Explore QA & QC Metrics & KPIs, defect trends, automation & manual testing KPIs, and quality measurement strategies
What you will learn
Monitoring and analyzing the progress of test case execution
Creating actionable insights from defect trends
Spotting inefficiencies or slowdowns in QA processes
Measuring defect concentration and how often bugs escape to production
Identifying gaps in test scenarios using metrics
Estimating the return on investment from test automation efforts
Using metric-driven approaches to improve test planning
Combining manual and automated metrics
Measuring productivity of QA teams over time
Set QA & QC KPIs and tailoring them to project needs
Using test metrics to support compliance and audits
Using metrics to evaluate quality level on a project
Quantifying the cost of poor quality (CoPQ)
Building metric-based QA OKRs for teams
Using metrics to support root cause analysis sessions
Differentiating between bug severity and priority for better triaging
Designing reports that clearly communicate QA results to stakeholders
Using data during retrospectives to improve QA strategies
How to identify and define useful QA indicators and performance metrics
Evaluating how much of the system is tested and how effective the tests are
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- Unlock the power of data to transform your Quality Assurance and Quality Control (QA & QC) processes. This course delves beyond simple tracking, equipping you with the strategic foresight to leverage metrics for tangible improvements.
- Master the art of **proactive quality management** by understanding how to anticipate and mitigate potential issues before they impact your software.
- Develop a sophisticated understanding of **defect leakage patterns**, enabling you to pinpoint the root causes of escaped defects and implement targeted preventative measures.
- Learn to **quantify the effectiveness of your testing efforts**, moving beyond just coverage to measure the actual impact of your tests on product quality.
- Gain the skills to **optimize resource allocation** within your QA teams by identifying areas of high return on investment and those requiring greater attention.
- Discover how to **build a data-informed culture** within your QA department, fostering collaboration and driving continuous improvement through evidence-based decision-making.
- Understand the critical link between **quality metrics and business objectives**, aligning your QA strategy with overarching organizational goals.
- Explore advanced techniques for **trend analysis** to predict future quality outcomes and adjust testing strategies accordingly.
- Learn to **translate raw data into compelling narratives** that clearly communicate the value and impact of QA initiatives to all stakeholders.
- Acquire the ability to **identify and address systemic weaknesses** in your development and testing pipelines through rigorous data analysis.
- Understand the nuances of **measuring the efficiency of different testing methodologies**, allowing for informed choices between manual and automated approaches.
- Develop strategies to **demonstrate the ROI of your testing investments**, showcasing the financial benefits of robust QA.
- Learn to **establish baseline quality metrics** to accurately gauge progress and the impact of implemented improvements.
- Empower yourself to **translate qualitative feedback into quantifiable data points**, enriching your understanding of user experience and product quality.
- Pros:
- Provides a strategic, data-centric framework for QA, elevating it from a reactive to a proactive function.
- Enables significant improvements in efficiency and effectiveness through actionable insights.
- Cons:
- Requires a foundational understanding of QA principles to fully grasp the strategic application of metrics.
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