Test Automation Strategy: A Step-by-Step Guideline for Your Team

The Purpose of a Test Automation Strategy

We’ll begin with a road trip. You pack everything you need. Pick the motels you’ll rest at. Choose the landmarks you want to visit. Plan your route according to the weather and traffic. And enjoy your relaxing drive where everything is structured and organized.

This scenario answers the question, “What is a test automation strategy?” It outlines:

• What you want to achieve with automation.
• What parts of your application will be automated.
• What resources you’ll need, etc.

It serves as a blueprint for what and how your automated software testing services will be doing. It also accounts for SDLC risks and unexpected scenarios. So, if anything goes awry, you don’t scream and panic but initiate your well-thought-out recovery.

Ultimately, a testing automation strategy is assurance. Assurance of getting your money’s worth from automated testing (AT).

Focused Automation Efforts

A strategy helps you prioritize which tests to automate. And instead of automating too much, too little, or at random, you work on areas of your product that get the biggest bang for your buck. In other words, you don’t waste time and resources automating tests that might not provide significant value.

Clear Roadmap & Direction

The purpose of a software test automation strategy is to outline the steps involved in implementing and maintaining AT. It defines the tools, technologies, and processes you’ll use. It gives a clear direction for your testing team. In turn, you avoid confusion and give your crews a tangible, common goal they’re to work on.

Refined Maintainability

Automated tests can become brittle and difficult to maintain over time. But among the core principles of an enterprise test automation strategy is accounting for the future. This means that a proper strategy prompts building reusable test components and using frameworks that promote maintainability. As a result, updating and upgrading tests becomes easier, saving time and effort in the long run.

Integration with the Development Process

If you create a high-quality strategy, integrating it into your development process will be much simpler. Why is that a noteworthy aspect? Because it enhances your efforts. For example, you might set up automated triggers to run tests after code changes. Or you can integrate AT with continuous integration (CI) pipelines.

When automated testing becomes an authentic part of your SDLC, it doesn’t disrupt any existing workflows or team duties. It functions as an extra cog in your marvelous dev mechanism, giving it an extra boost. Essentially, with a test automation strategy, AT carries out its duties without any “surprises” for your QA engineers or project quality.

Supported Scalability & Growth

As your application grows, its complexity is sure to increase. This means that you might need to update existing automated tests, create new ones, or even scrap those that are lacking. A well-defined strategy allows you to scale your test automation efforts in a targeted manner. It also allows you to be proactive by considering how to handle new features and functionalities from the get-go.

Some might think a test strategy for automation testing is just a glorified step-by-step instruction. Well, you don’t have to worry about them as competitors then. Remember, information is power. And a test automation strategy is exhaustive information on how you’re going to enrich your business with AT.

Exploring the Journey to Smart Test Automation

Things That Can Go Wrong without a Strategy

Let’s flip the coin. What exactly do you risk by not having an automation testing strategy? Turning your SDLC more chaotic, perhaps? Not quite. But you might just lose:

• Money.
• People.
• Reputation.
• Credibility.
• Your sanity.

That’s not an artistic exaggeration. It’s simply what might happen when the impact of a haphazard strategy accumulates.

Wasted Time & Effort

Without adequate test case prioritization, you’ll most likely automate instinctively, so to speak. Knowing the benefits AT offers, you’ll want to center on scenarios that are complicated (to ensure their accurate execution) or simple (to save your team’s time). Or you just might decide to automate everything in sight.

In reality, you’re just going to end up with low-value or high-maintenance tests, such as those that:

• Focus on highly unlikely user behaviors or extreme data inputs that have minimal impact on core functionalities.
• Simply verify the color of UI elements (buttons, text, etc.).
• Cover the same functionality via overlapping elements.
• Require constant updates and maintenance to keep functioning properly.
• Have intricate logic or decision-making processes behind them.

The result? A bunch of basically useless automated tests, effort that didn’t lead to anything, a confused team, and no real plan on how to get out of this mess.

Brittle & Unreliable Tests

When you don’t evaluate how AT impacts the testing process (and vice versa), you’re likely to get misaligned test cases. That is, they don’t contribute much, they don’t account for your project’s evolution, and have no definitive goal. Simply put, the tests can become fragile and break easily with code changes. This can lead to false positives and a loss of confidence in the entire test suite.

Incomplete Test Coverage

With software testing services, you always want to focus on crucial product areas. Because you want them to work flawlessly. They are the core of your app. Without a pre-analysis of your project, you won’t know what aspects are key, which of them might be better off with manual software testing, and how to valuably automate what you need.

So, not only will you be applying automation where it’s pointless or even harmful, you also can miss lots of bugs with an unfitting AT strategy.

Integration Issues

Without a test automation strategy, you won’t be able to integrate AT into your development workflows. For example:

• Automated tests might run at scheduled intervals that don’t align with development cycles.
• If tests only run periodically, there’s a window of opportunity for bugs to be introduced.
• If a large number of tests are run at once without proper planning, it can overload build servers or CI pipelines.
• Developers might not be aware of when or how automated tests are run, leading to confusion and frustration.

Briefly, you get stuck between your regular development and automation that seems to be its own thing. The two don’t support each other, existing as separate processes with no overlapping worth.

Scalability Challenges

When you want to introduce new features or see your user base skyrocket, you need to adapt quite a few things. So, let’s return for a moment to the above scenario. Your AT is detached from your SDLC. It does something, but you’re not very sure what. You know that when your project grows, automation is likely to spread out, too. But how do you scale your test automation if there’s essentially no understanding of its place in your project?

You pretty much have this AT appendage dangling from the SDLC. You need to do something with it – yet what exactly? See, the point is that, yes, you’re bound to have a cumbersome and inefficient test suite that struggles to keep up with the pace of development. But the sheer amount of confusion and doubt you’ll get from the absence of an automation testing strategy overshadows every other concern.

Unrealistic Expectations

Without a clear understanding of the goals and limitations of automation, you might expect too much. Or, even worse, not capitalize on the extent of AT advantages. This can lead to disappointment and a reluctance to continue investing in test automation. And in today’s IT industry, that’s almost always a loss.

Skills Gap

Implementing and maintaining productive AT requires specific skills and knowledge. Automation testing specialists need to:

• Be proficient at all elements of software development.
• Have fine programming skills.
• Understand AT methodologies and frameworks, etc.

Even if you opt for codeless automated testing, you need a base for it. You need someone who’ll set it up, adapt it to your project, and make it actually work for you. Without a plan for training and development, you might struggle to find or cultivate the necessary professionals within the testing team. Finding talent in the market right now is a task to behold.

To summarize, it’s better to invest some time and effort into creating a custom automation testing strategy than try and survive everything that comes crumbling down when you don’t have it.

QA Automation as a Key to Avoid Problems with Software in Production

How to Create a Test Automation Strategy

Let’s take our step-by-step guide on cultivating your AT a step further. What precisely would you need to include in your strategy? Here’s a breakdown of each component.

Define Your Goals & Objectives

1. Clearly define the overall goals you aim to achieve with test automation. This might involve improving test coverage, reducing manual testing efforts, or catching bugs earlier in the development lifecycle.
2. Specify measurable objectives that track your progress towards those goals. For example, aiming to automate 70% of regression tests or reducing manual testing time by 50%.
3. Do the same if you want to automate a specific type of testing. If you have a regression test automation strategy, align your targets with its potential effects (like achieving faster feedback loops).

Establish the Scope & Selection Criteria

1. Define the scope of your test automation efforts. This might involve focusing on specific functionalities, critical user journeys, or high-risk areas of the application.
2. Establish clear criteria for selecting which test cases to automate. Prioritize tests based on factors like frequency of execution, impact on functionality, and complexity of manual testing.
3. Pay attention to your application category. For instance, a mobile test automation strategy would mean focusing on compatibility testing, mobile-specific aspects, like touch interactions and network connectivity, etc.

Select Proper Tools & Technologies

1. Identify the specific tools and frameworks you’ll use for test automation. Be sure to select a testing framework (e.g., Selenium, Cypress), a test management tool (e.g., TestRail, Jira), and any scripting languages needed (e.g., Python, Java).
2. Justify your choices based on factors like compatibility with your application and development environment, team expertise, and desired functionalities.

Prepare the Test Environment Setup & Configuration

1. Define the requirements for setting up and maintaining a stable test environment for running automated tests. Specify the necessary hardware, software, and network configurations.
2. Outline procedures for managing test data and ensuring data consistency across test runs.

Refine Your Test Design & Development Practices

1. Establish best practices for designing and developing effective automated test cases. You might choose to promote modular test components, use a Page Object Model (POM) for UI automation, and write well-documented and maintainable test scripts.
2. Implement error handling and recovery mechanisms within your automated tests. This will ensure that tests can continue execution even if they encounter unexpected errors during the test run.

Integrate AT with the Development Workflow

1. Define how automated tests will be integrated into your existing development workflow. This might involve integrating with continuous integration (CI) pipelines for automatic test execution after code changes.
2. Outline communication protocols between QA and developers regarding test execution schedules, results reporting, and handling failing tests.

Have a Maintenance & Update Strategy

1. Establish a plan for maintaining and updating your automated test suite as the application evolves. This includes procedures for addressing test failures, refactoring code as needed, and keeping pace with new functionalities.
2. Regularly review and update automated tests to ensure they remain aligned with the latest application functionalities and requirements.

Keep Monitoring & Reporting

1. Define how you’ll monitor the performance and effectiveness of your automated tests. This might involve tracking test execution times, pass/fail rates, and identifying trends in bug detection.
2. Establish clear reporting mechanisms to communicate test results to stakeholders, including developers, product managers, and other team members.

Gather the Right Skills & Encourage Training

1. Assess the existing skills and knowledge within your testing team regarding test automation.
2. Define a plan for training and development to ensure your team has the necessary expertise to implement, maintain, and enhance the test automation strategy.

Consider Your Budget & Resources

1. Estimate the budget required to implement and maintain your test automation strategy. Include costs for tools, training, and potential hardware upgrades for the test environment.
2. Clearly define the resources needed for ongoing test automation efforts, including dedicated personnel and time allocation.

You can also add some helpful details like:

• Glossary of terms used in the document.
• Detailed test automation framework configuration steps.
• Sample test scripts or code snippets.

And remember that your automation testing strategy isn’t a stale document. It’s a living file that needs care in the form of amendments, updates, and upgrades. It should evolve with your project and business changes to be as productive as you need it to be.

Test Automation Strategy PDF

Types of Automated Testing to Include in Your Strategy

Now, when it comes to including tasks in your testing automation strategy, allow us to simplify the selection process for you. First, we’ll review the baseline. These are the testing types companies automate most often as they provide the largest chunk of value and don’t require too many resources.

Second, we’ll provide you with a brief guide on how to pick tests for your AT efforts. And, of course, we sought wisdom nuggets from our QA engineers here. As we wish to present you with only actionable tips.

Testing Types that Are Frequently Automated

So, here are the nearly-always first automation candidates.

Regression Testing

Regression testing means running the same set of tests after code changes to ensure existing functionalities work fine. Automation here is ideal because:

• It’s repetitive and time-consuming to perform manually.
• Automated regression tests can be run frequently with every code change, catching regressions early.
• They free up QA engineers to focus on more exploratory or complex testing scenarios.

Smoke Testing

Smoke testing involves basic tests to ensure core features run properly after a new build or deployment.

• It’s a quick way to get a high-level health check of the application.
• Automated smoke tests can be run before more extensive testing to identify critical issues early in the development cycle.
• They are relatively simple to automate and require minimal maintenance.

API Testing

API testing verifies the functionality, performance, and security of Application Programming Interfaces (APIs). They are like communication protocols for your product. Basically, they dictate how an app is to interact with other components or external systems. Automation is a good fit because:

• APIs can be complex and have many endpoints to test.
• Automated API tests can be run frequently and integrated into CI pipelines.
• They are less prone to human error compared to manual API testing.

Unit Testing

Unit testing focuses on securing the functionality of individual units of code (functions, classes).

• Unit tests are typically small and well-defined, making them easy to automate.
• They can be run frequently during development to identify and fix bugs early on.
• Automated unit tests provide developers with immediate feedback on code changes.

Performance Testing

Performance testing measures an application’s response times, stability, and resource usage under load.

• Performance tests are often complex and require simulating high user volumes.
• Automated tools can efficiently generate loads and analyze performance metrics.
• They can create complex load scenarios with diverse data patterns, providing more comprehensive coverage.

Integration Testing

Automated integration testing focuses on verifying how different components of your application interact and exchange data with each other. It ensures that the overall system functions as intended when individual parts are combined.

• Manually testing interactions between multiple components can be time-consuming.
• Automation tools can efficiently manage mocking and stubbing.
• Some AT frameworks allow parallel execution of integration tests, significantly speeding up the process.

Of course, you can always go the extra mile and automate more complex tests. For instance, you can make use of automated accessibility testing. It’s less common due to its intricacy. But for large projects or those that target lots of markets at once, it can be a good investment.

Website Accessibility Testing Checklist Your Team Should Know by Heart

How to Select Test Cases for Automation

Overall, you should tread lightly when trying to automate scenarios that require human judgment or are quite difficult to streamline, like usability and security testing. But you can still use tools to simplify such tricky tasks. For instance, you can use user journey tracking or vulnerability scanners to pinpoint basic issues.

Yet, generally, a test that’s a perfect candidate for automation is the one that:

• Has a well-defined set of steps with clear and unambiguous expected results. This makes it easier to translate the test logic into automated scripts.
• Focuses on functionalities that are unlikely to change frequently. Frequent modifications to the test would require constant updates to the automation scripts, reducing the benefit of automation.
• Runs often, such as regression testing or smoke testing, are good candidates for automation. Automating these repetitive tests saves time and effort for QA specialists.
• Is complex or involves many steps to execute manually, so automating it can significantly improve efficiency.
• Involves well-defined user actions like clicking buttons, filling forms, or navigating menus. These actions can be easily replicated through automation scripts.
• Functions reliably in a consistent testing environment. Frequent changes to the environment can cause automated tests to fail unexpectedly.

Plus, you should pay attention to other aspects that can impact your decision on what to automate.

• Maintainability. The long-term cost of maintaining the automated test should be weighed against the benefits. Complex tests might require significant effort to keep the automation scripts updated.
• Test value. Prioritize automating tests that provide high value and uncover critical bugs. Less critical tests might not justify the automation effort.
• Availability of tools. Ensure there are suitable automation tools available to automate the specific type of testing you have in mind.

But these are just some characteristics to look out for. The question is – what’s the process behind your selection?

Gather Information & Define Goals

Collaborate with developers, QA engineers, and product managers to understand their perspectives on testing needs and desired outcomes from automation. Based on these discussions, define the overall goals you aim to achieve with test automation. Or you can reverse engineer it and look for the perks automating a certain test offers.

Identify Areas for Automation

Work with the testing team to identify core functionalities, critical user journeys, and high-risk areas that are essential to automate for comprehensive coverage. Look for functionalities that are stable and less prone to modifications.

Evaluate Test Case Suitability

Establish clear criteria for selecting test cases. Center on factors like:

• How often do you need a test to run?
• How long does a test take to finish?
• How difficult would it be to automate a test?
• How does automating a test impact other functionality? Does it at all?
• How taxing would it be to maintain a test in the long term?

Review Existing Test Cases

Evaluate your existing test suite and identify manual tests that align with the selection criteria mentioned above.

Prioritize Test Cases for Automation

Consider the value a test case brings to your app’s quality versus the effort required to automate it. Prioritize tests that deliver high value with manageable automation efforts. Aim for a balanced approach that automates tests across different functionalities and user journeys to achieve comprehensive coverage.

Document Your Choices

Document the test cases selected for automation, along with the rationale behind each selection. This plan serves as a reference point for your team and helps track progress.
If this seems a bit complicated or worrisome to you – it’s okay. After all, while this guide offers you lots of insights on a test automation strategy, it can’t give you a full, real-life picture of how things go.

So, to save your nerves and secure triumph, don’t hesitate to work with external expertise, like QA outsource. They’ll be your objective perspective on the state of your product. And their ample knowledge will help you pick tests that will offer the greatest value for your app’s success.

The Challenges of Creating Automated Test Scripts (And Ways to Overcome Them)

The Role of AI in Test Automation Strategy

We anticipate what you might be thinking at that point. What about AI? It can help you create and implement an automation testing strategy. And AI-based tools can be great performance boosters for the team.

What AI Can Do For A Test Automation Strategy

It would be smart of you to consider artificial intelligence here. But you do need to be fully aware of the strengths and weaknesses of AI for this task.

AI-Powered Test Case Analysis & Prioritization

• AI can analyze your existing test suite and highlight test cases that qualify for automation.
• It can review historical test results, user behavior data, and application complexity to assess potential risk areas.

Intelligent Test Case Generation & Maintenance

• Algorithms can investigate user interactions, app logic, and data flows to generate new automated test cases.
• AI-powered automation tools can learn the intent behind a test and adapt to minor UI changes.

AI-Driven Test Data Management

• Some models can examine existing data patterns and user behavior to create more realistic test data for automated tests.
• They can closely mimic real-world usage scenarios and catch issues that generic test data might miss.

Streamlining Test Execution & Reporting

• AI can analyze past test results and risk assessments to intelligently select which automated tests to run first.
• It can also study test results and logs to provide more detailed and informative defect reports.

Where AI Might Be Lacking

These AI uses might just hit your sweet spot. But here’s a spoon of something bitter.

Data Dependence

• The effectiveness of AI relies heavily on the quality and quantity of data it’s trained on. Insufficient data can lead to inaccurate test case recommendations, prioritization, or even biased results.
• As your application evolves, the underlying data used to train the AI might become outdated. And regularly refreshing your training data to ensure AI recommendations remain relevant and accurate is another strain for your team and budget.

Decision-Making & Explainability

• AI tools can struggle with complex decision-making processes often required in exploratory testing or handling unexpected behavior. They might not be able to adapt to situations outside the data they’ve been trained on.
• Understanding how AI arrives at certain test generation or prioritization decisions can be challenging. Lack of transparency can make it difficult to trust AI recommendations and limit human oversight and control over the automation strategy.

Focus & Adaptability

• AI can create a tendency to over-automate tests, neglecting the importance of human expertise.
• Models trained for a specific application or functionality might not generalize well to other parts of the system. You might need to develop separate AI models for different testing needs.

Other Limitations

• Implementing and maintaining AI-powered test automation tools can involve additional costs for infrastructure, training data, and potentially specialized personnel.
• Biases present in the training data can be reflected in AI recommendations. Careful data selection and monitoring will be ongoing and will be an effortful process.

To sum it up, be mindful of how and why you use AI for your project. Don’t go for it with only expecting the best or hoping for an easy win. Cultivating and maintaining your AI models and tools is also a lot of work. So, focus on these three tips:

• Identify areas with the highest potential benefit from AI. Create a proof of concept for why it would work there. And secure a tangible plan for how your team will be utilizing it.
• Ensure you have a solid data foundation for your AI tools to function optimally. Make sure to have skilled specialists on the crew who can consistently advance and polish your solutions.
• AI is a powerful tool. But it shouldn’t replace human expertise entirely. QA engineers should view AI recommendations as support but prioritize their own knowledge and judgment to create a well-rounded test automation strategy.

We’ve discussed the subject of AI-based tools in software testing services at length in one of our previous articles. And if you want to know more, be sure to check the link below.

The Lies and Truths of AI Automation Testing Tools

Challenges & Pitfalls AT Teams Often Face

To get you well-armed for your automation adventure, you should also know the “enemies” you might face along the way. Specifically, we’ll discuss the difficulties that may affect your AT venture.

Misunderstanding Automation’s Role

If you rely solely on automated tests, you miss out on the valuable perspective of human specialists. Automated tests can’t identify unexpected behavior or usability issues that users might encounter. This can lead to bugs slipping through testing and causing problems for real users, damaging the business’ reputation and potentially leading to lost revenue.

Selecting the Wrong Tools

Choosing a complex tool that your team struggles to use can grind the testing process to a halt. This delays bug detection and fixes, which can push back release dates and frustrate customers waiting for new features. Additionally, wasted time spent on an unsuitable tool reduces overall team efficiency.

Maintaining Test Scripts

Brittle tests that break easily with minor code changes force QA engineers to spend more time fixing scripts than actually testing new functionality. This slows down the entire testing cycle and can lead to missed deadlines. Unreliable tests also create a false sense of security, potentially allowing bugs to go unnoticed.

Focusing on Code Coverage Over Quality

A high code coverage percentage might look good on paper, but it doesn’t guarantee a well-tested product. Focusing on covering every line of code can lead to creating a large suite of shallow tests that don’t target critical functionalities. This misses important areas and exposes the business to potential risks.

Skimping on Test Data Management

If your teams don’t have the right data to run tests properly, they can produce inaccurate or misleading results. This can lead to wasting time chasing down phantom bugs or missing real problems entirely. Inconsistent or unreliable test data can cause delays and create uncertainty in the testing process.

Ignoring Non-Functional Needs

Automation excels at functional testing, the nitty-gritty of whether specific features work as intended. But it has limitations when it comes to the broader user experience. For example, automation can’t tell you how user-friendly the software is or if the interface is intuitive.

These aspects require a human touch. They need someone who can assess usability and identify areas that are confusing or frustrating for real users. By neglecting these non-functional needs during testing, you risk deploying software that, while functionally sound, is clunky or difficult to use, ultimately hurting customer satisfaction and the business.

It’s great to be able to learn from others’ mistakes. So, let’s take a moment to thank all the pioneering specialists. Because of the hard work and innovation of QA experts and developers, we now, essentially, have an optimized roadmap to a fine project.

Be sure to take the above issues into account and include “safety measures” in your test automation strategy to minimize the occurrence and impact of potential mishaps.

• Balance automation and manual testing. Don’t separate them into different processes.
• Choose tools that fit your team’s skills and project needs.
• Prioritize maintainable tests and detail them unfailingly.
• Focus on test value, not coverage. Spotlight cases that target critical functionalities and user journeys.
• Invest in test data management to ensure your tests have the information they need to run effectively.
• Complement automation with manual usability testing to secure impeccable UX.

Tips for a Fruitful Test Automation Strategy

To finish up, allow us to share a few tips that our team has gathered over the years. These insights, though seemingly simple, have the greatest impact on your test automation strategy. So, don’t take the following aspects lightly.

It’s All About Your Vision – Stabilize It

Setting goals might bring you back to writing yet another school paper. But these “generic” bits will define your entire approach to the automation testing strategy.

For instance, if you wanted to automate your regression testing, you’d need to:

1. Identify regression test cases that fit AT efforts.
2. Select a test automation framework that aligns with your team’s skillset and the technologies used in your app.
3. Develop and maintain automated tests.
4. Integrate with CI/CD pipeline for automatic execution after code changes.
5. Secure a robust data management strategy.

Yet, if you, say, wanted to cut your manual testing by 20%, then you’d need to:

1. Define areas where manual testing is most time-consuming and repetitive.
2. Center on automating tests that cover core functionalities and user journeys.
3. Invest in automation skills if your team lacks experience with automation frameworks.
4. Make sure that this manual QA reduction won’t downgrade the product.

You see, the target is the same – to implement automation. The goal, however, that’s what dictates how you’ll go about everything. So, make sure your expectations for automated testing are crystal clear.

Tool Selection Matters More Than You Think – Pick Them Right

We tend to perceive tools as mere helpers. We get one or a few of them and enjoy a simpler workflow. But the reality is far from this idealistic version.

• If you pick tools that your team has no experience with, everyone will focus on learning them rather than testing.
• If you choose tools that are difficult to operate, your team will be continuously anxious, and your SDLC will crawl like a snail.
• If you go for the “best tools on the market” that don’t really cover your needs, you’ll get absolutely no value from them.

The truth is, you’re likely to spend quite some time on tool selection. It’s necessary because it’s worth it. So, prioritize options that:

1. Fit your team’s skills and work style.
2. Have a steep learning curve.
3. Are easy to grasp and use daily.
4. Deliver what your project requires in terms of features and scalability.

Quality over Quantity – Make It Your Motto

Imagine you have a large net with just a few sizable holes. The net does cover a decent area. But the large (and some small) fish will be able to escape. That’s what focusing on high-percentage test coverage might do to your project – letting in large (and some small) bugs.

It’s better to create narrow tests that target the big game:

• Major issues.
• Most valuable user journeys.
• Error-prone elements.
• Core features, etc.

Overall, create tests that genuinely improve your product. And avoid spawning a ton of them for the false sense of security with high percentage numbers.

Automation Is a Marathon – Keep It Thriving

Don’t expect to set up AT once and let it do its magic. With advancements in AI, this may be possible in the future. Alas, for now, a test automation strategy needs care to keep delivering value to you.

So, make sure your automation suite is incessantly productive by:

• Scheduling regular maintenance to review tests for flaky behavior.
• Updating them to keep up with the code changes.
• Refactoring cases to sustain their efficiency.

You should also:

• Implement tools to monitor the health and performance of your automated tests. Track metrics like execution time, pass/fail rates, and identify trends that might indicate issues.
• Link your test automation suite with your CI/CD pipeline. This will solidify it as a core value driver for the project and double AT’s benefits.
• Encourage your team to actively identify areas for improvement. For example, they could automate new tests, explore alternative tools and frameworks, or optimize existing scripts.

Your Team Is Everything – Cultivate Your Experts

You might have a perfect test automation strategy on paper. But its execution entirely depends on your team. So, before you commence the active phase of automation, make sure you have suitable experts on board.

1. Begin by evaluating your team’s current skill set. Pay attention to their knowledge of testing methodologies, scripting languages, and automation tools.
2. Invest in training programs or workshops to equip your team with the necessary skills.
3. Pair experienced QA engineers with those new to automation to foster knowledge transfer and accelerate learning.
4. Organize internal workshops or knowledge-sharing sessions where team members can present their learnings and best practices.
5. Cultivate a culture that encourages continuous learning and exploration. Provide resources like access to online forums, documentation, and industry publications to keep your team updated.
6. Bridge the gap between QA and developers. Encourage open communication and collaboration to ensure a smooth integration of automation into the development lifecycle.
7. Consider pairing QA experts with developers during the early stages of test design to ensure automation feasibility.

In the end, you’ll have a legion of experienced professionals, people who are thankful and dedicated to your project, and the opportunity to build an extraordinary product.

But, of course, if you don’t have the time or resources to create a team, you can always look into external expertise. Outsourced QA is now a staple in software development. It has:

• Readily available specialists for every need.
• Customizable cooperation models.
• Refined team management skills and more.

Plus, hiring experts is often cheaper and much faster than forming your own. It’s only a matter of what you can do with what you have. So, don’t feel pressured into either option. Both in-house and external QA engineers will do their job well. You only have to look at your situation realistically and decide what would give it a bigger advantage.

Working with Dedicated QA Teams: Answering Your Whys & Hows

To Sum Up

You know how people say, “The true destination is the journey”? That’s very much true for automation. The final stop is evident – AT will either work out or not. So, it’s, in fact, the path that matters more: how you approach automated testing will decide where it leads.

We hope that with this guide both your AT journey and destination will lead to greatness. And if you need some help with setting your automation train on the right track – we’re always here.