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This section defines concepts and metrics specific to Insights. For general Itential terminology, see the following resources:
Insights distinguishes between root jobs and child jobs to provide business-focused analytics.
A root job is the top-level job in an execution hierarchy. Root jobs are not triggered by other jobs and represent complete business operations.
Why root jobs matter: The Summary Dashboard focuses exclusively on root jobs because these represent the operations your stakeholders care about. Filtering out child jobs provides clean, business-focused metrics rather than technical implementation details.
A child job is a job triggered by another job as part of a workflow’s execution. Child jobs are technical substeps that support the root job’s objective.
Example hierarchy:
In Insights: The Summary Dashboard shows root jobs only. The Workflows Overview and Workflow Details pages enable you to toggle between “Root Jobs Only” and “All Jobs” views to analyze both business operations and technical implementation.
Pre-automation time is the estimated time required to perform a workflow’s tasks manually without automation. You configure this value in Studio at the workflow level.
Pre-automation time enables Insights to:
Without pre-automation time configured, the Time Saved metric displays as empty (“--”) in Insights. See Configure pre-automation time for step-by-step setup instructions.
The following metrics are specific to Insights analytics.
The total count of jobs executed during the selected time period.
Business value: Measures Itential Platform adoption and usage growth. Upward trends indicate increasing automation, while downward trends may signal reliability concerns or reduced confidence.
The percentage of jobs that completed successfully versus those that were canceled.
Jobs in error or running states are not included. This metric measures execution completion, not whether jobs accomplished their intended business outcomes.
Calculation: (Completed jobs / Total jobs) × 100 Where Total jobs = Completed jobs + Canceled jobs
Jobs can reach completion by either completing successfully through their intended path or completing through a defined error transition or failure path.
A declining completion rate indicates that more jobs are being canceled before reaching completion. This may signal workflow design issues, timeout problems, or infrastructure constraints.
Business value: Tracks job completion reliability and identifies when cancellations are increasing, helping you spot workflow issues before they impact operations.
The cumulative execution time of all jobs in the selected time period.
Business value: This metric helps identify performance trends. Runtime increasing with stable job volume indicates performance degradation requiring investigation. Runtime and job volume both increasing proportionally shows healthy growth. Runtime decreasing with stable or increasing job volume proves successful optimization.
The cumulative manual effort avoided through automation, calculated by summing pre-automation time for all jobs.
Time saved represents the manual effort eliminated, not the difference between manual time and automation execution time. The value of automation is in eliminating manual work, regardless of how long the automation takes to run.
Calculation: Σ(Pre-automation Time for each job)
Business value: Directly quantifies ROI. Essential for executive reporting, renewal conversations, and justifying automation investments.
The 50th percentile execution time. Half of all job executions complete faster than this time, and half take longer.
Business value: Median execution times provides more accurate typical performance than average because it’s not skewed by outliers. A workflow with a P50 of 60 seconds performs consistently even if occasional jobs take 5 minutes.
Use cases:
The 90th percentile execution time. 90% of job executions complete faster than this time.
Business value: Reveals performance consistency and catches edge cases that median misses. The gap between P50 and P90 shows performance variability.
Use cases:
Example:
Jobs are counted in time periods based on their completion time, not their start time.
Why this matters: If you select “Last 30 days,” only jobs that completed within those 30 days appear in results.
Implication: When reviewing metrics for a time period, counts reflect when work finished, not when it started.
Most metrics display a percentage change indicator, referred to as the “delta” (Δ), comparing the current period to the equivalent previous period.
Symbols:
Example: Viewing “Last 30 days” compares to the 30 days immediately before that period.