test-automation-roi

Test Automation ROI - How to Calculate It?

Implementing test automation often requires a substantial initial investment. From building frameworks to maintaining scripts, it’s not just about saving time but also about ensuring a tangible return on investment (ROI). Calculating the ROI for test automation helps justify the effort and resources spent while offering insights into efficiency gains, cost savings, and long-term benefits.

This guide will take you through the essentials of calculating test automation ROI, explain the key formulas, and break down each component to help you make informed decisions about your automation strategy.

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What is Test Automation ROI?

Test Automation ROI measures the financial and operational benefits gained from implementing automated testing compared to its total investment. It quantifies whether the resources dedicated to automation result in cost savings, efficiency improvements, and higher productivity.

roi-formula

Why should you calculate ROI for Test Automation?

Understanding ROI in test automation goes beyond financial benefits. It provides insights into how automation aligns with organizational goals and streamlines testing processes. Here are four reasons to calculate ROI:

  • Financial effect: Calculating ROI highlights the cost efficiency of automation, showing how much money is saved through reduced manual efforts and faster testing cycles.
  • Prediction impact: A detailed ROI analysis helps predict future performance, offering insights into whether automation efforts will remain beneficial as the project scales.
  • Prospective profits and losses: ROI calculations can reveal not only direct savings but also potential losses from failed investments or inadequate automation coverage.
  • Sustainability: ROI helps gauge whether the automation strategy is sustainable long-term by accounting for maintenance, scalability, and adaptability costs.

Benefits of Test Automation ROI

  1. Cost savings: Automation reduces repetitive manual testing hours, freeing up resources for more critical tasks. For example, automating login tests for an e-commerce platform can save hundreds of hours over a year.
  2. Faster time-to-market: Automation speeds up regression and smoke testing, ensuring that releases are quicker and more frequent without compromising quality.
  3. Improved accuracy: Automated tests eliminate human error, ensuring consistent results, especially in repetitive tasks like validating large datasets.
  4. Scalability: Automation frameworks can scale to handle increased test coverage without proportionally increasing costs, unlike manual testing.
  5. Reusability: Test scripts can be reused across different builds, saving effort and resources in the long term.
  6. Continuous Testing: Automation facilitates integration with CI/CD pipelines, enabling continuous testing and reducing delays caused by manual processes.
  7. Enhanced coverage: Automated testing can explore combinations and edge cases that might be overlooked in manual testing.
  8. Better resource allocation: By automating repetitive tasks, teams can focus on exploratory and usability testing, enhancing overall quality.
  9. Standardized reporting: Automated testing tools provide detailed and consistent reports that help track issues and improvements over time.
  10. Higher ROI with iterative improvements: As automation frameworks mature, the return on investment continues to grow, creating a compounding effect on savings.

Breaking down the ROI formula

1. Savings

Savings represent the value gained by automating repetitive and time-consuming manual tests. To calculate savings, consider how much time automation saves compared to manual testing across all test cases and test runs.

savings-formula

Explanation:

  • Time to run a single manual test: Average time taken to execute one test case manually.
  • Time to run the same test in automation: Time it takes to execute the same test automatically.
  • Number of tests: Total number of test cases automated.
  • Number of test runs: Frequency with which the test cases are executed over a given period.

Example: If a manual test takes 30 minutes and its automated counterpart takes 5 minutes, with 200 tests run 20 times:

savings-formula-example

2. Investment

Investment includes all costs associated with setting up and maintaining the automation framework. This includes framework development, test case creation, and ongoing maintenance.

investment-formula

Explanation:

  • Time required to build frameworks: Hours spent setting up the automation infrastructure.
  • Maintenance cost: Cost of updating and fixing scripts for failed tests.
  • Time to code one test: Average time taken to develop an automated test case.
  • Number of tests: Total test cases automated.

Example: If framework setup takes 800 hours, each test takes 3 hours to code, and there are 200 test cases:

investment-formula-example

3. Maintenance cost

Automated scripts need updates when application changes break tests. Maintenance costs cover the effort required to fix these issues.

maintenance-cost-formula

Explanation:

  • Maintenance time for one failed test case: Average time taken to update a failed test script.
    % of failed tests per run: Percentage of tests requiring maintenance per execution cycle.
  • Number of test cases: Total test cases automated.
  • Number of test runs: Frequency of test executions.

Example: If each failed test takes 2 hours to fix, 15% of 200 tests fail per run, and there are 20 test runs:

maintenance-cost-formula-example

Efficiency ROI calculation

1. Automated test script development time:

This formula calculates the total time spent creating automated scripts for the number of test cases in scope. Dividing by 8 converts the total hours into working days, making it easier to estimate the timeline for development.

Formula:

automated-development-time-formula

2. Automated test script execution time:

This measures how much time is spent executing automated scripts over a defined ROI period. Factoring in the number of tests and dividing by 18 accounts for a typical working day, including breaks and productivity variances.

Formula:

automated-execution-time-formula

3. Automated test analysis time:

This calculates the time required to analyze the results of automated tests over the ROI period. It includes identifying failures, debugging, and generating reports, with the formula standardizing this time in workdays.

Formula:

automated-analysis-time-formula

4. Automated test maintenance time:

Maintenance time estimates the effort needed to update automated scripts during the ROI period. Dividing by 8 provides a clear view of how many workdays are allocated to script upkeep.

Formula:

automated-maaintenance-time

5. Manual execution time:

This quantifies the time it would take to execute all test cases manually over the same ROI period, allowing for a direct comparison with automated efforts. Converting total hours into workdays provides an actionable metric.

Formula:

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How to calculate automation ROI in 4 simple steps

Step 1: Calculate savings

This step identifies the time saved by replacing manual tests with automation. The savings formula uses test execution times and the number of tests to estimate the total time saved. This time can translate into reduced costs, as fewer hours are required to perform repetitive tasks.

Step 2: Calculate maintenance costs

Maintenance costs address the time spent fixing broken scripts. This is critical, as automation scripts often need updates when the application evolves. Estimating maintenance costs ensures you account for ongoing efforts beyond initial setup.

Step 3: Calculate total investment

Total investment aggregates all the costs, including initial framework development, test creation, and maintenance. This step provides a comprehensive view of the resources committed to automation.

Step 4: Calculate ROI

Finally, calculate ROI by dividing savings by investment. This step demonstrates whether automation efforts are justified and helps evaluate its long-term impact on efficiency and cost-effectiveness.

Key metrics for measuring automation benefits

To measure the success and impact of test automation, you must track specific metrics that tie directly to ROI. Here are the most critical metrics:

  1. Time saved per test run: This measures the reduction in execution time for automated tests compared to manual ones. It directly correlates with savings.
  2. Defect detection rate: Tracks the number of bugs identified through automation compared to manual testing. A higher rate indicates better coverage and value.
  3. Automation coverage: Measures the percentage of test cases automated. Higher coverage typically results in greater ROI.
  4. Test execution frequency: Evaluates how often automated tests can be run. Frequent runs ensure faster feedback and better issue resolution.
  5. Cost per test case: Tracks the cost of creating and maintaining each automated test case compared to manual tests.
  6. Maintenance costs: Monitors the time and effort spent maintaining scripts. Lower maintenance costs signify a well-structured framework.
  7. Failure rate of tests: Measures how often automated tests fail due to script errors. A lower failure rate indicates higher stability.
  8. Mean time to resolve (MTTR): Tracks the time taken to fix issues detected during automated testing, helping gauge the efficiency of your team.
  9. Infrastructure utilization: Measures how effectively resources like cloud environments or test labs are used for automation.
  10. Return on investment (ROI): The ultimate metric to measure financial and efficiency gains against the costs.

Common mistakes that can impact ROI calculation

ROI calculations can go wrong due to several avoidable mistakes. Here are the most common ones and how to address them:

  • Ignoring maintenance costs: Neglecting to account for the ongoing maintenance of scripts can lead to overestimating ROI. Always factor in maintenance time and effort.
  • Underestimating initial setup costs: Framework setup and tool acquisition are significant investments. Missing these costs skews ROI calculations.
  • Overlooking test flakiness: Flaky tests can cause false positives or negatives, increasing debugging and maintenance costs, which impacts ROI.
  • Inadequate test coverage: Focusing only on automating simple tests may result in low savings and limited benefits. Prioritize high-value and repetitive test cases.
  • Failing to track metrics: Without proper tracking of key metrics, it’s impossible to measure ROI accurately. Use tools that provide detailed analytics and reporting.
  • Not considering scalability: If your framework cannot scale with increasing test cases or changing requirements, your ROI will decrease over time.
  • Poorly designed frameworks: A poorly structured framework can increase maintenance costs and test instability, reducing ROI.
  • Choosing the wrong tools: Using tools that don’t align with your testing needs can lead to inefficiencies and higher costs.
  • Neglecting team training: Lack of training can result in inefficient use of tools and frameworks, reducing the potential savings from automation.
  • Relying too much on automation: Automation is not a one-size-fits-all solution. Over-automating can lead to diminishing returns, especially for test cases requiring human judgment.

Final thoughts

Calculating test automation ROI allows teams to understand the tangible benefits of automation. It highlights how time, costs, and quality gains align with business goals. Avoid common pitfalls, track key metrics, and strategically approach automation to maximize your ROI and ensure long-term success in your software testing processes.

How can Global App Testing help with test automation ROI?

Global App Testing (GAT) offers a robust solution for manual software testing, helping businesses deliver high-quality digital products across industries. By leveraging a crowdsourced testing approach, GAT ensures comprehensive coverage, real-world insights, and actionable feedback, enabling organizations to identify critical issues that automated testing might miss. Here’s how GAT contributes to enhancing software quality through manual testing:

1. Real-world testing across devices and environments

  • Ensuring realistic scenarios: GAT conducts testing on real devices and across diverse environments to replicate how actual users interact with software. From varying screen sizes to operating systems and network conditions, this ensures a realistic assessment of performance and usability.
  • Example in action: For a global e-commerce platform, GAT’s testers validate that the website operates smoothly across desktop and mobile devices, handling regional differences such as language, currency, and localized user behavior.

2. Exploratory Testing to uncover hidden issues

  • Identifying critical bugs: Through exploratory testing, GAT’s testers investigate applications without predefined test scripts, uncovering unexpected bugs, usability challenges, and workflow gaps. This approach complements scripted testing by revealing hidden issues that might escape automated checks.
  • Example in action: For a fintech app, exploratory testing uncovers an issue where specific account settings fail to save when accessed via a particular browser version, ensuring critical flaws are addressed before release.

3. Usability Testing for better User Experience

  • Focusing on human-centered design: GAT provides usability testing services where real testers simulate end-user behavior, evaluating the intuitiveness, accessibility, and ease of use of an application. Feedback from diverse testers helps refine workflows and improve user satisfaction.
  • Example in action: For a travel booking application, GAT’s usability testing identifies that users struggle with multi-city flight searches due to unclear navigation, prompting design improvements that boost customer satisfaction.

gat-usability-testing

4. Comprehensive Functional Testing

  • Validating core features: GAT’s functional testing ensures that every feature of an application works as intended, from basic navigation to complex workflows. By focusing on core functionality, businesses can release software with confidence.
  • Example in action: For a SaaS platform, functional testing verifies that the subscription management system, user dashboards, and file-sharing features operate seamlessly under different user roles and permissions.

5. Compatibility Testing across platforms

  • Ensuring broad Accessibility: GAT tests software on a wide range of devices, browsers, and operating systems to ensure compatibility across platforms. This helps identify and fix issues that could affect performance or user experience.
  • Example in action: For a media streaming service, GAT’s compatibility testing ensures that the video player works without interruptions on iOS, Android, and Windows, regardless of browser or device.

gat-compatibility-testing

6. Regression Testing for stable updates

  • Maintaining reliability post-updates: GAT’s regression testing ensures that recent updates or code changes don’t break existing functionality. By focusing on critical workflows, this type of testing supports seamless deployments.
  • Example in action: For an HR management system, regression testing confirms that introducing a new payroll feature doesn’t disrupt existing attendance tracking and reporting functionalities.

Ready to elevate your software quality with Global App Testing?
Contact us today to learn more about our testing solutions!

We can help you drive software testing as a key initiative aligned to your business goals

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