QA and Testing Predictions for 2020
Mark Buenen, Head of Global Digital Assurance and Testing, offers his key predictions for Quality Assurance and Testing in 2020.
1. QA focus on customer experience and business outcomes
Today, more than ever, the quality of applications has a direct impact on business performance and customer experience. Depending on the nature of the applications and the ease and speed at which updates can be rolled out, there are huge differences in how the actual level of application quality is validated. This ranges from testing in production (beta releases, crowd testing), to more thorough planned and test &validation stages before deployment. I predict this latter category in particular to see a shift towards more focus on customer experience and understanding of actual user patterns. This is required to better target the validation activities towards the ultimate objectives of any application: increase customer satisfaction and growth of business. Additionally, validation in production and real-time analysis of production patterns will be used to re-direct and improve QA activities during the development stage.
2. Increased speed requires further shift left and smarter testing
Teams will be pushed further to speed up their development activities. As a result, the adoption of Agile and DevOps development models is naturally increasing. We still see that for most teams the speed of QA and test activities is lagging behind. This year’s World Quality Report survey revealed that 48% of participating companies felt the speed of QA and testing activities was too slow. The three main solutions to speed up testing are: shift left of testing to the level of unit testing and API testing; smarter solutions for risk analysis that allow team to reduce the amount of testing without compromising quality; and maximize the level of automation. In 2020 we will see more intelligent solutions in the market that help teams to achieve this.
3. More with less - getting smarter
Quality assurance today still is—to a high degree—a craft executed by development engineers and quality engineers. It even remains a highly manual activity, despite the abundance of automation technologies. In fact, as both the World Quality Report and the Sogeti 2019 Continuous Testing report indicate, the adoption of Agile has had the strange effect of actually decreasing the level of test automation. This is no longer sustainable, and we are seeing an uptake in the use of smart automation solutions across the life cycle.
These smart QA solutions range from requirement design, predictive risk analysis, automated test case generation, and automated test execution to the automated orchestration of all types of testing. To move forward here organizations will need more AI-based skills in areas such as data science, statistical analysis, and in the understanding of cognitive processes. I predict greater use of AI over the next two to three years. We will see automatic QA orchestrators with self-healing and self-learning technologies forming an ever-greater part of quality validation systems, enabling teams to do more with less.
4. Putting a structure in place
When it comes to QA, there is one big dilemma being faced by many organization’s—how to provide a sufficient and customized level of enablement to the autonomous teams through QA guidelines and QA tool platforms, while still leaving them with responsibility and ownership? This dilemma has come about with the adoption of Agile and DevOps. Together, these have ushered in the shift from centrally controlled and industrialized ways of working to smaller, independent autonomous teams. In this environment, quality is everyone’s responsibility. This leaves the autonomous feature teams to decide for themselves how to perform QA and with what tools. As a result, we see a proliferation of test automation tools and a lack of clarity on whether teams are really focusing validation activities on the right topics. Further, product owners lack transparency on quality and, across teams, validation of the end-to-end customer journey is not taken care off.
Thus, taking an enterprise QA perspective is important because it enables teams to work holistically, rather than on an ad hoc project-by-project basis. For 2020, I predict and encourage a stronger focus on orchestrating and upskilling all roles in teams, so that they are better equipped to manage increasingly complex testing activities consistently across the enterprise. Flying squads of QA experts should be part of this landscape, working with teams to help them select the right amount of testing, and the appropriate quality validation approach.