Month 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Jan 194.96 162.54 176.90 154.83 156.34 127.96 123.42 128.60 125.86
100.87 100.22 103.75
Feb 173.66 165.15 170.08 155.09 142.15 147.90 138.19 124.46 116.91 92.16
97.28 104.61
Mar 190.52 174.89 179.85 150.55 151.50 129.00 139.43 136.28 103.39
112.21 112.19 94.61
Apr 192.83 177.55 153.17 143.59 159.87 149.42 120.79 109.83 107.70 93.58
98.51 94.06
May 196.49 179.05 159.33 161.17 160.87 147.36 130.02 118.82 124.25
118.95 101.62 94.05
Jun 182.36 170.29 165.04 161.44 162.47 134.51 146.45 115.60 102.70
119.15 100.15 92.07
July 195.38 192.73 174.76 147.08 149.09 151.43 124.12 115.70 105.36
97.92 103.61 96.56
Aug 185.68 192.05 183.94 164.55 136.41 131.95 145.43 128.35 124.86
112.06 112.09 103.16
Sep 205.07 184.94 185.87 153.66 169.22 147.47 127.91 125.90 120.82
108.52 96.48 106.68
Oct 195.27 170.34 188.87 177.78 149.54 136.99 141.72 145.46 118.21
124.38 113.74 91.13
Nov 203.30 205.15 192.32 163.33 162.48 149.92 143.83 138.74 138.52
128.24 117.72 98.70
Dec 210.10 188.30 177.36 177.16 163.98 152.16 165.80 150.65 132.50
123.13 121.13 131.74
Business Homework Solutions
#12794
2423-strategy
Generico has been manufacturing videotapes since 1982. The 3-hour VHS format is by far the largest component of their product mix. Historical demand for these items since 1992 is listed below .
Don Wirtz, general managing partner of Generico is concerned about the state of the current market for VHS format tapes. If demand is seen to be falling, Wirtz may need to consider diversification, if demand appears to be strong, Wirtz may need to consider ways to enhance the competitiveness of his manufacturing enterprise.
QUESTION: Please provide Don with monthly forecasts for the years 2004 and 2005, while considering all relevant phenomena present in the historical demand pattern....
We have just started the semester, so the techniques we have discussed are limited to:
1) Time series analysis: SimpleMovingAverage, WMA, Exponential Smoothing
2) Differencing
3) Forecast errors: absolute deviation, mean absolute deviation (MAD), and tracking signal
4) Single linear regression
5) Seasonalized time series regression
I'm not sure how to approach this. How do I know what technique is best? do I need to try more than one and measure the error (MAD or tracking) to see which is most accurate? What "phenomena" do I need to consder? HELP....
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Melissa Brayman, PhD, MBA - 4.2/5
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