In: Operations Management
The following data are monthly sales of jeans at a local department store. The buyer would like to forecast sales of jeans for the next month, July.
(a) Forecast sales of jeans for March through June using the
naïve method, a two-period moving average, and exponential
smoothing with an ? = 0.2. (Hint: Use naïve to start the
exponential smoothing process.)
(b) Compare the forecasts using MAD and decide which is best.
(c) Using your method of choice, make a forecast for the month of
July.
| Month | Sales | 
| January | 45 | 
| February | 30 | 
| March | 40 | 
| April | 50 | 
| May | 55 | 
| June | 47 | 
Please refer below table highlighting relevant calculations :
| 
 Month  | 
 Actual sales  | 
 Forecast ( Naïve method)  | 
 Absolute deviation  | 
 Forecast ( 2 period moving average)  | 
 Absolute deviation  | 
 Forecast ( Exponential smoothing)  | 
 Absolute deviation  | 
| 
 January  | 
 45  | 
||||||
| 
 February  | 
 30  | 
 45  | 
 15  | 
 45  | 
|||
| 
 March  | 
 40  | 
 30  | 
 10  | 
 37.5  | 
 2.5  | 
 42  | 
 2.00  | 
| 
 April  | 
 50  | 
 40  | 
 10  | 
 35  | 
 15  | 
 41.6  | 
 8.40  | 
| 
 May  | 
 55  | 
 50  | 
 5  | 
 45  | 
 10  | 
 43.28  | 
 11.72  | 
| 
 June  | 
 47  | 
 55  | 
 8  | 
 52.5  | 
 5.5  | 
 45.62  | 
 1.38  | 
| 
 July  | 
 47  | 
 51  | 
 45.90  | 
||||
| 
 SUM =  | 
 48  | 
 33  | 
 23.50  | 
Following to be noted :
Forecasted value as per Naïve method :
Ft = At-1 , Ft = Forecast for period t and At-1 = Actual sales for period t-1
Forecasted value as per 2 period moving average :
Ft = ( At-1 + At-2 ) /2 , Ft = forecast for period t , At-1 , At-2 = actual sales for period t-1 and t-2 respectively
Forecasted value as per exponential smoothing method :
First we determine forecasted value for February = 45 as per Naïve method
Subsequently :
Ft = alpha x At-1 + ( 1 – alpha) x Ft-1
= 0.2 x At-1 + 0.8 x Ft-1
Where, alpha = exponential smoothing forecast = 0.2
Also to be noted:
Absolute deviation = Absolute difference between actual sales value and forecasted value
Mean absolute deviation ( MAD) = Sum of absolute deviation / Corresponding number of observations
Based on above definition of MAD ,
MAD for forecast as per Naïve method = 48/5 = 9.6
MAD for forecast as per 2 period moving average = 33/ 4 = 8.25
MAD for forecast as per exponential smoothing method = 23.5 / 4 = 5.875
Since MAD for exponential smoothing forecast is the LOWEST , Exponential smoothing forecast is the best
| 
 FORECAST FOR JULY AS PER NAÏVE METHOD = 47  | 
| 
 FORECAST FOR JULY AS PER 2 PERIOD MOVING AVERAGE = 51  | 
| 
 FORECAST FOR JULY AS PER EXPONENTIAL SMOOTHING METHOD = 45.90  |