Recurring overtime: what does it tell you about your workforce?

In some companies, overtime can look like a sign that employees are dedicated and keen to finish their work on time. But when overtime turns from an exception into a recurring pattern, human resources (HR) should stop and ask a more important question: what do these extra hours tell us about how the company runs and how its workforce is distributed?

In many workplaces, overtime hours are treated as numbers to be calculated at the end of the month and added to what employees are owed. But the data that working hours produce can reveal far more than a sum in the payroll register.

High overtime in one department may point to a shortage of employees, seasonal pressure, poor task distribution, or shift schedules that do not fit how the work actually runs. Sometimes it is the result of relying on a small number of employees to get a large volume of work done.

Reading overtime data correctly therefore helps management move from dealing with a problem after it happens to understanding its causes and making better decisions about how employees, tasks and schedules are distributed.

At the same time, it is not enough for a company to know only how many overtime hours there were. It needs to manage the whole overtime cycle: from the employee's request and prior approval, to recording the actual hours, processing the overtime, then calculating what is owed and linking it to payroll.

What is recurring overtime?

Recurring overtime means employees regularly working more than their normal working hours, rather than overtime being tied to a temporary situation or an exceptional case.

Overtime in a given period does not necessarily mean there is a problem. A company may need more working hours during a particular season, when launching a new project, or during a temporary operational situation.

But when overtime becomes a fixed part of how a department runs, and it shows up week after week and month after month, HR should treat it as an indicator that needs analysis.

This is where accurate management of working hours matters, because the right management decision starts with correct data: the actual hours worked, how they are spread across employees, which departments record the most overtime, and the periods when demand for working hours rises.

Does high overtime mean there are not enough employees?

Not always.

This is one of the most important points to watch when analysing overtime.

High overtime may come from a genuine shortage of employees, but it may also be caused by poor workforce distribution, or by departments whose size does not match what operations need.

For example, if one department has a large number of employees while another consistently records high overtime, the problem may not be the company's total headcount but how employees are distributed.

In another case, the number of employees may be right, but the work schedules do not match peak hours, which puts extra pressure on one team at certain times.

That is why a hiring decision should not be made just because overtime has risen, without analysing the rest of the workforce data.

What does overtime tell you about your workforce?

1. It reveals ongoing operational pressure

When overtime stays high for a long time, the company may be facing more operational pressure than the team's normal capacity can absorb.

This can show up in service companies, restaurants, factories, project-based companies, and sectors that run on shifts or see demand change through the year.

If employees constantly need to stay after the end of the working day to finish core tasks, it may be necessary to review the workload against the number of employees available.

2. It reveals poor distribution of employees

A company may have enough employees, but they are not distributed the right way.

One department may have fewer employees than it needs, while another has a relative surplus.

In that case, overtime becomes an indicator that helps management find the imbalance in how the workforce is distributed.

This is where Dawmt's attendance management helps you track actual working hours, overtime and late arrivals, and compare the recorded data with each employee's actual schedule.

3. It reveals shift scheduling problems

In companies that run on shifts, the problem may not be the number of employees but the schedule itself.

One shift may be very busy at a certain time, while another is under less pressure.

Frequent schedule changes, or a poor spread of working days and rest days, can also increase reliance on overtime.

This is why analysing schedules alongside attendance data matters for seeing the full picture.

Dawmt's shift and schedule management helps you organise shifts and swap them, so management can compare what operations need with the hours employees actually work, as the attendance records show them.

How is the overtime cycle managed?

One of the most important points when choosing an HR system is that it should not stop at recording overtime hours: it should support the whole overtime cycle.

Overtime can be handled through more than one path, depending on how the company works and its internal procedures, from requesting overtime before it is worked to processing hours identified after the work is done.

This makes overtime management more organised than relying on separate files or entering hours by hand at the end of the month.

First: prior approval of overtime (pre-handling)

In some companies, it is not enough for an employee to work extra hours: they must get prior approval before working them.

In this case, the employee submits an overtime request, and the request then goes to the responsible manager for review and a decision.

This means the company can deal with overtime before it happens, instead of only discovering the hours after the work is done.

Why does prior approval matter?

Prior approval helps the company:

• Control overtime before it happens.
• Know why the extra hours are needed.
• Have the responsible manager review the request.
• Reduce unplanned overtime.
• Document approvals in the system.
• Tie overtime to the company's approved procedures.

Overtime then stops being just hours that appear at the end of the month, and becomes a process with a request, an approval and a clear path.

Second: processing overtime after it happens (post-handling)

In other cases, no request is submitted in advance, or actual overtime hours appear from the attendance data.

In this case, the overtime hours can be processed after they are recorded.

For example, an employee works after the end of their working day, and overtime hours then appear for them from the actual attendance data. The responsible manager can then review these hours and process them according to company policy, either accepting or rejecting them.

This is where a system that combines attendance and overtime matters, because the manager does not need to rely on a separate record to know how many hours the employee worked.

In Dawmt, overtime is checked along with leave and absence when the month's attendance period is closed, before payroll is calculated.

What is the difference between pre-handling and post-handling?

Put simply:

Pre-handling:

The employee needs to work overtime → submits a request → the manager reviews it → it is approved → the employee works the extra hours.

Post-handling:

The employee actually works extra hours → the hours appear from the working and attendance data → they are reviewed and processed → they are accepted or rejected according to the approved policy.

So it is better for company policy to set when overtime needs approval in advance and when hours are reviewed after the work, instead of forcing one method on every case.

How is overtime pay calculated?

Once overtime hours are recorded and approved, the most important stage follows: working out what is owed for them.

Here you need to tell apart the number of overtime hours and the value of an overtime hour, because the amount owed does not depend on the number of hours alone, but on the type of overtime, the company's rules and policy, and the approved calculation settings.

The calculation can differ by the nature of the hour, for example:

• Overtime during the day.
• Overtime at night.
• Overtime on rest days.
• Overtime on holidays.
• A different calculation multiplier depending on the type of overtime and the policy applied.

So the system needs to know more than that the employee worked two extra hours: it needs to know the type of hours and the rules that apply to them, so that what is owed is calculated correctly.

In companies that use different calculation multipliers, such as 1.5 or 2, the multiplier can be linked to the type of overtime and the company's approved settings instead of applying one rate to every case.

These multipliers are a policy the company sets. What the Saudi Labour Law requires is set out in Article 107: the employer must pay the worker, for overtime hours, an additional wage equal to the hourly wage plus 50% of the basic wage. So check the multipliers in your company's policy against this text before you set them up in the system.

This is where automation adds value: instead of an HR employee calculating each case by hand, the system can process the hours according to the defined rules and settings.

Daytime and night-time overtime

How overtime hours are handled can differ depending on when they are worked.

Some company policies distinguish between overtime during the day and overtime at night, so the way the amount owed is calculated may differ according to the rule the company adopts.

So when analysing overtime, knowing the total number of hours is not enough. It is important to know:

• Were the hours worked during the day or at night?
• Were they worked on a normal working day or a rest day?
• Were they tied to a particular shift?
• Were they approved in advance?
• Were the hours processed after they were recorded?

These details help you reach a more accurate calculation of what is owed.

Overtime on holidays and compensatory leave

Another important case is when an employee works on a holiday or a rest day.

In this case, compensation under company policy may take the form of a payment or compensatory leave, depending on the rules applied.

The Saudi Labour Law counts all working hours performed on holidays and Eids as overtime hours, and allows the employer, with the worker's consent, to grant paid compensatory leave days instead of the pay owed for the overtime hours (Article 107). In other words, compensation in leave needs the employee's consent: company policy alone does not decide it.

In Dawmt, compensatory leave is the Days in lieu leave type, with a balance managed alongside the other leave balances.

This means overtime management does not stop at calculating the value of the hours: it can extend to managing the effect of those hours on leave balances.

For example, if an employee works on a holiday and agrees to take compensatory leave instead of pay, the days go to their compensatory leave balance instead of into payroll.

This links overtime, leave and attendance in one cycle instead of handling each part in a separate system.

How is overtime linked to attendance?

HR needs to know when an employee clocked in and clocked out, not just the time they were scheduled for.

The reason is that the gap between planned and actual time can reveal overtime, late arrival, early departure or changes in working patterns.

When attendance and payroll sit in one system, attendance data flows straight into HR and payroll processes.

This makes attendance data a core input for analysing overtime, instead of recording overtime separately.

For example:

• Scheduled working time: 8 hours.
• Actual working time: 10 hours.

The hours beyond the set working hours can appear in the overtime data, and are then processed according to company policy and approval procedures.

So the path becomes:

Actual attendance → overtime hours identified → hours processed or approved → amount owed calculated → payroll.

The link between overtime and payroll

There is a direct financial side to this.

The more overtime hours there are, the more they need to be calculated, reviewed and approved within the payroll cycle according to the policies and regulations that apply.

The problem appears when overtime is recorded in one place, attendance in another, and payroll in a separate file.

In that case, the chance of discrepancies that need manual review goes up.

When the data is linked, approved hours can move into the payroll calculation within one connected cycle.

In Dawmt, the payroll run starts by closing the month's attendance period once leave, absence and overtime are checked, and payroll is then calculated.

You can learn about payroll management in Dawmt to see how attendance data and what is owed are linked in one system.

When does overtime become a signal worth acting on?

There is no single number that works as a fixed threshold for every company.

What is normal in a company that runs on shifts may be completely different from a company with fixed office hours, and how the work runs differs from one sector to another.

But there are some indicators that make overtime more important to analyse.

When it keeps falling on the same employees

If a small number of employees record most of the overtime hours, the company may be relying on them too much.

This can put ongoing pressure on those employees, while the rest of the workforce is not used to the same extent.

When it rises in one department

If one department consistently records the highest overtime, it is important to find out why.

• Is the workload bigger?
• Is there a shortage of employees?
• Are tasks spread unevenly?
• Do peak hours match the times employees are at work?

Each of these questions can lead to a different decision.

When it rises in a particular period

If overtime rises only in a certain season, the cause may be a temporary increase in workload.

In that case, the better answer may be seasonal workforce planning rather than a permanent increase in headcount.

When it rises together with other indicators

If overtime hours rise at the same time as late arrivals, absence, shift change requests and falling productivity, there may be a wider operational problem that needs analysis.

Here, overtime should not be looked at as a separate indicator.

Why overtime hours rise in companies

A shortage of employees

A shortage of employees is one of the obvious causes of rising overtime.

When the workload is bigger than the available team can handle, employees start working longer hours to finish what is needed.

But first make sure the problem really is the number of employees, and not task distribution or scheduling.

Poor task distribution

A company may have the right number of employees, but some of them carry a bigger share of the tasks.

This drives their overtime up, while the rest of the team shows no such rise.

Analysing working hours by employee, department and project can help you spot this pattern.

Seasons and peak periods

Some businesses are affected by particular seasons.

Orders may rise at a certain time of year, projects may increase during a season, or operations may need intensive work for a limited period.

In these cases, rising overtime is expected, but the problem starts when the company has no plan in advance for handling that period.

Weak shift planning

In companies that run on shifts, an unsuitable schedule can increase the need for overtime.

If there are not enough employees at peak hours, the employees who are there may have to work longer.

That is why linking working hours management with shift planning helps management see the relationship between the actual schedule and overtime hours.

Relying on particular employees

Sometimes one employee becomes the person the company relies on to get certain tasks done.

Over time, this can turn into a steady increase in their working hours.

At first this may look positive, because the employee gets the work done, but it can become an operational risk if the company can no longer spread those tasks without them.

How do you analyse overtime correctly?

Analysing overtime does not start from the total number of hours alone.

The data should be broken down into levels that help management find the cause.

Analysing overtime by employee

• Which employees record the most overtime hours?
• Are they in the same department?
• Do they have the same job title?
• Do they work on the same project?
• Do their overtime hours recur every month?

These questions help you find patterns.

Analysing overtime by department

Comparing departments helps management see where the problem is concentrated.

The company's total overtime may be high, but the real cause may come from one department only.

Then the intervention can be more precise.

Analysing overtime by period

It is important to compare overtime weekly and monthly, because a yearly average can hide significant rises in certain periods.

You may find, for example, that overtime rises at the end of every month, which points to pressure tied to closing operations or delivering reports.

Analysing overtime by shift

In companies that run on shifts, comparing shifts can show that one shift carries more pressure than the others.

Here, schedule data and attendance hours become a core part of the analysis.

The role of self-service in managing overtime

Employee self-service makes overtime management clearer, because the employee does not need to rely on paper requests or separate messages to submit a request.

In the Dawmt app, employees clock in, see their attendance history and swap shifts, while managers find their team's requests in one inbox in the app.

Whichever way requests are submitted, the path should keep a clear separation between:

Employee request → manager review → decision → hours recorded → processing → calculation.

How do companies reduce unnecessary overtime?

1. Monitor the data continuously

Do not wait until the end of the year to find out that a department relies on overtime all the time.

A monthly review helps you step in early.

2. Identify the departments with the most overtime

Comparing departments helps you find where the imbalance is.

3. Review shift schedules

A small change to a schedule may be enough to reduce the need for overtime.

4. Distribute tasks better

If a small number of employees carry most of the pressure, the company may need to redistribute tasks.

5. Link attendance to payroll

Linking attendance data to payroll reduces manual data entry and makes calculating what is owed more organised.

6. Use reports to make decisions

Reports are not just for showing numbers: they help management understand trends and make decisions based on data.

How Dawmt handles overtime

In Dawmt, the attendance, shift, leave and payroll modules run in one platform.

Employees clock in through the app with a geofence and selfie verification, or through fingerprint and facial recognition terminals, so actual hours come from attendance records, not handwritten sheets.

When the month's attendance period is closed, overtime is checked along with leave and absence, and payroll is then calculated.

Days in lieu are one of Dawmt's leave types, with its own balance, so if an employee agrees to be compensated with leave instead of pay, the days are managed within their leave balances.

Dawmt's plans list overtime, approval flows, the shift schedule and days in lieu among the features of the Professional package.

Whatever system you use, the overtime cycle should be clear:

Overtime requested or recorded → approved or processed → actual hours recorded → overtime type and calculation multiplier set → amount owed approved → added to payroll or converted to compensatory leave according to company policy.

Is overtime always bad?

No.

It is a mistake to treat overtime as a problem in itself.

It may be necessary in some cases, especially during a temporary operational situation, a project that needs to be finished quickly, or a season when orders rise.

The problem is not that overtime exists, but that it becomes the normal way of getting work done.

If the company relies on overtime all the time to cover core tasks, it is worth reviewing the operating model instead of treating this as normal.

The difference between temporary and recurring overtime

Temporary overtime

It is usually tied to a clear event:

• A particular season.
• A new project.
• A temporary rise in orders.
• A set delivery period.
• The temporary absence of some employees.

In these cases, the needs of the period can be planned in advance.

Recurring overtime

It happens when extra hours keep recurring with no clear temporary cause.

This is where deeper questions need to be asked:

• Is the team smaller than it needs to be?
• Are tasks spread unevenly?
• Is there a problem with the schedules?
• Are some employees relied on too much?
• Are there peak times when the right number of employees is not at work?
• Does the company need to review how overtime is approved?
• Can some of the hours be handled as compensatory leave under the approved policy?

These questions make overtime a tool for understanding how the company really works, instead of just a line on the payslip.

How do HR reports help you find the problem?

Data alone is not enough if it is not turned into indicators people can read.

Management needs reports that show:

• Total overtime hours.
• Average overtime per employee.
• The departments with the most overtime.
• The employees who record the most overtime.
• The monthly change in hours.
• The relationship between overtime and attendance.
• The relationship between overtime and shifts.
• The cost of overtime hours.
• The hours approved or rejected.
• Overtime compensated with leave.

Dawmt offers reports and dashboards that help you follow attendance and working hours data, and lets you process and analyse HR data in a more organised way.

This kind of analysis helps HR move from the question:

"How many overtime hours did we record?"

to a more important one:

"Why did we record these hours, and were they managed the right way?"

Overtime and workforce planning

Workforce planning does not just mean deciding how many employees to hire.

It means understanding the size and timing of the work, and distributing your people in a way that helps the company reach its goals without putting ongoing pressure on one team.

If the data shows that a department consistently records high overtime, that may be a reason to review what the department needs.

But before opening a new position, analyse:

• The volume of tasks.
• The current number of employees.
• How working hours are distributed.
• Schedules and shifts.
• Seasons.
• Productivity.
• The cost of overtime.
• Hours approved in advance.
• Hours that appeared after the work and were processed later.

In some cases the answer may be hiring new employees, while in others it is redistributing tasks or adjusting shifts.

Does more overtime mean more productivity?

Not necessarily.

Rising overtime can increase the number of hours worked, but it does not automatically raise productivity by the same proportion.

If an employee works long hours all the time, the quality of their work, their focus and their ability to keep going at the same level may suffer.

So it is better not to use working hours alone to judge a team's performance.

What matters more is comparing working hours with the results achieved, the volume of tasks, the quality of work and what operations need.

Overtime as a decision-making tool

The most suitable way to deal with overtime is for management not to see it only as a cost.

It is also an important source of information.

Rising hours can tell you where the pressure is, when it happens, who carries it, and whether it is temporary or ongoing.

When this information is linked with attendance, shift, payroll and leave data, it becomes possible to build a clearer picture of how well the workforce is distributed.

This is where an integrated system adds value, because HR does not need to move between several files to find out whether overtime hours were approved, how they were recorded, whether they will go into the salary, or whether the employee will be compensated with leave.

Recurring overtime is not just a number that appears at the end of the month in the payroll data: it can be an important indicator of the real state of the company's workforce.

Overtime can reveal a shortage of employees, poor task distribution, seasonal pressure, a problem with shifts, or too much reliance on a small number of employees.

But finding the real cause takes accurate data and integrated management of the overtime cycle.

So start with a clear cycle: prior approval where company policy requires it, or a review of hours that appear in the attendance data after the work, then acceptance or rejection under the approved procedures.

The approved hours then go into payroll, with the type of overtime and its multiplier set in company policy and checked against Article 107 of the Labour Law.

Where appropriate, overtime can also be compensated with compensatory leave instead of pay, with the employee's consent.

The path then becomes clearer:

The employee requests overtime or clocks in → it is approved or processed → the hours are reviewed → the calculation method is set → the amounts owed are approved → they go to payroll or are converted into compensatory leave according to policy.

So when you notice overtime rising in your company, do not only start by asking:

"How much will we pay for these hours?"

Start with the more important question:

"What are these extra hours trying to tell us about the way we work?"

Sources

• Labour Law issued by Royal Decree No. M/51, with amendments up to Royal Decree No. M/44 dated 8/2/1446 AH, Ministry of Human Resources and Social Development (in Arabic), Article 107 (pay for overtime hours, compensatory leave in its place, and hours worked on holidays and Eids).

This information was reviewed in October 2026. Regulations can change, so check the official source before relying on it.