Must-Know Quality Assurance Kpis [Latest Report]

Highlights: Quality Assurance Kpis

  • 1. Defect Density
  • 2. Test Case Execution Rate
  • 3. Test Case Pass Rate
  • 4. Requirements Coverage
  • 5. Defect Removal Efficiency (DRE)
  • 6. Defect Leakage
  • 7. Test Automation Coverage
  • 8. Code Review Coverage
  • 9. Mean Time To Detect (MTTD)
  • 10. Mean Time To Repair (MTTR)
  • 11. Test Case Effectiveness
  • 12. Test Effort Variance
  • 13. Customer Reported Defects

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In today’s highly competitive business landscape, organizations are constantly striving to deliver products and services that meet and surpass customer expectations. One crucial driver of success in this endeavor is the effective implementation and tracking of Quality Assurance (QA) processes. By consistently monitoring key performance indicators (KPIs), businesses can optimize their quality assurance practices and enhance the overall performance of their offerings.

In this comprehensive blog post, we will take an in-depth look at the most crucial QA KPIs, how to accurately measure them, and ways to leverage this information in elevating your organization’s QA strategies for maximum customer satisfaction and profitability.

Quality Assurance KPIs You Should Know

1. Defect Density

It refers to the number of defects detected during the testing phase of software development, relative to its size. A lower defect density indicates a higher quality product.

2. Test Case Execution Rate

This KPI measures the efficiency of the testing process, specifically the percentage of test cases executed in a given time period. Higher test case execution rates generally indicate better test planning and allocation of resources.

3. Test Case Pass Rate

The percentage of test cases that pass during a testing cycle. A high pass rate indicates that the software product meets its requirements and is of good quality.

One crucial driver of success in this endeavor is the effective implementation and tracking of Quality Assurance (QA) processes.

4. Requirements Coverage

This KPI measures the extent to which the software product’s requirements are represented in test cases. High requirements coverage ensures that all the necessary functionality is tested.

5. Defect Removal Efficiency (DRE)

A metric that calculates the percentage of defects found and fixed before a product is released. A high DRE represents effective defect identification and removal processes in place.

6. Defect Leakage

Refers to the percentage of defects that make it past the testing phase and into production. Lower defect leakage rates indicate a more effective quality assurance process.

7. Test Automation Coverage

This KPI measures the extent to which the test suite comprises automated test cases. High test automation coverage indicates a more efficient testing process and reduced manual effort.

8. Code Review Coverage

The percentage of code that is reviewed during the development process for errors and coding standards compliance. A higher code review coverage means more thorough quality control during development.

In today’s highly competitive business landscape, organizations are constantly striving to deliver products and services that meet and surpass customer expectations.

9. Mean Time To Detect (MTTD)

Measures the average time it takes to identify a defect during the testing phase. A shorter MTTD indicates a more efficient defect detection process.

10. Mean Time To Repair (MTTR)

Refers to the average time it takes to fix a defect once it’s identified. A shorter MTTR indicates a faster and more efficient defect resolution process.

11. Test Case Effectiveness

This KPI evaluates the accuracy and relevance of the test cases in detecting defects. High test case effectiveness ensures that the test suite is suitable for identifying issues in the software product.

12. Test Effort Variance

Measures the difference between the planned and actual effort expended in testing a software product. Low test effort variance indicates adherence to the testing schedule and effective resource allocation.

13. Customer Reported Defects

The number of defects reported by end-users after a product is released. A lower number of customer-reported defects signifies a higher-quality product and successful quality assurance efforts.

Quality Assurance KPIs Explained

Quality Assurance KPIs are essential for ensuring that the software products and services delivered by an organization meet the desired level of quality and performance. Defect Density, Test Case Execution Rate, Test Case Pass Rate, Requirements Coverage, Defect Removal Efficiency, Defect Leakage, Test Automation Coverage, Code Review Coverage, Mean Time To Detect, Mean Time To Repair, Test Case Effectiveness, Test Effort Variance, and Customer Reported Defects are all critical KPIs that each provide valuable insights into different aspects of the software product’s quality.

These KPIs enable organizations to identify areas for improvement, optimize resource allocation, and streamline testing processes. Ultimately, these metrics contribute to the overall goal of reducing customer-reported defects and ensuring a high-quality, reliable product for end-users.


In conclusion, Quality Assurance KPIs are the backbone for evaluating and enhancing the performance of your QA processes. Implementing the right set of KPIs not only ensures the highest level of product quality but also drives continuous improvement within the organization.

By closely monitoring these metrics, businesses can identify potential bottlenecks, make informed decisions, and establish a culture of excellence that leads to customer satisfaction and sustained success. Remember, consistently measuring, analyzing, and refining your KPIs is imperative for maintaining a robust and effective quality assurance ecosystem.


What are Quality Assurance KPIs and why are they important?

Quality Assurance KPIs (Key Performance Indicators) are measurable values used by businesses to evaluate the performance and efficiency of their quality assurance processes. These metrics help organizations identify areas of improvement, monitor progress, and ensure that products and services meet customer expectations and regulatory requirements.

Can you list some common Quality Assurance KPIs used by organizations?

Some common Quality Assurance KPIs include defect density, test coverage, test case pass rate, mean time to detect (MTTD) defects, and mean time to resolve (MTTR) defects. Other KPIs might involve customer satisfaction ratings, process compliance, and first-time pass rate.

How can Quality Assurance KPIs help improve overall product quality?

By monitoring Quality Assurance KPIs, businesses gain insights into the efficiency of their testing processes and the effectiveness of their quality control measures. This enables them to identify trends, pinpoint areas of concern, and implement corrective actions. Furthermore, tracking these KPIs allows organizations to continually refine their processes, ensuring higher product quality and increased customer satisfaction.

How often should Quality Assurance KPIs be reviewed and updated?

The frequency of reviewing and updating Quality Assurance KPIs depends on the organization's needs, the complexity of the project, and the industry in which they operate. Generally, it's recommended to review them at regular intervals, such as monthly or quarterly, to ensure that they remain relevant and aligned with the organization's objectives. Additionally, KPIs may need to be updated when significant process changes are implemented or if customer requirements shift.

Can Quality Assurance KPIs be tailored to specific industries or business models?

Yes, Quality Assurance KPIs can be customized to meet the unique needs and requirements of specific industries, business models, or organizational structures. While some KPIs, such as defect density or test coverage, may be applicable across various sectors, other KPIs can be developed to address industry-specific concerns, regulatory requirements, or unique characteristics of the products and services being delivered.

How we write our statistic reports:

We have not conducted any studies ourselves. Our article provides a summary of all the statistics and studies available at the time of writing. We are solely presenting a summary, not expressing our own opinion. We have collected all statistics within our internal database. In some cases, we use Artificial Intelligence for formulating the statistics. The articles are updated regularly.

See our Editorial Process.

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