When it comes to workforce management, artificial intelligence (AI) is a tool already routinely deployed across all types of businesses, in a wide variety of industries. Whether in the form of powerful algorithms that claim to sift easily through CVs, automated scheduling of rotas or even forecasting tools that attest to predict staffing levels, AI tools and technologies now boast a dizzying array of capabilities.
For busy organizations looking to improve efficiencies, reduce costs and boost employee engagement it isn’t hard therefore to spot the appeal. After all, these cutting-edge innovations promise sweeping solutions too good to overlook. For instance, one global survey of 34,000 workers found two-thirds (64 percent) reported reduced stress levels and a more manageable workload thanks to the introduction of AI. Similarly, nearly three-quarters (72 percent) of those with low stress levels attribute this in part to access to tools and technology to work productively.
The benefits on both productivity, efficiency and employee wellbeing make a strong case for the implementation of such technologies. Yet, to fully obtain these benefits, it’s critical that organizations don’t simply leap in blind when it comes to AI.
Testing tools in the retail space
Increasingly, these developments in workforce management tools mean that business leaders are handing over responsibility for a complex and business-critical system to yet another solution. In few sectors is that riskier than in retail, where workforces combine multiple functions, schedules and demands. This also makes it even more important that retail companies test the emergent behaviors of software they are looking to implement and are likely to become reliant upon. Ultimately, this requires retail organizations to test these tools to ensure they deliver true business value, rather than simply create disruption.
For many years, of course, the challenge has been a reliance on ‘old’ ways of testing. Too often organizations are dependent on manual testers, which forces a compromise between quality, cost and time. If they test quickly and cheaply, businesses risk low quality. Yet, investing in high quality at low cost is likely to eat into hours and hours of time. That’s not to mention the huge reliance on people power.
The drawbacks of manual testing are almost too numerous to list. Among the most substantial are the significant amounts of time and money that are taken up by the creation of regression testing scripts, as well as the repetitive nature of the work, which means mistakes are often made, and often overlooked, too. Further to this, limited resources mean fixes can’t be implemented in tandem with testing – adding more time to the process. It also fails to provide sufficient scale or enable load testing due to the small number of transactions that can be carried out. With such an important piece of work placing high demands on labor, without the guarantee of accurate end results, retailers have been crying out for a solution to these problems for years.
Automated software testing
Thankfully, as much as AI has created the challenge, it has also presented the solution. In particular, automated software testing has surfaced as a tonic to the many drawbacks experienced with manual testing. This approach to testing makes it possible to drastically reduce the time and effort involved in this undertaking and significantly increases quality at the same time. For many other industries, such as telecommunications, IT and healthcare, automation testing has become the default option.
According to one survey, more than 90 percent of enterprises believe automation testing to be the single most crucial factor in accelerating innovation. Its ability to speed innovation and efficiency without compromising on quality is driving significant growth, with the automation testing market is expected to grow at 14.2 percent CAGR during the forecast period from 2021 to 2026. Yet, despite all of this, in the retail sector, the complexity of technology and systems has meant adoption of automated testing has been far slower.
All of this could be about to change though as solutions are now emerging that are able to leverage the innovations that are driving the revolution in workforce management to create automated testing that reflects the particular demands of retail. In some instances, using robotic process automation (RPA) can help to reduce the time it takes to run each test by a factor of 400-500x. At the same time, it massively increasing repeatability.
This approach makes it possible to execute dozens of tests of an automated workforce schedule with full end-to-end validation, including everything from shifts and punches, to holidays and timetables, in just a minute. With a manual tester, the same process would likely have taken two days. By this logic, using RPA, it would be possible to automate a set of scripts involving around 1,000 test scenarios overnight – something which would take six weeks to perform manually.
However, it’s not just about speed. This approach also delivers unwavering accuracy, deploying underlying technology, and is able to test across a wide selection of workforce management activities. For any organization looking to quickly and accurately validate the effectiveness of configuration changes this shortening of the process is invaluable.
Catching up with innovation
Slow and inaccurate software testing is a recipe for poor business health and potential disaster. The reality is as workforce management software gets more innovative, automated and data-driven, the testing of these solutions needs to step up a gear to deliver the equivalent speed, accuracy and rigor. Until now, the inherent complexity of a retail workforce has left this hard to achieve but solutions are becoming available to make testing more efficient, more cost-effective and of higher quality. As organizations begin to implement these solutions, they will be able to enjoy the fruits of AI, without the complications historically associated with deploying this technology.
Antony Kaplan, Test Services Director, REPL Group, part of Accenture