An American corporation with more than 700 retail locations worldwide saw a significant uptick in purchases of its popular clothing and footwear. Although its distribution centers and warehouses could handle the influx, the company’s growth projections warranted a re-examination of its manual intake, shipment-change, and order-processing systems. The global brand and retailer was particularly interested in scalability and automation, as it anticipated even greater sales volume in the future through its online channels.
Wipro worked closely with the retailer to identify and solve potential pain points in its B2B workflows. Efficiently handling and tracking orders was critical, both from a sales-volume and system-integration standpoint. Wipro deployed an intelligent automation system for order management that optimized & processed orders, mapped to the customer’s SAP system, intelligently routed shipments, and ensured a consistent & consolidated flow of information across the organization.
Mindful of the retailer’s B2B network, Wipro created a business exception management system. The system is a centralized Pega application in which role-based business users handle business-processing fallouts from different Pega and non-Pega applications. Wipro also introduced Splunk, a cloud-based service for operational intelligence, so the operations team could conduct complete monitoring of both Pega and non-Pega application logs.
This touchless order management system would enable the retailer to manage order logistics and returns seamlessly, even as its sales grew over time. Furthermore, the entire workflow automation was executed on the Pega 7 Cloud platform, easing the retailer’s overall experience and ensuring its long-term scalability.
The new touchless order management system enabled the retailer to process 91.5% of its orders in a touchless manner. This intelligent automation reduced an order-entry process that once took more than 2,000 hours per year down to approximately 20 hours. The system also helped the organization reduce order-processing times by 90% and processing errors by 99%, dramatically increasing the retailer’s productivity while reducing its operating costs.