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Behaviour Analytics

Behaviour Analytics focuses on how people are working rather than how much — login cadence, overtime burn, and the balance between productive and non-productive time. It's the view HR managers reach for when trying to spot burnout, attrition, or shift-pattern issues before they become attrition.

Filters​

  • Start Date / End Date — Period under analysis
  • Department — Filter to a single department, or All Departments
  • Role — Filter to a single role, or All Roles
  • Location — Filter to a single location, or All Locations
  • Reset — Circular arrow icon

Summary Tiles​

  • No. of Employees — Distinct employees in the filtered scope
  • No. of Days — Calendar days covered by the selected window

Charts​

Login Trend​

A line chart showing the percentage of employees with at least one login per day across the period. Sustained low values indicate a fleet of devices that are either offline or unmapped — verify in Agent Installation.

Work Life Balance (Overtime %)​

A line chart of the share of time spent outside the resolved shift (see Shifts). High overtime % over multiple weeks is a leading indicator of burnout. Compare against project deadlines to validate if the spike is project-driven or chronic.

Productive vs Non-Productive (Hrs)​

A stacked or grouped bar chart contrasting productive vs non-productive hours per day. Together with Login Trend, this view tells a complete story — are people logged in, and is their time productive?

Best Practices​

  • Run a 4–8 week window for the cleanest behaviour signal — single-week windows are too noisy.
  • A consistent Overtime % above 20% for an individual department is grounds for a workload review — verify whether Shifts are correctly assigned before drawing conclusions.
  • Cross-check Login Trend against Agent Installation — a falling login % may be a fleet of devices going dormant rather than a real behavioural shift.
  • For a single-employee deep dive, switch to Screen Time with the same filter set.