In: Operations Management
Given the time series sales data for years 2018 (quarter 1 to 4), 2019 (quarters 5 to 8) as reported in the table below, forecast sales in quarters 9 to 12 of 2020. (20)
|
Quarters |
Sales |
Trend |
Seasonal Factor |
Average seasonal factor |
Forecasted Sales |
|
1 |
750 |
703.33 |
? |
? |
|
|
2 |
680 |
737.02 |
? |
? |
|
|
3 |
720 |
770.71 |
? |
? |
|
|
4 |
900 |
804.4 |
? |
? |
|
|
5 |
890 |
838.09 |
? |
||
|
6 |
800 |
871.78 |
? |
||
|
7 |
780 |
905.47 |
? |
||
|
8 |
1050 |
939.16 |
? |
||
|
9 |
? |
? |
|||
|
10 |
? |
? |
|||
|
11 |
? |
? |
|||
|
12 |
? |
? |
The interpolation of historical data is

The above tabular values are put in the excel and found following equation
Y = 669.64+ 33.69x
Where Y represents the trend of sales and x represents the serial number of quaters
Using the above value, following table found


Seasonal factor = Actual Sale/Average sale
Grand Average = Average of two year's average = (762.5+880)/2 = 821.25
The values of seasonal factoors are written below

Forecasted sales for year 3 = Grand average*Average seasonal factor of that particular quater

Put all the values in a single table
