With increasing pressures on controlling labor costs and tying resources to operational income, automation has been seeing aggressive exploration, especially now that cloud and network software options have become widespread and easily available. An incredible push has been moving forward with the combination of automation and AI, harnessing the computing ability of programming that “learns” from scenarios and automated process performance that can work 24/7 versus in shifts.
However, automation is only as good as how it works, and incorrect designs can create more headaches than expected. Everything from poor accuracy in scanning and reaction processing to incorrect input and output results occurs daily because the design was tested enough before going into production. This is where quality testing matters so much.
Poor Design Can Have Real Impacts
If a process system for forms doesn’t account for variability or human input mistakes, the automation can end up creating more delays as exceptions have to be manually reviewed and cleared. If a medical prescription system makes a mistake in issuing the wrong medicine to a nurse for patient delivery, it can result in serious health reactions or even mortality.
In both mundane and sensitive work processes, untested automation can result in serious mistakes that can cost millions of dollars for the companies using it. There is no corner-cutting when it comes to automation testing. It needs to be done and handled comprehensively to ensure the process is working correctly.
How Quality Assurance Testing Helps
Commonly referred to as QA, quality assurance provides a standardized testing approach that can apply to all types of digital interaction models in automation. Whether evaluating the performance of a new app for mobile devices or a form intake process into a network and database, QA is essential to identify recurring issues and design defects.
Integrated properly, QA can work at every step of project development, ensuring it is ready to move forward based on original expectations and criteria as well as new challenges that are identified in testing. QA works with all types of development processes, too, whether they be agile, waterfall, iterative, or lean. The key benefit continues to be catching concerns early versus having damage control after significant investment has already been made.
QA via automation testing companies can also be applied to the online digital world as well. Websites and portals can be easily evaluated, not just for design standardization but also for traffic performance and complexity. This becomes very applicable when issues of speed, consistent and reliable access, and traffic behavior come into play.
Maintaining a high-traffic-volume site isn’t just about bringing an audience to the digital address; it’s also about finding ways to improve the visiting experience and tweaking areas that are dropping off or not performing well. QA can be applied to all types of web automation platforms, whether it involves an e-commerce basket performance for accuracy or a responsive AI user interface in different programming languages like Python or C++. Whatever the paradigm, QA can be applied to confirm the activity is occurring as desired versus being unknown.
QA also takes the evaluation bar well beyond what is provided with basic site analytics. Many will argue that tools like Google Analytics or similar are more than enough to evaluate a website platform.
While these tools are very useful for raw performance feedback in identifying key SEO-based traffic generation as well as backlinking performance, they don’t tell the whole story, especially with a site using automation. QA goes multiple steps further, focusing on why a site’s behavior is occurring the way it does and how to make changes. The above analytical tools only point where a gap exists, leaving it to the user to figure out the rest. QA completes the picture, providing the actual solution options on a technical basis.
Internal vs. External Testing
While it might be tempting to use internal resources for QA, it can be a mistake. The problem stems from people trying to protect what they have built or looking for ways to create advantages. This ends up pitting internal teams against each other, and it also creates negative office politics that management ends up having to arbitrate.
Instead, with an external QA approach, accusations of influence and subjective testing don’t apply. QA is applied objectively, and the results speak volumes on who or what needs to change outside of internal positions on the matter. Then, management simply needs to decide whether the cost-benefit analysis is worth the change or not.
Parsing between objective metrics and subjective assumptions can be challenging as well.
QA clears up what would otherwise turn into a nasty finger-pointing session between experts and online traffic practitioners on a team. Everyone involved in a hard-working project can speak to their aspect of the development, but sometimes it takes a third-party view that looks at metrics, interprets them without influence, and points out the issues everyone might be missing. QA involves seeing the forest for the trees.
One of the big areas that QA really shines in also applies to compliance. Many times, an operation may be motivated to move a project along by streamlining or ignoring regulatory requirements. This is where QA can point out the risks associated with them and where exactly they are occurring.
Compliance with either external or internal rules and requirements is essential; it’s oftentimes built on real issues that have occurred in the past and need to be avoided. While a current project may not see the value of compliance, the organization could be painfully exposed without its enforcement.
QA resolves the matter by ensuring that compliance is maintained and where modifications need to be made when lacking. This becomes even more important when compliance rules have been updated with recent changes that not everyone is aware of as well.
A Beacon in Operational Fog
If your company or organization needs a firm footing in process quality and current metrics are not delivering a clear picture of what’s going on in real-time, as well as what it means for long-term risk exposure, then it’s time to rely on the expertise of a professional QA evaluation.
Not only does it provide a clear window into current operations, QA automation evaluations cut through operational confusion to point out when vulnerabilities are occurring as well as to what extent. They can be applied easily to traditional software development as well as online platform performance and human behavior scenarios. Stop making strategic decisions in the dark; bring in a QA perspective from the beginning of a project to confirm its viability and delivery to original expectations.
Click here to learn more about applied QA.