Challenge

City Mart Holdings (CMHL) one of Myanmar’s largest retail outlet, employing more than 8,000 employees. The City Mart Group started as a modern supermarket in 1996 in the north wing of Bogyoke Aung San Stadium but has since expanded into many different aspects of modern retail trade such as supermarkets, pharmacies, bookstores, baby stores, convenience stores and bakery & coffee shops. The stores are primarily located in the cities of Yangon, Mandalay and Naypyitaw.

Being one of the Largest Conglomerates in the country City Mart required certain capabilities that was not being catered through the required sets of functionalities within the organization.

City Mart was also one of the Largest Adopters of SAP within the country. Hence, they lacked a proper L2 Support partner not only to look at day to day support requests but to also work with them on enhancements and process improvements within the SAP System.

Being the Largest Retail Chain in Myanmar maintaining 106 retail outlets, the organization had a unique problem of streamlining operations between suppliers. The Accounts Payable team itself consisted of 53 personnel and the process of settling a supplier took 27 days in average with a significant paper trail to be maintained by the company. Being an Organization, which has limitless potential, POTENZA saw key areas on which further ROI could be generated to the company

The Organization also required more transparency in terms of data across the organization as KPI’s required for strategical, tactical, and operational users could not be seen clearly where the data was not properly captured (KPI’s such as Department Performances, Product Profitability, Regional Behaviors)

Solution

POTENZA created a dedicated supplier portal for CMHL where both the company as well as the suppliers could easily log in to whether it be from the office or even through mobile. Suppliers then had the functionality to transparently view the orders that were raised towards them and had the clear option to accept or decline orders. Hence the raising of invoices and GRN would also be done in the supplier portal and would consequently run till the payment run where an integration is done through the centralized ERP of CMHL (SAP)

Create a data warehouse which makes it easier for corporate decision-makers to analyze and share data insights. Standardizing data from different sources also reduces the risk of error in interpretation and improves overall accuracy. This provided a platform which acted as a single source of truth for all Data within City Mart to Reside within. Our Data Engineers and Scientists also were able to provide insightful dashboards and visualization tools for the organization to take better decisions.

POTENZA also provided their proprietary “SAP Support +” to CMHL where the organization could mix and match their requirements between dedicated support, Enhancement, Change Requests or Process Alignments to their SAP System. During this engagement in certain instances POTENZA provided dedicated full-time resources to be deployed at CMHL locations (e.g. – SAP BASIS

Impact

With the Implementation of the Bespoke Supplier Portal for CMHL, there was an optimization of staff size which resulted in a reduction of staff size in the AP team from 53 members to 13 members. Supplier Settlement days fell from 27 days to 3 days. The organization was able to get confirmation on orders faster resulting in outlets having adequate SKU stocks at any given time. This also provide CMHL a great degree of transparency to their end-to-end supply chain as well as utilizing the integration to better benefit from the rich feature set of the current SAP ERP within CMHL

By implementing BI, CHML have been able to increase their revenue by making effective merchandising decisions, including restocking the stores when necessary, and re-ordering cards when data shows it is a good idea.

BI ensures in-store needs are met and that efficient decisions can be made quickly and cost effectively. Key advantages of implementing BI at CMHL

• Improved customer experience
• Predictive modeling
• Optimized price