Background on the Study: Dramatic changes to airline industry revenues have forced management at most U.S. airlines to review many long-standing business approaches. The rapid growth of low cost carriers (LCCs) and shifts to Internet distribution channels put downward pressure on airfares and, in turn, airline revenues. Many of these changes accelerated as airline revenues began falling behind their historic relationship with the Gross Domestic Product since late 2000. Ancillary revenues have become a critical source to individual airlines as can be seen by the various and expensive options for checking baggage, selecting priority and desirable seats, etc. This exercise provides you historic data from 1995 through 2013 for two important airlines, Delta Airlines and Southwest Airlines. Delta, as you probably know, is a full service airline flying internationally and is one of the nation?s largest air carrier. Southwest has a long history of low-cost, low frills service to generally smaller or regional airports, although that has changed somewhat over the past years. Both airlines invest heavily in projecting out the future passenger load (the number of passengers carried for X miles). Data from the Massachusetts Institute of Technology?s Airline Data Project has been used for this case study, and is not covered by any implied copyright. Only several parts of the data for these two airlines has been used in this case study and is available with the accompanying Excel Spreadsheet ? Airline Forecasting Case Study. There are many other factors that impact making an accurate forecast for future passenger load, but for this exercise the only factor used for both airlines is their operating revenue (all amounts in billions of dollars). ? Your tasks for this Airline Forecasting case study: You are to create a 3 year forecast, from 2014 through 2016 for both Delta and Southwest airlines that uses the following forecasting and statistical techniques: 1. The one variable summary for both airlines in StatTools ? analyze the results for the two companies, do not just put the output in the report without completely analyzing the results for both airlines. 2. The runs test to determine if the airline data is random or not. 3. The annual box and whisker plot for both airlines. 4. The moving average with a span of 3 ? in this case it will be 3 years. 5. The simple exponential smoothing forecast. 6. The Holt?s linear method for trends (seasonalized) and the Holt?s linear method deseasonalized. Both methods are required. 7. NOTE: The Winters method for trends and seasonality will not work for annual data, thus it is NOT required for this case study. To decide which of these has the best forecast for both airlines you will concentrate on the following results as provided by the StatTools software: 1. The mean absolute error (MAE) of each forecasting technique; 2. The root mean square error (RMSE) of each forecasting technique; 3. The mean absolute percentage of error (MAPE) of each forecasting technique; 4. The average and cumulative error (see slides 81 to 83 from week 7 PowerPoint) 5. Which forecasting technique best follows the actual earnings line, and provides the best forecasted earnings. NOTE: This technique may be different for the two airlines. 6. NOTE: You MUST include the Airline Forecasting Data ? Table One (page one of the Excel file) completed with the forecast for the years 2014 though 2016 for both airlines. Important things you need to know: 1. You may assume that both companies fiscal year goes from January to December. 2. All operating revenue are in billions of dollars, thus 11.22 = $11,220,000,000 in operating revenue for that year. Your Tasks: 1. Carry out the various statistical tests as indicated above. 2. Analyze the resulting data, and determine which of the forecasting techniques provides the best forecast for each airline, and why. 3. Report on each of these forecasting techniques in your report, explaining what you did, what you found out, and how you decided which forecast is the best. 4. Put the relevant output graphs, tables and figures INTO the report and discuss them where they are placed in the report. Do NOT just put the output into the Appendix or in the attachment of the report. OUTPUT figures MUST be included and discussed in the report itself. 5. Forecast the next three years of operating revenue for both airlines. 6. Submit your individual report on time as determined by your section?s Monthly/Weekly Calendar.
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