is the percentage of products that are manufactured correctly without needing rework
What good looks like for this metric: Typical benchmark values are around 90-95%
Ideas to improve this metric- Enhance quality control checks
- Train workers in quality standards
- Reduce variance in input material
- Standardise production processes
- Use automated quality inspection tools
3. Kitting Accuracy
Kitting accuracy measures the percentage of kits that are assembled correctly without errors
What good looks like for this metric: Typical benchmark values are 98-99%
Ideas to improve this metric- Provide detailed kitting instructions
- Use barcode scanning technology
- Regularly audit kitting processes
- Conduct staff training sessions
- Implement an error-proofing system
4. Order Turnaround Time
Order turnaround time is the time taken from order receipt to shipment completion
What good looks like for this metric: A typical benchmark is 24-48 hours
Ideas to improve this metric- Optimise workflow processes
- Enhance line balancing
- Streamline communication with suppliers
- Automate inventory updates
- Prioritise orders based on delivery schedules
5. Waste Reduction Percentage
This metric measures the percentage of waste reduced in the production and kitting processes
What good looks like for this metric: A typical benchmark is 5-10% waste reduction
Ideas to improve this metric- Implement waste reduction programmes
- Reuse and recycle materials
- Train staff on waste management strategies
- Conduct regular waste audits
- Adopt lean manufacturing principles
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 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 Customer Application Support
1. First Response Time
The average time taken to respond to a customer's initial request for support
What good looks like for this metric: Less than 60 minutes
Ideas to improve this metric- Implement automated response systems
- Prioritise tickets based on urgency
- Train staff on efficient support processes
- Increase staffing during peak times
- Regularly review and adjust response protocols
2. Customer Satisfaction Score (CSAT)
A metric that measures how satisfied customers are with support service provided
What good looks like for this metric: Above 80%
Ideas to improve this metric- Conduct regular feedback surveys
- Provide comprehensive training for support staff
- Implement a robust Quality Assurance process
- Ensure clear communication with customers
- Continuously optimize support processes
3. Resolution Rate
The percentage of customer issues that are resolved upon first contact
What good looks like for this metric: Above 70%
Ideas to improve this metric- Implement a comprehensive knowledge base
- Allow agents access to customer history
- Offer advanced training sessions
- Utilise AI tools for troubleshooting
- Encourage proactive problem resolution
4. Average Resolution Time
The average amount of time taken to resolve a customer's issue
What good looks like for this metric: 2-4 hours
Ideas to improve this metric- Ensure efficient ticket triaging
- Provide agents with advanced tools
- Identify and eliminate bottlenecks
- Streamline communication channels
- Regularly review unresolved cases
5. Net Promoter Score (NPS)
A measure of customer loyalty and how likely they are to recommend the service
What good looks like for this metric: Above 50
Ideas to improve this metric- Focus on enhancing customer experience
- Identify and support brand advocates
- Deliver consistent and reliable service
- Engage in active listening and feedback
- Implement loyalty programmes
Metrics for Assessing Data Quality Maturity
1. Percentage of Basic Data Quality Checks Implemented
Measures the proportion of datasets with basic data quality checks applied
What good looks like for this metric: 80% or higher
Ideas to improve this metric- Prioritise the implementation of basic checks on all datasets
- Provide training for team members on basics of data quality
- Allocate resources for implementing basic checks
- Automate basic data quality checks to ensure consistency
- Regularly review and update checklists for basic checks
2. Percentage of Advanced Data Quality Checks Implemented
Measures the proportion of datasets with advanced data quality checks applied
What good looks like for this metric: 60% or higher
Ideas to improve this metric- Identify datasets requiring advanced checks
- Develop a strategic plan for advanced data quality implementations
- Seek external expertise for complex checks
- Increase budget for advanced data quality tools
- Regularly review advanced check requirements
3. Month-Over-Month Improvement in Data Quality Maturity
Tracks the percentage change or improvement in the implementation of data quality checks month-over-month
What good looks like for this metric: 5% increase
Ideas to improve this metric- Set monthly targets to improve data quality metrics
- Analyse bottlenecks from previous months and address them
- Ensure consistent reporting and monitoring of progress
- Incorporate regular feedback loops from data teams
- Recognise and reward teams exceeding targets
4. Data Quality Issue Resolution Time
Measures the average time taken to resolve data quality issues
What good looks like for this metric: Less than 48 hours
Ideas to improve this metric- Streamline issue reporting processes
- Establish clear guidelines for issue prioritisation
- Provide tools and training for faster issue resolution
- Monitor and analyse common issue types
- Implement a rapid response team for data quality issues
5. User Feedback on Data Quality
Collects user feedback regarding the perceived quality and reliability of data
What good looks like for this metric: 80% user satisfaction
Ideas to improve this metric- Conduct regular surveys to gather user feedback
- Engage with users for detailed feedback sessions
- Communicate improvements to users regularly
- Set up feedback loop in data systems
- Address user concerns and demonstrate improvements
Metrics for Ensuring sticker quality
1. Defect Rate
The percentage of stickers that are found to have defects during inspection
What good looks like for this metric: Less than 5%
Ideas to improve this metric- Implement detailed inspection checklists
- Conduct regular staff training sessions
- Enhance quality control processes
- Increase random sampling frequencies
- Utilise automated inspection technology
2. Inspection Time per Unit
The average time taken to inspect each sticker
What good looks like for this metric: 1-2 minutes per sticker
Ideas to improve this metric- Streamline the inspection process
- Provide adequate training for inspectors
- Utilise technology to assist with inspections
- Optimise workflow layout
- Reduce distractions in the inspection area
3. Inspector Error Rate
The rate at which inspectors overlook defects
What good looks like for this metric: Less than 1%
Ideas to improve this metric- Conduct periodic retraining sessions
- Use peer review methods
- Establish a clear feedback loop
- Utilise double-check systems
- Implement incentive programs for accuracy
4. Cost of Inspection
The cost associated with the inspection process per batch of stickers
What good looks like for this metric: 10-15% of production cost
Ideas to improve this metric- Invest in more efficient equipment
- Reduce overtime by optimising schedules
- Train staff to enhance productivity
- Adopt digital record-keeping systems
- Utilise economies of scale in inspection
5. Customer Complaints related to Defects
The number of customer complaints received about sticker defects post-inspection
What good looks like for this metric: Fewer than 2 per 1000 units
Ideas to improve this metric- Enhance communication with customers
- Revise inspection criteria to align with customer expectations
- Implement immediate feedback systems
- Conduct regular customer satisfaction surveys
- Utilise complaints as training points for inspectors
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 Quality Leakage Control
1. Defect Rate in Outbound Products
Percentage of products with defects after outbound quality checks
What good looks like for this metric: Less than 1%
Ideas to improve this metric- Implement additional quality checks
- Conduct regular training sessions for quality inspectors
- Establish clear quality standards and criteria
- Enhance defect tracking systems
- Perform root cause analysis for identified defects
2. Recall Rate
Frequency of products being recalled due to defects discovered post outbound checks
What good looks like for this metric: Below 0.5%
Ideas to improve this metric- Improve supplier quality management
- Optimize quality assurance processes
- Increase frequency of internal audits
- Enhance product testing methodology
- Strengthen communication channels for issue reporting
3. Customer Complaint Rate
Number of customer complaints received about product quality issues related to outbound checks
What good looks like for this metric: Below 10 complaints per 1,000 units
Ideas to improve this metric- Use customer feedback for continuous improvement
- Establish a robust complaint resolution process
- Monitor complaint trends for proactive measures
- Train customer service teams on quality issues
- Regularly review and update quality control protocols
4. Cost of Poor Quality (COPQ)
Financial measure of the costs associated with defects, rework, and warranty claims
What good looks like for this metric: Less than 2% of total production costs
Ideas to improve this metric- Increase investment in quality training
- Adopt lean manufacturing techniques
- Enhance process standardisation
- Implement automated quality control systems
- Regularly review cost data for insights
5. First Pass Yield (FPY)
Percentage of products that pass outbound quality checks without rework
What good looks like for this metric: Above 95%
Ideas to improve this metric- Analyse process flows for inefficiencies
- Focus on equipment maintenance and calibration
- Develop comprehensive training programs
- Implement statistical process control (SPC)
- Conduct regular process audits
Metrics for Monitor finish good leakage
1. Defect Rate
Measures the percentage of defective goods identified during quality checks
What good looks like for this metric: Less than 3%
Ideas to improve this metric- Enhance employee training on quality standards
- Implement stricter inspection protocols
- Utilise advanced detection technology
- Review and refine supplier quality
- Increase frequency of random sampling
2. First Pass Yield
Percentage of products that pass quality checks on the first attempt without rework
What good looks like for this metric: Over 95%
Ideas to improve this metric- Conduct thorough root cause analysis on failures
- Implement process improvements based on collected data
- Regularly maintain and calibrate equipment
- Collaborate with production for consistent quality
- Provide feedback loop for continuous improvement
3. Cost of Quality
Total cost associated with ensuring products meet quality standards
What good looks like for this metric: Less than 10% of total sales
Ideas to improve this metric- Streamline quality control processes to reduce costs
- Invest in automated systems to lower labour costs
- Focus on preventing defects over correcting them
- Improve efficiency in quality testing procedures
- Negotiate with suppliers for better component quality
4. Customer Complaints
Number of complaints received related to product leaks and defects
What good looks like for this metric: Less than 1% of total deliveries
Ideas to improve this metric- Implement real-time feedback systems
- Increase responsiveness to complaints
- Analyse complaint data for common issues
- Involve customers in quality assurance processes
- Develop clear communication channels for feedback
5. Return Rate
Percentage of goods returned due to defects or leakage issues
What good looks like for this metric: Below 2%
Ideas to improve this metric- Enhance packaging techniques to prevent damage
- Conduct thorough pre-shipment inspections
- Offer incentives for defect-free production
- Analyse excessive return patterns
- Incorporate strict documentation control
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 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 L2 Support Team Development
1. Average Resolution Time
The average time taken to resolve a customer's issue once it has been escalated to the L2 support team
What good looks like for this metric: 24-48 hours depending on complexity
Ideas to improve this metric- Implement clear escalation protocols
- Provide advanced training for common issues
- Utilise automated tools to assist in diagnostics
- Conduct regular team meetings to discuss complex cases
- Evaluate individual performance regularly
2. First Contact Resolution Rate
The percentage of escalated tickets that are resolved without needing further escalation
What good looks like for this metric: 70-85%
Ideas to improve this metric- Ensure comprehensive knowledge base is available
- Regularly update FAQs and common issue solutions
- Implement effective troubleshooting frameworks
- Provide ongoing training focused on first contact resolution
- Encourage collaboration and knowledge sharing among team members
3. Customer Satisfaction Score (CSAT)
A measure of customer satisfaction with their support experience, often gathered through post-resolution surveys
What good looks like for this metric: 80-90%
Ideas to improve this metric- Enhance communication skills training
- Follow-up with customers post-resolution for feedback
- Design clear and concise feedback surveys
- Offer customer service workshops
- Address any negative feedback promptly with corrective action
4. Case Backlog
The number of unresolved cases that get carried over from previous time periods
What good looks like for this metric: Less than 10% of active cases
Ideas to improve this metric- Optimise workflow management tools
- Set realistic daily targets for case resolutions
- Identify peak times and allocate resources accordingly
- Review complicated cases in team discussions
- Utilise prioritisation strategies to address high-impact cases first
5. Employee Satisfaction Score
A measure of the L2 support team's job satisfaction and engagement, often gathered through internal surveys
What good looks like for this metric: 70-85%
Ideas to improve this metric- Implement recognition and reward programmes
- Create career development opportunities
- Hold regular feedback sessions
- Encourage work-life balance initiatives
- Foster a supportive and inclusive work environment
Tracking your Quality Assurance Team metrics
Having a plan is one thing, sticking to it is another.
Having a good strategy is only half the effort. You'll increase significantly your chances of success if you commit to a weekly check-in process.
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 Ensuring sticker quality- The best metrics for Packaging Operations Metrics
- The best metrics for Job Reception Overview
- The best metrics for L2 Support Team Development
- The best metrics for Vendor Compliance Standards
- The best metrics for Improving vendor cleanliness
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