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Retail operations reporting
Project background
The Client is a leading global technology company which also operates retail stores. The retail business started with 2 stores in United States. Over the years, it has grown into more than 180 stores worldwide. The company sells its own as well as third party products/services through online stores, retail stores, direct sales force, third-party wholesalers and resellers.
Key drivers
Prior to this initiative, information on store operations was limited to ad-hoc queries and primitive daily reports. No reports were available for store managers to analyze and forecast. As retail business grew over the years, volume of data also grew at the rate of 50M+ records per year. There was a need for sophisticated infrastructure to consolidate data, analyze the performance of stores and take appropriate actions.
Project scope
EXILANT team was engaged to create/enhance various reports on upstream sales, billing, forecast and reference data. The reporting requirements range from providing simple widgets to complex analytical reports, catering to a wie range of user groups. The scope also included implementation of appropriate security restrictions, knowledge transfer, training and support.
Technology platform
Database : Oracle 9i
ETL / Data Integration : JCM, PL/SQL and DBLINK
Reporting platform : Oracle Report and Crystal Report
Approach to implement BI solution
Establishing initial business intelligence platform with associated layers is critical. If this is done correctly with futuristic view, additional information requirements can easily be accommodated.
Project details
Data pertaining to sales, invoices, orders, billing, forecast along with reference data from upstream systems had to be inducted into respective data warehouse databases. Data from these warehouse databases were then extracted, transformed and consolidated to create reporting information repository. Reporting views were created based on the requirements. Real time custom reports were also created utilizing real time data from data marts.
The team worked through the challenges of performance tuning of data marts, rebuilding the ETL to make it compatible with Crystal Reports, automation of product launch, building complex reports and data modeling through Business Objects.
The project team created 25 fixed format reports and 10+ real-time reports. At high level, the reports presented to clients an be classified as a) corporate reports; b) company reports; c) region reports and d) store reports. Analysts and senior management used key analytic reports to understand trends and support decision making. Delivery of reports to various users was enabled through emails, which was configured through a web portal.
Benchmarking commercial website
This case study is centered on how EXILANT helped the online sales channel to measure, collect, analyze and report data for the purpose of optimizing the web usage.
The key reports for retail operations include.
- Retail flash report - Most widely used by top management, which reports on parameters such as sales, sales forecast, store traffic and store performance measures for analysis.
- Shopper track reports - These reports provide details of traffic entering and leaving a store at various time frames. Metrics such as Store Popularity Index and Conversion Ratio are derived from these reports.
- Red zone report - This provides real time information for store operations and used by store manager. Tracking return of items and also discounts at item level increases the importance of this report.
- Store performance recognition report - Performance recognition report provides details of measures and ranks associated with various stores.
- Peak hour report - This is used by store manager and identifies peak selling hours for upcoming week based on a prior 6-week trend of sales and traffic of the stores.
Analyze data to formulate strategies
EXILANT helped marketing department of global technology company that processes more than 35 million transactions per day to formulate marketing strategies using the data analytics.
Project results
The reports helped managers analyze historic data to develop accurate forecasts and better strategies for upcoming quarters. Store managers were able to successfully predict peak selling hours for the upcoming week. The reports assisted management in keeping track of metrics such as Store Popularity Index and Conversion Rates. Performance related information of each store helped in planning appropriate campaigns. Performance tuning of data mart and rebuilding of the ETL helped improve availability of data for reporting purposes.
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