Understanding our dashboards and analytics

Overview

At Siit, Reporting and Analytics help IT and HR teams monitor their performance, track SLAs, and identify opportunities to optimize internal service delivery.
Our reporting capabilities are designed to make this effortless through:

• Dashboards – to visualize performance and trends

• Exports – to deep dive or re-compute data for custom analysis

Together, they provide complete visibility over requests, workload distribution, SLA compliance, and productivity.

Below are answers to the most frequently asked questions about how metrics and calculations work in Siit.

General structure and scope

How are dashboards organized?

There are three types of dashboards in Siit:

• Individual dashboards: your own performance metrics.

• Inbox dashboards: volume, performance, and insights for your inbox.

• Company dashboards: consolidated view at a company level (requests overview, SLA, AI & Automation)

What’s the difference between exports and reporting data?

• Exports represents all the requests raw data you can export in various formats (csv, xlsx) which included archived requests

• Reporting dashboards only include unarchived requests and is presenting the data in different formats and insights for you to leverage it more easily and take decision

Are archived requests taken into account in my analytics?

• Reporting: no, archived requests are excluded.

• Exports: yes, archived requests are included and can be filtered.

 

Metrics computation and logic

How is the average solving time computed?

• Calculated in hours, based on the solving date.

• Office hours are always taken into account.

• If an SLA applies:

  • Waiting and snooze pauses follow SLA configuration.

• If no SLA applies:

  • Only working hours are considered.

How is the average first reply time computed?

• Calculated in hours, based on the first reply date.

• Office hours are always taken into account.

• If an SLA applies:

  • Waiting and snooze pauses follow SLA configuration.

• If no SLA applies:

  • Only working hours are considered.

Why can my average first reply time be higher than my solving time?

Because the metrics are not associated with the same date:

• First reply time → associated with the date of the first reply.

• Solving time → associated with the date of resolution.

On a given date, one request could have a 10-hour first reply time, while another was solved in 2 hours — both appearing on the same graph.

Are office hours taken into account in SLA calculation?

Yes, always. SLA calculations only consider office hours as defined in your service settings.

SLA calculations and impact

How are SLA completion and breach rates computed?

• SLA completion:

  • If both SLA criteria apply (first reply + resolution), both must be met for the request to be compliant.

  • If only one applies, only that one must be met.

• SLA breach:

  • At least one SLA criterion has been violated.

Are SLA completion rates updated when SLA settings change?

No. Once an SLA starts, any later updates to SLA configuration do not affect requests already linked to an existing SLA.
The SLA starts when a request is associated with a service that includes one.

Are SLA dashboards calculated differently from other dashboards?

Yes.

• SLA dashboards only display requests where an SLA applies.

• Other dashboards include all requests (with or without SLA).

Exports and manual calculations

How can I use export data to re-compute first reply time and solving time?

In your export file, you’ll find several useful fields:

How to compute:

• When SLA applies → use: SLA configuration – SLA interval

• When no SLA applies → use: time in seconds (office hours)

Data interpretation and dashboard logic

Why do metrics differ between dashboards?

Because not all dashboards use the same dataset:

• SLA dashboards: only requests with SLA applied.

• Other dashboards: all requests (regardless of SLA).

Why does my colleague see different numbers in their reports?

Each admin sees data based on requests they have access to:

• If you’re assigned to a request and your colleague isn’t, that request affects your dashboards but not theirs.
  Check your request permissions to confirm visibility.

Why doesn’t the date filter impact first-line metrics?

First-line metrics (e.g. “last 7 days” or “last 30 days”) are static references, not affected by date filters.
They ensure consistent comparison when viewing filtered data.

Allocation, visibility, and thresholds

How is a request associated to an admin in dashboards?

Requests are assigned to the current assignee — not necessarily the person who first replied or closed the request.
That means:

• First reply time = first reply of the assignee.

• Solving time = solving time under that assignee’s ownership.

What do colors mean in tables?

Colors represent value thresholds, not your SLA configuration.

Productivity and insight

How to read productivity metrics in the Requests dashboard?

• Admin allocation: compares the number of requests solved per admin per month vs. requests created.
  → Helps you estimate how many admins are needed.

• Employees & requests created over time: shows employee engagement in Siit.

• Admins & requests solved over time: tracks admin activity and workload trends.

What constitutes an “involved request”?

You’re considered involved if:

• You’re assigned to the request, or

• You sent at least one message in the request (notes don’t count).

How to leverage the Insights tab in Inbox dashboards?

Use the visual correlation between distribution and performance:

1. Look at the two right-hand graphs to identify where bubbles are large (high volume).

2. Check the left graph to see if performance drops relate to volume peaks.

3. If patterns appear, consider reallocating resources by time or category.

Key KPI definitions (recap)

• Avg First Reply in Hours → time between creation and first reply, in office hours.

• Avg Solving Time in Hours → time between creation and resolution, in office hours.

• SLA Compliance Rate → % of requests meeting SLA criteria.

• SLA Breach Rate → % of requests that violated at least one SLA rule.