DEMAND FORECASTINGDEFINITIONA forecast is a prediction or estimation of a future situation, under given conditions.Forecasts can broadly be classifed into categories: (i) Passive forecasts (ii) Active forecasts. Passive forecasts: Where prediction about future is based on the assumption that the frm does not change the course of its action.Active forecasts: Where forecasting is done under the condition of liely future changes in the actions by the frm. !enerally, business frms are interested in both passive and active forecasts."#$P" %& '$(A&' F)*$+A"#%&!'emand forecasting is a scientifc e,ercise and has to go through a number of steps. At each step critical considerations are re-uired.#he follo.ing steps are re-uired for demand forecasting.%dentifcation of ob/ectives.&ature of product and maret.'eterminants of demand.Analysis of factors.+hoice of method.#esting accuracy.OBJECTIVES OF DEMAND FORECASTING#he need of 'F di0ers according to the time span of forecasting.When the 1uctuations in demand are more, relatively shorter period should be chosen.NEED FOR SHORT TERM FORECASTING."hort term forecasting may cover a period of 2 months, 3 months to 45 year depending on the nature of business.%t is generally done for forecasting products. #he uses include:Appropriate production scheduling."uitable purchase policy.Appropriate price policy."etting realistic sales targets for salesmen.Forecasting fnancial re-uirements.NEED FOR LONG TERM FORECASTING6ong term forecasting covers a peroid of 7, 54 or 84 years.Follo.ing are its uses:9usiness planning.Financial planning.Planning manpo.er re-uirements.CHARACTERISTICS OF A GOOD DEMAND FORECASTING METHOD: ma/or characteristics can be identifed .ith forecastingmethods: #ime hori;on i.e. length of time over .hich a decision is being made. 6evel of detail:< #his must match the focus of the decision maing unit in the forecast. "tability:< "ituations that are relatively stable over time re-uires less attention. Pattern of data:< 'ata re-uired for use should be available on timely basis. #ype of model:< the assumption of each techni-ue must be satisfed and the easily comprehended by the management. +ost Accuracy $ase of applicationMETHODS OF DEMAND FORECASTINGForecasting methodsForecasting methods"urvey method"urvey method+onsumer survey method+onsumer survey method+ollective opinion method+ollective opinion method'elphi method'elphi method(aret e,periments method(aret e,periments method"tatistical method"tatistical method#ime series analysis#ime series analysis!raphical method!raphical method"emi averages method"emi averages method(oving averages method(oving averages method6east s-uares method6east s-uares method*egression analysis*egression analysisSURVEY METHODS =nder this approach surveys are conducted about the intentions of consumers, opinion of e,perts or of marets. %t could be a census survey (considering entire population) or a sample survey (selected subsets of the population). #hese methods are suitable for short term forecast due to volatile nature of consumer intentions. #he survey methods include: Consumer survey meto!: under this method a from can as consumers .hat and ho. much they are planning to buy at various prices of the product for the forthcoming time period, usually one year (could be census or sampling method) De"#$ meto!:< this consists of an attempt to arrive at a consensus in an uncertain area by -uestioning a group of e,perts repeatedly, until the responses appear to converge or the disagreement is clear. a Co""e%t$ve o#$n$on meto!:< >ere salesmen (sales force polling method) are re-uired to estimate future demand of the product in their respective territories and sections. #he estimates of individual salesmen are averaged or consolidated to fnd out the total estimated sales and then revie.ed by top e,ecutives to eliminate bias of optimism on the part of salesmen and pessimism on the part of others. Also revie.ed in the conte,t of factors a0ecting demand M&r'et e(#er$ments meto!)* in this the main determinants of demand of a product are identifed, these factors are varied separately over di0erent marets or di0erent time periods, holding other factors constant. #he e0ect of the e,periment on consumer behavior is studied and this demand forecasted.&)#$:< *efer prescribed te,tboo for detailed study, merits and demerits of each method.STATISTICAL METHODS#hese methods mae use of historical data as a basis for e,trapolating -uantitative relationships to arrive at the future demand patterns and trends.#hese are useful for long term forecasting and for forecasting old products.#hey are broadly classifed under:#ime series analysis:< %t is an arrangement of statistical data in a chronological order that is in accordance .ith its time of occurrence. 9ased on the time series data on the variable under forecast, a trend line or curve is plotted. #rend line can be .ored out ftting a trend e-uation to time series data through least s-uares method or some other estimation method. *egression analysis:< it is the most popular method of forecasting. %t is a mathematical analysis of the average relation bet.een t.o or more variables in terms of the original units of the data. >ere there are t.o types of variables. #he variable .hose value is to be predicted is called the regressed or dependant variable and the variable .hich in1uences the dependant value is called the ?regressor@ or predictor or e,planatory variable. When the study is confned to 8 variables it is called ?simple regression@ and to study the e0ect of more than one predictor on the value of the predicted variable is called ? multiple regression@.