Why You’ll Need QE for Successful Digital Transformation

Digital transformation has steadily climbed up the priority list in business terms until it is now a C-suite imperative. What’s a little less well known is that organizations struggle to gain the desired results, despite this high-level focus from within the business. Did you know that as many as 66% to 84% of digital transformation initiatives fail? So claims a 2016 report from Harvard Business Review, 7 Questions to Ask Before Your Next Digital Transformation.

The report then goes on to invite readers to make an important distinction: are we talking about a digital upgrade or a digital transformation here? Because digital transformation is about more than creating efficiencies and speeding up processes. It actually requires a fundamental re-think of the processes themselves, starting with putting the customer right in the very center of things. Digital transformation is about re-imaging the business from the customer’s standpoint

While these goals sound great in theory, the customers and prospective clients we talk to always want to understand how to implement it in practice. We often get asked if there’s a framework or model that can be followed. The answer is yes. The model with the flexibility and the power to underpin this kind of organizational change is an approach called Quality Engineering, or QE.

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, thanks to CI/CD.

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 our 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.

Another great benefit is the reduction in cycle times organizations can expect to gain from being able to leverage test automation data. We worked with one of the top five global financial services firms to roll out new web and mobile solutions. Thanks to our CI/CD deployment, the company was able to launch products to market twice as fast as before. There were other advantages, too, such as a 20 percent reduction in costs and a 35 percent reduction in their mean time to recovery, to name but a few.

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. Now I can’t promise that QE will take the politics out of a business, but it can certainly help enterprises leverage data in order to spot trends and respond quickly to market disruption.

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!

If digital transformation is a priority for you this year and you would appreciate some guidance on the best approach to help you realize your goals most effectively, contact us. We will be happy to provide an in-depth analysis of your situation and suggest next steps to get your digital transformation underway successfully.