So why does software testing take such a big share of budgets? It’s in part because testing tends to happen at the end of the development cycle, when bugs are expensive to fix, and often cause release delays and bottlenecks. But testing is also one of the last elements of the software delivery pipeline to be modernised, with the majority of organisations only automating 20 per cent or less of their total testing efforts.

It’s time for a change because by de-prioritising software testing, organisations are missing the opportunity to save significant amounts of money and add significant value to their offerings by improving both the quality and the ability to adapt customers’ needs. 

Scaling test automation can significantly reduce an organisation’s testing costs and time. AI-powered impact testing can reduce those costs even further - pinpointing the specific areas of an application affected by a given release and identifying the test cases needed to test those areas.

AGL is one company that has realised the benefits of automated testing, following a recognition that their customers expected faster and more personalised ways to interact with their utility provider. 

As part of a $300 million investment in a Customer Experience Transformation (CXT) program, AGL launched an “Idea to Production in five days” initiative for its SAP delivery units, which necessitated an overhaul and acceleration of their previously week long regression SAP backend test cycles to accommodate the new five day schedule. 

Underpinning AGL’s transition and that of other organisations is the recognition that testing should be transitioned from a necessary cost to a driver of value which can be achieved by addressing three key areas. 

1.Automate at scale

Many organisations lack the coding skills needed to scale test automation. Demand for these skills far outstrips supply, so resources are often dedicated to other areas considered more visible or mission-critical. As a result, test automation rates will remain low across the business.

A model-based approach to test automation which doesn’t require coding skills, will enable enterprises to rapidly scale test automation with the resources they already have. This approach breaks the automation process down into reusable building blocks, or models, that can be accessed and reused across different projects and teams. A script less tool means that if most or all of an organisation’s testing is still performed manually, it can rapidly scale its test automation using only the resources it has available.

2.Implement a risk-based testing approach

Enabling testing teams to identify and create the tests most important for minimising business risk, will significantly reduce the total number of test cases that need to be created and run before a release can be deemed production-ready. By aligning testing activities with business priorities, a focused, risk-based approach will enable an organisation to reach optimal coverage more quickly and assess release readiness with greater confidence.

In the case of AGL, it’s SAP testing transformation focused on business goals including accelerating time to market by reducing regression time from over a week to a day; increasing automation rates to reduce the testing time required for SAP initiatives, shifting QA focus to thoroughly assessing release quality, and maximising system quality by adopting continuous testing.

3.Understand the impact of enterprise application upgrades

Rather than running an entire regression test suite for each update to their enterprise applications, organisations should work to understand what impact these updates will have on critical business processes and focus testing on those areas.

Traditional update tools will reveal what areas of a system have changed following an update, whereas a tool that can also identify the areas that need to be tested because of that update will deliver far greater efficiencies.

For example, an AI-powered impact analysis focuses the scope of a test down to the impacted objects with each release. Any testing gaps discovered will be automatically added as requirements so that automated test cases can be created to fill the gaps. Pinpointing the area’s most at risk, and that need to be tested, has been found to reduce testing times by 85 per cent, on average, while ensuring 100 risk coverage. 

In fact, AGL’s shift from manual to automated testing reduced its testing times from 360 hours for manual testing to just 15 hours when testing was run automatically, an overall time savings of 95 percent. It’s a compelling argument for modernising software testing.