Core Performance Metrics
While every organization tracks promotional performance a bit differently, the table below outlines the most common KPIs and how they are calculated in your dashboards. Note that all "days" calculations are calendar days. We also exclude, by default, canceled and rejected jobs to avoid skew.
| Metric | Definition | How Calculated | What it Measures |
|---|---|---|---|
| # Jobs Approved | Number of jobs that completed an approval workflow | Distinct count of jobs with that reached an approved lifecycle state | Throughput |
| First Pass Approval | Percentage of jobs that reached an approved state with only 1 circulation | Count of approved jobs with 1 circulation divided by count of all approved jobs | Content quality |
| Job Duration (Days) | Elapsed days from when the job started to when it was completed | Difference between two timestamps: Date started and date completed | Speed to market |
| Avg Circulations | Number of circulations required to complete the job | N/A - references count of circulations on job record | Content quality |
|
Review Duration (Days) or Days in Review |
Total time the job was in a review step between start and approval (across all circulations) This metric excludes time spent by the preparer of the job (upload, substantiation, incorporating feedback) |
Sum of elapsed time (days) the job was in a review step of any kind | Review team speed |
| Incorporating Feedback Duration (Days) | Total time the job was in the "incorporating feedback" stage (across all circulations*) | Sum of elapsed time (days) the job was in the "incorporating feedback" stage | Content preparer/submitter speed |
| Task Duration (Days) | Elapsed days the user took to complete an assigned task | Difference between two timestamps: When the task was assigned and when it was completed | Task velocity |
| The below variations are applicable for customers with outside-system dependencies, such as external health authority submissions, that would otherwise inflate the reported workflow runtime | |||
| Days to Internal Approval |
Elapsed days from when the job started to when the custom-defined "internal approval" workflow step completed This metric includes time spent by all parties involved (preparer, agency, coordinator, reviewers) |
Difference between two timestamps: Date started and date the custom-defined "internal approval" workflow step completed | Speed to internal approval |
| Internal Review Duration (Days) |
Total time the job was in an internal review step between start and approval (across all circulations)
|
Sum of elapsed time (days) the job was in a review step among those scoped to the customer's definition of "internal review" | Internal review team speed |
*When a job has multiple circulations, the calculated duration is the average across the circulations.
For example, a job with the below would have an Average Incorporating Feedback duration of 3.5
- Job 2:
Circulation 1, 2 days incorporating feedback
Circulation 2, 5 days incorporating feedback
Aggregations: Average vs. Median
Most of the core metrics above are aggregated as averages and/or medians.
To get a complete picture of your promotional review process, it is best to look at both the average and the median. Depending on the specific questions you are trying to answer, each metric provides a different, valuable perspective.
Average (Mean): Reflects the overall total of all jobs combined. Because it factors in every single data point, it is highly sensitive to outliers—meaning a few jobs that took an exceptionally long or short time will heavily skew this number.
Median: Represents the exact middle value of your dataset. Because promotional review timelines are often unevenly distributed, the median offers a more accurate look at a "typical" job outcome by minimizing the influence of extreme outliers.
💡 Example
If your company’s average job duration is 17 days but the median is 8 days, this gap tells a specific story:
The median reveals that half of your jobs are actually wrapped up in 8 days or less.
The high average tells you that a small handful of jobs took an exceptionally long time, dragging the overall mean upward.
Relying on just one of these metrics would hide this operational reality.
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