Forecasting

Chapter 13
forecasting


Review and Discussion Questions

1. What is the difference between dependent and independent demand?

Independent demand is forecasted item demand that occurs separately from the demand for other items. Dependent demand is calculated from the demand for another item. The difference lies in the way the two demands are determined.

2. Examine Exhibit 13.4 andsuggest which model you might use for (1) bathing suit demand, (2) demand for new houses, (3) electrical power usage, (4) new plant expansion plans.

While any of the models in Exhibit 13.4 can potentially be used to forecast any of the items, the following models are generally appropriate: (1) Bathing suit demand could be forecasted using exponential smoothing. The time horizon is short,model complexity and cost is low, model accuracy is fair and data requirements are very low. (2) Demand for new houses can be forecasted using linear regression. The time horizons are long, model complexity is medium high, model accuracy is medium high and data requirements are high. (3) Causal regression models might be used to forecast electrical power usage. The time horizon is long, modelcomplexity is fairly high, model accuracy is high and data requirements are high. (4) New plant expansion plans can be forecast using qualitative forecasting techniques. This takes into account nonquantifible issues when planning plant expansion.

3. What is the logic in the least squares method of linear regression analysis?

The least squares method fits a line to the data whichminimizes the sum of the squared error between particular points on a regression line and actually observed data lying in the same X plane. If a central point (X-bar, Y-bar) is located in a scatter plot, an infinitely large number of regression lines could be found to represent the data equally well in terms of absolute error. However, there is only one, unique regression line that minimizes the sum ofthe square errors.


4. Explain the procedure to create a forecast using the decomposition method of least squares regression.

The steps are as follows:

I. Decompose the time series into the components.

a. Find the seasonal component.

b. Deseasonalize the demand.

c. Find the trend component

II. Forecast future values of each component.

a.Project trend components into the future.

b. Multiply trend component by seasonal component.

5. Give some very simple rules you might use to manage demand for a firm’s product. (An example is “limited to stock on hand.”)

Demand management can be in terms of: order control—“limited to stock on hand,” lead time—“allow six weeks for delivery,” need—“supply the parts to inoperativeunits first,” time open—“close up early every day,” or “closed on Saturdays,” plus others as mentioned in the text such as price cuts, incentives, promotions, etc.

6. What strategies are used by supermarkets, airlines, hospitals, banks, and cereal manufacturers to influence demand?

Supermarkets—several sales items, free giveaway items (such as a pound of butter or a loaf of bread), anoccasional “midnight madness” sale where the store is open late or even all night.

Airlines—excursion rates, age rates (senior citizens, children, youth fares), charter flights, off-season rates, exceptionally good meals (or no meals for further reduced prices), more flights, tie-in with hotels or auto rental, and tour agencies for “package tours,” free champagne, free stop-over at a third point,or new terminals.

Hospitals—patients generally go to the hospital recommended by their physician. Therefore, hospitals offer free office space, nursing assistance, lab equipment, staff positions, and patient billing to physicians. Hospitals frequently advertise their occupancy rate and room rates, which tend to influence demand. Also, they could become a preferred provider organization....