Question 03 Suppose you sell stylish leather bags targeting young office going people who can use your bags to carry laptops and necessary stuff. You have already launched leather bags in February of this year and now based on the demand results of last 7 months, you want to predict the demand for your bags for the month of September. Hence, you want to select the right forecasting techniques and you are considering 2 period Moving Average, Naive technique and Exponential Smoothing (use any value between .10 - .15 as the value of alpha). Now figure out the better forecasting technique among 2 period Moving Average, Naive technique and Exponential Smoothing by doing the error calculation with the help of MAD, MSE, MAPE. Period Demand 2period Moving Average  (Demand forecast) Naive technique (Demand forecast) Exponential Smoothing (Demand forecast) February 70 75 ** ** March 74 78 ** ** April 80 ** ** ** May 88 ** ** ** June 92 ** ** ** July 95 ** ** ** August 98 ** ** **

Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
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Question 03

Suppose you sell stylish leather bags targeting young office going people who can use your bags to carry laptops and necessary stuff. You have already launched leather bags in February of this year and now based on the demand results of last 7 months, you want to predict the demand for your bags for the month of September. Hence, you want to select the right forecasting techniques and you are considering 2 period Moving Average, Naive technique and Exponential Smoothing (use any value between .10 - .15 as the value of alpha). Now figure out the better forecasting technique among 2 period Moving Average, Naive technique and Exponential Smoothing by doing the error calculation with the help of MAD, MSE, MAPE.

Period

Demand

2period Moving Average  (Demand forecast)

Naive technique (Demand forecast)

Exponential Smoothing (Demand forecast)

February

70

75

**

**

March

74

78

**

**

April

80

**

**

**

May

88

**

**

**

June

92

**

**

**

July

95

**

**

**

August

98

**

**

**

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