Optimization Candidate Scoring

This page explains how the system scores overlicensing candidates before selecting an action.

Activity class calculation

Each assigned user/SKU seat is classified into one activity bucket:

• active_30d: recent activity inside stale threshold (default 30 days).
• stale_30_89d: no recent 30-day activity, but still active before inactive threshold (default 90 days).
• inactive_90d: report identity exists, but activity is outside threshold.
• unknown: no mapped report identity.

Weighted overlicensing formula

For each SKU:

weightedOverlicensedSeats = inactiveSeats90d + (staleWeight * staleSeats30to89d)

Default staleWeight is 0.5.

Why this exists:

• inactive_90d seats are treated as strong reclaim candidates.
• stale_30_89d seats are treated as weaker signals and discounted.

Candidate priority score

Priority score is used to rank candidates for operator attention:

score = (reviewPressureSeats / assignedSeats) * 100
      + waitingMembersCount * 10
      + assignmentErrorCount * 8
      + (nearDepleted ? 12 : 0)
      + assignedByRank * 2
      + activityBonus
      + activationPenaltyBonus
      - rankWithinSku * 0.01

Where:

• activityBonus: +30 for inactive_90d, +16 for stale_30_89d.
• activationPenaltyBonus: +6 when identity is mapped but no activation evidence exists.
• assignedByRank: direct=3, inherited=2, group=1.

Why this exists:

• Seat pressure (queues/errors/depletion) increases urgency.
• Inactivity and no activation evidence increase reclaim confidence.
• Direct assignments are prioritized because they are usually easiest to reclaim quickly.

Confidence calculation

Confidence is computed from report availability and mapping completeness:

• No report snapshot: low.
• Reports available but stale/partial: medium.
• Reports fresh and mapping complete (>=95% mapped seats): summary can be high.
• A candidate is high only when summary is high and that specific user maps to report identity.

Why this exists:

• It prevents aggressive actions when telemetry quality is weak.
• It supports safer defaults (review_only) when evidence is incomplete.