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S/4 performance assessment for a leading supermarket chain

Published on 13 October 2021
Quality Engineering in SAP S/4 Transformation

Customer Profile

The client is a leading regional supermarket chain in the US, operating over 200 supermarkets. The company mainly focuses on selling grocery, meat and dairy products, produce, frozen foods and other perishables, and non-food products.

Business Challenge

The client was saddled with a 20-year old legacy sales audit process with posting only at the department level that needed to be upgraded due to a lack of support, changing business models and lack of detailed sales analysis data. They wanted to go with SAP standard Sales Audit to put in the foundation for new business models and future use cases with SAP Customer Activity Repository (CAR)

The client did not have any performance baselines established in their existing system. With nearly 55000 transactions happening daily across all their stores, the available test environment did not mirror production, had no correlation to production size, and the data volume in the test environment was quite small compared to the expected production volume.

Applexus InSITE

Quality Engineering in SAP S/4 Transformation

Partnering with Applexus 

Applexus’ solution experts ran an end-to-end performance assessment across their SAP and Non-SAP systems to identify the pain points. The team analyzed the enterprise network and infrastructure impact on overall systems performance to draw the best solution roadmap. A root-cause analysis was designed and instrumented in order to unveil the root cause of the performance bottlenecks, which were then resolved. In addition to that, Applexus’ team documented the key findings and tunings implemented across the infrastructure to ensure continuity for future rebaselining.

Benefits Delivered

  • The client’s enterprise system was tuned to support the expected production workload without any performance block.
  • Established performance baselines for future enhancements and system changes to foster a performance-based measurable business model.
  • Reduced the time to process the data for almost 2 million transactions across all stores by 50%.

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