Performance Analytics (PA) is one of the most powerful but most misused capabilities in ServiceNow. Dashboards are easy to build. Dashboards that correctly represent what is actually happening in your processes are much harder. This article covers both.
Understanding Indicators vs Reports
The fundamental confusion: PA Indicators are not the same as Reports. Reports query live data. PA Indicators collect snapshots on a schedule and track change over time. This distinction matters enormously for what you should use each for.
Use PA when you need:
- Historical trending (how has our P1 volume changed over 6 months?)
- Score targets and thresholds
- Breakdown by dimension over time
Use Reports when you need:
- Current state snapshots
- Ad-hoc analysis
- Data exports
Key Indicator Types
Automated Indicators
Collect data automatically from ServiceNow tables on a schedule. Best for operational KPIs — incident volume, resolution time, SLA compliance.
Manual Indicators
Data entered by users. Use sparingly — manual data entry is unreliable and creates maintenance burden. Only use when the data genuinely cannot be automated.
Derived Indicators
Calculated from other indicators using formulas. Use for ratios and rates — SLA compliance percentage, first contact resolution rate, cost per incident.
Breakdown Sources
Breakdowns let you slice an indicator by a dimension — by assignment group, by category, by location. Configuring breakdowns correctly is the difference between a useful dashboard and a meaningless one.
// Example: Incident volume broken down by assignment group
Indicator: Active Incident Count
Table: incident
Condition: active=true
Aggregate: COUNT
Breakdown Source: Assignment Group
Breakdown Field: assignment_groupLimit breakdowns to 20-25 values maximum. More than that and the charts become unreadable and the data collection becomes slow.
Common Mistakes That Make Dashboards Misleading
1. Not accounting for data collection time
PA collects snapshots — if your indicator collects at midnight and you look at the dashboard at 3pm, you're seeing yesterday's state. Always label dashboards with when data was last collected.
2. Mixing current and historical data
Showing "current open incidents" next to "incidents closed last 30 days" on the same dashboard mixes point-in-time and period data. The comparison looks meaningful but isn't.
3. SLA compliance calculated wrong
SLA compliance percentage = (SLAs met / total SLAs) × 100. A common mistake is calculating it as (SLAs met / active SLAs) which excludes already-breached SLAs and artificially inflates the percentage.
4. Target lines set incorrectly
For indicators where lower is better (MTTR, breach count), the target line should be below the current value. Dashboards where every metric is green regardless of actual performance are actively harmful — they give leadership false confidence.
The Dashboard Design Principles That Work
- No more than 7-8 widgets per dashboard — information overload makes everything invisible
- The most important metric goes top-left — that's where eyes go first
- Use colour consistently — red always means bad, green always means good, across every widget
- Every dashboard should answer one question — not six questions
- Include a timestamp showing when data was last refreshed
Useful Built-in PA Indicators to Enable
- ITSM — Incident volume by priority and assignment group
- ITSM — Mean time to resolve by category
- SLA — SLA compliance percentage by service
- CMDB — CI compliance score over time
- Change — Change success rate by change type
These are available in the Performance Analytics Content Pack and are significantly faster to enable than building from scratch.