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- 1. Demand forecasting is an estimation of sales inmoney or physical units for a specified futureperiod under a proposed marketing plan.We can thus define demand forecasting as thescientific and analytical estimation of demand fora product(good or service) for a particular periodof time.
- 2. It is the basis of planning production program.It is an estimate or a forecast of sales infuture.It depends on market planning.It tries to find out lines or profitableinvestment.It is done for a particular period.It tries to arrange appropriate promotionalefforts, advertisement, sales etc…
- 3. To produce required quantity.To access probable demand.Sales forecasting.Control of business.Inventory control.To plan investment and employment.To help Govt. to import a export policies.Man power planning.To call for team work
- 4. Appropriate production scheduling. Helping the firm in reducing costs of purchase of raw materials. Determine appropriate price policy to maintain consistent sales. Forecasting short term financial requirements.
- 5. Planning of new unit or expansion of an existing unit. Planning long term financial requirements. Planning man-power require. Planning a suitable statuary to produce goods in accordance with the changing needs of society.
- 6. There are two methods of demand forecasting.Subjective methodconsumer’s opinion method-in this method buyers are asked about their future buying intentions of products.sales force method-in this method salespersons are asked about their estimated sales targets in their respective sales territories in a given period of time.Expert opinion method (Delphi method)-in this method a group of experts come to a consensus on the demand of a particular good(generally a new one).It is less expensive.Market simulation- Firms may create artificial market where consumers are instructed to shop with some money.Test marketing- in this market product is actually sold in certain segments of the market, regarded as test market.
- 7. QUANTITATIVE METHOD trend projection method a. Secular trend-change occurring consistently over a longtime and is relatively smooth in its path. b. Seasonal trend-seasonal variations of data within a year.e.g. demand for woolen, ice cream. c. Cyclic trend- cyclic movement in demand for a productthat may have a tendency to recur in a few year d. Random Events-these are natural calamities, social unrestetc.Different Methods of trend projection-a. Graphical methodb. Least square method
- 8. GRAPHICAL METHODThis is the simplest technique to determine the trend. All values ofoutput or sells for different years are plotted on a graph. Year Sales 1990 30 1991 40 1992 35 1993 50 1994 45 60 50 40 30 20 10 0 90 91 92 93 94
- 9. LEAST SQUARE METHODWe can find out the trend values for each of the 5 years and also for thesubsequent years making use of a statistical equation, the method of LeastSquares.In a time series, x denotes time and y denotes variable. With the passage oftime, we need to find out the value of the variable.To calculate the trend values i.e., Yc, the regression equation used is-Yc = a+ bx.As the values of ‘a’ and ‘b’ are unknown, we can solve the following twonormal equationssimultaneously.(i) ∑ Y = Na + b∑x(ii) ∑XY = a∑x + b∑ x2Where,∑Y = Total of the original value of sales ( y)N = Number of years,∑X = total of the deviations of the years taken from a central period.∑XY = total of the products of the deviations of years and corresponding sales(y)∑x2 = total of the squared deviations of X values .When the total values of X. i.e., ∑X = 0
- 10. EXAMPLEYear = n Sales in Deviation Square of Product Computed Rs Lakhs from Deviation sales trend Y assumed X2 and time values Yc year X Deviation XY1990 30 -2 4 -60 321991 40 -1 1 -40 361992 35 0 0 0 401993 50 1 1 50 441994 45 2 4 90 48N=5 ∑Y=200 ∑X=0 ∑x2=10 ∑XY=40 CALCULATION Regression equation = Yc = a + bx To find the value of a = ∑Y/N = 200/5 = 40 To find out the value of b = XY/ ∑x2 = 40/10 = 4
- 11. For 1990 Y = 40+(4*-2) Y = 40-8= 32For 1991 Y = 40+(4*-1) Y = 40-4= 36For 1992 Y = 40+(4*0) Y = 40+0 = 40For 1993 Y = 40+(4*1) Y = 40+4 = 44For 1994 Y = 40+(4*2) Y = 40+8 = 48For the next two years, the estimated sales would be:For 1995 Y = 40+(4*3) Y = 40+12 = 52For 1996 Y = 40+(4*4) Y = 40+16 = 56
- 12. Barometric techniquesIn barometric forecasting we construct an index of a relevanteconomic indicator and forecast future trends on the basis ofthese indicators. Regression analysisRegression analysis relates a dependent variable to one ormore independent variable in the form of linear equation.Y = a+bxWhere , y indicates future demand a indicates fixed demand b indicates rate of change of demand x indicates value of related variables like price,incomeof consumer,price of related commodity etc.
- 13. Change in fashion- it is an inevitable consequence ofadvancement of civilisation.Results of demand forecastinghave short lasting impacts especially in a dynamic businessenvironmentConsumers’ psychology-results of forecasting dependlargely on consumers’ psychology, understanding which itselfis difficult.Uneconomical-forecasting requires collection of data inhuge volumes and their analysis, which may be too expensivefor small firms to efforts.Lack of experts-accurate forecasting necessitatesexperienced experts who may not be easily available.Lack of past data-demand forecasting requires past salesdata, which may not be correctly available.

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