Ch05_48-60 - 72106 CH05 GGS 3/30/05 3:15 PM Page 48 C H A P...

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48 Actual Three-Week Week Bicycle Sales Moving Average 18 21 0 39 41 1( 8 1 10 1 9)/3 5 9 5 10 (10 1 9 1 11)/3 5 10 61 3 ( 9 1 11 1 10)/3 5 10 7 (11 1 10 1 13)/3 5 11 Z\c Alternative Example 5.2: Weighted moving average Bower’s Bikes decides to forecast bicycle sales by weighting the past 3 weeks as follows: Weights Applied Period 3 Last week 2 Two weeks ago 1 Three weeks ago 6 Sum of weights A 3-week weighted moving average appears below. Actual Bicycle Week Sales Three-Week Moving Average 0 4 11 [(3 3 9) 1 (2 3 10) 1 (1 3 8)]/6 5 9 Z\n 5 10 [(3 3 11) 1 (2 3 9) 1 (1 3 10)]/6 5 10 Z\n 6 13 [(3 3 10) 1 (2 3 11) 1 (1 3 9)]/6 5 10 Z\n 7 [(3 3 13) 1 (2 3 10) 1 (1 3 11)]/6 5 11 X\c Alternative Example 5.3: A Frm uses simple exponential smoothing with a 5 0.1 to forecast demand. The forecast for the week of January 1 was 500 units, whereas actual demand turned out to be 450 units. The demand forecasted for the week of Janu- ary 8 is calculated as follows. F t 5 F t 2 1 1 α ( A t 2 1 2 F t 2 1 ) 5 500 1 0.1(450 2 500) 5 495 units 5 () weight for period )(demand in period weights nn T EACHING S UGGESTIONS Teaching Suggestion 5.1: Wide Use of Forecasting. ±orecasting is one of the most important tools a student can master because every Frm needs to conduct forecasts. It’s useful to moti- vate students with the idea that obscure sounding techniques such as exponential smoothing are actually widely used in business, and a good manager is expected to understand forecasting. Regression is commonly accepted as a tool in economic and legal cases. Teaching Suggestion 5.2: Forecasting as an Art and a Science. ±orecasting is as much an art as a science. Students should under- stand that qualitative analysis (judgmental modeling) plays an im- portant role in predicting the future since not every factor can be quantiFed. Sometimes the best forecast is done by seat-of-the- pants methods. Teaching Suggestion 5.3: Use of Simple Models. Many managers want to know what goes on behind the forecast. They may feel uncomfortable with complex statistical models with too many variables. They also need to feel a part of the process. Teaching Suggestion 5.4: Management Input to the Exponential Smoothing Model. One of the strengths of exponential smoothing is that it allows de- cision makers to input constants that give weight to recent data. Most managers want to feel a part of the modeling process and appreciate the opportunity to provide input. Teaching Suggestion 5.5: Wide Use of Adaptive Models. With today’s dominant use of computers in forecasting, it is possible for a program to constantly track the accuracy of a model’s forecast. It’s important to understand that a program can automatically select the best alpha and beta weights in exponential smoothing. Even if a Frm has 10,000 products, the constants can be selected very quickly and easily without human intervention.
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Ch05_48-60 - 72106 CH05 GGS 3/30/05 3:15 PM Page 48 C H A P...

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