Case Study: a American multinational fashion holding company automates batch workload management with Digitate ignio AIOps

American Multinational Fashion Holding Company cuts manual batch work by 12,000+ hours a year with Digitate

An American multinational fashion holding company faced significant challenges in managing its complex batch workload system. With over 12,000 batch jobs running 5.5 million executions monthly, a lack of end-to-end observability led to more than 600 potential SLA misses. This manual, reactive process also required handling 15,000+ exception requests manually, risking compliance and efficient operations. The company turned to Digitate and its ignio AIOps solution to address these issues.

Digitate implemented its ignio AI. Workload Management to automate and predict batch job behavior. This solution automated nine different types of batch administration requests and eliminated the manual exception intake system. The results were transformative, including a 90% reduction in mean time to detect and resolve issues, over 12,000 manual hours saved annually, and the autonomous resolution of approximately 3,600 stuck orders per year. This greatly improved operational efficiency and customer experience for the fashion retailer.