In the customer-centric digital age, every organization is in the business of producing quality code. Code quality, in fact, is an integral part of everything a business does today. And the job of quality assurance (QA) isn’t finished once a digital solution is brought to the market. IT must monitor performance in terms of how the product or service is received by end users – bugs and all – and then apply user feedback to build a better digital solution. With the rise of the Internet of Things (IoT) and smart, connected devices, testing becomes a far more complex and dispersed endeavor.

This makes the role of QA essential to business success. QA is no longer an after-thought; it now becomes the central tenet for market readiness and business assurance.

We have  long advocated for QA to shift left to build quality early into the lifecycle and then shift right to take into account end-user feedback as a quality parameter. Today, enterprises need at-scale adoption of Agile methodologies such as DevOps and advanced process automation to speed the release of quality software.

For instance, by introducing more than 90%  automation across front-end, back-end and database layers, we helped a leading European bank  significantly speed up application readiness for audit purposes. This also contributed to a 65% improvement in QA productivity.

Injecting AI into QA

As smart connected devices and IoT arise across the enterprise, ecosystems have become critical to today’s digital environments. To ensure business continuity, QA organizations must, therefore, test each connected device as a node and validate the ecosystem end to end. This can be tricky, but by applying elements of artificial intelligence, QA can step up to the task.

By investing in machine learning engines through big data and analytics, organizations can augment QA from a preventive to a predictive function. They can speed up release cycles by analyzing data generated at every stage of the lifecycle. Machine learning bots that analyze test data are touted as the next big thing for QA. These bots take over tasks such as defect triage or root cause analysis to detect code errors before they occur.

For instance, we deployed a robotic QA solution to help a UK energy provider to adequately test its home automation system without human intervention. The bot simulated human actions to test devices in a connected, smart home ecosystem. This enabled the QA team  to deliver a more satisfying  customer experience, which helped the utility provider secure top ranking for its mobile app in the Apple App Store.

Charting the Path Onward, Together

To explore such avenues and help our clients enhance quality in their emerging digital enterprises, we are bringing together the best minds in the IT industry at two events, in London and Boston. At both events, decision makers, analysts, and IT and QA experts will gather to discuss trends and deliberate on challenges in the QA path to being digital. Both events will offer fresh approaches to QA and unearth proven ways to proactively manage the pivot to digital.

At our London summit on June 8, 2017,  Diego Lo Giudice, vice-president and principal analyst at Forrester Research, will elaborate on why Quality@Speed is the key to digital success. Also on the agenda is Dan Cobley, former managing director of Google UK and Ireland, who will reveal how IT organizations can extend quality across the digital enterprise. Nathalie Nahai, web psychologist and author of the best-selling book Webs of Influence, will provide insights into online behavior and the art of online engagement. And Euan Davis, an associate vice-president in the Cognizant Center for the Future of Work, will convey how enterprises should embrace artificial intelligence.

On June 20, our QualitE Convention in Boston will feature Thomas Murphy, research director at Gartner, who will share his perspectives on the role of QA in engineering a digital tomorrow. Ben Pring, vice-president and director of the Cognizant Center for the Future of Work, will present a keynote on What to Do When Machines Do Everything, the title of the new book he co-authored with Malcolm Frank and Paul Roehrig. Theresa Lanowitz, founder and principal analyst at Voke, Inc., will shine a spotlight on reimagining digital with the new-age quality professional.

Also scheduled at both events are panel discussions, followed by break-out sessions for networking opportunities. Together, we look forward to engineering quality for the new digital enterprise.

 

Anbu Muppidathi is a member of Cognizant’s executive leadership team and is a senior leader in  the company’s Digital Systems and Technology line of business.  He is also the Global Markets Leader for Cognizant’s Quality Engineering & Assurance (QE&A) Practice. Previously, Anbu spearheaded Cognizant’s Banking & Financial Services Practice in North America for more than a decade.  Anbu obtained his MBA from Duke University as well as a master’s in computer applications from Alagappa University in India. He can be reached at Anbu@Cognizant.com.Andreas Golze leads the Quality Engineering & Assurance (QE&A) Practice at Cognizant for UK, EMEA and APAC. In this capacity, Andreas is responsible for service delivery and other market-facing activities in the region. Andreas joined Cognizant in 2010 and has more than 20 years of experience in the field of software quality assurance and engineering. Before joining Cognizant, Andreas worked for Hewlett-Packard as head of consulting for testing worldwide. He can be reached at Andreas.Golze@cognizant.com.
Anbu Muppidathi

Anbu Muppidathi

Anbu Muppidathi is a member of Cognizant’s executive leadership team and is a senior leader in the company’s Digital Systems and Technology... Read more

  • Dickson Xavier

    its great to know! 🙂