Were you the lucky one during Amazon sale “Prime Day”?

Time and again we have seen instances where the quality of an application is compromised leading to challenges, customer escalations and financial loss to organizations. A similar incident happened recently with Amazon during their annual prime day in the US where consumers were able to buy camera equipment’s worth $13,000 for $94.Such a huge difference wasn’t an expected discount offered but was a software glitch. We have seen similar incidents with few airlines as well recently where a software bug allowed users to get a long-haul first-class ticket for $1.

In today’s world, a user is constantly accessing applications through multiple media devices and expect to have similar user experience on all of them. Still, we hear a lot of technology teams questioning the need of QA in their teams. The common myth is that QA is not a specialized function like development, data science or even DevOps and anyone in the team can learn it and deliver.

The quality of the application is very crucial in giving a better user experience to end-users. In the rapidly changing technology world, we need a mechanism where we can automate certain tasks and reduce human effort. Automation methodology has brought huge benefits in terms of reducing overall time to test and perform repetitive test executions with more data combinations.

But automation has its own challenges with concerns around its stability, usability, cost of tolls, and maintenance. Also, one can only automate what is documented and even if one automates to 90% or more, it is difficult to achieve more than 60% coverage.

Quality is non-negotiable and is the foremost important factor to retain your customers and insulate your business from leakage.

Humans are still required to perform validations and check an application using their intelligence, sense of purpose and social use cases. It will be a great use of human talent to perform validations keeping end-user behaviour in mind and leave scripted scenarios for automation to execute.

Intelligent QA is the path forward where we can combine intelligence of the human mind with trends created by using machine learning. The data to be used can be captured during software development lifecycle and production lifecycle. The outcome can be data combinations and missing use cases which can then be automated and validated using automation. These insights will also help functional QA to identify focus areas and user journey to help them test better for avoiding situations like Amazon Prime Day in the future.

By Vikas Mittal, Global President digital Assurance at Xebia