Global Demand Forecast Settings

The Global Demand Forecast settings screen controls various system-level ("global") settings in your StockIQ forecasting configuration.

It is accessible by clicking on Admin --> System Configuration --> Global Demand Forecast Settings

General Settings

• Top-Down Disaggregation Mode - This sets how forecasts are distributed when you save them from a top-down level.
  • Skip Overridden Child Forecasts - This is StockIQ's default.  Any children with their own overrides are skipped, reducing your initial total forecast.
  • Prorate For Overridden Child Forecasts - Your top-down value is preserved, as are child forecast quantities.  The total to each child node is adjusted to make sure the final total is the same as your initial quantity.
    • WARNING:  This can lead to warnings/errors if your new total is less than the sum of child forecast totals, and StockIQ will warn you of this.
• Fair-Share Weight Method- This sets how you'd like top down forecasts to be distributed across children in the hierarchy
• Operational Forecast Series - StockIQ supports multiple forecast series.  Generally, you will have just one, so for most folks this is always going to be the first, default, Independent Forecast series.
• Sales Forecast Series - Specifically determining which forecast series, if any, is particular to salesperson input.  This is a placeholder for future features.
• Budget Forecast Series - Specifically determining which forecast series, if any, is particular to accounting/finance's input.  This is a placeholder for future features.
• # Years Forecast History - How many years of history to consider when generating forecasts.  3 years is a good guideline here
• # Years of Future Forecast - How far into the future should we generate forecast.  2 years is usually more than enough here.

Forecast Error

• Error Calculation - which error calculation to use, MAE% (Mean Absolute Error Percent) or RMSE (Root Mean Squared Error).  For more discussion on which one to use, see the Forecast Error KPIs topic.
• Error Sample Length - What duration to use when calculation the standard error numbers shown in the application, such as on the Forecast Manager Forecast Errors tab.  One Quarter, 6 months, and 1 year are the available options.
• Low Error Max - Sets the threshold for what you consider "Low" forecast error.
• Medium Error Max - Sets the threshold for what you consider "Medium" forecast error.
• High Error Max - Sets the threshold for what you consider "High" forecast error.  These three settings affect coloring/highlighting in the Forecast Error tab.

Other Settings

• Fair Share Weight # Months History - Allows you to configure how many months are used when evaluating the fair-share-weights to be used in top-down forecasting and the resulting distribution of top-down forecast.
• Monthly Forecast Snapshot Target Day- Sets which day of the month Demand Forecast Snapshots are captured
• Re-Apply New Fair Share Weights Each Period - When you have a manual forecast, when you save a top-down manual forecast, you can select that this forecast is locked in time, or, when enabled, this will re-apply your top-down forecast according to changing fair-share weights over time, so that the distribution of your forecast to the children of your top-down forecast stays updated as buying mixes change.
• Calculate Customer-Specific Average Costs & Prices - When enabled, StockIQ will look at historical demand data and calculate expected per-customer average cost and price information for use in Revenue and COGS forecasting.  It starts by looking at the last 3 months of data.  If no data is found, we will go to 6 months, and finally to 12 months of data to try and find item-site-customer history.  If no data is found, or when this option is disabled, item-site level values from the history table are used only, and if no history is available, current-day StandardCost and Standard Price values are used.
• Allow Zero As Valid Cost Or Price? - Allows zero cost or revenue values to be marked as valid data points instead of being marked as missing data points
• Adjust Model for Future Sales - StockIQ has the option of upwardly adjusting the statistical model in response to future sales, if those future sales are higher than what the model called for.  This is useful if you are doing forecast consumption in your Replenishment Forecast Series settings, but is generally not used.
• Calculate Depletion Forecasts - When an item is detected as discontinued, this option enables calculation of a depletion forecast, so you can predict when on-hand and demand will drop to zero for the product.  See the Discontinued Items screen for more.

Seasonality Detection

These settings control how items are marked as no, low, or medium seasonality in StockIQ:

• Min Avg Annual Quantity - Very low volume items can sometimes appear, coincidentally, to be seasonal, when in fact they just have sporadic demand.  This filter sets a lower limit on how many sales per year the item must have on average to be considered for seasonality.  Lowering this value makes an item more likely to be considered for seasonality.
• Min Months of Demand History - Specifies the minimum length under which an item is not evaluated for seasonality.  This is in place because StockIQ must have some amount of year-over-year overlap to be able to determine the difference between yearly seasonality and simple variation in demand.
• Seasonality Min. Correlation Threshold - Specifies the minimum value of year-over-year correlation under which an item is considered to be even mildly seasonal.  Items with 1.0 correlation are 100% seasonally correlated, items with 0% or less have no evident correlation for year-over-year demand.  Raising this limit makes items less likely to be considered for mild seasonality.
• High Seasonality Min Correlation Threshold - Specifies the minimum value of year-over-year correlation under which an item is considered to be highly seasonal.  Items with 1.0 correlation are 100% seasonally correlated, items with 0% or less have no evident correlation for year-over-year demand.  Raising this limit makes items less likely to be considered for the special highly seasonal method of the StockIQ forecast algorithm.
• High Seasonality - Min Std Dev of Demand - Specifies a minimum standard deviation above which variation of actuals must be to be considered for seasonality. Lowering this makes seasonality
  more likely to be allowed, whereas raising it means more items will be set to no/flat seasonality.  This test primarily affects very low volume items, to prevent very low volume items from being falsely detected as seasonal among slow or sporadic demand

Under & Over Forecasted Reports

These settings control how much data is generated on the under and over forecasted reports, such as what is considered an under- or over- forecast, whether to alert on current period settings, and so on.

• Tolerance Factor - This factor, expressed in terms of a number of standard deviations, specifies how tight the limits are on what StockIQ considers out-of-range for the under or over forecast comparison.  A higher tolerance factor allows a wider variance before an alert is generated.  Standard Deviation here is used since it is more useful than a flat percentage, since different items have different amounts of observed variability in their demand history.
• Over/Under Periods Back - How far back to be checking for over- and under-forecast records.  This determines how much data you see in the report.  One quarter is pretty typical.  By limiting this threshold, you can avoid getting alerts for periods from 6-12 months ago if you don't want to make adjustments for those.
• Alert on Low-Volume Items - Allows you to disable the alert for items with less than 1 unit per period of forecast.  Generally recommended to avoid getting alerts that are not helpful for items that don't matter much.
• Alert On New Items - Allows you to suppress alerts for new items, since they will almost surely have periods outside limits, as there is limited data. Once the item is not new, alerts will appear.
• Alert On Sporadic Items - Allows you to suppress alerts for items with sporadic/slow/dead usage types, since most activity for those items will be outside of forecast expectations.  However, notifications for activity on such items can be useful.
• Alert on Non-Forecast Policies - Allows you to set whether you want to see alerts for over/under forecast on items that are set to order policies that do not use forecast, such as Buy To Order, Min/Max, Build To Order, etc.
• Show For Current Period - Sets if you want to see under and over forecasted alerts for current period or not
• Show for Future Periods - Sets if you want to see under and over forecasted alerts for future periods or not.
• Min % Thru Period - Specifies how far the period you must be before current period forecast vs actuals messages begin generating.  This is intended to prevent getting messages that are not helpful just a few days into a month or week.

Forecast Export Settings

StockIQ provides standard forecast export tables in easy-to-read formats.  These settings control what data is published into these tables.  By default, no data is outputted, so you must turn these options on if you will make sure of the outputted data.   Item-Site, and Item-Site-Forecast-Group level detail is available for both independent and dependent forecast, published to tables in the "dato" schema for data output in the StockIQ database.  Please contact StockIQ for more information on consuming these tables.

• Forecast Summary Update Frequency - how often you would like these tables updated.
• # Years to Export - How many years of historical forecast to publish to the output tables.
• # Years of Future To Export -  How many years of future-dated forecast to publish to the tables.
• Generate Monthly Export - enables or disables monthly forecast summary table creation.  Disabling saves some startup/calculate/refresh time.
• Generate Weekly Export - enables or disables weekly forecast summary table creation.  Disabling saves some startup/calculate/refresh time.