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he demand for rental cars in Florida and other warm climates peaks during college spring break season. Call centers and rental offices are flooded with customerswanting 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.What do you think? 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?
• Forecasting is the process of projecting the values of one or more variables into the future.
• Poor forecasting can result in poor inventory and staffing decisions, resulting in part shortages, inadequate customer service, and many customer complaints.
• Many firms integrate forecasting with value chain and capacity management systems to make better operational decisions.
• Accurate forecasts are needed throughout the value chain, and are used by all functional areas of the organization, including accounting, finance, marketing, operations, and distribution.
Colgate-Palmolive Colgate-Palmolive is a global consumer products company that manufactures such products as toothpaste, laundry detergents, pet foods, and soap, and it operates in over 200 countries. To reduce supply chain costs, Colgate-Palmolive implemented a supply chain planning process with its suppliers and customers to manage promotional demand, improve forecasts, and synchronize activities along the supply chain. These initiatives have improved on-time order performance from 70 to 98 percent for vendor managed inventories, reduced total inventories by 10 percent, and improved customer order fulfillment rates to 95 percent.
• The planning horizon is the length of time on which a forecast is based. This spans from short-range forecasts with a planning horizon of under 3 months to long-range forecasts of 1 to 10 years.
Basic Concepts in Forecasting• A time series is a set of observations
measured at successive points in time or over successive periods of time. A time series pattern may have one or more of the following five characteristics: Trend Seasonal patterns Cyclical patterns Random variation (or noise) Irregular (one time) variation
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.
Because of these random variations, forecasts are never 100 percent accurate.
Irregular variation is a one-time variation that is explainable. For example, a hurricane can cause a surge in demand for building materials, food, and water.
Forecast Errors and Accuracy• A major difference between MSE and MAD is that
MSE is influenced much more by large forecasts errors than by small errors (because the errors are squared).
• MAPE is different in that the measurement scale factor is eliminated by dividing the absolute error by the time-series data value. This makes the measure 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 α = 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.
Chapter 11 Forecasting and Demand Planning
• The forecast “smoothes out” the irregular fluctuations in the time series.
• 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.
• When no historical data is available, only judgmental forecasting is possible.
• 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, natural disasters, or labor complications.
A tracking signal provides a method for doing this 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)/MAD Tracking signals between plus and minus 4 indicated 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 information in Exhibit 11.18, how would you forecast short-term demand?