Accounting Forecasting for the Winter Essay

Excerpt from Essay :

This is demonstrated in figure 1, with the data shown and the regression line shown. The equation for the line can be used to forecast the demand for any point in the future.

Figure 1; Chart for month 1 with forcast and regression line

The line shown has the equation y = 0.0289x + 0.9278, where x is the year, so for year 5 the equation would be (0.0289x 5) + 0.9278 = 1.07. 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 is useful, but the forecast may also be complimented with the use of graphs. 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…

Sources Used in Document:

References

Brockwell, Peter J; Davis, Richard a, (2010), Introduction to Time Series and Forecasting, Springer

Morlidge S, (2009), Future Ready: How to Master Business Forecasting, John Wiley & Sons

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