In this section we will describe how Forecast Pro reconciles the forecast hierarchy when overrides are made to a single level of the hierarchy.
Important: If you restrict your overrides to a single level of the hierarchy, the reconciliation process is simple and intuitive. We strongly urge you to limit your overrides to a single level if at all possible.
Figure 1 below depicts a simple forecast hierarchy prior to any overrides being entered. Notice that at this point the Statistical forecasts equal the committed Forecasts.
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Total S = 5 F = 5 |
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GroupA S = 2 F = 2 |
GroupB S = 3 F = 3 |
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ItemA1 S = 1 F = 1 |
ItemA2 S = 1 F = 1 |
ItemB1 S = 1 F = 1 |
ItemB2 S = 2 F = 2 |
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Figure 1.
Let’s now modify the above hierarchy by overriding the forecast for ItemA1 to equal 75. This results in the hierarchy shown in Figure 2 below.
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Total S = 5 F = 79 |
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GroupA S = 2 F = 76 |
GroupB S = 3 F = 3 |
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ItemA1 S = 1 O = 75 F = 75 |
ItemA2 S = 1 F = 1 |
ItemB1 S = 1 F = 1 |
ItemB2 S = 2 F = 2 |
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Figure 2.
Notice that at this point the committed Forecasts for GroupA and Total do not equal the Statistical forecasts.
If we had started with the hierarchy depicted in Figure 1 and adjusted the GroupB forecast to 75 (rather than ItemA1) we would generate Figure 3.
Total S = 5 F = 77 |
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GroupA S = 2 F = 2 |
GroupB S = 3 O = 75 F = 75 |
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ItemA1 S = 1 F = 1 |
ItemA2 S = 1 F = 1 |
ItemB1 S = 1 F = 25 |
ItemB2 S = 2 F = 50 |
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Figure 3.
Notice that the committed Forecasts for ItemB1, ItemB2 and Total do not equal the Statistical forecasts. Notice also that Forecast Pro allocated the GroupB override to ItemB1 and ItemB2 based on the proportions established by their Statistical forecasts.