DLP Escalation Dashboard / Customer Escalations

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SLA Targets
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MTTR Targets
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Project

Reported vs Resolved — by Severity

SLA Compliance — by Severity

Escalation Tickets

Projects: NEO · DPS
Key ↕ Severity ↕ Status ↕ Customer ↕ Summary Assignee ↕ Created ↕ Age / Resolved ↕
Project

Reported vs Resolved — by Severity

SLA Compliance — by Severity

Escalation Tickets

Projects: DLP · FSM
Key ↕ Severity ↕ Status ↕ Customer ↕ Summary Assignee ↕ Created ↕ Age / Resolved ↕

Team Score — How It Works

The Team Score (0–100) measures how well a team is handling customer escalations. It combines four components, each severity-weighted so that Showstopper failures count far more than Major ones.

TeamScore = 0.40 × ComplianceScore + 0.25 × SpeedScore + 0.25 × BacklogScore + TrendBonus ← −5 to +5 pts Severity weights: Showstopper = 5 · Critical = 3 · Major = 1

Component Definitions

1. SLA Compliance Score (40%)

The most important signal — are tickets being resolved within the committed deadline?

comp_p = tickets_met_SLA_p / (closed_p + open_past_SLA_p) ComplianceScore = (5·comp_SS + 3·comp_CR + 1·comp_MA) / 9 × 100

Open tickets already past their SLA deadline count as definite breaches, not just "pending". This prevents a team from hiding poor performance behind unresolved tickets.

2. Speed Score (25%)

How efficiently are tickets resolved relative to their SLA target? Resolving faster than the target earns full marks; resolving at 2× the target earns 50%.

speed_p = min( SLA_target_p / MTTR_p , 1.0 ) ← capped at 1 SpeedScore = (5·speed_SS + 3·speed_CR + 1·speed_MA) / 9 × 100

3. Backlog Health Score (25%)

Penalizes teams that let open tickets accumulate past their SLA deadline without resolving them.

overdue_ratio_p = open_past_SLA_p / max(total_open_p, 1) BacklogScore = (5·(1−over_SS) + 3·(1−over_CR) + 1·(1−over_MA)) / 9 × 100

4. Trend Bonus (±5 pts)

Rewards improvement and penalizes regression. Computed by comparing average MTTR across the two most recent time buckets, severity-weighted.

TrendBonus = +5 (MTTR improving > 10% vs previous period) = 0 (stable, ±10%) = −5 (MTTR worsening > 10% vs previous period)

Grade Scale

GradeScoreMeaningAction
A85 – 100Excellent — team is consistently meeting or exceeding SLAMaintain process, share best practices
B70 – 84Good — minor gaps in compliance or backlogReview 1–2 recurring miss patterns
C55 – 69Needs improvement — compliance or backlog has visible issuesSet improvement targets per severity
D40 – 54At risk — SLA breaches are frequent, open tickets stacking upEscalate to management, review capacity
F0 – 39Critical — team is consistently failing on escalationsImmediate intervention required

SLA Targets

Default SLA targets are set based on severity impact. You can adjust them in the filter bar above — all scores and charts update in real time.

SeverityDefault SLAWeightRationale
Showstopper3 days5×Customer-impacting outage or total loss of function — requires immediate R&D response
Critical7 days3×Major feature broken, significant customer impact — high urgency but workaround may exist
Major14 days1×Functional issue with manageable impact — standard resolution timeline

Data Source

Data is fetched from Jira (forcepoint.atlassian.net) for the Escalation issue type across four projects:

TeamProjectsTab
DLP CloudNEO · DPS☁️ DLP Cloud
DLP OnPremDLP · FSM🖥️ DLP OnPrem

The ticket table at the bottom of each tab is the raw data source. Use the Time Range filter to compare performance across different periods.