What are the best practices for ticketing system reporting and analysis in software testing?

1 Choose the right ticketing system

When selecting a ticketing system for your testing needs and goals, you should consider the size and complexity of your project and team, the type and frequency of testing activities and deliverables, the integration and compatibility with other tools and systems, the features and functionality that support reporting and analysis, such as filters, charts, dashboards, and metrics, as well as the cost and maintenance. Additionally, it is important to evaluate the usability, reliability, and security of the ticketing system before implementing it.

2 Define and follow a ticketing workflow

A ticketing workflow is an essential set of rules and procedures that define how tickets are created, assigned, updated, and closed. It helps software testers maintain a consistent and efficient process for managing issues and communicating with stakeholders. This should include the roles and responsibilities of each team member, the criteria and format for creating tickets, the categories and priorities for classifying tickets, the statuses and transitions for tracking tickets, the notifications and escalations for alerting tickets, and the documentation and verification for closing tickets. It is important to review and improve your ticketing workflow regularly based on feedback and results.

3 Collect and report relevant data

A ticketing system can generate a lot of data, but software testers should only collect and report the data that reflects the quality, progress, and performance of their testing activities and outcomes. This could include the number of tickets created, resolved, and pending by category, priority, status, or time period; the average time taken to resolve tickets; the distribution and trend of tickets; the root causes and impacts of tickets; and the feedback and satisfaction ratings of tickets. It is also important to use clear and concise language, visual aids, and summaries to present this data effectively.

4 Analyze and act on data insights

The final step in software testing is to analyze and act on the data insights that you obtain from your ticketing system. Utilizing data analysis techniques, such as descriptive, diagnostic, predictive, and prescriptive analytics, can help identify patterns, problems, opportunities, and solutions related to testing processes and results. Examples of useful data insights include the most common and critical issues found during testing and their root causes and impacts, areas or aspects of the software that need more testing or improvement, gaps or bottlenecks in the ticketing workflow and how to optimize it, best practices and lessons learned from the ticketing process and how to apply them, as well as recommendations and actions for improving the quality, efficiency, and effectiveness of testing. It is also important to share these insights with your team and stakeholders and monitor/measure the outcomes of your actions.

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?