Out Of Stock Forecasting

Impact generated: #OutOfStockForecasting #RetailDataAnalytics #TimeSeriesAnalysis #PySparkDatabricks #SalesOptimization #InventoryManagement #DataScienceSolutions #PredictiveAnalytics

(Q2 2020)

This was one of the key initiatives within the company’s broader data-driven transformation. It focused on developing an advanced forecasting algorithm to predict out-of-stock situations in the retail channel, spurring mitigating actions and preventing potential revenue losses. 

I directed a multidisciplinary team of data engineers, scientists, and analysts to address critical operational supply chain management processes and model it using various predictive techniques, embedded in a robust app.

The resulting algorithm generated daily forecasts for 20.7 million product-location combinations, providing real-time alerts on potential stock shortages. These insights were integrated into the sales field application, empowering sales teams to proactively manage inventory and prevent lost sales. Rigorous five-month field tests validated the algorithm's accuracy, achieving an astonishing success rate, paving the way for scalable deployment.

The project's impact was substantial, effectively reducing lost sales due to out-of-stock situations and receiving huge acclaim. By providing accurate, actionable forecasts, inventory management was optimized, enabling more sales opportunities. This project exemplifies my ability to lead complex data science initiatives, deliver tangible business results, and leverage cutting-edge technologies to drive operational efficiency