System Usage Details
The System Usage Details report page presents the visuals listed below. Each row gives the on-screen name, its underlying metric, and a short description; see the metric glossary for the full formula and interpretation.
Visuals:
| Name | Measure | Description |
|---|---|---|
| % Logged in (managers) | Count of distinct managers who signed in÷ count of all managers | Login rate among managers; i.e. of the people flagged as managers, the share who signed in. It isolates manager engagement, which matters because reviews, approvals and comp steps wait on them, so a low value is an early warning for stalled workflows. Compare with % Workers Logged In to see whether managers show up more or less than their reports. |
| % Logged in (workers) | Count of distinct non-manager workers who signed in÷ count of all non-manager workers | Login rate among individual workers who are not managers; i.e. of the non-managers, the share who actually signed in. It isolates rank-and-file adoption from managers, so a low value points to the wider workforce not engaging even if leadership does. Read it against % Managers Logged In to compare turnout between the two groups. |
| Used the Feedback feature (managers) | Count of distinct managers who sent or requested feedback÷ count of all managers | Share of managers who actively used the feedback feature by either giving or requesting feedback. It's an adoption measure of active participation, so a manager who only received feedback (never sent or requested) is not counted. A manager who both sent and requested is counted once. Read against the worker rate ( % Workers used feedback ) to see whether managers model feedback more than their reports. |
| Used the Feedback feature (workers) | Count of distinct non-manager workers who sent or requested feedback÷ count of all non-manager workers | Share of individual contributors (non-managers) who actively used the feedback feature by either giving or requesting feedback. It's an adoption measure of active participation, so a worker who only received feedback (never sent or requested) is not counted. A worker who both sent and requested is counted once. Read against the manager rate ( % Managers used feedback ) to see whether the wider workforce engages with feedback as much as leadership. |
| Used the Goals feature (managers) | Count of distinct managers who own at least one goal÷ count of all managers | Goal-setting adoption rate among managers; i.e. of the people flagged as managers, the share who own at least one goal. It gauges whether leadership is modeling goal-setting. Compare with the worker gauge to see if managers are ahead of or behind their reports. A low value is worth attention since managers not setting goals often cascades to their teams. Shared goals: this counts goal owners, so a goal only counts for the person who owns it. A goal shared with a manager does not make them "having goals"; only goals they own do (and a goal the manager owns and has shared out still counts for them). Own goals only, by owner attribution. |
| Used the Goals feature (workers) | Count of distinct non-manager workers who own at least one goal÷ count of all non-manager workers | Goal-setting adoption rate among individual non-manager workers; i.e. of the workers who are not managers, the share who own at least one goal. It shows whether the wider workforce is setting goals, independent of leadership; compare with the manager gauge to see if the two groups track together. A low value flags rank-and-file disengagement from goal-setting even if managers are active. Shared goals: counts goal owners only, so a goal shared with a worker does not make them "having goals"; only goals they own do (a goal they own and shared out still counts). Own goals, by owner attribution. |
| Used the Check-ins feature (managers) | Count of distinct managers who took part in a check-in÷ count of active managers | Share of managers who participated in at least one check-in, i.e. check-in adoption among managers. It puts # Managers having check-ins in context so it compares fairly regardless of how many managers there are; a low value flags managers not using check-ins with their teams. A manager with many check-ins still counts once in the numerator. Read against the worker equivalent to see whether managers drive check-in use. |
| Used the Check-ins feature (workers) | Count of distinct non-manager workers who took part in a check-in÷ count of active non-manager workers | Share of individual contributors (non-managers) who participated in at least one check-in, i.e. check-in adoption among the wider workforce. It puts # Workers having check-ins in context so it compares fairly regardless of team size; a low value flags rank-and-file staff not using check-ins. A worker with many check-ins still counts once in the numerator. Read against the manager equivalent to see whether check-in use sits with managers or their reports. |
| Total active users | Count of worker IDs | Number of users in scope, used as the denominator for the adoption percentages (for example % users having plans ). It sets the "out of how many people" baseline, so every share on the page is read against it. Filtering to a team or org unit re-bases it to that population. |
| Last data refresh | Timestamp of the most recent successful data refresh | Shows when the report data was last refreshed, so readers know how current every figure on the page is. It is a freshness stamp, not a business metric. Read against your expected refresh schedule to spot stale data. |
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For more information about the visuals and metrics used in Analytics Hub, refer toVisuals in Analytics hub and Metric dictionary, respectively.