Case Study - Forecasting Ticket Sales at CineBarn
DISCUSSION QUESTIONS
1. Develop a forecasting model based on Liam's suggestion to use a multiple regression model.
2. Develop a forecasting model based on Waverly's suggestion to use a multiplicative decomposition model.
3. Compare the two models. Which model yields more accu¬rate forecasts for daily ticket sales?
4. For the multiplicative decomposition forecast the next week (seven days) of ticket sales.
5. Assuming that the pattern established in the sample data can be regarded as representative of daily ticket sales, on which days of the week would you recommend that the staff should be reduced by four persons?
A provincial credit union has been growing steadily since it was established in 1961. Deposits have increased slowly but surely over the years, despite some years when the econ¬omy has been sluggish. To help develop a strategic plan, management at the credit union wants to develop a one-year forecast of deposits. Historical data for deposits from the inception of the credit union in 1961 up until 2004 are shown in the table above. The table also shows the provin¬cial GDP for the corresponding years.
(a) Using three forecasting models: (1) exponential smoothing with a= 0.6, (2) trend analysis, and (3) lin¬ear regression, discuss which forecasting model fits best for the credit union's strategic plan. Justify why one model should be selected over another.
(b) Examine the data carefully. Can you make a case for excluding a portion of the information? Why? Would that change your choice of model?
Attachment:- Operations.pdf