Use Case Lazada Reconciliation Report
Goals of the project
- Enhanced Root Cause Analysis: Implement a proactive approach to identify and address underlying causes of missing Lazada transactions and loyalty points discrepancies
- Timely Issue Resolution: Aim to promptly resolve any identified discrepancies and patch data within a timeframe of 1 week
- Minimize Customer Complaints: To minimize customer complaints related to incorrect loyalty point credits
The missions
- Build a reconciliation report and dashboard for data comparison with data from cross-domain systems: Lazada x Order Management System (OMS) x CRM
- Conduct a pilot study to one brand, one market (TH KIEHL’S), then expand to other brands from other markets in SAPMENA (11 brands in 4 markets: TH, ID, MY, VN)
- Identify data quality and integration issues in the Zone based on reconciliation report
- Work with cross-domain teams (Lazada x OMS x CPRV x HIP x Project team) to implement robust data quality control measures
Accomplishments
- Successfully built reconciliation report and Power BI dashboard and set up daily send out of report to stakeholders including L'Oréal CIO and Operations Lead
- Reduced data quality issues within L'Oréal from 33% of transactions down to 0.4%
- Expanded report to 11 brands in 4 markets, TH, ID, MY, VN within 4 months
- Automated the daily matching file using SQL scripts in internal Federated Data Layer (FDL) system and saved processing time by 40%