9 exponential smoothing exponential smoothing is yet

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9. Exponential Smoothing : Exponential smoothing is yet another projection method of sales forecasting. It is similar to moving averages and is used fairly extensively. It represents the weighted sum of all past numbers in a time series with the heaviest weight placed on the most recent data. This method is particularly useful when forecasts of a large number of items are made. It is not necessary to keep a long history of past data. The method can have a stable response to changes and responses can be adjusted as required. 10. Time-series Analysis : It is a common device of mathematical projections of future sales. It involves the projection of past sales trends into the future. To predict future sales we analyse four kinds of historical sales variations (1) seasonal variation, (2) movements related to changes in the business cycles (Depression, Revival, Prosperity, Boom followed by Slump and so on. (3). the long-term trends of sales, and (4) irregular or unexplained variations. By isolating and analysing these four types of variations in sales, an analyst can estimate with accuracy the probable level of sales for a coming period. Of course, it is assumed that the past trend will continue in the future under such extrapolation. This is an objective method of sales forecast. 11. Regression Analysis : Regression analysis is another analytical technique of sales forecasting. This technique tries to functionally relate sales to those variables that influence sales. They may be economic factors, competitive factors or price. The variable which is to be forecasted is the dependent variable and the factors which cause changes in the dependent variable are explanatory or casual variables. The association between the dependent variable (i.e. the sales forecast of the company) and the explanatory or causal variables is determined and measured. An Annamalai University
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64 equation is fitted to explain the fluctuations in sales in terms of explanatory or causal variables. After establishing the relationship based on past data and with the estimated values for the factors for future years, we can get the sales estimates for the future years. Where sales are influenced by two or more causal variables acting together, multiple regression analysis is applied. Computers are used for regression analysis involving complex calculations. The regression method, in general, will give more accurate forecasts than the trend method since regression takes into account causal factors. At the same time, in regression analysis involving a number of causal variables, the error of forecasting will multiply along with the error in determining measuring the relationship or influence of each of these variables. 12. Econometric Models : Econometric models constitute yet another analytical method of sales forecasting. Econometrics basically attempts to express economic theories in mathematical terms so that they can be verified by statistical methods and used to measure the impact of one economic variable upon another for predicting future event.
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