You use this program to track the performance of the forecast for individual items or a group of items. This enables you to measure and compare your historical forecasts against your actual sales movements, including lost sales.
This report calculates the same information as the Forecast Accuracy Review program, so you do not have to run the Forecast Accuracy Review first.
The report should be run as part of the monthly forecast cycle to validate the forecast and to identify items with high forecast error. It can also be run at any time for all items or a group of items. Items with high forecast error or high forecast error value may require that their forecast be manually updated to reduce the error.
Forecast accuracy is an essential measure of how well the forecast is performing. It uses the actual error achieved (forecast - actual) over a period of months into the past selected at run time. It is therefore essential to store the forecasts made over a period of time to ensure that they can be compared to the actual sales achieved.
Field | Description | ||||||||||
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Selection | |||||||||||
Use selection set | Select this to run the report using a selection set.
This option is selected by default and you indicate the
selection set to use in the Selection set
field below. When you deselect this option, all the other options are enabled and you can indicate the selections you require. |
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Selection set | Indicate the selection set you want to report on. | ||||||||||
Run date | Enter the report run date to use. This run date enables you to run the report using forecast snapshots, which allows you to see the change in accuracy over time. |
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Options | |||||||||||
Return period details | Select this to list the values within the Months to compare indicated. | ||||||||||
Values | Indicate the values you want to print on the report.
One of the following can be selected:
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Forecast accuracy | These options are only available if you did not select to run the report using a selection set. | ||||||||||
Calendar to use | Indicate the calendar to use to calculate the periods against which forecast accuracy is calculated. | ||||||||||
Months to compare | Enter the number of months into the past to use to
compare sales history against forecasts to check the forecast
accuracy. In the calculation, the maximum number of months will be less than or equal to the months of history available. |
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Comparison type | Select either period on period or moving average
comparisons.
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Forecast to use | Select the forecast to compare to the sales. A key consideration is which forecast to use when calculating accuracy for a particular month. There may have been several forecasts made for the particular period (known as forecast shots). In general, the forecast accuracy should be based on a forecast that could influence the future. Any forecasts made inside the lead time should not be used, as such forecasts may artificially improve the accuracy. The report addresses this by allowing for several options in calculating the accuracy.
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Snapshot months | Indicate how many months of forecasts you want to use to calculate the average forecast. | ||||||||||
Return accuracy levels | Select the category or level of forecast accuracy you
want to print on the report. This is the sequence in which the
report is generated. SKU accuracy levels lists the values against each individual stock item included in the report. Stock items are listed multiple times if they are stocked in more than one warehouse. Consolidate accuracy levels lists the values against the stock items included in the report, but each item is listed only once (i.e. the values for the stock item in each warehouse are consolidated). Pareto analysis must be run for entries to be accurately listed on Pareto accuracy levels (see Pareto Analysis). |
Selection | Description |
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Warehouse selection | Indicate the warehouse(s) for which you want to generate the report. |
Stock code selection | Indicate the stock code(s) for which you want to generate the report. |
Supplier selection | Indicate the supplier(s) for which you want to generate the report. |
Product class selection | Indicate the product class(es) for which you want to generate the report. |
Buyer selection | Indicate the buyer(s) for which you want to generate the report. |
Planner selection | Indicate the planner(s) for which you want to generate the report. |
These options are only available if you are not using a selection set.
Field | Description |
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Part type |
Indicate the part types to include in the report. Phantom, Planning Bill and Notional Part types have no bearing in the IO modules and are therefore not available here. |
Pareto classification | This enables you to include/exclude items based on
their Pareto classification. You use the Pareto Analysis program to
analyse and classify inventory items. At least one of these classifications must be selected. |
Analysis type |
Indicate what the Pareto classification, for the inclusion of stock items, must be based on. This can be Sales, Current forecasts or Draft forecasts. Once you have selected an analysis type, you can select the Pareto level at which the analysis must be performed. For example, if you select Sales and Stock code, then the Pareto classification of items used for inclusion purposes will be retrieved based on sales at the stock code level. |
Sales | Select this to perform the analysis based on sales. |
Current forecasts | Select this to perform the analysis based on current
forecasts. This allows you to compare expected contribution with past contribution. |
Draft forecasts | Select this to perform the analysis based on draft forecasts. |
Pareto level |
Indicate the level at which the Pareto analysis must be performed. |
Other | Against each of the following options, you can
select:
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Manual forecast items | Indicate how manually forecasted items must be handled for the report. |
Replenishment items | Indicate how replenishment items must be handled for the report. |
MPS items | Indicate how MPS items must be handled for the report. |
Make to order items | Indicate how make to order items must be handled for the report. |
These options enable you to apply a theme to the report and to define multiple output destinations for the report once it has been compiled (SRS Output Options).
The report is generated in the sequence you selected at the Return accuracy levels option.
An entry of {Unclassified} indicates that the information is not saved in the Inventory Master file/table. For example all selected stock items that do not have the buyer defined against them are listed in the unclassified section for Buyers on the report.
The following information is included in the report:
Column | Description |
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Forecast | This indicates the forecast value for the forecast used. |
Sales | This indicates the actual sales value used to compare against the forecast value. |
Hits | This indicates the number of actual sales. |
CFE | Cumulative forecast error. This is the cumulative difference between the forecast and the actual sale(s) for the period under review. A positive number indicates a forecast that is too high for a period and a negative number indicates a forecast which is too low for the period. |
MAD |
Mean Absolute Deviation. The is the average absolute deviation from the mean (i.e. the average error, ignoring the sign of the error). |
MSD |
Mean square deviation. This is the sum of the squared forecast errors for each observation divided by the number of observations. It is an alternative to the Mean Absolute Deviation except that, because the errors are squared, more weight is placed on larger errors. |
MAPE |
Mean Absolute Percentage Error. This is calculated as the average of the sum of all the absolute percentage errors for the data set. The absolute values of the percentages are summed and the average is computed. The difference between actual value and the forecast value is divided by the actual value. The absolute value of this calculation is summed for every forecast point in time and divided again by the number of fitted points. |
Tracking signal |
This is calculated as the algebraic sum of forecast errors divided by the Mean Absolute Deviation (MAD). It indicates whether the forecast average is keeping pace with any genuine upward or downward changes in demand. |