A retail chain with 8 stores and 25 POS terminals needed daily sales reports aggregated from multiple data sources. The manual process of logging into each POS system, downloading data, reconciling, and creating formatted Excel reports was taking 4 hours every morning. We automated the entire pipeline to deliver reports by 7 AM every day.
25
POS Terminals
8
Stores
7 AM
Report Delivery
90/mo
Hours Saved
Time Saved
90+ hours per month
Estimated ROI
Rs 2,00,000+ monthly savings
Tech Stack
8 Technologies
Every morning, the operations team spent 4 hours downloading sales data from 25 POS terminals, consolidating into a master Excel file, calculating KPIs, and formatting reports for management. Reports were often delayed until noon, and manual errors in calculations led to incorrect business decisions.
We built a Python automation that connects to all POS systems via API, aggregates sales data, calculates KPIs, generates formatted Excel reports with charts, and emails them to management by 7 AM daily. The system also generates weekly and monthly summary reports automatically.
Scheduled job runs at 6 AM daily
Data is pulled from all POS terminals via API
Sales, returns, and inventory data is aggregated
KPIs are calculated per store and overall
Excel reports are generated with formatting and charts
Reports are emailed to management by 7 AM
Weekly and monthly reports are generated on schedule
Yes, the system can export data to Google Sheets, Power BI, or Tableau in addition to Excel reports. API endpoints are available for custom integrations.