Attendance Analytics by Department and Employee

Attendance analytics turns a month of punches into a few charts HR and the company head can act on. It shows how many people came in late or on time each day, which departments are late most and take long breaks, where absences cluster by day, and who is late most often. Every number comes from the same graded days as payroll, so the charts and the payslips never tell different stories.

How it works

HR or the company head opens Attendance Analytics and picks a month, and a department if needed.
The daily chart shows, for each day, how many people came in on time and how many came in late against their shift.
Department charts compare late days or average minutes late, and average break time with the days breaks ran over the shift allowance.
The absence grid shows departments against days, shaded from fewer to more absent, so a bad Monday or a festival week stands out.
The top 10 table lists the people late most often, with their late days, counted late marks and average lateness.
Worked days with no shift are shown as not timed, because lateness cannot be judged without a shift.

What you can set

Filters: month and department.
Late day: any day with a punch-in after the shift start plus grace.
Counted late mark: a late day the rules counted, on a full day that was not turned into a half day and not waived.
Over-break day: a day whose punched breaks ran over the shift's break allowance.
Absent day: a working day with no punch, or with too few hours for a half day.
Access: needs Reports view, and the numbers follow the viewer's data scope.

What to look for in the charts

Patterns matter more than individuals. If late days rise on Mondays, look at weekend travel back from home towns. If one department's average break is well over its allowance, the canteen queue may be the issue rather than the people. If absences in the grid cluster after a festival or a long weekend, plan leave approvals earlier next year. The top 10 list is for a quiet conversation with the person and their manager, not for a notice board.

Worked example: reading August at a Pune IT services firm

A Pune IT services firm with 180 employees has its attendance rules on. For August the daily chart shows late days rising every Monday. The summary shows 148 late days but 131 counted late marks: 17 late arrivals fell on days that ended as half days, so they were not counted a second time. The Support department's average lateness is 21 minutes, against 6 to 9 minutes elsewhere, and its breaks ran over the 30-minute allowance on 40 days.

The absence grid shows 9 absences in Sales on one Monday, and the top 10 list holds four people from Support. HR and the Support manager find that the department's 9 am start clashes with the company bus, which reaches the campus at 9:05 am. They move Support to a 9:30 am shift from September, and the September chart no longer shows the Monday spike.

Using analytics fairly

Analytics is most useful when people trust it. Keep individual numbers between the person, their manager and HR, and use the department views to fix causes rather than to rank teams. People change habits faster when they see the numbers used to solve problems, not to embarrass anyone.

Share department charts with managers; share individual rows only with the person and their manager.
Read late days and late marks together, since the gap shows how many late days already cost a half day.
Fix shifts that do not match reality before you tighten the late rules.
Compare the same month last year before planning festival leave.

See attendance analytics in a demo

We show it on a video call with your own shifts, leave types and rules. Free for your first 50 employees.

Book a free demo See pricing

Frequently asked questions

What is the difference between a late day and a late mark?

A late day is any day someone punched in after their shift start plus grace. A late mark is a late day that the attendance rules counted, which happens only on a day that is still a full day and not waived. A late arrival that already turned the day into a half day is a late day but not a late mark.

Why do attendance analytics match payroll?

Because they are built from the same graded days. Analytics has no counting logic of its own; it reads the same day rows that feed the payable days of Direct Payroll, the day log and the live board. A change in the rules or an approved correction shows up in all of them together.

Who can see attendance analytics?

People with view access to Reports, which usually means HR and the company head. The numbers follow the viewer's data scope, so a branch head with branch scope sees only that branch. You can give analytics to a plant head without giving them the right to edit attendance.