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.
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…
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
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.
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.
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.
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
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
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
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
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
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.
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.