SUPPLY CHAIN MANAGEMENT SYSTEM (SCM) OF A DEPARTMENTAL STORE

Abstract

The aim of this project is to help businesses in delivering goods to the customers in efficient manner. The departmental stores in Pakistan are following traditional ways of handling business processes through manual techniques such as using heuristic for predicting product requirements for order placement. Our system presents a solution for sale forecasting using Machine Learning algorithms such as Multiple Linear Regression and Naive Bayes. We performed experiment on previous four years’ data to predict the sales of coming year. Efficiently predicting the sales depicts intelligent, real time customer requirements which means we have the demand of the customers that they are going to make in future for any specific product. Having an accurate demand on hand has multiple benefits such as, warehouse requirements and human interference in core business processes of supply chain management system of a departmental store will be minimized to a great extent. In presented proposed solution we have covered two main business situations i.e. a departmental store where they agree to integrate a new utility into their currently working point of sale and another business situation is, a departmental store where they are not willing to integrate any new system into their existing point of sale but they want a separate utility for analytics