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warm climates peaks during college spring break season. Call centers and rental offices are flooded with customers wanting to rent a vehicle. National Car Rental took a unique approach by developing a customer-identification forecasting model, by which it identifies all customers who are young and rent cars only once or twice a year. These demand analysis models allow National to call this target market segment in February, when call volumes are lower, to sign them up again. The proactive strategy is designed to both boost repeat rentals and smooth out the peaks and valleys in call center volumes.
Think of a pizza delivery franchise located near a college campus. What factors that influence demand do you think should be included in trying to forecast demand for pizzas?
• A trend is the underlying pattern of growth or decline in a time series.
• Seasonal patterns are characterized by repeatable periods of ups and downs over short periods of time.
• Cyclical patterns are regular patterns in a data series that take place over longer periods of time.
• Random variation (sometimes called noise) is the unexplained deviation of a time series from a predictable pattern, such as a trend, seasonal, or cyclical pattern.
• Irregular variation is a one-time variation that is explainable.
• MSE is influenced much more by large forecasts errors than by small errors (because the errors are squared).
• The measurement scale factor in MAPE is eliminated by dividing the absolute error by the time-series data value, making it easier to interpret.
• The selection of the best measure of forecast accuracy is not a simple matter; indeed, forecasting experts often disagree on which measure should be used.
Develop three-period and four-period moving-average forecasts and single exponential smoothing forecasts with a = 0.5. Compute the MAD, MAPE, and MSE for each. Which method provides a better forecast?
• Single Exponential Smoothing (SES) is a forecasting technique that uses a weighted average of past time-series values to forecast the value of the time series in the next period.
• Regression analysis is a method for building a statistical model that defines a relationship between a single dependent variable and one or more independent variables, all of which are numerical.
Yt = a + bt (11.7)- Simple linear regression finds the best values of
a and b using the method of least squares.- Excel provides a very simple tool to find the
best-fitting regression model for a time series by selecting the Add Trendline option from the Chart menu.
• A linear regression model with more than one independent variable is called a multiple linear regression model.
- Multiple regression models can include other independent variables such as economic indexes or demographic factors that may influence the time series.
• Judgmental forecasting relies upon opinions and expertise of people in developing forecasts.- Grass Roots forecasting is simply asking
those who are close to the end consumer, such as salespeople, about the customers’ purchasing plans.
- The Delphi method consists of forecasting by expert opinion by gathering judgments and opinions of key personnel based on their experience and knowledge of the situation.
• Managers use a variety of judgmental and quantitative forecasting techniques.
• Statistical methods alone cannot account for such factors as sales promotions, competitive strategies, unusual economic disturbances, new products, large one-time orders, labor complications, etc.
• Statistical forecasts are often adjusted to account for qualitative factors.
A tracking signal provides a method for monitoring a forecast by quantifying bias—the tendency of forecasts to consistently be larger or smaller than the actual values of the time series.
Tracking signal = Σ(At – Ft) [11.8] MADTracking signals between plus and minus 4 indicate an adequate forecasting model.
BankUSA: Forecasting Help Desk Demand by Day Case Study1. What are the service management
characteristics of the CSR job?2. Define the mission statement and
strategy of the Help Desk contact center. Why is the Help Desk important? Who are its customers?
3. How would you handle the customer affected by the inaccurate stock price in the banks trust account system? Would you take a passive or proactive approach? Justify your answer.
4. Using the data on Call Volume in the accompanying table, how would you forecast short-term demand?