The top 6 actions that help you move from quality assurance to quality engineering

The digital landscape is changing at an increasingly fast pace as customers across industries demand products and services of the highest quality with shorter delays. This has created a need for enterprises to prioritize a test-as-you-build model with enhanced customer experience as the key area of focus.

You can transform your traditional approach to Quality Assurance (QA) into the more efficient Quality Engineering (QE) model by considering six factors.

Workforce transformation

You need to evaluate your existing testing teams to reskill them to make a successful leap from QA to QE. This involves changing the team’s mindset, updating their skills and tools, and transforming the culture as a whole. By doing this, you will effectively move from testing as a people activity to testing as a service.

Upstream testing

Testing itself will have to be flipped on its head. While the traditional way involves testing the product once it has been developed, the Agile way brings in testing right from the beginning of the software development lifecycle, at the ideation stage itself. This is done by incorporating feedback and continuous integration during the development lifecycle.

Automation framework

Having an automation framework in place is key to making the transition from QA to QE. It is already common practice to have automation on routine testing processes but there is scope for greatly expanding the role of automation in testing with tools like Selenium, QTP, TOSCA, QFTest, cognitive AI and Machine Learning.

Enterprise CI/CD

A Continuous Integration (CI) and Continuous Deployment (CD) pipeline helps save a lot of time and effort spent on manual, error-prone deployment work. It works in tandem with the upstream testing lever to drive quality from the start of the software development lifecycle.

Crowdsourcing

Crowdsourcing platforms like Topcoder allow you to crowdsource work to public, private and certified communities via the Hybrid Crowd extension. Crowdsourcing allows organizations to expand their spectrum of digital services, meet last-minute requirements and accelerate design, coding, testing and data science. Organizations using crowdsourcing benefit by getting access to the best ideas and pay only for output that fits their requirement.

Outcome-based model

Adopting an outcome-based model increases efficiency while reducing operational costs. Using measurable performance metrics, you can align your QE process with the outcome you desire and move away from managed capacity models which cost more. With outcome-based models, you will pay for outcomes instead of individuals, bringing in transparency and making it a win-win situation that increases your rewards and decreases the risks.

To sum up, you need to look at these factors while embarking on the shift from traditional testing to quality engineering. And depending on the maturity of your organization, the applicability of these will vary.

About the Author

Vineet Kak

Sales Director, Modern Application Services, Wipro

Vineet is an accomplished and performance-driven IT professional with more than 20 years of extensive experience advising customers on Digital Transformation, Quality Engineering, Innovation and Cloud adoption journey. He manages Wipro’s Application portfolio for some of the key financial clients globally and is based out of Amsterdam, Netherlands.

He is reachable at Vineet.kak@wipro.com

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