Forecasting is an important approach to plan the future effectively and efficiently. A time series is a sequence of data points, typically consisting of successive measurements made over a uniform time interval. Time series forecasting is the use of a model to predict future values based on previously observed values. A leading retailer in USA, wants to forecast sales for their product categories in their store based on the sales history of each category. Sales forecast has very high influence on the performance of the company’s business and hence these sales forecasts can be used to estimate company’s success or performance in the coming year. Accurate forecasts may lead to better decisions in business. Sales or revenues forecasting is very important for retail operations . Forecasting of retail sales helps retailer to take necessary measures to plan their budgets or investments in a period (monthly, yearly) among different product categories like women clothing, men clothing and other clothing and at the same time they can plan to minimize revenue loss from unavailability of products by investing accordingly.
- Target attribute is “Sales(In ThousandDollars)”
- To build a framework that provides monthly forecasts of the next 12 months for each product category (3 product categories) with past sales history using time series model.
- To build a framework that provides monthly forecasts of the next 12 months for “WomenClothing” product category alone with other causal attributes using regression model.
- Compare the results obtained from time series model and regression model for “WomenClothing” product category and analyse the impact of causal variables.