Demand forecasting refers to predicting future demand under constraints. There are various types and objectives of forecasting. Factors that influence demand include time period, purpose, forecasting methods, nature of commodity, and competition. Common methods of forecasting include survey, statistical, and simulated market techniques. Accurate, plausible, durable, available, and economical forecasts are ideal. Regression analysis and moving averages are statistical techniques used to analyze past demand and extrapolate future trends.

1. DEMAND FORECASTING By [email_address]

7. METHODS OF FORECASTING SURVEY METHOD STATISTICAL METHOD 1.Survey of buyer’s intentions 1.Trend projection method 2.Expert opinion method or Delphi Method 2.Moving averages method 3.Controlled Experiments 3.Regression analysis 4.Simulated market situations 4.Barometric method

12. A producer of soaps decides to forecast the next years sales of his product. The data for the last five years is as follows: YEARS SALES IN Rs.LAKHS 1996 45 1997 52 1998 48 1999 55 2000 60

13. The data is plotted on a graph:

15. Substituting the above values in the normal equations: 260=5a +15b (Eq.3) 813=15a + 55b (Eq.4) solving the two equations, a = 42.1 , b = 3.3 YEARS SALES Rs. LAKHS (Y) X X 2 XY 1996 45 1 1 45 1997 52 2 4 104 1998 48 3 9 144 1999 55 4 16 220 2000 60 5 25 300 N=5 ∑ Y=260 ∑ X=15 ∑ X 2 =55 ∑ XY=813

18. 3 yearly period: The value of 1993 + 1994 +1995 12 +15+14 = 41 written at the capital period 1994 of the years 1993, 1994 and 1995 YEAR SALES (Rs. LAKHS) 3 YEARLY MOVING TOTAL 3 YEARLY MOVING AVG. TREND VALUES 1993 12 - - ’ 94 15 41 41/3= 13.7 ’ 95 14 45 45/3= 15 ’ 96 16 48 48/3 =16 ’ 97 18 51 51/3 =17 ’ 98 17 54 54/3 = 18 ’ 99 19 56 56/3 = 18.7 2000 20 61 61/3 = 20.2 ’ 01 22 67 67/3 = 22.3 ’ 02 25 71 71/3 = 23.7 ’ 03 24 - -

19. 4 YEARLY MOVING AVERAGES 57 = ‘93 + ‘94 +’95 + ‘96 = 12 + 15 + 14 + 16 120= 57 +63, 128 = 16 +65 and so on. 120 is total of 8 years and so the avg. is calculated by dividing 120 by 8 57 63 65 70 74 78 86 91 YEAR. SALES (Rs. LAKHS) 4 YEARLY MOVING TOTAL MOVING TOTAL OF PAIRS OF YEARLY TOTAL 4 YEARLY MOVING AVG. TREND VALUES ’ 93 12 - - - ’ 94 15 - - - ’ 95 14 120 120/8 = 15 ’ 96 16 128 128/8 = 16 ’ 97 18 135 135/8 = 16.9 ’ 98 17 144 144/8 = 18 ’ 99 19 152 152/8 = 19 ’ 00 20 164 164/8 = 20.5 ’ 01 22 177 177/8 = 22.1 ’ 02 25 - - ’ 03 24 - - -

20. The trend values from the previous tables can be plotted on a graph as follows:

23. “ Method of Simple linear Regression ” The linear trend can be fitted in the equation Sales = a + b (Price) i.e. S = a + bP where in, a and b are constants. b = n ∑S i P i - (∑S i )(∑P i ) n ∑P i 2 – (∑P i ) 2 a = ∑S i - b ∑ P i n

24. e.g. fit a linear regression line to the following data & estimate the demand at price Rs.30 YEAR ’ 81 ’ 82 ’ 83 ’ 84 ’ 85 ’ 86 ’ 87 ’ 88 ’ 89 ’ 90 ’ 91 ‘ 92 PRICE (P i ) 15 15 12 26 18 12 8 38 26 19 29 22 SALES (S i ) in 1000 units 52 46 38 37 37 37 34 25 22 22 20 14

25. To find the values of a and b the following table is constituted: P i S i P i 2 S i 2 S i P i 15 52 225 2704 780 15 46 225 2116 690 12 38 144 1444 456 26 37 676 1369 962 18 37 324 1369 666 12 37 144 1369 444 8 34 64 1156 272 38 25 1444 625 950 26 22 676 484 572 19 22 361 484 418 29 20 841 400 580 22 14 484 196 308 ∑ P i = 240 ∑ S i = 384 ∑ P i 2 = 5708 ∑ S i 2 = 13716 ∑ S i P i = 7098