The manager of a travel agency asked you to come up with a forecasting technique that will best fit to the actual demand for packaged tours. You have observed and recorded the actual demand for the last 10 periods. You also identified two possible techniques for consideration: 2-month moving averages (F1), and exponential smoothing (F2) with a smoothing constant of 0.25. Using Cumulative Forecasting Error (CFE) and Mean Absolute Deviation (MAD) as your performance measures you will determine the technique that will best fit to the actual demand data provided in the following table. STEP 1: Given start forecast values in period 3, compute forecast values from period 4 to 10. You are asked to provide the forecast values for period 6 and 10 for both techniques. 2-Month MA Exponential Period Demand F1 F2 1 115 -- -- 2 176 -- -- 3 97 146 129 4 141 5 98 6 132 7 114 8 129 9 107 10 180 STEP 2: Using data from period 3 to period 10, Provide the performance measures for F1 technique: CFE = MAD = Provide the performance measures for F2 technique: CFE = MAD = Based on these measures, which technique best fit to your data? (Enter F1 or F2) = NOTE: All computed forecast values should be rounded to the nearest integer (no decimal, for example 190). Performance measures (CFE and MAD) must be rounded to the nearest hundredth (two decimals after the dot, for example 30.99).

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.7: Exponential Smoothing Models

Problem 26P: The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel...

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The manager of a travel agency asked you to come up with a forecasting technique that will best fit to the actual demand for packaged tours. You have observed and recorded the actual demand for the last 10 periods. You also identified two possible techniques for consideration: 2-month moving averages (F1), and exponential smoothing (F2) with a smoothing constant of 0.25. Using Cumulative Forecasting Error (CFE) and Mean Absolute Deviation (MAD) as your performance measures you will determine the technique that will best fit to the actual demand data provided in the following table.

STEP 1: Given start forecast values in period 3, compute forecast values from period 4 to 10. You are asked to provide the forecast values for period 6 and 10 for both techniques.

		2-Month MA	Exponential
Period	Demand	F1	F2
1	115	--	--
2	176	--	--
3	97	146	129
4	141
5	98
6	132
7	114
8	129
9	107
10	180

STEP 2: Using data from period 3 to period 10,

Provide the performance measures for F1 technique:

CFE = MAD =

Provide the performance measures for F2 technique:

CFE = MAD =

Based on these measures, which technique best fit to your data? (Enter F1 or F2) =
NOTE: All computed forecast values should be rounded to the nearest integer (no decimal, for example 190). Performance measures (CFE and MAD) must be rounded to the nearest hundredth (two decimals after the dot, for example 30.99).

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