A retail company manages a complex supply chain involving multiple suppliers, warehouses, and distribution centers. They face challenges in optimizing inventory levels, minimizing stockouts, and reducing transportation costs. The company is interested in utilizing data analytics with R to analyze historical sales data, forecast future demand, and optimize inventory levels across the supply chain to improve operational efficiency and customer satisfaction.
 

Learning Objectives

 

1. How can we use time series analysis techniques in R to forecast demand for various products accurately, considering factors such as seasonality, trends, and external influences?
2. What data mining techniques in R can we apply to identify patterns and correlations in sales data that could help optimize inventory stocking levels and distribution routes, ultimately reducing costs and improving supply chain efficiency?