Retail — Sales Forecasting and Inventory Optimization Pipeline

Overview

The primary purpose of the retail_kmds_sales_forecasting DAG is to accurately forecast future sales based on historical sales data and various key performance indicators (KPIs) sourced from ERP systems. The ingestion pipeline begins by collecting historical sales records, promotional data, and seasonal trends from multiple ERP sources. These data inputs are then processed using advanced forecasting models that analyze patterns and predict future sales volumes. The processing logic incorporates a

The primary purpose of the retail_kmds_sales_forecasting DAG is to accurately forecast future sales based on historical sales data and various key performance indicators (KPIs) sourced from ERP systems. The ingestion pipeline begins by collecting historical sales records, promotional data, and seasonal trends from multiple ERP sources. These data inputs are then processed using advanced forecasting models that analyze patterns and predict future sales volumes. The processing logic incorporates adjustments for planned promotions and seasonal fluctuations, ensuring that forecasts are as accurate as possible. Once the sales forecasts are generated, the results are published to a user-friendly dashboard. This dashboard serves as a central hub for sales and marketing teams, enabling them to visualize forecasts and make informed decisions regarding pricing strategies and inventory levels. Key performance indicators, such as forecast accuracy and stock turnover rates, are monitored to assess the effectiveness of the forecasting process. By leveraging this DAG, retail businesses can enhance their operational efficiency, reduce stockouts, and optimize inventory levels, ultimately leading to increased revenue and customer satisfaction.

Part of the Pricing Optimization solution for the Retail industry.

Use cases

• Improves sales strategy alignment with accurate forecasts
• Reduces excess inventory and stockouts
• Enhances promotional effectiveness through data-driven insights
• Increases operational efficiency in inventory management
• Boosts customer satisfaction with optimized stock levels