Uncommon (but essential) Metrics for Measuring Software Test Automation ROI

Introduction

Test automation is often seen as an “Easy Button” that is solved with a moderate investment in tools. However the reality is often quite different and it’s usually a significant investment for a company. To measure the return on investment on your software test automation, it is essential to have the right metrics. Having clear metrics allows stakeholders to understand the value that test automation is providing to the organization. Without these metrics, it‘s very challenging to determine whether the investment in test automation was worth the cost. Clear metrics can help stakeholders make informed decisions about how to continue investing in test automation to ensure it provides powerful value.

Analyzing common metrics such as the number of tests run, test failure rates, and the time spent executing tests, stakeholders can identify areas for improvement and optimize the test automation process. While these are important to monitor, they are not designed to drive the right behavior of the overall software development organization. Quality is a team sport where all players must be on the field and attacking the same goal to make it work.

Uncommon metrics and why should they be measured

Collecting metrics for IT projects can be a challenging process for companies due to a variety of reasons. One of the main challenges is obtaining accurate data and measuring progress consistently, especially when dealing with complex and dynamic projects. Lack of stakeholder buy-in and insufficient resources for tracking and analyzing metrics can also hinder the collection process. Furthermore, companies may struggle to effectively communicate and use the metrics they collect to drive decision-making and improve project outcomes.

In many years of providing quality engineering services to our customers, we have realized there are several important aspects of software test automation to measure such as:

TRUST: The lack of trust in software testing automation.

This is due to concerns about the accuracy of the results generated by automated testing, which can lead to redundant testing being performed. As a result, the business team may be duplicating testing efforts to compensate for this lack of trust in automation. Overall, there is a need for increased confidence in automated testing to reduce redundancy and streamline the testing process.

SCOPE: Issues of not having a clear scope for test automation.

Several issues arise due to the absence of a clear scope, including the lack of hygiene in test automation assets, infrequent reviews of the assets, and no clear understanding of automation efficiency and associated costs. The whole team should understand the need for a more structured and systematic approach to test automation, with clear guidelines for maintaining and evaluating automation assets.

AUTONOMY: The elimination of the need for human interaction to run automated tests.

most companies, test automation still requires manual intervention to run, which can slow down the testing process and introduce errors. Likewise, a poor or non-implementation of DevOps is lacking, which limits the effectiveness of automation. Investing in test automation also requires investments in automating as much of the testing process as possible including DevOps practices to streamline the process and improve efficiency.

MAINTENANCE: A large effort dedicated to test automation maintenance.

Often, the majority of the team’s time is spent on modifying and updating existing automated tests, which can be a time-consuming and resource-intensive process. There is no proper tracking of changes from a business workflow level, which can make it difficult to assess the impacts of changes on existing automated tests and lead to inefficiencies and errors in the testing process. For a more effective, streamlined and systematic approach to test automation maintenance, it is crucial to have clear guidelines for tracking and assessing changes and their impacts on existing automated tests.

READINESS: Challenges related to manual dependencies and pre-and-post-conditions in test automation.

The deployment process is complex and infrequent, and not fully automated, which can lead to inefficiencies and errors in the testing process. The test environment setup and updates are usually not automated, which can further slow down the testing process. Likewise, test data creation and updates are (totally or partially) manually performed, which leads to inconsistencies and inaccuracies in the testing process. It is essential to have a more streamlined and automated approach to test automation, with automated deployment, environment setup, and test data creation and updates, to improve the efficiency and accuracy of the automation testing process.

VALUE: Not considering all direct and indirect costs when calculating the ROI of software testing automation.

The costs of test automation are often not fully considered, such as the costs of tools, labor, environments, and expertise, as well as the value of early defect detection, including defect prevention and coverage increase. This can lead to inaccurate ROI calculations and underestimation of the true value of test automation. However, only the costs of manual labor and defect leakage are usually considered, which can further limit the accuracy of ROI calculations. It is critical to consider all relevant costs and benefits when calculating the ROI of test automation to obtain a more accurate assessment of its value.

Having effective software test automation metrics is paramount for companies to measure the return on investment (ROI) properly. While conventional metrics such as the number of executed tests, test failure rates, and the duration of test execution are fundamental, they may not adequately stimulate the intended behavior of the overall software development organization. Therefore, it is imperative to go beyond the standard metrics to enhance ROI for test automation programs. Doing so will enable stakeholders to make informed decisions on how to continue investing in test automation, optimizing the test automation process to ensure that their investment is cost-effective and brings value to the organization.

Download our Automation Metrics guide for more information about the metrics to measure the six themes above, their definitions and scorecard. They include:

Toni is the test automation practice leader, head of emerging technology and testing at QA Consultants. Focus on continuous quality within the DevOps practices implementation, development of new approaches and technologies to support QE for Deterministic and Cognitive Systems.