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Succeed in Digital Transformation by Choosing Path of Least Resistance
In the digital age, applications are the primary mode of consumption for nearly all products and services and brand differentiation lies in providing seamless, omnichannel customer service experience. Organizations have already adopted lean and DevOps ways of development and they have to afford new approaches to test new ecosystem of complex, highly interconnected, APIs and cloud-driven applications. IT leaders cannot pick the two out of Speed, Quality and Cost. They need all three–Speed, Quality and Cost for creating all-inclusive digital journeys.
Companies like Netflix are already changing how media consumption works and all credits to their engineering practices, right from development to testing. The company has gone from a manual mode to continuous, fully automated and high-volume testing. We are not talking here to replicate their engineering practices.
It is impractical to replicate the automation framework of any organization as there are stark differences in applications, technology stack, leadership style, team structure and size. Testing automation should happen in incremental ways to achieve required maturity. Every IT leader has to develop a unique blueprint for testing their applications to ensure a fully functioning digital customer experience. This blog talks how teams should re-imagine their test automation approach to complement their digital transformation journey.
The path to test automation in the age of Digital Transformation
Test automation is a buzzword but still not a household practice in organizations. Digital tsunami requires pro-responsive test strategies focused to deliver differentiated and high-touch services to reinforce brand identity in the digital era. The change in testing strategies need to touch myriad of processes, from challenging the status quo of established testing model to cater to the need for speed in dealing with changing development course with customer and partner feedback. Some of these changes that are required for test automation in the age of Digital Transformation are –
Focus on business tests – Teams are required to zoom out of the code and testing details; and take a closer look at the important business-level problems and write tests to solve these business problems vis-à-vis deliver seamless digital experience. One way of doing this is looking beyond the requirements and scope documents and build tests by looking at the real-time and operational data on how users are interacting with the application. Yes, it is possible. There are tools available in the market that gives idea metrics about end-user interaction. Teams need to understand these and develop tests accordingly.
Digital transformation revolves around customer-centricity and thus test strategies should focus on writing the test cases from a customer’s point of view. Behavior Driven Development (BDD) encourages use of simple language to blur the lines between engineering and business teams. BDD holds relevance for a digital future as it focuses on the outcomes and not the product important for the success of digital transformation.
Introduce Continuous Testing into your development – Digital transformation is beyond responsiveness and agility, its pro-adaptation to the future and related outcomes. Continuous testing ensures that engineering team are proactively testing every new feature in the development stage.
To introduce continuous testing in development, engineering heads have to introduce automation and leverage tools available for environment provisioning to test continuously at developer-machine level. Organizations often term test data management and generation as challenges because they are highly manual and time-consuming. These are the areas where organizations should use automation heavily to have testing running in parallel with the development. Test automation is required to test new codes continuously and this ensures a timely feedback about the bugs and issues to fix them early in the cycle.
Improving processes with Automation – Human-driven processes are prone to error, forgetfulness and skipping when they are redundant and highly manual. But with machines programmed for a specific function, there are zero possibilities of skipping or forgetting any test to run or data to generate.
Automating tests is pivotal to achieve continuous testing and make them apt for Digital age. Achieving 100% automation is an ambitious target because of constant changing requirements but achieving 85 to 90% test automation is doable even for the complex applications. Some areas of automation are test data generation, test data and environment management, running test suites and generating reports.
Test automation is a time and effort taking task. It’s very important to identify right tests to automate at the first attempt so that efforts and time do not go waste. Testing teams must create mini regression suite covering critical user journeys of high business value and run them first. Once teams have confidence about mini regression suite, the complete test suite is run, and results are collected to act upon among teams. There needs to be a defined acceptance criterion for every user story to ensure story is completed and functioning as expected.
Allocate budget for test automation – Testing requires same treatment and importance as given to the development activities. Testing is development cum testing as testers are developing code to test application under test. Businesses have to invest in right tools and technologies to make every-step automated and trouble-free. Teams devoting separate budgets have clear goals to be achieved out of testing and how to contribute to the software development lifecycle which makes it as a critical function.
Testing smartly with AI –Newer development methodologies around user interaction are uncovering the limitations of test automation. Testers write test scripts with guesses of how end users are interacting with the application. Though it’s a good way as testers are thinking from end-user perspective but successful test automation scripts must cover the end to end user journeys accurately. This is the larger issue with the current test automation practice.
Enters AI that can speed up the test automation practices by applying algorithms to large amounts of data produced by testing activities. Moving from manual and partial tests to matured CI integrated end-to-end functional suite includes a lot of manual and repetitive tasks. Organizations can use human capabilities to explore the areas of Automation, AI and Big Data in application usability, feature and integrations and test data analysis. Further, AI-powered test automation creates a knowledge base for self-learning and taking proactive actions.
A critical function, driving Digital Transformation
Organizations using AI for testing are surely creating a niche advantage for themselves rather than their counterparts by using data instead approximates and automation–two imperatives of digital transformation.
Qentelli’s test automation strategies are well-suited for DevOps and Agile environments to provide ROI to clients. Our test automation services cover web and mobile applications to get new digital services of client faster to the market. Do you feel manual testing is holding you back from right time releases? It’s time to engage deeper with us to address existential challenges in software deliveries at firstname.lastname@example.org.