You may want to exclude values in your time series data (historical or related data) that could skew your forecasts. For example, you may want to exclude values that are outliers, or zeros that represent missing data and are not true zeros.

Use the exclude values function so PlanIQ can replace undesired values with values that fit better with your data sequence. The new value is generated using automated logic and is based on where the value is in the time series. 

The exclude values function does not affect your original data, it only affects how PlanIQ interprets your data. 

To exclude values from your data collection setup and apply the automated value replacement logic:

  1. Open a historical or related data module and identify the items with the values you want to exclude.
  2. Add a new numeric line item to the module, and give this item the same name as the original item. 
  3. Add ___exclude_value  to the end of the name of this new line item.
  4. For your identified values, insert 1 beside them in the exclude value column.
    All other values remain as 0

To name the new line item, follow this format:

Original line item name + three underscores + exclude + one underscore + value


If you have a line item called Units sold, the new line item would be Units sold___exclude_value:

Units soldUnits sold___exclude_value

The table below illustrates a grid of historical data with excluded values. The excluded values are in bold italics. 

Historical sales actuals

Units soldUnits sold___exclude_value

Item 100

Item 200

Item 300

Item 410

Item 500

Item 600
Week 1 FY20Item 701

Item 800

Item 9841

Item 1000

Item 1100

Item 1200

Item 1300

Item 1400

Item 1500

Item 1610

Item 1710

Item 1800

Next, you can create an attributes module, or skip to the next section


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