What are Quality Improvement Team metrics? Finding the right Quality Improvement 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 Improvement 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 Improvement Team metrics and KPIs 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
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1. Review Cycle Time The average time taken from the initiation of a review process to its completion
What good looks like for this metric: 2-4 weeks
Ideas to improve this metric Streamline the review process steps Implement deadlines for each review stage Utilise automated tools for routine tasks Provide training for faster review Conduct regular process audits 2. Review Quality Score A quality score assigned to reviews based on predefined criteria and feedback
What good looks like for this metric: 80-90%
Ideas to improve this metric Enhance reviewer training programmes Develop a detailed review checklist Incorporate peer feedback into reviews Regularly update review criteria Reward high-quality reviews 3. Review Completion Rate The percentage of reviews completed out of all initiated reviews
What good looks like for this metric: 90%+
Ideas to improve this metric Set clear roles and responsibilities Implement a tracking system for reviews Ensure adequate resourcing for review tasks Address common delay points in the process Regularly review incomplete review reasons 4. Reviewer Utilisation Rate The percentage of time reviewers spend on review activities out of their total available work time
What good looks like for this metric: 60-80%
Ideas to improve this metric Balance reviewer workloads effectively Provide additional resources during peak times Cross-train staff to assist with reviews Automate or delegate non-essential reviewer tasks Set priorities for review assignments 5. Review Feedback Loop The percentage of reviews followed by actionable feedback and subsequent improvements
What good looks like for this metric: 70%+
Ideas to improve this metric Establish a clear feedback protocol Encourage open and honest feedback Implement a follow-up mechanism for feedback actions Regularly review the effectiveness of feedback Foster a culture of continuous improvement
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1. Process Efficiency Ratio The ratio of the output value produced to the resources used, indicating the efficiency of processes.
What good looks like for this metric: 80-90%
Ideas to improve this metric Identify and eliminate bottlenecks Automate repetitive tasks Streamline workflows Conduct regular process audits Implement continuous improvement programs 2. Process Cycle Time The total time taken to complete a process from start to finish.
What good looks like for this metric: Depends on industry standards
Ideas to improve this metric Analyse and reduce wait times Utilise process mapping tools Adopt lean management principles Use time management software Conduct time-motion studies 3. Process Compliance Rate Percentage of processes that adhere to established procedures and standards.
What good looks like for this metric: 95% or above
Ideas to improve this metric Regularly train employees on process standards Implement compliance checks Utilise process management software Develop clear process documentation Encourage a culture of adherence 4. Employee Productivity Index Measure of employee output relative to the resources used in a process.
What good looks like for this metric: Varies across industries
Ideas to improve this metric Set clear performance goals Provide regular feedback Offer training and development Ensure resources are adequate Recognise and reward high performance 5. Quality Defect Rate Percent of outputs that require rework or result in customer complaints.
What good looks like for this metric: Below 5%
Ideas to improve this metric Implement rigorous quality control Provide employee training Utilise root cause analysis Adopt six sigma methodologies Engage with quality assurance teams
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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
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1. Healing Rate The percentage of wounds that heal within a specified timeframe
What good looks like for this metric: 70-90% healing within 12 weeks
Ideas to improve this metric Implement evidence-based treatment protocols Provide ongoing staff training Enhance patient education on wound care Use advanced wound care products Conduct regular wound assessments 2. Patient Satisfaction Score Patients’ satisfaction levels with wound care services received
What good looks like for this metric: Average score of 4.5 out of 5
Ideas to improve this metric Enhance communication with patients and families Reduce wait times for appointments Improve clinic or hospital facilities Offer personalised care plans Gather regular feedback and act on it 3. Infection Rate The percentage of wounds that become infected post-treatment
What good looks like for this metric: Less than 5% infection rate
Ideas to improve this metric Follow strict hygiene protocols Use antimicrobial dressings Educate patients on signs of infection Perform regular wound monitoring Ensure proper wound cleaning during dressing changes 4. Rehospitalisation Rate The rate at which patients are readmitted due to wound-related complications
What good looks like for this metric: Below 10%
Ideas to improve this metric Develop comprehensive discharge plans Increase follow-up care and monitoring Address any underlying health issues Provide patients with detailed wound care instructions Use technology to monitor patient progress remotely 5. Cost per Treatment Average cost incurred per wound care treatment session
What good looks like for this metric: $150-$300 per treatment
Ideas to improve this metric Standardise treatment protocols Use cost-effective supplies Minimise unnecessary testing Reduce treatment duration with effective interventions Negotiate better pricing on supplies
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1. Average Response Time The average time it takes for support staff to respond to student queries
What good looks like for this metric: 24 hours or less
Ideas to improve this metric Implement automated responses for common queries Provide additional training sessions for support staff Utilise CRM software to track response times Set goals for individual team members Analyse and optimise workflow processes 2. Student Feedback Quality Score The average rating of feedback provided by mentors as rated by students
What good looks like for this metric: 4.5 out of 5
Ideas to improve this metric Provide training on giving effective feedback Develop a standard feedback template Review and discuss feedback in team meetings Gather feedback from students on mentor performance Conduct regular mentor evaluations 3. First Contact Resolution Rate Percentage of support queries resolved during the first interaction with support staff
What good looks like for this metric: 70% or higher
Ideas to improve this metric Conduct root cause analysis on frequently unresolved topics Empower staff to make decisions without escalation Improve access to solution resources Develop a comprehensive FAQ section Increasing collaboration with mentors for complex issues 4. Mentor Availability Measures the average time mentors are available to provide feedback during scheduled office hours
What good looks like for this metric: 85% of scheduled hours
Ideas to improve this metric Optimise scheduling to align with student needs Provide incentives for maintaining high availability Introduce flexible working hours for mentors Utilise technology to aid remote mentoring sessions Increase cross-training for coverage 5. Net Promoter Score (NPS) A measure of student loyalty and satisfaction based on their likelihood to recommend the training to others
What good looks like for this metric: 70 or above
Ideas to improve this metric Regularly survey students for feedback Improve mentor-student engagement Enhance curriculum based on student feedback Ensure a seamless onboarding process Create a supportive community for student interaction
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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. Number of Parameters Differentiates model size options such as 1 billion (B), 3B, 7B, 14B parameters
What good looks like for this metric: 3B parameters is standard
Ideas to improve this metric Evaluate the scalability and resource constraints of the model Optimise parameter tuning Conduct comparative analysis for various model sizes Assess trade-offs between size and performance Leverage model size for specific tasks 2. Dataset Composition Percentage representation of data sources: web data, books, code, dialogue corpora, Indian regional languages, and multilingual content
What good looks like for this metric: Typical dataset: 60% web data, 15% books, 5% code, 10% dialogue, 5% Indian languages, 5% multilingual
Ideas to improve this metric Increase regional and language-specific content Ensure balanced dataset for diverse evaluation Perform periodic updates to dataset Utilise high-quality, curated sources Diversify datasets with varying domains 3. Perplexity on Validation Datasets Measures the predictability of the model on validation datasets
What good looks like for this metric: Perplexity range: 10-20
Ideas to improve this metric Enhance tokenization methods Refine sequence-to-sequence layers Adopt better pre-training techniques Implement data augmentation Leverage transfer learning from similar tasks 4. Inference Speed Tokens processed per second on CPU, GPU, and mobile devices
What good looks like for this metric: GPU: 10k tokens/sec, CPU: 1k tokens/sec, Mobile: 500 tokens/sec
Ideas to improve this metric Optimise algorithm efficiency Reduce model complexity Implement hardware-specific enhancements Utilise parallel processing Explore alternative deployment strategies 5. Edge-device Compatibility Evaluates the model's ability to function on edge devices with latency and response quality
What good looks like for this metric: Latency: <200 ms for response generation
Ideas to improve this metric Optimise for low-resource environments Develop compact model architectures Incorporate adaptive and scalable quality features Implement quantisation and compression techniques Perform real-world deployment tests
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Tracking your Quality Improvement Team 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.
More metrics recently published We have more examples to help you below.
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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