07. Thins can be repeated for each of the months.
The result of the equation gives the new index figure for the fifth year. To assess the level of inventory needed the index needs to be converted back to units: this in undertaken by multiplying the index by the base line for that month, as shown in table 2.
Table 2; Forecast for the winter inventory
Month
Average
Forecast Index
Forecast in Units
1
47,370
1.07
50,790
2
56,638
1.01
57,125
3
29,855
1.21
36,210
4
39,638
1.22
48,300
5
27,323
0.81
21,995
6
19,350
1.34
25,900
7
39,600
1.42
56,400
8
37,080
1.53
56,720
9
30,000
1.68
50,450
10
59,210
1.32
78,145
11
64,375
0.88
56,600
12
57,750
0.90
52,250
The forecast for the forthcoming year is complete. The forecast...
The data in the previous section of the paper were assessed comparing each month against the same month in other years to assess monthly patterns. Graphs may also be used to assess the patterns seen in a year to identify the periods where there is the greatest demand and the periods where the demand is lowest (Morlidge, 2009). Figure 2 shows the results for the four years so patterns over the year may be seen.
Figure 2; Monthly demand over the four years
The graph shows the four years, demonstrating that the demand is greatest between months 10-2, and lowest between months 5 and 6. The years do show some variance; for example, looking at the peak demand in year 1 the greatest demand was in month 11, in year 2 it was month 2, as these months were close it maybe the same influence impacted over this period, for example, it may have been a particularly cold winter. In year 3 the greatest demand was ion month 10 and in year 4 it was equally high in months 10 and 11. The patterns appear to indicate high demand in the winter months and low demand in the summer, with some years showing a slight increase in the middle of the summer.
References
Brockwell, Peter J; Davis, Richard a, (2010), Introduction to Time Series and Forecasting, Springer
Morlidge S, (2009),…
