Some values in your historical or related data may skew your forecasts. Examples for such values include outliers and zeros that represent missing data and aren't true zeros.
The exclude values functionality can replace undesired values with values that fit better with your time series data. The new values are generated with the use of an automated logic and are based on where the values are in the time series.
To use the exclude values functionality, follow the instructions detailed in Stage 1: Create PlanIQ modules. Then, return to this page and follow the instructions below.
Note: The exclude values functionality does not affect your original data, and only affects how PlanIQ interprets your data.
To use the exclude values functionality:
- Open the historical or related data module that contains values you want to replace.
- Add a new numeric line item to the relevant module, and give it the same name as the original line item. Then, add the string ___exclude_value to the end of the name of this new line item.
To name the new line item, follow this format:
Original line item name + three underscores + exclude + one underscore + value
Example:
If you have a line item called Units sold, the new line item would be Units sold___exclude_value:
- Identify the forecast items with the values you want to exclude, and insert 1 to the new exclude value line item. All other values remain as 0.
The table below illustrates a grid of historical data with excluded values. The excluded values are in bold italics.
| Historical data | |||
| Units sold | Units sold___exclude_value | ||
| Item 1 | 0 | 0 | |
| Item 2 | 0 | 0 | |
| Item 3 | 0 | 0 | |
| Item 4 | 1 | 0 | |
| Item 5 | 0 | 0 | |
| Item 6 | 0 | 0 | |
| Week 1 FY20 | Item 7 | 0 | 1 |
| Item 8 | 0 | 0 | |
| Item 9 | 84 | 1 | |
| Item 10 | 0 | 0 | |
| Item 11 | 0 | 0 | |
| Item 12 | 0 | 0 | |
| Item 13 | 0 | 0 | |
| Item 14 | 0 | 0 | |
| Item 15 | 0 | 0 | |
| Item 16 | 1 | 0 | |
| Item 17 | 1 | 0 | |
| Item 18 | 0 | 0 |
