“Productivity is never an accident. It is always the result of a commitment to excellence, intelligent planning, and focused effort.” – Paul J.Meyer

The best way to determine productivity is to measure the key metrics and factors related to Software Testing, keep track of it, and continuously put in the right measures to improvise it. “Measurement of a test process is a required competence for an effective software test manager for designing and evaluating a cost-effective test strategy”
says a recent report by ResearchGate.

Testing strategy metrics help organizations to obtain the information they need to continue to improve productivity, reduce errors, improve acceptance of processes, and achieve the desired business goal.

The following are the key testing strategy metrics and factors when constantly monitored, optimized, and improved will provide us the best productivity.

  1. ROI – The customer should be able to yield a good return of investment by making savings in the conversion of the manual test cases into automation scripts.
  2. Test Toolsmith – In the QA team, an experienced, as well as a skilled resource, should take the role of a toolsmith whose primary tasks would be to research and analyze tools in the market, find productivity issues, and try to address them at the earliest. Along with that, they should be the SPOC (Single Point Of Contact) for all the requests/queries from the testing team members.
  3. In-Sprint Automation – It is very important to be aware of what is the percentage of test cases are automated for the sprint and how much is taken up later and completed in the following sprints more quickly. This helps us to groom on the backlogs and the stability of the user stories for that sprint.
  4. Framework Re-usability – The automation framework should be more modular and re-usable so that creating or updating the existing scripts becomes faster and easier.
  5. Cycle Time – The number of cycles of test suites that were executed will be sufficient to ship the product. It is important to ensure that we meet the right exit criteria. If this is optimized and kept at a minimum then this will increase a lot of time and the cost apparently.
  6. Automate the non-automatable test cases by analyzing existing/new tools in order to achieve maximum automation coverage
  7. The test Manager and the testing team should be very pro-active in case of any deviations in the below-expected metrics and resolve the issues at the earliest.
    • Manual Test Case Productivity – Review the test scenarios/cases created with the respective stakeholders to ensure that all business scenarios are completely transformed for performing a complete validation of the application/product.
    • Defect Acceptance and Defect Rejection – Based on the number of defects that were rejected, the testing team should get the business requirements expectations rightly aligned and focus on that perspective going forward.
    • Bad Fix Defects and Re-opened Defects – The total number of re-opened defects and the total number of defects that are newly occurring due to developers’ bad fix needs to be addressed pro-actively.
    • Manual Test Execution Productivity – The number of manual/non-automatable test cases executed per day should be improvised each sprint/iteration/cycle.
    • Test Efficiency – This indicates if the testing team has identified any defects post-release and takes necessary steps to mitigate such occurrence in the future.
    • Automation Scripting Productivity – It is crucial to script in the right approach so that all the automatable manual test cases are transformed into automated scripts. All the validation points that were performed during the manual test execution should be covered during automation scripting. This ensures more chances of identifying the defects.
    • Automation Test Execution Productivity – The test scripts should be executed in multiple browsers and parallel execution should be performed using the open-source frameworks/tools or if needed a cloud-based cross-browser testing partner like Sauce Labs, Browser Stack, AWS, etc. should be helpful in optimizing the execution time.
    • Automation Coverage – Automation scripting should be performed for all automatable test cases. We also need to keep track of the total code that is covered using automation.
    • Effort Variation and Schedule Variation – When there is a deviation in the effort and schedule that was planned then we need to highlight/improvise to avoid such situations in the future.
    • Equivalent Manual Test Effort – What effort it would have taken if these test cases were executed manually? This shows the benefits of running automation scripts against the time it takes for running the same test case manually.
  8. Project Information Repository – One of the best way to improve quality assurance is by ensuring all the proper information is available, including design specifications, and support documentation, in a common and accessible location for the team. A proper test management tool that tracks the QA process efficiently should be used. QA team requires a variety of information that is crucial to the success of a project i.e. business timelines, performance metrics, etc. An erratic flow of information can hinder productivity and cause unnecessary delays in deadlines so choosing right testing strategy metrics is important.
  9. Use Effective Communication Tools – Integrate communication and chat tools so that team members spend more time on the application rather than emailing developers, IT engineers, or other stakeholders with trivial issues or questions.
  10. Review and Audit Processes – Reviewing and auditing QA processes is critical for any QA team seeking productivity improvements. You can witness a boost in QA productivity through these reviews by identifying bottlenecks encountered by the team, accurately planning future goals, and assessing if the team is meeting project goals and deadlines.
  11. Rewards and Recognitions – The engineers should be motivated every sprint/iteration by providing deserving rewards/awards, and recognition. This increases the productivity of the deserved employee and it helps the other employees to work more effectively.
  12. Enhance Troubleshooting Skills – All the QA engineers should be capable of troubleshooting spontaneously without seeking developers for help or support. It is wise to do troubleshooting then and there rather than spending too much time in drafting and reporting issues since the former practice can significantly increase QA productivity. Troubleshooting guidelines maintained in a commonly accessible repository should help save a lot of time back and forth.

It is a smart way to increase the productivity of your team and achieve business goals by implementing the right testing strategy after considering all the above-mentioned factors and metrics. With the appropriate testing strategy metrics, you can easily estimate the quality and state of your software testing efforts.

Vijay Radhakrishnan

Vijay Radhakrishnan

Project Lead (Testing) at Aspire Systems
Vijay Radhakrishnan

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