metrics measuring automation success

Organizations invest heavily in test automation to find defects early and release faster. The process usually starts with hiring skilled testers, forming an automation team, and building an automation framework with the plethora of tools and frameworks available these days.

Once the considerable time is spent building the framework, teams start integrating the tests into their CI/CD pipeline and make them run periodically based on checked-in code. Most teams come to the conclusion that this is the endpoint of the entire automation creation and execution cycle.

But there is one more critical aspect of test automation teams that need to spend time and research on measuring the success of the automated tests.

Misleading metrics for automation success

Measuring automation is a highly debated topic, as organizations view metrics in different ways. But there are some that are just objectively not good indicators of automation success. These are a couple of the most common metrics teams track that aren’t useful when measuring automation.

Number of automated test cases

This is one of the most common ways teams measure automation success. They believe if there are a certain number of automated tests, the entire automation effort is successful.

However, this may not be a good indicator of automation success, as the focus is more on the effort the team has invested to automate the manual test cases rather than the actual value the automated tests provided to the team.

Also, having a large number of automated tests does not mean the right modules are tested. For example, if there are 100 test cases and 90 of them are automated, does it mean we are 90% successful in doing automation? Maybe not, as this information does not convey whether the test cases automated were actually valuable to the team.

Number of defects found

Using the number of defects found by the automation script as a measurement of success is misleading and gives a false sense of accomplishment to teams.

For example, if the automation script found 10 defects, it could mean the developer did not do their job correctly; and if there are zero defects found, it could mean the automation scripts weren’t effective. There are multiple ways to interpret these results.

These two metrics are open to different interpretations, so they can steer the team’s mindset from the value provided by these automated tests to false goals and benchmarks.

Let’s explore some alternative metrics teams could use to bring the focus back on value.

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Good metrics for automation success

Here are some good metrics to consider, based on the context of the project and the team. These metrics could reduce the ambiguity in measuring automation success and thereby provide more valuable information.

Testing time saved

One of the main reasons for building automated tests is to save valuable manual testing effort. While the automated tests are repeating mundane testing tasks, testers can focus on the more critical and higher priority tasks, spend time exploring the application, and test modules that are hard to automate and need extensive critical thinking.

The amount of testing time saved is a good metric to know how much value is provided to the team. For example, in a two-week sprint, if the automated tests could reduce the manual testing effort from two days to four hours, that is a big win for the team and the organization — and it converts into money saved — so it should be tracked and communicated.

The flakiness of automated tests

If the team spends four months building a robust automation framework, then spends more time maintaining the automated tests than actually using them to find defects, the entire effort is wasteful. Surprisingly, this is a common problem in teams; their tests are unstable and keep failing due to multiple factors. As a result, teams stop trusting the automated tests and eventually decide to go back to testing all the features manually.

It is important to start with a small number of tests, run them constantly, identify flaky tests and separate them out from the stable tests. This methodical approach helps to bring back the value of having automated tests.

Number of risks mitigated

Testing needs to be prioritized based on risks. These could be unexpected events that would impact business, defect-prone areas of the application, or any past or future events that could affect the project.

A good approach to measure automation success in relation to risk is to rank the risks based on high to low priority. Then, automate test cases based on risk priority, and track the number of risks that have been mitigated by the automated tests.

Ease of use of the automated framework or tests

Teams often forget that their automated tests need to be low-maintenance, should be easy to run by anyone, must have simple and understandable code, and should give great information about the tests that run in terms of passed and failed tests, logs, visual dashboards, screenshots and much more. This is a great indicator of whether the automation effort was successful. It is a subjective metric, but the information has a huge impact on teams.

All these metrics need to be adapted based on the context of the project; this is not a “one size fits all” solution. But they do help change the mindset of teams to shift focus to the value of automated tests, instead of arbitrary numbers and the effort expended.

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About the Author

Raj Subrameyer is an international keynote speaker, writer and tech career coach with a rich technical background. In his blog, rajsubra.com/blog/, he posts inspirational news, resources, and updates to help his readers lead a better life.

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