A banking system or a platform might have minor patches, enhancements, and configurations after they are sent to production. These changes may seem negligible, but even a little change can affect the features and functionalities in the BAU flow.
Think of a usual day, when you have pre-defined tasks to complete. The OEM introduces a new patch deployment that requires you to fix it in the running systems. This addition can disrupt the entire business workflow if not addressed on time. You can put your usual workflow on hold. You would need an adequate strategy supported with process validating tools to ensure that workflows are not disrupted. It is necessary to prioritize and strategize your daily activities accordingly, which will help you complete your task without disrupting your usual business flow.
The problems will arise when you fail to validate, prioritize, and strategize the critical tasks. The patch fixes, enhancements and configurations may seem minor, but it is strong enough to impact the regression test cases. The continuous back and forth for every change can disrupt the entire business flow. End-to-end BAU testing is necessary when there is a need to validate the BAU flow. The BAU testing team ensures that the minor changes do not disrupt the everyday business operation.
BAU testing challenges
Why is this a challenge now? What has changed? Need for urgency to handle the challenges
In current times, OEMs frequently release multiple application versions with configurations and enhancements due to regulatory changes, business requirements and others. The banks and FIs must update the same so that their applications remain relevant to their customer requirements, and they can serve their customers without any issues. In an ideal situation, banks and FIs would test the new features or minor patches, presuming that the old features would function as usual. In the practice, most banks and FIs will ignore the existing functionalities. Each time a new addition is done, there is a huge possibility that the existing functionalities may face a few changes, which over a period would be degraded if not tested.
BAU testing is a continuous maintenance work that includes business upgrades, defect fixes, security patches, feature improvements, support tickets raised, and minor changes to existing features based on customer feedback. BAU projects are not flexible to changes. There is a risk of losing employee engagement by focusing more on meeting customer requirements. The repetitive actions in BAU testing lead to more mistakes. As measuring the success of BAU testing projects is based on the team’s progress, the errors occurred can deeply impact the project. All these reasons make the BAU testing project hard to control and monitor.
BAU testing has not been a serious challenge until now because the frequency of version release was 5 times less as per a recent report. As customer demand and digitalization have compounded, banks and financial institutions are upgrading updated versions at close succession that can meet customer requirements. The continuous testing of new feature integration with the older ones becomes a challenge now. It requires an adequate testing methodology and approach. BAU testing methodology is essential to streamline the testing and periodic regression run process so that it can analyse the patch fixes, enhancements, and ad hoc fixes through functional testing and enhance the regression pack for future usability.
Building and enhancing a regression test pack is an integral part of BAU testing methodology. BAU testing requires repeated testing of application features and functionalities. Repeated testing is time-consuming and liable to human errors. It is becoming exceedingly essential for banks and FIs to consider BAU testing methodology as application features are vulnerable. When new features are introduced, they might disrupt the old features. Also, writing codes every time a new feature is introduced can be liable to manual errors. Therefore, by creating a regression test pack, banks and FIs save a substantial amount of time and prevent applications from human errors.
It is also essential for banks and FIs to consider the BAU testing approach for an unhindered and quality release. BAU testing approach tracks the quarter-to-quarter improvement by reducing effort, improving efficiency, and increasing test coverage.
Is the current BAU testing approach adequate?
BAU testing is essential to ensure that the business process flow remains uninterrupted. Banks and FIs are initiating BAU testing but it is hard to quantify the outcome of the testing process. Users may have several questions,
- Is BAU testing measurable with the right methods and approach?
- What are the right methods of BAU testing?
- What approach should banks and FIs take to ensure quarter-to-quarter improvement in BAU testing practice?
- How can we streamline the BAU testing process?
- How can we speed up the release cycle and ensure quality and efficiency?
Here are the solutions.
Business-as-usual (BAU) requires banks and FIs to keep up a routine work environment and maintain a smooth efficient workplace. BAU testing is done to ensure that this everyday routine work remains interrupted, and the process flow remains smooth. Since BAU is a continuous process, testing must be executed with due diligence.
To ensure the successful outcome of your BAU testing effort it is crucial to consider reducing the time, cost, and effort invested in testing. Banks and FIs must evaluate the ROI of the testing practice to measure the outcome of BAU testing. Breaking down the criticalities, we must also understand that achieving the 100% desired result for BAU testing is not possible without a proper methodology and testing approach.
Let us evaluate the parameters of measuring the outcome of BAU testing.
- Time constraint – Integrating new features in existing BAU models and expecting 100% accurate results on time is hard. Accommodating testing in the continuous workflow is a challenge that most banks and FIs must put up with. Will it harm the workflow, can we expect quality results, these are the common questions that banks and FIs muddle with. Planning a BAU testing project comes with experience and skill. A skilled and experienced team can design a BAU testing project through appropriate methodologies and proper approaches. Executing the BAU project and measuring the outcome quality in less time determines the success of the BAU testing project.
- Cost monitoring – BAU testing requires a lot of customization in order not to disrupt the continuous workflow. There is a fair amount of cost for customization that banks and FIs must incur, and it tends to go overboard if not monitored or controlled. Will the expense increase rapidly with multiple customizations, will there be a need for new software to support the new additions, will there be a need to incur an extra cost to accommodate the changes and more are the most common questions that Banks and FIs dwell over. Monitoring the BAU project testing and incurring the price is a work of competency. The most competent team can monitor and control the overboard expenditure with the right methodologies and approach. Executing the BAU project and measuring the quality outcome in a cost-efficient way determines the success of BAU testing projects.
- Effort management – BAU testing involves managing the effort towards the quality outcome of the project. BAU testing involves a substantial amount of regression cycles, where the dependency is more on the test automation solution than on manual effort. There must be a logical distribution of manual effort and test automation solutions. This parameter ensures that the project is completed within time and following a strict budget without involving extra resources required towards project completion. Managing effort without depleting more than you can handle is the work of the skilled and experienced testing team. The proper distribution of resources determines the success of the BAU testing project.
The end-to-end testing methodology and approach are essential to reduce errors in BAU testing projects. At Yethi, we follow an organized end-to-end BAU testing methodology. Our BAU testing methodology consists of,
- Analyse the regression impact
- Map the impacted regression test cases
- Execute the impacted regression test cases and execute Tenjin-based automation
- Retesting and reporting, defect logging and tracking
- Enhance and maintain regression pack – Add test cases for the patch fixes and enhancement to the regression pack
Our BAU testing and periodic regression run consist of patch fixes, enhancements, and ad hoc fixes. We conduct BAU functional testing in three areas, integration, acceptance, and UI/UX.
We follow a 3-stream structure in Patchset Regularization Methodology. We understand Patch Set backlog and impact analysis and build test strategy for backlog validation. We design test cases for backlog validation, backlog patch deployment in the test environment, backlog cases test execution (manual), automated regression testing, and deploy patch set backlog production.
We build and maintain an automated regression pack. We understand the application configuration and customization, design base regression cases, install Tenjin (5th generation codeless test automation solution), configure Tenjin application BOT, automate regression cases, validate automated regression pack, and update automated regression pack with patch set regression cases.
Either the banks and FIs or Yethi can handle the final stream, BAU-regularized patch set to test and deployment based on preference. It is divided into two quarters, each quarter consisting of patch set analysis, design and execution of manual patch set cases, and automated regression of impact area.
The approach Yethi takes for BAU testing is allocating the Core and Flexi team for projects. The core team is a team consisting of fixed resources, while resources are flexible and can be easily moved to other projects from the Flexi team based on the requirements. The project is monitored with review and report to track the project improvement. The approach reduces effort, improves efficiency, and increases test coverage. We maintain a systematic cycle in BAU testing through requirement analysis, design & execution test cases, defect logging & retest, execution sign-off, and maintaining regression pack.
We have proven results in handling multiple BAU testing experiences. We have more than 30 years of collective industry expertise and experience. Our testing process focuses on quality, a systematic approach, and automation by leveraging people, processes, tools, and technology. We reduce the amount of testing with our automation-driven process. Our outcome-based managed services model focuses more on predicting and preventing errors than detecting defects. Our codeless test automation solution is tools agnostic and optimized to provide quality output.