World Quality Report is back for its 15th edition! The only global report of its kind analyzes the latest in quality engineering and software testing trends.
OpenText has teamed up with Capgemini™ and Sogeti™ to conduct the global survey (see the recent press release). This year, we interviewed 1,750 executives and professionals across 8 sectors from 40 countries.
Read the report to see the key recommendations for each of these areas. The complete report and country pullouts are available here.
Two new areas with potential impact
One of the key trends that emerged from this year’s World Quality Report is the importance of artificial intelligence. In addition, automation is increasing in popularity. A lot of organizations have moved to an execution phase with clearly defined goals and timelines. Let’s take a closer look at these two emerging trends:
- Artificial intelligence (AI): The application of generative AI is poised to be a game-changer in quality engineering and fundamentally redefining the art of the possible.
- Automation: While quality automation is certainly on the rise, organizations still face critical challenges.
Key statistics and recommendations
Business assurance: 56% of organizations are aligning strategic business goals, products, and value streams.
- Elevate the testing function to deliver the best business outcome and enable shift in the organization’s culture and mindset.
- Augment business assurance by value stream mapping and aligning processes with customer objectives for improved business results and long-term success.
- Boost business performance by embracing change and fostering a culture of continuous improvement.
Agile quality management: Many organizations are evolving their traditional quality engineers into full-stack quality engineers.
- Organizations must adopt a build-or-buy mentality—either by looking for new talent in the market or upskilling their current workforce to meet the evolving demands of the business.
- Forging a seamless integration with DevOps/DevSecOps practices through close collaborations can ensure smooth incorporation of quality engineering assets into CI/CD pipelines.
- Establish lightweight capability units for test process and governance, test automation, performance engineering, test data management, and test environment management to establish enterprise frameworks and tooling platforms.
Quality engineering lifecycle automation: Delivering good systems with quality is a priority and has to be done in a timely manner.
- Automation can be prioritized against legacy systems.
- Upskill teams to use AI and test AI systems.
- Consider creating an automation marketplace for other teams to pick up and re-use the automation assets developed by the quality expert team (QET).
AI, the future of quality engineering: 77% of organizations today consistently invest in AI and utilize it to optimize quality assurance processes.
- Higher productivity driven by AI will rapidly increase the velocity of development and organizations should continue the investment.
- Implementation of use cases will require careful thought and analysis for prioritization along with unambiguous KPIs measuring tangible outputs.
- An iterative approach towards chosen use cases along with an MVP approach as there is going to be considerable experimentation around AI solutions in the near future.
Quality ecosystem: 71% of organizations prefer cloud-native tooling to perform cloud testing.
- Accelerate the inclusion of cloud and infrastructure testing as part of the software development lifecycle.
- Continue to consider intelligent integrations (including customizing specific features).
- Adopt stringent practices to test the impact of failure events in the cloud and continue to give extremely high priority to the performance and resiliency of applications in the cloud.
- Embrace and support the emerging trends (e.g., chaos engineering) in digital and cloud migration strategies.
Digital core reliability: 35% of organizations have their business users testing digital core solutions to ensure end-to-end quality.
- Find newer approaches such as test isolation, contract testing, etc. to drive more automated test execution.
- Utilize service virtualization to overcome challenges around multiple applications, environments, and data dependencies.
- Quality assurance teams of the future will need to have a mix of skills.
Intelligent product testing: 46% of respondents consider root cause analysis to be of high priority which denotes a shift to the left and a willingness to use test results.
- Invest in AI solutions for test prioritization and test case selection to drive maximum value from intelligent testing against the millions of possible combinations.
- Focus on an end-to-end testing approach to ensure seamless customer experience through effective utilization of abstraction of various architecture layers.
- Give equal priority to the non-functional aspects (performance, security, etc.) of the system as the functional aspects as they equally influence the end-user experience.
Quality and sustainability: 97% felt quality engineering was active or continually active in driving the sustainability agenda in their organizations.
- Have a set of key KPIs or metrics that can be easily understood across the organization.
- KPIs need to be considered not just in quality engineering and testing but through requirements gathering, production support, and working with external vendors.
- Sustainability needs to be part of the whole lifecycle.
- Know your green success factors and ensure they are part of your strategy.
For an in-depth evaluation of this year’s trends, findings, and recommendations, download the report today!
