Analysis And Forecast Of The Retail Sale

1. Executive Summary

This report forecasts that the retail sales of a large department store will continue to grow in the next 12 months and hit a record $ 14.3 billion dollar by the end of 2007. The forecast is that retail sales are expected to be up 10 per cent growth over 2006, which will be driven by a positive economic environment.

The regression technique is first applied on the historical retail sale data of the time by establishing the exponential trend model to estimate and interpret an exponential trend for the years 1947 through 2006. Then Holt's linear exponential smoothing is used to forecast the sale for the end of the year 2007.

2. Problem Statement

The data contains quarterly sales (in millions of dollars) for a large department store from the first quarter of 1947 through the fourth quarter of 2006. If the retail sales of this department store are growing exponentially through this entire period? What should the retail sales of this department store be projected for the end of the 2007 according to its historical sale record? The objective of this data analysis is to estimate and interpret the company's exponential growth and to see whether it has been maintained during the entire period from 1947 until the end of 2006. Based on such a trend, the retail sale for the next year is to be forecasted by Holt's linear exponential smoothing.

3. Problem Analysis & Conclusions

Forecasting Methods

Many time series follow a long-term trend except for random variation. This trend can be upward of downward. A straightforward way to model the trend is to estimate a regression equation for the sale, using time t as the single explanatory variable. In this analysis, an exponential model used to forecast the sale trend from the history sale data and Holt's linear exponential smoothing is used to forecast the next four quarters sales.

Regression Analysis

An exponential trend is appropriate since the time series changes by a constant percentage