> For the complete documentation index, see [llms.txt](https://docs.we360.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.we360.ai/how-to-and-best-practices/improving-employee-wellness/spotting-burnout-early.md).

# Spotting Burnout Early

Detect employee burnout early with We360.ai Wellness analytics — identify overburdened and underutilized employees using wellness trends.

We360.ai's **Wellness** module goes beyond productivity metrics — it classifies employees as Healthy, Overburdened, or Underutilized, helping you spot fatigue, overwork, and disengagement before they escalate.

## Warning Signs to Watch For

| Pattern                                     | What It Signals                      |
| ------------------------------------------- | ------------------------------------ |
| Consistently working beyond shift hours     | Overload or unmanageable workload    |
| High active time with very high idle spikes | Context-switching and mental fatigue |
| Drop in productivity score week-over-week   | Disengagement or burnout onset       |
| Frequent short breaks and long idle periods | Difficulty concentrating             |

## How to Identify At-Risk Employees

{% stepper %}
{% step %}

#### Review the Wellness Dashboard

Navigate to the **Wellness** section in Analytics. The dashboard classifies employees into three categories:

* **Healthy** — Balanced workload and activity.
* **Overburdened** — Excessive activity or hours beyond their shift.
* **Underutilized** — Insufficient engagement or very low activity.

Use the overall score donut chart for a quick snapshot and the trends chart to see how the distribution changes over time.
{% endstep %}

{% step %}

#### Review the Employee Wellness Table

The day-by-day wellness table shows each employee's wellness status across the month. Look for employees consistently flagged as overburdened — this is the clearest early-warning signal. You can export this data to CSV for further analysis.
{% endstep %}

{% step %}

#### Take Action

Once at-risk employees are identified, engage managers with concrete data to redistribute workloads, approve leave, or initiate a 1-on-1 conversation. Use the data to inform — not punish.
{% endstep %}
{% endstepper %}


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