Technology Category
- Analytics & Modeling - Robotic Process Automation (RPA)
Applicable Industries
- Education
- Transportation
Applicable Functions
- Maintenance
- Quality Assurance
Use Cases
- Experimentation Automation
- Visual Quality Detection
Services
- Testing & Certification
- Training
About The Customer
Radixx International is a leading provider of an Internet-based airline reservation and passenger service system. The company offers ticketless direct Internet distribution to travelers, as well as full E-ticket distribution through traditional travel agent channels. Radixx provides a modern and complete replacement for legacy airline hosting systems and hosts thirty airlines worldwide. As a Software as a Service (SaaS) provider, it is crucial for Radixx to ensure that its new products are error-free and of high quality from the onset. The company strives to introduce enhancements to its products semimonthly to maintain its competitive position using legacy task automation.
The Challenge
Radixx International faced a significant challenge in testing its software quickly and efficiently to maintain its quality reputation, without slowing delivery to market and incurring excessive costs that would impact product profitability. The company initially replaced manual testing with one of the leading testing suites on the market. However, this solution required a substantial initial investment and significant staff hours for training, coding, and suite maintenance. After trying a second suite with similar poor results, Radixx returned to manual testing as the more cost-effective option. The company needed a testing solution that better fit its scrum-based agile development methodology, without the high price tag and labor costs of the testing suites currently on the market.
The Solution
Radixx International adopted the Nintex Foxtrot RPA solution to address its testing challenges. This solution significantly increased the speed of Radixx’s new product launch. Since Nintex Foxtrot RPA requires no coding and minimal training, it was immediately implemented and effectively reduced testing time from 24 hours manual execution per test to less than 40 minutes per test. Testing was run as many as 4 times per week, resulting in an overall decrease from 96 hours of manual testing by software engineers to 2.7 hours of automated testing by QA staff. After a brief training, the QA team was able to quickly automate release testing in a very short time without the programming staff’s involvement.
Operational Impact
Quantitative Benefit
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