Accounting Forecasting for the Winter

Accounting Forecasting for the Winter Inventory Firms that wish to assess the potential demand for inventory may forecast the potential demand by looking at past sales. Different months may have different demand patterns, so forecasting should be undertaken looking at the seasonal variations rather than on an annual basis. The data that has been provided for the winter inventory may be used to assess the demand for the following year.

The first stage is to create an index; this is undertaken by looking at the sales for each month and then calculating a mean (Brockwell and Davis, 2010). The mean may be used as the base of the index and the level of the historical sales for each month calculated as a proportion of the base for that month (Brockwell and Davis, 2010). The calculations are shown in table 1.

Table 1; Calculation of the index for winter inventory Month Average Year Year Year Year 1 47,370 2 56,638 3 29,855 0.52 1.59 0.84 1.05 4 39,638 0.70 1.09 1.29 0.92 5 27,323 0.78 1.44 1.16 0.61 6 19,350 0.88 0.53 1.61 0.98 7 39,600 0.45 1.14 1.51 0.90 8 37,080 0.53 1.25 0.83 1.38 9 30,000 0.52 0.74 1.59 1.15 10 59,210 0.91 0.70 1.25 1.15 11 64,375 1.29 0.71 0.94 1.06 12 57,750 1.26 0.72 0.96 1.06 The data may also be placed onto a graph, showing the overall patterns of the demand; each month's line may also be used to calculate the intercept. The index may then be used to create a chart, showing the trends for that pattern over the four-year period.

To assess the most likely demand for the fifth year straight line can be drawn on the graph, with the line that passed at the closest point to all the existing data points used to forecast, with the forecast being the point it reaches when at year 5 (Brockwell and Davis, 2010). 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.