Rates of digital adoption are years ahead of where they were predicted to be before the pandemic. Many organisations set up solutions to meet the new demands brought on by the pandemic, such as developing tools for remote workers or new eCommerce capabilities.
Executive outlooks on the role of tech in business have also changed as they looked to software-based innovation to drive growth. As a result, the accelerated pace of creating digital offerings will no longer be due to extraordinary circumstances, instead becoming business as usual.
But with these digital offerings come new challenges. IT and product teams are under increasing pressure to deliver high-quality solutions, which means software complexities and testing can cause bottlenecks.
While it may be tempting to sidestep testing, that would be a major business mistake. The smallest friction or frustration encountered by a customer could result in abandonment in favour of a competitor. Testing is critical to delivering reliable and secure applications.
When done correctly, software testing reduces development costs and improves performance. The rigorous process ensures end-user satisfaction, detects software defects before go-live and evaluates whether software does what it is supposed to do. These steps also ensure that the work of software engineers aligns with the goals of the business.
But for organisations without mature software testing processes, the evaluation process can be slow and expensive. Many businesses are faced with two bad options: release fast with inadequate testing or lose their time-to-market advantage.
AI and automation
Quality applications can't be released quickly unless most of the testing is automated. Manual testing simply can't keep pace with the highly accelerated release cycles required for digital transformation.
According to the latest World Quality Report, the vast majority of testing is still performed manually, adding to the overall cost and slowness of the process.
Testing is no longer the final closing phase, but something that can happen in parallel with development. As well as using automation, testing earlier in the software development cycle reduces common testing pain points. Spotting bugs earlier means they are less expensive to fix and reduces the risk of bottlenecks and release delays.
Automation is getting smarter, leveraging AI to simulate human behaviour and improve software quality faster. Deep-learning-driven automation that can 'see' and use a UI as a human would. This adds a layer of intelligence to automation that is smart enough to work through the vast majority of UI changes — things that inevitably trip up traditional automation but wouldn't make a human think twice.
AI also supports earlier testing. Software engineers can now build an automated test before a UI exists based on a mockup and construct a running automation case based on it.
The increased importance of digital will bring bigger budgets and more scrutiny from the C-suite as software enables more business-critical projects. The delivery of software has changed dramatically over the last five years, and speed has emerged as a critical component to remain competitive.
But ever-rising customer expectations means businesses cannot afford to cut corners and risk losing business due to poor performing software. Taking a modern approach to testing can balance delivery speed and quality of applications, unlocking new competitive advantages for businesses.
