Last updated on Aug 5, 2024

How do you choose the best defect metrics for your dashboard?

Defect tracking is a vital process for ensuring software quality and customer satisfaction. But how do you measure and communicate the status and progress of your defect resolution efforts? One way is to use a defect metrics dashboard that displays relevant and actionable data in a clear and concise way. In this article, you will learn how to choose the best defect metrics for your dashboard, based on your goals, context, and audience.

1 Define your purpose

Before you select any defect metrics, you need to define the purpose of your dashboard. What are you trying to achieve with it? Who are you reporting to and what do they care about? How often do you need to update and share it? Your purpose will guide you to select the most appropriate and meaningful metrics that align with your objectives and expectations.

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jaya Krishna tummala ,MS, CSM

Award Winning Senior Functional Quality Assurance|BSA|SAP QA|Safe 6.0 Agilist|Sigma Xi Full Member|IEEE Senior Member|Fellow IETE|Author
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Starting with a broad exploration of available defect metrics can uncover valuable insights and patterns that could influence or refine your objectives. By examining a range of metrics first, you might identify key areas that you hadn’t initially considered, which could lead to a more comprehensive and effective dashboard. In essence, exploring the metrics themselves can help shape and inform the purpose of your dashboard.

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2 Choose your metrics

Once you have your purpose, you can choose your metrics from a variety of sources and categories. Some common sources of defect metrics are your defect tracking tool, your test management tool, your code repository, and your customer feedback system. Some common categories of defect metrics are defect density, defect severity, defect status, defect resolution time, defect root cause, and defect impact. You can use a combination of these metrics to create a balanced and comprehensive dashboard that covers different aspects of defect tracking.

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3 Visualize your data

After you have your metrics, you need to visualize them in a way that makes sense and highlights the key insights. You can use different types of charts, graphs, tables, and indicators to display your data, depending on the nature and level of detail of your metrics. For example, you can use a pie chart to show the distribution of defect severity, a line chart to show the trend of defect resolution time, a bar chart to show the comparison of defect density across modules, and a gauge to show the current defect status.

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Kaushik Maitra CSM®

Technical Consultant in TCS BENGALURU|| 🟩Certified ScrumMaster® ||🟩36K LinkedIn Family.|| Web Accessibility Test Lead ||Automation Tester|| PMO Operations||
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Data visualization is the process of using visual elements like charts, graphs, or maps to represent data. This process can help people understand trends, outliers, and patterns in data, and can make it easier to process complex, high-volume, or numerical data. Data visualization can also help people make better decisions and drive informed decision-making

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4 Evaluate your dashboard

Finally, you need to evaluate your dashboard and make sure it is effective and useful. You can do this by asking yourself some questions, such as: Does it answer the questions that your purpose defined? Does it show the data that your audience cares about? Does it present the data in a clear and accurate way? Does it highlight the main points and actions that you want to convey? Does it fit the format and frequency that you need to share it? You can also solicit feedback from your stakeholders and users and make adjustments accordingly.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you choose the best defect metrics for your dashboard?

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1 Define your purpose

2 Choose your metrics

3 Visualize your data

4 Evaluate your dashboard

5 Here’s what else to consider

Defect Tracking

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