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Victor Chen
ServiceNow Employee

You can measure the assists consumption across your user's department via using Platform Analytics, breakdowns, and the department field on the User table. 

 

VictorChen_0-1784132469658.png

See the companion article on how to measure cumulative assists and agentic assists consumption plus forecasting here: https://www.servicenow.com/community/now-assist-articles/build-an-assists-and-agentic-assists-foreca... 

 

Part 1 — Create the Indicator Source

The indicator source defines the dataset: the sys_gen_ai_usage_log table contains the assists consumed per Now Assist execution. 

  1. Navigate to All > Platform Analytics Administration > Data Sources > Indicator Sources and select New.
  2. In the Name field, enter something descriptive like Cumulative assists source.
  3. Add a Description, e.g., Daily records from the Gen AI Usage Log table for assists consumption tracking.
  4. In the Calendars field, leave it set to the Standard calendar.
  5. In the Valid for frequency field, select Daily.
  6. In the Facts table field, select sys_gen_ai_usage_log (the Gen AI Usage Log table).
  7. Under Conditions, add:
    • [Created] [at or before] [Today]
    • AND
    • [Created] [at or after] [accumulation start date]
      This ensures the data collector fetches records created today and prior for historical record. And depending on your entitlement start date or your choice of accumulation start date, this is when assists cumulative sum will start at "0" and begin accumulating. Assists usage resets annually based on a customer's contract anniversary date, so the accumulation start date may have to be manually reset every year. 
  8. On the top bar, right-click and Save.

Part 2 — Create the Automated Indicator

The indicator will aggregate the count of assists from the indicator source.

  1. Navigate to All > Platform Analytics Administration > Indicators > Automated Indicators and select New.
  2. In the Name field, enter something like Assists by Dept.
  3. Add a Description
  4. Under Indicator properties, set Direction to Maximize (more assists consumed over time is directionally increasing).
  5. Set Unit to Number (#).
  6. Click the Source tab and select your indicator source from Part 1 (Cumulative assists source).
  7. In the Aggregate field, select Sum 
  8. In Field field, select Assists
  9. Check Collect records so you can drill down from the chart later if needed.
  10. Expand the context menu and click Save.
  11. Then in the Jobs related list, associate the appropriate data collection jobs, be sure the jobs are set to Active = true:
  • A Historic job (run once to backfill past data. Run again AFTER you configure the breakdown below.)
  • A Daily scheduled job (run daily going forward, collecting the previous day's data)

Execute the historic job immediately to populate the chart with past data.

 


Part 3.1 — Configure the department Breakdown Source

 

  1. Navigate to All > Performance Analytics > Breakdown Sources and click New.
  2. Name: GenAI.UsageLog.User.Department
  3. Description: Departments derived from the User field on the Gen AI Usage Log table, for breaking down assists by department.
  4. Facts table: cmn_department 
  5. Field: Sys ID — this field contains a unique value for every record, which is required
  6. Optional: Under Conditions, add a filter to exclude inactive departments:
    [Active] [is] [true]
  7. Click Preview to verify the department records returned look correct.
  8. Click Submit.

Part 3.2 — Create the Automated Breakdown

  1. Navigate to All > Performance Analytics > Automated Breakdowns and click New.
  2. Name: User.Department
  3. In the Automated tab, select the breakdown source you just created: GenAI.UsageLog.User.Department
  4. Leave Default elements filter blank unless you want to restrict which departments are visible by default.
  5. Right-click the form header and click Save — do not submit yet, as you need to add the mapping next.

Part 3.3 — Create the Breakdown Mapping

  1. On the breakdown record you just saved, scroll to the Breakdown Mapping related list and click New.
  2. Facts table: sys_gen_ai_usage_log — this is your indicator source table
  3. In the Field table, scroll down to User, then expand the field tree to then select Department. 

VictorChen_0-1784145353111.png

 

This dot-walks from the user reference field on sys_gen_ai_usage_log through to the department field on sys_user, and returns the sys_id of the department record — which matches the sys_id elements in your breakdown source.

  1. Click Submit.

Part 3.4 — Assign the Indicator to the Breakdown

  1. Navigate to All > Performance Analytics > Automated Breakdowns and open the User.Department breakdown.
  2. Scroll to the Indicators related list and click Edit.
  3. In the slushbucket, find and move Assists by Dept to the selected column.
  4. Click Save. (Or vice versa, from the Indicator, navigate to the Breakdowns related list, click Edit, and select the breakdown from the slushbucket.)
  5. If you haven't already, run the historical job to populate data, which should include breakdowns. 

Part 4 — Create the Dashboard with a visualization of assists consumed by department

 
  1. Navigate to All > Platform Analytics > Library > Dashboards.
  2. Select Create new dashboard.
  3. Give it a name (e.g., Assists Consumption by Department) and save.
  4. The dashboard opens in edit mode automatically.
  5. In the dashboard editor, select Add new element. Select Data Visualization > New data visualization.
  6. To create the chart that shows vertical bars by department, in the Visualization Designer, select Visualization type as "Vertical". 
  7. Select Add data source and choose Indicator = Assists by Dept indicator. 
  8. In the Metric section, leave as default
  9. In the Group by section, select from dropdown: User.Department
  10. Click Save on the top-right. 
  11. To create the chart that shows the increasing assists consumption over time with stacked bars for department, in the Visualization Designer, select Visualization type as "Time Series > Columns". Data sources, Metric, and Group By are the same as above.
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