Active Picklist Value Distribution

The Active Picklist Value Distribution analysis reviews picklist fields, and reports, per active value, the number and percentage of records that use it. This makes it easy to see whether usage is spread evenly across a field's active values, or concentrated in just one or two.

Use this analysis to evaluate whether a picklist's active values are being used as intended, or whether the field needs cleanup, consolidation, or better defaults.

Detailed Job Results

For each analyzed picklist field the Active Values by Field doughnut chart shows its top active values by usage. Hover over a chart section to see the details per value, such as the number of records using it and the percentage of total records it represents.

Below in the Field Summary table, the details of each picklist field are displayed: the number of active values for that field (Total Active Values), and the number of records using one of those active values (Records with Value). Tick or untick a field to display or remove it as a doughnut chart above.
Fold open a field row to see the details per field value, including the number of records with each value as a percentage of all records with a value (Percentage).

Key Insights

• Usage concentration: See which active values are used the most, and which are barely used at all.
• Overreliance on generic values: Detect overuse of catch-all options like "Other" or "Unknown", which can hide the real reason a record was categorized that way.
• Configuration feedback: Discover picklists that carry more active values than users actually need, or values that could be renamed, merged, or deprecated.
• Analytics and AI readiness: A field where one value dominates carries little predictive power for segmentation, reporting, or scoring models.

Recommended Actions

Scenario	Actions
One or two values dominate the field	- Check whether the dominant value is a default, a catch-all, or a sign that users are unsure which option to pick. - Adjust the default value or page layout to guide better selection instead of users leaving it at the default value. - Clarify field labels and help text.
Some active values are rarely used	- Decide whether the value is still needed. - Consider merging it into a related value or deprecating it.
Preparing the field for reporting or segmentation	- Group or hide near-unused values in reports. - Avoid letting an overused "Other" value skew key metrics. - Re-run this analysis after cleanup to confirm a healthier spread.
Preparing the field for AI or scoring models	- Review whether the field has enough meaningful variety to be useful as a model input. - Treat heavily skewed picklists with caution in feature engineering.