How is the “Suggested” target value calculated in Proactive Analytics?

[Kohei Tominaga1]

Hello ServiceNow Community,

In Proactive Analytics target configuration, the Value field is pre‑populated as “Suggested”, as described in the documentation below:
https://www.servicenow.com/docs/r/now-intelligence/proactive-analytics/proactive-analytics.html

However, I could not find details explaining how this suggested value is calculated.

Could you please clarify:

• What logic or statistical method is used to derive the “Suggested” value?
• Is it based on historical data (average, trend, percentile, etc.)?
• What time range of data is evaluated?
• Does this value adjust over time or is it fixed at creation?

Understanding this would help administrators decide whether to use the suggested value and explain the rationale when questions arise.

Thank you for your support.

[Tanushree Maiti]

Hi @Kohei Tominaga1 ,

From your shared documentation, it seems it is using Predictive Intelligence at backend .

ServiceNow uses Predictive Intelligence (PI) to analyze historical data and suggest values for fields (e.g., Assignment Group, Category) or suggest solutions (e.g., Knowledge Articles).

• Machine Learning Models: PI uses classification and similarity algorithms trained on historical data, such as closed incidents.
• Precision and Recall: The model's effectiveness is calculated based on:
  • Precision: How many of the "Proposed" (suggested) values were actually correct (reducing False Positives).
  • Recall: How many of the total records that should have been classified were correctly identified (reducing False Negatives/misses).
• Confidence Thresholds: The system only suggests a value if the probability of accuracy exceeds a predefined threshold