By Chinthi Weerasinghe
The world around us is changing—there are cab companies that don’t own cabs and room reservations systems that don’t own any real estate. All of these businesses disrupted their respective ecosystems by leveraging a digital platform that delivered unparalleled customer experience. The digital economy has shifted the power of technology from large enterprises to the hands of the end user. Customer experience and customer engagement have taken center stage, responsiveness to dynamic customer needs is what drives the competitive edge.
Along with this change we see an escalation of expectation from business teams. They not only expect greater agility in delivery, but have far greater expectations around application availability, reliability, security, and adoption.
This has changed the dynamics of everything we do in IT organizations today, especially around how we assure the quality of solutions delivered. Many of the yesterday’s key buzzwords in testing are the norm today.
Automation
Automation has been the mantra for a few years now. However, it is no longer a nice to have, it is now a must have. The question most organizations fail to realize is that automation is more than test or lifecycle automation that gets integrated into their DevOps journey. It’s looking at the possibility of automating every operational element and engineering a solution to assure quality, whether it is requirements review, test design, test environment, test data, or even production issue analysis.
However, organizations must get smarter about what it takes to be more automated. While it should be a no brainer to simply hire the high-end skilled software development engineer testers to get aligned to each release sprint teams, the challenge that most organizations encounter is finding and building these high-end skills with both domain and technical capability without breaking the bank. However, when one door closes, another opens and that is exactly what provides the impetus to smart platforms today.
Smart Platforms and In-Life Intelligence
Smart platforms, like its early ancestor the smartphone, must be intuitive and easy to use. They should not be limited to supporting test functions such as design, build, and execute, but extend to support test environments and test data management. While many platforms are available, those that venture into building them should focus on the ability to increase adoption, democratizing its usage into the hands of many versus the skilled few.
Another aspect is the platform’s ability to feed in-life intelligence—think of these as lessons
learned in electronic format—may it be from end users, prior releases, or intelligence from individual or team performances to make better informed decisions, faster. This becomes a critical success factor as we see teams moving away from a centrally governed center of excellence to decentralized decision making.
Empowered Hybrid Teams
Becoming more agile drives the need to move away from centrally controlled testing teams to more decentralized, empowered practitioners. This isn’t to say there is no centralization or centralized governance at all, but it is limited to ensuring that best practices are shared and standards are maintained across all teams. In some situations, the workforce is optimized through shared pools of resources—i.e. automation and performance centers—to manage costs and/or accelerate the achievement of an organization’s goal.
Driving change in these hybrid-decentralized organizations falls clearly on setting common goals and ensuring they receive information—like performance metrics, analytics—that leads to smart decision making. Metrics should also play a bigger role in instrument behavior and change in organizations. Instrumenting Behaviors
While each organization peers out at the changing tide that is the digital economy we live in today, some organizations miss the opportunity to utilize the behaviors of the millennial workforce that is in part responsible for the change. Let’s face it, they are different—and for good reason. Harnessing the same energy that is changing the world around us into helping to transform the enterprise can be done by designing behavior instrumenting metrics and gamification.
Millennial teams also consume and share information in a very different way. The right information needs to be available all the time, at their fingertips, and they need to be able to share feedback and information freely and openly. Building an environment conducive to this generation bodes well in an organization’s transformation journey.
Engineering the Change
The digital age has brought about change, not just in the demands of our businesses, but also in our workforce. While demands have increased, budgets have simultaneously tightened; stressing the change and making it harder than it needs to be.
So how does an IT organization drive this change? Like they say, “culture eats strategy for breakfast.” It becomes more about how you build or change the culture of your organization.
It is important to bring in partners who not only adjust the scale of technological capabilities, but also have the ability to drive the cultural shift. These partners must also posses the engineering know-how to truly foster a change. These considerations will help organizations make a more seamless shift from quality assurance to quality engineering. SW
Chinthi Weerasinghe is head of Virtusa’s independent software quality assurance(QA) practice. She is a career technologist focused on accelerating business outcomes for client organizations. She offers in-depth experience directing teams of practitioners and consultants engaged in both consulting and operational IT projects in QA; aligned to multiple industry verticals.
Feb2018, Software Magazine
