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Digital transformation is the implementation of digital technology into all aspects of business, and over the years, it has grown rapidly, especially in the banking industry. Innovation has produced newer technologies for keeping customers satisfied and increasing efficiency simultaneously.

Important key progress in digital transformation includes increasing adoption of increased use of machine learning (ML) & AI, cloud technology for reduced costs, and focus on the long-term effects of digital transformation initiatives. Digital transformation will continue to see tremendous growth in the coming years that will continually disrupt the status quo.

Let us first understand why quality engineering (QE) practices are in super demand for combating the present wave of hyper digitalization.

Why QE practices are advised rather than QA Models for digital transformation?

Development in digital transformation has necessitated the development of QE for better and efficient testing. Here are a few reasons why you should move from QA models and adopt QE practices in their workflows:

  • QE simulates how the end-users think and interact with products to deliver an improved customer experience in any industry, with tremendous success seen in testing mobile applications.
  • Most QE teams work closely with the product developers and operations team to process quicker and consistent releases using test automation methods.
  • QE helps teams to integrate several automated processes and integrate new tools early in the developmental cycle to ensure the products are released faster with test automation. This allows them to use quality test automation frameworks to guarantee faster releases and provide quality products.
  • With the shift-left testing processes in QE methods, developers can quickly find defects and push the products out to markets faster. Shift left testing allows developers to fix defects as soon as they discover them at low cost, faster than QA models and ensure customer satisfaction.
  • Mobile apps are becoming increasingly complex every day, and new IoT devices make it difficult for QA models to keep up with this rapid evolution. QE practices ensure testers can access the latest information and real-time scenarios to detect real-world defects faster before they become harmful to the finished product.
  • Device sharing is a common feature in today’s age, and this puts an increased security risk across systems and devices. QA models typically focus on only the security requirements of standalone applications meaning the process would be carried out across different systems. On the other hand, QE methods can handle all the security risks when data is shared across multiple systems.

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Top QE Best Practices for Accelerating Digital Transformation

In the banking industry, there are many quality dimensions to surmount, and it is important to make sure there is nothing at risk for several clients using the systems daily. This is why you should encourage and foster digital transformation in your business, and the fastest way to do that is through QE.

Here are the top five QE best practices for fostering the culture of continuous quality to accelerate digital transformation journeys

  • Use Automated Web Services Testing on Time

    Automated web services are the most common way of communicating with legacy systems that you can use across several areas. Detecting the issues early on in this stage could save your team a lot of time and effort on downstream work. Through this, you can check and quickly detect if a web service has misleading responses or it is incomplete.

    Another important aspect to consider is that third parties typically provide and maintain them, so it would be beneficial to have a dedicated Defect Management Team to handle it.

  • Determine Performance Metrics that Best Define Customer Experience

    Apart from understanding what a company wants in a digital transformation, QE teams will also run tests across several aspects, including accessibility, security, functional and non-functional tests. These tests will explain how the modifications in their business goals and processes have affected customer experience.

    Other metrics that could also help measure their customer experience to other similar apps on the market, including their direct competitors. Over time, these metrics will help increase customer experience in a company’s digital environment and be aware of customers’ expectations in the industry.

  • Communicate with your Clients in the Easy-to-Understand Language

    Products typically have a lot of features that need to be delivered fast. This also means your client will make change requests to dissect into several tasks and user stories. When you get to the final stages and user acceptance testing levels, you have to provide these details in a list that your client can understand and follow through to speed up approval.

    Throughout the development process, make sure the list gets updated and linked to your Product Backlog. You might consider a specific workflow so that when you implement these features in your tracking application, dependencies mapping will be easier.

  • Develop Automation Methods While Communicating with Other Teams
    Automation is a great strategy for extracting vital information about consumer responses and behavioral data. In particular, metrics like the number of users, time spent, bounce rate are very important, and you can collect this automatically. You can easily link this information with conversion rates and other customer experience statistics that inform your performance.

    This method also requires your QE team to collaborate with the development team to create codes that include development tools, frameworks and technologies. The ability of your QE team to scale QE through different environments is a factor in making this work.

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  • Continuous Performance Testing Through Specialized Teams

    Grouping your teams to work with a focus of the feature through web services to web and mobile applications requires more skills from testers, but it provides reliable results compared with working based on specific technology areas. Efficient testing plays a role in this and has important considerations to consider.

    You should take steps to test every Micro Service when it’s available and, if possible, do the testing across several environments. Through the testing, develop test timeframes for production-like environments.

    The other two key spaces are functionalities consuming 3rd party services and public website areas as they could create negative reactions if they have a poor performance.

Conclusion

Many of these QE strategies and best practices for digital transformation take time to integrate with your process fully and could be very challenging. You should make sure every member of your team is carried along through the adjustment period as it is a complete paradigm shift from what some know. A great way to make the process easier is to use a governance layer through the test organization to ensure the tactical and strategic vision stays on track.

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