Analyzing Service Desk Metrics
Understand and interpret service desk metrics in the Harmony Dashboard: ticket volume, response and resolution times, SLA compliance, and ticket breakdowns.
Path: /dashboard
Tracking Service Desk Overview
The dashboard surface key service desk metrics at a glance. Add these widgets to monitor current state:
Tickets Opened
Number of tickets created in the selected date range
Open Tickets
Current count of tickets in open or active states (Open, In Progress, Pending)
Unassigned Tickets
Current count of tickets without an assignee
SLA Breached
Current count of open tickets that have exceeded their resolution SLA deadline
These metrics use live data from your service desk and update when you refresh.
Understanding Ticket Volume Trends
Total Tickets
The Tickets Opened widget shows how many tickets were created during the selected time range. It counts unique tickets by ticket-created events and is useful for tracking support demand over time.
Opened vs Resolved Tickets
The Opened vs Resolved Tickets chart compares ticket creation and resolution over time. It shows:
Open - Tickets created each day
Resolved - Tickets resolved each day
Use it to see whether backlog is growing or shrinking. Available as line or bar chart.
Monitoring Response and Resolution Time
Average Response Time
Time from ticket creation to the first non-internal reply. Displayed as a single number (e.g. 45m, 2h 15m) for the selected range.
Average Resolution Time
Time from ticket creation to resolution. Also shown as a single number for the selected range.
A resolution timestamp is now recorded for every request, giving you a precise record of when each request reached its final state. The timestamp is calculated based on request type and outcome:
Pending requests - timestamped at the moment the request was first created
Requests resolved by Harmony or escalated with a linked ticket - uses the ticket's SLA completion time, falling back to the ticket event log time, then the last message timestamp
Requests resolved or escalated without a linked ticket - uses the last message timestamp as the resolution point
This ensures that response time, resolution time, and SLA compliance calculations are as accurate as possible across all request types.
Response vs Resolution Time Trends
The Response vs Resolution Time chart shows daily averages for both metrics over time. Helps spot trends and correlate response speed with resolution speed.
Tracking SLA Compliance
SLA Compliance Percentage
The SLA Compliance number widget shows the percentage of tickets that met their SLA (no breach) within the selected range. Computed as tickets without breach / (tickets + breaches) × 100.
You can now filter and group SLA compliance by service catalog item, so you can track SLA performance across the different catalog item types your team has configured. This makes it easier to identify which services are most at risk of breaching their targets.
SLA Compliance Trends
The SLA Compliance Trend chart shows how SLA compliance changes over time. It stacks "SLA met" and "SLA breached" so you can see the proportion of each by day.
SLA Breaches
The SLA Breached widget shows how many open tickets have passed their resolution deadline without being completed. This is a point-in-time count, not a trend.
Analyzing Ticket Breakdowns
Breakdown by Status
Ticket Breakdown by Status shows tickets grouped by status: Open, In Progress, Pending (split into sub-states - see below), Resolved, Closed. Use donut or bar view. Statuses use consistent colors (e.g. green for Open, orange for Pending).
Resolution labels now use clearer, more consistent display names across all status breakdowns and reports, making it easier to interpret ticket data at a glance. Internal identifiers such as desk IDs are automatically translated into human-readable names wherever they appear in your reports.
A dedicated status breakdown view is also available in the Service Desk, with filtering support so you can narrow the breakdown by criteria relevant to your team's workflow. Use this to quickly identify bottlenecks and track open versus resolved volumes.
Understanding Pending States
The pending status now distinguishes between two specific states, giving you better visibility into where work is queued:
Pending Harmony - the request is open and assigned to Harmony (AI is handling it)
Pending Human - the request is open and assigned to a human agent
This makes it easier to identify bottlenecks, whether the queue is building on the AI side or the human agent side.
Breakdown by Priority
Ticket Breakdown by Priority shows ticket volume by priority over time: Low, Medium, High, Urgent. Available as bar or line chart. Clicking a bar can navigate to filtered tickets.
Breakdown by Assignee
You can now filter and group key ticket metrics by assignee, giving you a more granular view of support performance across your team. The following metrics support assignee-level breakdowns:
Tickets created - see volume broken down by assignee
Open ticket age - understand how long tickets have been open per assignee
Closed ticket age - analyse resolution time per agent
Assignees are displayed by their human-readable display name rather than internal identifiers.
Breakdown by Service Catalog Item
Ticket metrics can also be filtered and grouped by service catalog item. This gives you a clearer picture of which catalog items are driving the most support volume and how your service catalog is being used in practice. The following metrics support this dimension:
Tickets created - see volume per catalog item
Open ticket age - understand how long tickets remain open per service
Closed ticket age - analyse resolution time across catalog items
SLA compliance - track SLA performance by service catalog item
Breakdown by Tag
You can now view aggregated data by tag across your service desk tickets. Tag aggregations make it easier to identify trends, spot recurring issues, and understand which topics are driving the most support volume at a glance.
Breakdown by Employee (Created/Resolved)
Tickets Resolved by Employee - Resolution count by employee over time (top contributors by resolver).
Tickets Created by Employee - Creation count by employee over time (requesters or internal creators).
Both use the reports API with groupBy on the actor. Useful for workload and contribution analysis.
Measuring User Satisfaction Scores
The User Satisfaction widget shows an average satisfaction score from survey responses. Scores are shown with a label (e.g. excellent, very good, good, fair, needs improvement) based on the average rating. Add this widget from the Widget Library to include it on your dashboard.
Tracking AI Deflection and Autonomous Resolution
Harmony tracks how effectively it handles employee requests without human intervention. These metrics give you a clear picture of your support operation's AI performance over time.
Autonomous vs. Escalated Requests
The deflection metrics show how many employee requests Harmony resolved autonomously versus how many were escalated to a human agent. You can track whether your autonomous resolution rate is improving, declining, or holding steady over any selected time range.
Every support conversation is classified into one of the following resolution states:
Resolved by Harmony - the AI determined the request was fully answered without human intervention
Escalated - a human agent was assigned to the ticket; no AI classification is needed for these requests
Pending Harmony - the request is open and Harmony (AI) is handling it
Pending Human - the request is open and assigned to a human agent
Unresolved - the request could not be conclusively classified
Resolution detection uses a layered approach: ticket assignment signals are checked first (escalated tickets are flagged immediately without further AI analysis), followed by AI-powered conversation analysis for the remaining cases. This makes resolution signals more accurate and decisions faster.
Requests by Category
The Requests by Category report now lets you slice data by resolution status, giving you a clearer picture of how support volume breaks down across both topic and outcome. Each category can be segmented across three resolution states:
Resolved by Harmony - requests handled automatically by the AI
Escalated - requests passed on to a human agent
Pending - requests still in progress
Use this breakdown to spot which request categories drive the most escalations or remain unresolved, so you can tune your automations more precisely.
Conversation Analytics
Conversation data can be broken down by category and resolution type, making it easier to spot trends across different ticket types and outcomes. Resolution metrics are accurately zero-filled for terminal states, ensuring your charts and trend lines reflect complete, consistent data even when there is no activity in a given period.
Related Resources
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