The monthly demand for WMT Corporation for the past five years is shown in the table below. Forecast the total demand for year 6 using exponential smoothing. Assume the initial forecast for year 1 is 70,000 and the smoothing constant is 0.3. After estimating the forecast for year 6, compute the seasonality index for each month of the year and estimate the monthly demand for year 6.
Sales |
Year 1 |
Year 2 |
Year 3 |
Year 4 |
Year 5 |
Jan |
2000 |
3000 |
2000 |
5000 |
5000 |
Feb |
3000 |
4000 |
5000 |
4000 |
2000 |
March |
3000 |
3000 |
5000 |
4000 |
3000 |
April |
3000 |
5000 |
3000 |
2000 |
2000 |
May |
4000 |
5000 |
4000 |
5000 |
7000 |
Jun |
6000 |
8000 |
6000 |
7000 |
6000 |
July |
7000 |
3000 |
7000 |
10000 |
8000 |
Aug |
6000 |
8000 |
10000 |
14000 |
10000 |
Sept |
10000 |
12000 |
15000 |
16000 |
20000 |
Oct |
12000 |
12000 |
15000 |
16000 |
20000 |
Nov |
14000 |
16000 |
18000 |
20000 |
22000 |
Dec |
8000 |
10000 |
8000 |
12000 |
8000 |