Default Value Usage

Plauti Context Analysis Types

Last published at: June 8th, 2026

Measure how frequently a field's predefined default value remains unchanged across records.

 

The Default Value Usage analysis type analyzes fields that have a configured default value, such as a picklist, checkbox, text, or number. It then calculates what proportion of records still hold that default value. 

Only records that contain a value are included; blank records are excluded from the calculation. Furthermore, formula and calculated fields are excluded from this analysis. 

Use this analysis to identify whether users are actively engaging with a field, or simply accepting the default without review. Alternatively, the default value could be rightfully used almost all the time, indicating that the field itself might not be worth keeping.

Configuration

In Library Analyses you might want to disable this analysis type for fields where it's normal and expected to have the default value remain unchanged, unless you want to monitor for unexpected changes in default value usage over time.

Set a threshold for what constitutes a good, warning level, or critical default value usage rate. This can differ quite a bit per field; for example 90% of Cases can probably indeed keep their “Standard” default value, while for other fields the default value might need to be changed far more often according to your processes.


Threshold setting for a field that is expected to have its default value changed in most cases, according to procedures.

Detailed Job Results

The bar chart shows, for each field with a default value set, the percentage of records that still carry that default value. Records with no value at all for the field are not taken into account.

In the Field Details table the percentage of records using the default value is displayed again, color-coded by the threshold settings (green for Good, orange for Warning, red for Critical).

Key Insights

  • Passive fields: a high percentage of records retaining the default, higher than expected according to processes, can indicate that users are not actively engaging with the field. It might be irrelevant to their workflow, or they skip over it because of time constraints or too many fields. Alternatively, the default value might be the right value for the record more often than you'd expect it to be.
  • Active fields: fields where a large share of records overrides the default indicates that users are actively engaging with the field. However, this can mean that the default value is not appropriate and may need revisiting.
  • Impact on reporting: if most records have the same default value, reports and filters on that field provide little to no segmentation. Furthermore, it can be misleading if report recipients assume that the value was actively chosen instead of a predefined default value.
    On the other hand, if the default value is hardly ever kept, the field likely has good analytical value. Use the field in routing rules, reporting filters, and scoring or segmentation.
Scenario Actions
More default values than expected (passive fields)
  • Confirm whether the default value is correct for the records that have it
  • Update field labels and add help text to clarify when to override the default value
  • Adjust the page layout so the field is better visible
  • Change the default value to a neutral placeholder (e.g. “— Select —”) if possible
  • Consider making the field required with no default for key flows
  • If the field is not useful, deprecate or hide it
Fields with high override rate (active fields)
  • Check if the default needs changing to a value that is used more often, to make it easier to fill out records. You can use the Value Distribution analysis for this.
  • Or remove the default value altogether if the field is critical.
  • The field likely has good analytical value since many records deviate from the default. Use it in routing rules, reporting filters, and scoring or segmentation.
Protecting reports and process logic
  • Avoid basing key KPIs, executive dashboards, critical SLAs or routing rules on fields that are default‑dominated without clear business intent, and give preference to active fields.
  • Mark passive fields as ‘low-signal’ in your data dictionary.
Preparing data for AI or scoring models
  • Exclude or down-weight fields where almost all values equal the default.
  • Prefer fields with healthy default override rates; they reflect real user or process behavior.
  • Create and populate default value flags such as:
    Is_Default_Value__c (checkbox)
    Default_Usage_Rate__c at field level (for documentation / model feature selection)
    and use them when building AI models to filter out fields with a high default value usage rate.