Question

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 0.40. 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	128	--	--
2	172	--	--
3	89	150	129
4	143
5	72
6	140
7	129
8	140
9	98
10	174

  
  
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).
  
  

Answer 1

Answer:

Below is the screenshot of the formula applied -

Below is the screenshot of the result -

Provide the performance measures for F1 technique:
  
            CFE = -15 MAD = 33.63
  
Provide the performance measures for F2 technique:
  
            CFE = 28 MAD = 34.50

For the given data, 2 month moving avrege is best fit as it has lower value of CFE & MAD both.  

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