What Are the Best QA Practices Enterprises Can’t Afford to Ignore?

Learn how leading enterprises, including fast-paced digital publishing sector, mission-critical engineering systems, and rapidly evolving public sector digital services, implement effective QA strategies and best QA practices that balance various types of testing at scale.

1. Client QA Practice Analysis

1.1 QA in Mission-Critical Engineering Systems

Overview:

• Nature of the Domain:
  
  Digital Logistic Systems are critical communication tools for transportation coordination across global offices. These solutions operate within the offshore engineering domains, where reliability and precision are essential.


• QA team structure:
  
  The QA function is part of a cross-functional team that includes development, design, product management, and QA. The team collectively defines, builds, tests, and delivers product increments.


• Development lifecycle:
  
  Work is managed within a 2-week Agile sprint framework, prioritizing the delivery of potentially shippable increments for new features or bug fixes.

Testing Practices:

• Emphasis on Reliability & Integration:
  
  
  
  Testing is focused on accuracy, reliability, and system integration. This ensures minimal risk in logistics and material tracking.


• Types of Testing Conducted:
  
  Functional testing, regression testing, exploratory testing, integration testing, acceptance testing, and non-functional testing (including performance and security testing) are all part of the QA process. Testing occurs early and frequently, with structured steps before release: requirements analysis, test strategy preparation, execution, validation and reporting, UAT, and post-release monitoring.

• Automation coverage:
  
  Test automation is in place, but primarily covers basic, repetitive tasks. Complete regression testing remains largely manual, highlighting an opportunity to expand automation for broader coverage and faster cycles.

Team & Compliance Alignment:

• Documentation & Traceability:
  
  QA maintains test plans, test cases, test data, execution reports, and bug reports as core artefacts. These ensure clear traceability of testing efforts, decisions, and outcomes—critical in a regulated engineering context.


• Collaboration with Domain Experts:
  
  The cross-functional team holds daily stand-ups, sprint planning, retrospectives, and demos to align progress and resolve blockers. Involving domain experts ensures business needs are accurately translated into functional and testable requirements.

Conclusion:

• Key Differentiators & Maturity:
  
  This client demonstrates a disciplined and structured QA approach, striking a balance between comprehensive manual testing and selective automation. Strong emphasis is placed on documentation, early involvement of testers, and alignment across teams.


• Takeaways for Enterprise QA in Critical Systems:
  
  
  
  • Structured planning, documentation, and detailed validation are non-negotiable in safety-critical systems.
  
  
  • Automation should be planned from the start and developed alongside manual practices to achieve true QA maturity.
  
  
  • Early tester involvement in planning, design, and development phases prevents issues downstream.
  
  
  • A mature QA process ultimately ensures higher-quality software, reduced costs, faster delivery, and greater customer satisfaction.
  
  
  
  

1.2 QA in Rapidly Evolving Public Sector Digital Services

Overview:

• Type of Digital Services Delivered:
  
  National-scale e-government platform for regulated workforce management, serving as the central platform for companies and government entities to request and manage labor forces from domestic and foreign markets. It is a large-scale e-government solution, supporting highly regulated workflows and national-scale demand.

• Agile QA Team Setup and Client/Vendor Collaboration:
  
  The team is cross-functional, including developers, QA, product owner, and Scrum master. The Scrum framework is followed with 2-week sprints and ceremonies (planning, refinement, estimation, demos, retrospectives). Each sprint, one team member is designated as the point of contact (PoC) to streamline communication with the wider organisation.


• Need for Quick Iteration & Change Management:
  
  Delivery happens in a “big bang” release, WoW, where domains are deployed together after extensive approval cycles. QA needs to plan testing within these constraints, balancing fast iteration in sprints with organisation-wide delivery requirements.

Testing Practices:

• Types of Testing:
  
  Functional, regression, exploratory, API, and non-functional testing are conducted depending on the ticket scope. Developers contribute early with unit tests and code reviews (both FE and BE).


• Tooling & Test Environment Challenges:
  
  Test execution is managed through Jira with integration into TestMo. Documentation, test data, and domain knowledge are maintained in Confluence. Testing occurs across development, staging, and production environments, but QA does not own deployments. Lack of a dedicated QA environment is a recurring challenge.


• Manual vs. Automation Strategy:
  
  Testing is predominantly manual. There is currently no automation in place, but plans exist to start with regression packs. To prepare for automation, test cases are marked as eligible or not for future automation during task validation.

QA Metrics & Continuous Improvement:

• KPIs Used:
  
  
  
  Defects are tracked in Jira by sprints, teams, and product domains. Progress transparency is maintained across teams with clear reporting on defect trends.


• Feedback Loops & Collaboration Patterns:
  
  Daily syncs, planning, refinement, demos, and retrospectives ensure transparency and alignment. QA maintains test cases, test data, and execution logs, ensuring knowledge is preserved and reusable. A QA community of practice exists across domains, with fluid QA resources occasionally rotating (every 3–12 months). This supports knowledge sharing and smooth transitions between domains.

Conclusion:

• How QA Scaled to Meet Public Demand:
  
  QA is embedded in a highly collaborative Agile environment, with structured ceremonies, documentation, and transparent communication ensuring large-scale delivery in a regulated public sector context. Early QA involvement in planning and refinement ensures blockers are caught early, while collaboration with developers provides continuous testing support.


• Takeaways for Fast-Moving Digital Transformation Projects:
  
  
  
  Strong documentation and communication practices are key to scaling QA across large, regulated systems.
  
  
  
  Regression testing remains a pain point. It lacks a clear schedule and often competes with new deployments. Planning dedicated regression cycles and environments is critical. Even without test automation, QA can deliver value if test cases are well documented, regression packs are maintained, and transparency is high. However, automation planning should start early to ensure long-term scalability. A QA community across domains strengthens knowledge continuity and helps organisations scale QA coverage effectively.

1.3 QA in Fast-Paced Digital Publishing Sector

Overview:

• Type of Product/Project:
  
  A custom-built large-scale digital publishing platform serving editorial and mobile-first content needs that enables editors to create and manage articles. It includes both a frontend for article presentation and a mobile app for iOS and Android. Unlike a traditional CMS, this solution is fully developed in-house.


• QA Team Structure:
  
  
  
  A hybrid model combining outsourced QA engineers and in-house staff. The QA team is separate from development and product teams, but supports testing throughout the product lifecycle.


• Development Methodology: Agile methodology, with testing and release cycles adapting to product roadmap priorities and new feature/fix schedules.

Testing Practices:

• Types of testing employed: Manual functional and regression testing. Limited automation is in place (not all areas are yet automated). Regression testing before every release, aligned with the version scope. Frequent regression cycles, typically 2–3 times per week across environments.


• Tools used: No specialised tools, such as Cypress or BrowserStack, are used for automation or similar types of testing. Instead, QA relies on physical devices for testing desktop and mobile solutions. Ticketing and test management are handled in Jira.


• Test Case Management: Test cases are created after each ticket is tested (if they do not already exist), ensuring coverage and building regression packs for future cycles.


• Role of manual vs. automation testing:
  
  
  
  Manual testing is the majority of the workload. Automation exists but still has room to grow.

Team Collaboration & QA Culture:

• Integration with dev teams, DevOps, and product
  
  
  
  QA functions as a standalone group, not directly embedded with development or product. Communication with developers or product owners is ad hoc and on an as-needed basis. QA’s are not integrated into daily standups or continuous synchronization points within the project development teams.


• Communication practices, documentation, and process alignment
  
  
  
  Documentation exists and is used daily, but not all processes and scenarios are fully documented. While test cases are maintained, gaps in coverage exist.

Conclusion:

• Key strengths and lessons: Strong consistency in regression testing. Disciplined approach in test cases creation after the ticket is validated. Ability to cover both web and mobile testing without reliance on external tools.


• Challenges and how they were addressed: Limited integration with development and product teams is partly offset by structured regression cycles and documentation practices.Low automation coverage is compensated for by strong manual test coverage.


• Takeaways for other enterprise QA teams: Even without extensive tooling, QA can deliver significant value with consistent regression cycles and actively maintained documentation. However, scaling QA requires balancing manual and automated testing and improving collaboration with development teams.

2. General Conclusion: Best Practices and Recommendations

Consolidated Lessons:

Looking across our three clients, it’s clear that enterprise QA is never a one-size-fits-all discipline. Each organisation has shaped its QA practices to fit domain needs:

• In safety-critical industries, the structure, documentation, and traceability are the backbone of quality.


• In the public sector, digital transformation requires scale, transparency, and collaboration across large stakeholder groups.


• In a fast-moving digital media environment, the speed, consistency, and disciplined regression cycles keep delivery on track despite limited automation.

What unites them is a common set of principles:

• Early QA involvement in planning and design prevents downstream issues.


• Consistent regression testing, whether manual or automated, safeguards release quality.


• Strong documentation and communication ensure knowledge is retained and shared across teams.


• Automation is a long-term goal, even if manual testing currently carries the load.

For enterprises, the lesson is simple: QA maturity is not defined by tools or automation alone. It’s about adapting practices to the domain, embedding QA into the lifecycle, and fostering a culture of collaboration and accountability.

Done right, QA becomes more than defect detection! It becomes a driver of business resilience, customer trust, and sustainable delivery at scale.

Also, today, AI is in every corner of software development, as it is in Quality Assurance.

Tools like Cursor, Copilot, and specialised solutions from QA tooling companies such as BrowserStack can significantly accelerate test automation, demanding fewer resources than before. Embracing AI solutions early is a strategic move for the future, offering substantial benefits in cost savings and reduced time to market.

Recommended Best Practices:

• Shift-left approach and QA as part of design:
  
  
  
  • Involve QA from the earliest stages of planning and design.
  
  
  • Ensure testers participate in requirement analysis, backlog refinement, and sprint planning to prevent defects before development begins.
  
  
  • Leverage domain experts early to make sure business-critical logic is validated upfront.
  
  
  
  


• Hybrid testing strategy:
  
  
  
  • Balance speed and depth by combining manual exploratory/regression testing with automated smoke/regression packs.
  
  
  • Start automation with high-value, repetitive regression scenarios, while keeping manual testing for complex, evolving, or business-critical workflows.
  
  
  • Evolve the automation scope incrementally to avoid bottlenecks and maintain coverage, especially in fast-paced environments.
  
  
  
  


• Toolchain recommendations:
  
  
  
  • Integrate test automation into CI/CD pipelines for faster release confidence and early defect detection.
  
  
  • Use test management solutions (e.g., Jira + XRay, TestMo, Confluence, or similar) to centralize test cases, results, and traceability.
  
  
  • Invest in cross-device/browser testing tools (e.g., BrowserStack, LambdaTest, Cypress, Playwright, etc.) to scale coverage efficiently beyond physical devices.
  
  
  
  


• QA documentation and knowledge sharing as assets:
  
  
  
  • Treat documentation (test cases, test data, execution logs, glossaries) as a living asset that ensures continuity and accelerates onboarding.
  
  
  • Build communities of practice across domains to strengthen knowledge sharing and reduce silos.
  
  
  • Keep regression packs up to date after every release cycle to ensure repeatability and reduce risk.
  
  
  
  

• Aligning with compliance when necessary:
  
  
  
  • For regulated industries, maintain structured documentation and traceability aligned with compliance standards.
  
  
  • Encourage QA team members to adopt ISTQB-aligned practices for consistency in test design, execution, and reporting.
  
  
  • Where applicable, map QA processes to organizational or industry standards (ISO 9001, ISO/IEC 25010) to meet both regulatory and customer expectations.
  
  
  
  

Supporting Sources and References:

• Industry white-papers or studies (e.g., Capgemini World Quality Report):
  
  
  
  • Capgemini World Quality Report – annual insights into global QA and testing practices, trends, and challenges.
  
  
  • Gartner Research on Agile and DevOps QA – recommendations on evolving QA roles in enterprise transformations.
  
  
  • State of DevOps Report (by DORA/Google Cloud) – data-driven guidance on testing, automation, and CI/CD maturity.
  
  
  
  


• Internal QA maturity models or frameworks to search for:
  
  
  
  • QA Excellence Maturity Model – an internal agency framework for evaluating enterprise QA maturity across people, process, and tooling.
  
  
  • Agile Test Quadrants framework – categorising testing practices across functional, non-functional, manual, and automated layers.
  
  
  • Test Automation Pyramid (Mike Cohn) – prioritising automation layers (unit, integration, UI) to guide sustainable automation.
  
  
  
  


• Certifications and standards:
  
  
  
  • ISTQB Advanced / Agile Extension – structured knowledge base for advanced test design, automation, and Agile integration.
  
  
  • ISO/IEC 29119 – internationally recognised standard for software testing processes, documentation, and lifecycle management.
  
  
  • IEEE 829 & IEEE 1012 – standards for test documentation and software verification/validation processes.
  
  
  • ISO/IEC 25010 – quality model for software and system product evaluation, often referenced in enterprise QA.
  
  
  
  


• Relevant blog posts, tech talks, or documentation for deeper reading:
  
  
  
  • Ministry of Testing – articles, courses, and community discussions on enterprise QA, test automation, and scaling practices.
  
  
  • ThoughtWorks Technology Radar – emerging tools and practices in test automation and CI/CD.
  
  
  • Google Testing Blog – practical insights on testing at scale in large engineering organisations.
  
  
  • Martin Fowler’s blog – resources on continuous delivery, test automation strategy, and system reliability.
  
  
  
  

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