Client background
Client: Apparel, footwear and accessories
Areas of operations: Global (170+ countries)
Customer base: Global suppliers, end consumers
Total annual revenue: $12 billion
Challenges
Since multiple ERP systems interact with each other for seamless data flow, ITIL methodology is in place that creates incidents when there is an issue, but they are worked upon service level agreements. Sometimes, wrong priority incidents are opened by business users which slows down resolution. During holiday season in the US, ecommerce and retail orders placed by external customers and end users in customer organization systems increase manifold. It becomes tedious to zero in on the exact source of the problem. This slowness can impact trust. The company could also incur revenue loss if not remediated immediately.
Solution
Wipro proactively developed an automated dashboard framework that monitored retail and ecommerce orders and the corresponding pieces from source to target systems that traversed through various ERP systems where multiple applications would send the required data at defined intervals, which will be stored in a database and can be queried anytime from the dashboard. The dashboard gives interactive information on the number of orders and the number of pieces ordered by customers’ customer including end users. Any difference in the numbers of orders or pieces noticed between systems were marked and worked upon immediately for resolution. This helped to locate the source of the problem and ensured quick turnaround of fixes, which in turn ensured external customers received their product on time and the customer could invoice their customers on time.
Business impact
Wipro’s automation solution reduced 1,500 hours of manual monitoring effort that support teams would usually spend during the holiday season to ensure business is up and running 24/7. Since order placement to fulfilment was tracked, the customer business functioned smoothly. The team spent numerous hours from conceptualization to go-live in addition to their support duties. No major incidents were reported during the peak season. This automated framework monitored 2.2 million eCommerce orders and 1 million retail orders catering to 15 million pieces.