Lookup Tables are customized tables that house values based on multiple sets of criteria, where the output value represents the intersection of multiple dimensions.
Lookup Tables:
- Contain a table of values based on multiple sets of criteria where the stored values represent the intersection of multiple dimensions.
- Are also known as Multi-Dimension Lookup Tables (or MDLTs). They locate values as a result of the intersection of multiple dimensions or axes.
- Are constructed using dimensions and indices.
- Can be populated manually or through data loads.
The following image is an example. In this case, the Region, Products, and Sales Status are the Dimensions.
This Lookup Table tells the system the commission rate is 4%, when the Region is EMEA, the Product is Bikes, and the Sales Status is Silver. The value returned can be used in the Incentive Rule.
Lookup Tables vs Rate Tables
Some similarities exist between lookup tables and rate tables. The following matrix shows the differences and similarities between the two and may help you decide when to use each one.
| Rate Tables | Lookup Tables |
|---|---|
| Easy to set up | Complex initial setup |
| Handles step commission | Does not handle step commission |
| Only calculates commission rates based on attainment or a calculated result | Can calculate any numeric value based on any input of any data type including strings and categories |
| Can only be used in Incentive Rules | Can be used in any rule or formula |
| Can be effective dated | Each individual cell in the matrix can be effective dated |
Best Practices for Lookup Tables
- Map out your lookup table before creating them.
- If you leave values null, check the box to make all null values zero or use conditioning to ensure a rule does not attempt to calculate using a null value.
- Avoid many nested Lookup Table references. Keep them as simple as possible.
- Use Lookup Tables when the list of indices is relatively static.

