Today, with rapidly evolving technologies and IT trends such as the digitalization of business, adoption of agile, DevOps, cloud technology, the blockchain, and IoT, the objectives and expectations of QA and testing are changing.
Products and applications are becoming smarter and futuristic. To create differentiation and maintain a competitive advantage, organizations will have to maneuver their QA and testing journey toward Cognitive Quality Assurance.
Technologies such as artificial intelligence enable testing teams to test faster and lead to an innovative way of testing. The function of QA and testing has evolved from a mere defect finding to being an enabler of customer satisfaction and business outcomes.
According to the World Quality Report 2018 (WQR2018), for the first time ever the top objective of QA and testing strategy is “end-user satisfaction”.
Executive management objectives with QA & testing
Smarter products proliferate the market at record speeds. The robustness of testing these smarter products also needs to be commensurate. Yet another finding from the WQR2018 was the response from 45% of the respondents showing interest in adopting intelligent automation and 35% of the participants showing interest in adopting predictive analytics, descriptive analytics, and predictive dashboard within their testing organization.
Cognitive QA leverages self-learning and analytical technologies via predictive QA dashboards, smart QA analytics, intelligent QA automation. This intelligent approach enables QA and testing teams to deliver quality with speed and at an optimized cost.
The challenges faced by businesses today are not just deciding what to test, but also whether the test cases being used are targeting the right things. Cognitive QA ensures that both manual and automated testing targets the right risk areas. The volume of testing and the required speed of testing can be achieved using Cognitive QA.
Cognitive QA ensures that testing focuses on features and configurations that are influenced by client behavior, customer centricity, and end-user feedback on client needs. Thus CQA concentrates on testing strategy for an enhanced customer experience.
Businesses still rely heavily on manual testing processes, which interferes with their own growth by impeding quality outcomes. Cognitive QA is going to be the next big trend in QA and testing and organizations will have to build their strategies around this.
In my upcoming blogs, we will look at the challenges in implementing analytics for QA, and the benefits of analytics across the product development lifecycle.