Forecasting Sales Using The Box-Jenkins Approach: The Case Of Gulele Soap Factor
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Date
2003-02
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A.A.U
Abstract
This study is conducted to facilitate the decision making process of
Gule1e Soap Factory by developing an appropriate forecasting model. It
aims at providing accurate sales forecasts for future sales, which is a
vital input in decision-making. Particularly, the focus is given for
forecasting monthly laundry soaps sold by the factory.
Towards achieving its objective the study considered the Box-Jenkins
approach to time series analysis. A total of 68 monthly sales data has
been taken for analysis or model building purpose. Moreover, additional
5 months sales data has been used for forecasting purpose.
The analysis of the data, which is carried out using S-Plus 2000
package, suggested that ARIMA (3,1,0) model represents the pattern of
monthly laundry soap sales data. According to this model, forecasting
current sales essentially requires the inclusion or consideration of the
previous four consecutive sales data occurring at the four successive
lags. Moreover, it is found that the sales data recorded in the first lag has
greater influence or contribution in forecasting current sales volume.
On the other hand, it is observed that the sales data involves a seasonal
component that turns out to affect the sales volume approximately in 3.5
months. In other words, the analysis indicated that there is a seasonal
component that occurs with 3 or 4 months periodicity. This in turn
resulted in attaching high importance to the third and fourth lag
coefficients as compared to the coefficient of the third lag.
The results obtained led to the conclusion that the time factor IS the
major but not the only relevant factor in forecasting sales. Other
considerations in relation to promotional activities, competitors action,
seasonal factors, etc should be kept in mind.
Description
A Project Report Submitted In Partial Fulfillment
. Ofthe Requirements For The Degree Of Masters Of
Business Administration
Keywords
Forecasting Sales, Box-Jenkins Approach