forecast for 21 tv sales yasmine yahia mohamed tantawi ossama kamal yasser abd-elbary under...
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Forecast Forecast for 21” TV Sales for 21” TV Sales
Yasmine Yahia Mohamed Tantawi Ossama KamalYasser Abd-Elbary
Under Supervision:Prof. Sayed Elkholy
QA– ESLSCA_29B25 October 2009
Simple Moving AverageWeighted Moving AverageSmoothing ForecastSeasonal IndexComparison
ContentsContents
Simple Moving Average Simple Moving Average Month Actual
Sales (2008)
Actual Sales
(2009)
SMA (3months)
SMA (4months)
SMA (6months)
Jan 4100 4286
Feb 2655 2978
Mar 3221 3689
Apr 2100 2200
May 2250 2460
Jun 3150 3396
Jul 3347 3788
Aug 4550 5788
Sep 3367 3870
Oct 2116 4482 4211 3584
Nov 3245
Dec 4760
Weighted Moving Average Weighted Moving Average Month Actual
Sales (2008)
Actual Sales (2009)
Wi
(0.74)
AiWi
Jan 4100 4286 0.106 452.90
Feb 2655 2978 0.068 203.40
Mar 3221 3689 0.082 304.25
Apr 2100 2200 0.054 119.10
May 2250 2460 0.058 142.65
Jun 3150 3396 0.081 275.70
Jul 3347 3788 0.086 327.06
Aug 4550 5788 0.117 678.75
Sep 3367 3870 0.086 334.14
Oct 2116 0.054 3836.63
Nov 3245 0.084
Dec 4760 0.122
Smoothing Forecast Smoothing Forecast SFSFt+1t+1=SF=SFtt+ + αα(A(Att-SF-SFtt))
Month Actual Sales (2008)
Actual Sales
(2009)
SF
(α=0.2)
SF
(α=0.5)
SF
(α=0.85)
Jan 4100 4286 4286 4286 4286
Feb 2655 2978 4286 4286 4286
Mar 3221 3689 4024 3632 3174
Apr 2100 2200 3957 3661 3612
May 2250 2460 3606 2930 2414
Jun 3150 3396 3377 2695 2453
Jul 3347 3788 3381 3046 3255
Aug 4550 5788 3462 3417 3708
Sep 3367 3870 3927 4602 5476
Oct 2116 3916 4236 4111
Nov 3245
Dec 4760
Seasonal IndexSeasonal IndexMonth
XActual Sales (2008) Y
X2 Y2 XY
Jan 1 4100 1 16,810,000 4,100
Feb 2 2655 4 7,049,025 5,310
Mar 3 3221 9 10,374,841 9,663
Apr 4 2100 16 4,410,000 8,400
May 5 2250 25 5,062,500 11,250
Jun 6 3150 36 9,922,500 18,900
Jul 7 3347 49 11,202,409 23,429
Aug 8 4550 64 20,702,500 36,400
Sep 9 3367 81 11,336,689 30,303
Oct 10 2116 100 4,477,456 21,160
Nov 11 3245 121 10,530,025 35,695
Dec 12 4760 144 22,657,600 57,120
78 38,861 650 134,535,545 261,730
Seasonal Index … Seasonal Index … ContinueContinue
Y’ = a + bX
b = (n ΣXY – ΣX ΣY)/(n ΣX2 –(ΣX)2)
a = (ΣY – b ΣX) / n
ΣX = 78; ΣY = 38,861; ΣX2 = 650;
ΣY2 = 134,535,545; ΣXY=261,730
b = 63.87;
a = 2,823.3
Y’ = 2823.3 + 63.87 X
Month
XActual Sales (2008) Y
Y’ Y\Y’
Jan 1 4100 2,887.17 1.420
Feb 2 2655 2,951.04 0.900
Mar 3 3221 3,014.91 1.068
Apr 4 2100 3,078.78 0.682
May 5 2250 3,142.65 0.716
Jun 6 3150 3,206.52 0.982
Jul 7 3347 3,270.39 1.023
Aug 8 4550 3,334.26 1.365
Sep 9 3367 3,398.13 0.991
Oct 10 2116 3,462.00 0.611
Nov 11 3245 3,525.87 0.920
Dec 12 4760 3,589.74 1.326
Seasonal Index … Seasonal Index … ContinueContinue
Month
XSales Forecast (2009) Y’
Y/Y’From 2008
Sales Forecast
Oct 09 22 4,228.44 0.611 2584
Nov 09 23 4,292.31 0.920 3950
Dec 09 24 4,356.18 1.326 5776
By applying Y’ for remaining months and use Y/Y’ from 2008 data for its equivalent months, we got the below table:
Note: “we couldn’t have ASI, as we have only year data”
Seasonal Index … Seasonal Index … ContinueContinue
Seasonal Index … Seasonal Index … another calculationsanother calculations
Month
XY
(2008 & 2009)
X2 Y2 XY Y’ Y/Y’
Jan 08 1 4100 1 16,810,000 4,100 2913.55 1.407
Feb 08 2 2655 4 7,049,025 5,310 2961.80 0.896
Mar 08 3 3221 9 10,374,841 9,663 3010.05 1.070
Apr 08 4 2100 16 4,410,000 8,400 3058.3 0.687
May 08 5 2250 25 5,062,500 11,250 3106.55 0.724
Jun 08 6 3150 36 9,922,500 18,900 3145.80 0.998
Jul 08 7 3347 49 11,202,409 23,429 3203.05 1.046
Aug 08 8 4550 64 20,702,500 36,400 3251.30 1.399
Sep 08 9 3367 81 11,336,689 30,303 3299.55 1.020
Oct 08 10 2116 100 4,477,456 21,160 3347.80 0.632
Nov 08 11 3245 121 10,530,025 35,695 3396.05 0.956
Dec 08 12 4760 144 22,657,600 57,120 3444.30 1.382
Jan 09 13 4286 169 18,369,796 55,718 3492.55 1.227
Feb 09 14 2978 196 8,838,484 41,692 3540.80 0.841
Mar 09 15 3689 225 13,608,721 55,335 3589.05 1.028
Apr 09 16 2200 289 4,840,000 35,200 3637.30 0.605
May 09 17 2460 324 6,051,600 41,820 3685.55 0.667
Jun 09 18 3396 361 11,532,816 61,128 3733.80 0.910
Jul 09 19 3788 400 14,348,944 71,972 3782.05 1.002
Aug 09 20 5788 441 33,500,944 115,760 3830.30 1.511
Sep 09 21 3870 3,311 14,976,900 81,270 3878.55 0.998
231 71,316 260,633,750 821,625
Month
XSales Forecast (2009) Y’
Y/Y’From 2008
Sales Forecast
Oct 09 22 3,926.80 0.632 2481.96
Nov 09 23 3975.05 0.956 3798.25
Dec 09 24 4023.30 1.382 5560.17
Y’ = a + bXb = 48.25; a = 2,865.30Y’ = 2865.3 + 48.25 X
By applying Y’ for remaining months and use Y/Y’ from 2008 data for its equivalent months, we got the below table:
Note: “we couldn’t have ASI, as we have only year data”
Seasonal Index … Seasonal Index … another calculationsanother calculations
Comparison Comparison Oct Nov Dec
SMA (3months) 4482
SMA (4months) 4211
SMA (6months) 3584
WMA 3837
SF (α=0.2) 3916
SF (α=0.5) 4236
SF (α=0.85) 4111
Seasonal Index (1st Calculations)
2584 3950 5776
Seasonal Index (2nd Calculations)
2482 3798 5560