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
