Forecasting. Y.-H. Chen, Ph.D. Production / Operations Management International College Ming-Chuan University. Forecasting Outline. Introduction Forecasting Process Forecasting Methods Forecast Accuracy and Control Forecast Method Selection and Usage.
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Y.-H. Chen, Ph.D.
Production / Operations Management
Easy to use
Mostly for long-range planning and introduction of new products. The view of one person may prevail.
Direct customer contact composites.
Consumer survey or point-of-sales (POS) data.
Opinions of managers and staff.
Delphi method (Rand Corp., 1948): Managers and staff complete a series of questionnaires, each developed from the previous one, to achieve a consensus forecast.
Technological forecasting. Long-term single-time forecasting. Data are costly to obtain.
A long term upward or downward movement in data.
Short-term regular variations related to weather, holiday, or other factors.
Wavelike variation lasting more than one year.
Caused by unusual circumstances, not reflective of typical behavior.
Residual variation after all other behaviors are accounted for.
Use exponential smoothing to develop a series of forecasts for the data, and compute (actual-forecast)=error for each period.
Calculate sales for a California-based firm over the last 10 weeks are shown in the table. Plot the data and visually check to see if a linear trend line would be appropriate. Then, determine the equation of the trend line, and predict sales for weeks 11 and 12.
a. A plot suggests that a linear trend line would be appropriate.
b. For n=10, we have
Thus, the trend line is yt=699.40+7.51t, where t=0 for period 0.
c. By letting t=11 and t=12, we have
Healthy Hamburgers has a chain of 12 stores in northern Illinois. Sales figures and profits for the stores are given in the following table. Obtain a regression line for the data and predict profit for a store assuming sales of $10 million.
Sales of 19-inch color television sets and 3-month lagged unemployment are shown in the table below. Determine if unemployment levels can be used to predict demand for 19-inch color TVs and, if so, derive a predictive equation.
It is necessary to monitor forecast errors to ensure that the forecast is performing adequately over time. This is generally accomplished by comparing forecast errors to predefined values, or action limits.
Example 11 (Page 93).