Why Quality Engineering is Necessary for Successful Digital Transformation

Digital transformation has steadily risen up the company priority list to the point that it is now a C-suite must. What is less commonly recognized is that, despite this high-level emphasis from within the business, businesses struggle to achieve the intended objectives. Did you realize that 66% to 84% of digital transformation projects fail? According to a 2016 Harvard Business Review report, 7 Questions to Ask Before Your Next Digital Transformation.

The paper then asks readers to make an essential distinction: are we discussing a digital update or a digital transformation? Because digital transformation entails more than just increasing efficiencies and shortening procedures. It truly necessitates a thorough rethinking of the processes themselves, beginning with putting the customer at the center of everything. The goal of digital transformation is to reimagine the business from the perspective of the customer.

While these objectives seem great in principle, the consumers and prospective clients we speak with always want to know how to put them into action. We are frequently asked if there is a framework or model that can be used. Yes, the answer is yes. Quality Engineering, or QE, is the model with the flexibility and strength to enable this type of organizational change.

What is QE?

At its simplest it is a means of improving software quality by focusing on improving the whole process, in contrast to more traditional methods where quality control happens in the final testing phase. For QE to work, a certain degree of preparation is essential. DevOps practitioners will be familiar with the preliminary work required to bring different business areas together to brainstorm and build the product. Once the product dev and test phase is underway, the main difference you’ll notice is the high degree of automation implemented into the SDLC, leading to continual or very frequent software outputs.

The reason QE may seem familiar is because its heritage is in agile and it owes a lot to DevOps. Here is why it is a preferred approach to successful digital transformation.

Breaking down barriers? Not a problem for QE

When organizations embark on digital transformation, they’re encouraged to redefine the customer relationship, tear up the rule book, and go ahead and break down those siloes that are holding the business back. This actually goes hand in hand with a QE approach too, which involves aligning people, practices and tools to achieve the business’ goals.

Customer obsession? QE ticks the box

When businesses are at the planning phase of the digital transformation, customer focus and customer experience are always big priorities. While we all want a consumer-friendly interface at the front-end of the product, a truly seamless design requires an enterprise-grade back-end. Creating awesome customer experience that is seamless across a growing range of devices, platforms, interfaces, etc. is turning into a herculean task! QE, with its focus on automation throughout the SDLC, can deliver. Automation is fundamental in order to take advantage of the speed and quality improvements that QE offers.

Better outputs, faster? QE to the rescue

When we talk to clients looking to initiate digital transformation, they long for digital agility, whether it is the capability to respond quickly to user feedback, to integrate new features fast or to take advantage of changing market conditions. With QE, the emphasis is on improving the whole process and involves overhauling any bottleneck areas.

When we talk about “quality” in QE, it comes in many forms. For example, early defect detection is a big differentiator for the QE approach. QE lets us apply prescriptive models to test data in order to detect defects early. As soon as code is checked from a developer’s separate pipeline, a unit test is run over that code. If there is a problem in the code, it gets reported and fixed immediately, before the code gets merged into the main pipeline. The probability of defects occurring at a later stage is reduced, saving a great deal of time and headaches in the long run.

Continuous improvement reduces the implicit assumptions that developers need to make, since their work is integrated continuously into the actual application, which reduces the amount of backtracking required later.

Business decisions based on data? That’s what QE is about

When you instigate QE in your software development, you enable a data-driven transformation, which is after all, what digital is all about. All too often the right data is not available at the time that business decisions are taken. So, organizations go with what they do have, which is some data, what has worked in the past, and a bit of guesswork, all laced with politics.  

One of the potential advantages large enterprises have over digital native startups operating in their markets is a vast treasure trove of customer information and all the other associated data. You just need to unlock it!

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