Classification and Regression Tree Model to Predict the Probability of a Product being Backordered in Supply Chain

Supply chain uncertainties pose a massive and ever-present challenge for modern companies. These can manifest in two contrasting scenarios: supply surplus, where companies have excess items, shortages, there is an insufficient quantity of goods. Each situation demands different approach from businesses to adapt the varying outcomes maintain competitive edge market. Product backordering one important things that need deal with uncertain chain. A backorder occurs when customer-ordered product or service not stock cannot be supplied immediately, customer has wait. Companies striving balance managing backorders. Machine learning models help determine probability being backordered. In this research, we develop Classification Regression Tree (CART) model uses previously known parameters predict likelihood We also use evaluate accuracy model.