Perfaware

case study

Urban Outfitters

Founded

1970

Headquarters

USA

Industry

Retail

Number of Locations

260+

Abstract

Urban Outfitters was launching a large enterprise-wide order management system upgrade which included the migration of their On-Premise Sterling OMS from v9 to v10.  This upgrade included migration from Oracle to Postgres DB.  Urban was looking for Sterling OMS Performance expertise to help with a complete performance assessment to ensure the newly upgraded system would perform comparably with the existing OMS solution.

About UrbanOutfitters

Urban Outfitters is a global lifestyle retailer known for its bohemian-inspired apparel, accessories, and home goods.
The company operates a portfolio of brands including Urban Outfitters, Anthropologie, Free People, and BHLDN, catering to diverse customer segments. With a significant online presence and a growing international footprint, Urban Outfitters is a leader when it comes to omnichannel commerce excellence in the specialty retail industry.

IBM Sterling OMS Performance Testing Execution

Business Challenge

  • Perfaware needed to be flexible given Urban’s migration from on-prem to cloud was delayed and now without some troubles. Some components could not be tested as they were not available at the moment. 
  • Perfaware had to carefully navigate the constant scope creep that Urban requested. Despite no clear scope definition being provided initially, Perfaware was able to come up with a proposed scope to address their most pressing needs and this only required a couple of changes along the way to fully deliver the expected results.
  • The NFRs and test scenarios were corrected as the test was going on. Luckily, Perfaware had the necessary skills, time and flexibility to prevent these issues from impacting the cost to the customer..
  • There were periodic access issues, changes in the topology and infrastructure.
  • Perfaware had to adapt to the lack of adequate testing of core components in the infrastructure such as JMS, AlloyDB, and Kafka and helped to stabilize these components without impacting the cost to the customer.

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