The Challenge
Retail company with massive historical sales data (125MB+ transaction files) lacking analytical capabilities to extract insights, forecast demand, and optimize inventory decisions.
Our Approach
- Processed and cleaned large-scale sales transaction data
- Analyzed sales patterns by product, category, location, and time period
- Developed time series forecasting models for key product categories
- Conducted lead time analysis for supplier performance evaluation
- Created interactive dashboards for sales performance monitoring
- Provided inventory optimization recommendations based on demand patterns
Analytical Methods Used
Time Series Forecasting
Descriptive Statistics
Sales Pattern Analysis
Lead Time Analysis
Category Performance Analysis
Trend Analysis
Seasonality Detection
Key Outcomes & Results
- Processed 3+ years of transaction data successfully
- Identified top-selling product categories and seasonal patterns
- Delivered accurate demand forecasts with 80%+ accuracy
- Reduced forecasting cycle time from weeks to hours
- Enabled data-driven inventory decisions