Recurring overtime may appear to be a sign of employee dedication and commitment to completing tasks on time. However, when overtime shifts from an exceptional situation to a recurring pattern, HR management should pause and ask a more important question: What do these additional hours tell us about the way the company operates and distributes its workforce?
In many work environments, overtime hours are treated simply as numbers that need to be calculated at the end of the month and added to employees’ payroll. However, the data generated from working hours can reveal much more than just a financial figure on a payroll statement.
High overtime in a particular department may indicate a shortage of employees, seasonal pressure, poor task distribution, or work schedules that do not match operational requirements. It may also result from relying on a limited number of employees to handle a large volume of work.
Therefore, properly analyzing overtime data helps management move from dealing with problems after they occur to understanding their causes and making better decisions about employee allocation, tasks, and schedules.
At the same time, it is not enough for a company to know the number of overtime hours. It needs to manage the entire overtime cycle: from the employee’s request and prior approval, to recording actual hours, processing overtime, calculating its value, and linking it to payroll.
Recurring overtime refers to employees consistently working beyond their regular working hours rather than overtime being limited to a temporary or exceptional situation.
Having overtime hours during a specific period does not necessarily indicate a problem. A company may need additional working hours during a particular season, when launching a new project, or due to a temporary operational situation.
However, when overtime becomes a fixed part of how a department operates and continues to appear week after week and month after month, HR management should treat it as an indicator that requires analysis.
This is where accurate working-hours management becomes important. Effective management decisions start with reliable data showing actual working hours, how those hours are distributed among employees, which departments record the highest overtime rates, and the periods when demand for additional working hours increases.
Not always.
This is one of the most important points to consider when analyzing overtime.
High overtime may result from a genuine shortage of employees, but it may also be caused by poor workforce distribution or having employees in departments whose staffing levels do not match operational requirements.
For example, if one department has a large number of employees while another department consistently records high overtime, the issue may not be the total number of employees in the company, but rather how they are distributed.
In another case, the number of employees may be sufficient, but work schedules may not align with peak hours, creating additional pressure on a particular team during specific periods.
For this reason, a company should not decide to hire additional employees simply because overtime has increased without analyzing the other workforce-related data.
When overtime hours remain high for an extended period, the company may be experiencing operational pressure that exceeds the team’s normal capacity.
This can occur in service companies, restaurants, manufacturing businesses, project-based companies, and industries that rely on shifts or experience changing demand throughout the year.
If employees consistently need to stay after their scheduled working hours to complete essential tasks, it may be necessary to review the workload compared with the number of employees available.
A company may have enough employees overall, but they may not be distributed correctly.
One department may be operating below its staffing needs, while another has a relative surplus.
In this case, overtime becomes an indicator that can help management identify an imbalance in workforce distribution.
This is where Dawmt’s Smart Attendance and Departure Management can help track actual working hours, overtime, lateness, and compare recorded data with employees’ schedules. Dawmt automatically calculates actual working hours, breaks, and overtime.
In companies that rely on shifts, the problem may not be the number of employees but the schedule itself.
One shift may be significantly busier at a particular time, while another shift experiences less pressure.
Frequent schedule changes or an inappropriate distribution of working and rest days can also increase reliance on overtime.
This makes it important to analyze schedules alongside attendance data to understand the complete picture.
Dawmt’s Shift and Schedule Management helps organize shifts and connect them with actual working hours, allowing management to compare operational requirements with the hours employees actually work.
One of the most important considerations when choosing an HR management system is that it should not be limited to recording overtime hours. It should support the complete overtime workflow.
With Dawmt, overtime can be handled through more than one workflow, depending on the company’s internal procedures and operating model. This can begin with requesting overtime before it takes place and extend to processing hours that actually appear after the employee has worked them.
This makes overtime management more organized than relying on separate files or manually entering hours at the end of the month.
In some companies, employees cannot simply work additional hours without prior approval.
In this case, the employee can submit an overtime request through Dawmt, after which the request is sent to the responsible manager or authorized person for review and approval.
This allows the company to manage overtime before it happens rather than discovering the additional hours only after the work has been completed.
Through Dawmt’s Employee Self-Service Application, employees can submit overtime requests, while managers can process overtime requests through the system.
Prior approval helps companies:
Control overtime before it occurs.
Understand why additional hours are required.
Allow the responsible manager to review the request.
Reduce unplanned overtime.
Document approvals within the system.
Connect overtime with the company’s approved procedures.
This means overtime is no longer simply a number that appears at the end of the month. Instead, it becomes a structured process with a request, approval, and clear workflow.
There are also situations where no prior request is submitted, or where actual overtime hours appear based on attendance data.
In this case, the overtime hours can be processed after they are recorded.
For example, an employee works beyond their scheduled hours, and the additional time appears based on actual attendance data. The responsible person can then review and process these hours according to company policy, either accepting or rejecting them.
This is where having a system that connects attendance with overtime becomes important. The responsible person does not need to rely on a separate record to determine how many additional hours the employee actually worked.
Dawmt connects attendance with overtime calculation and provides functionality for processing overtime hours as part of its HR management capabilities.
The difference can be simplified as follows:
The employee needs to work overtime → submits a request → the responsible person reviews it → approval is granted → the employee works the additional hours.
The employee actually works additional hours → the hours appear based on working and attendance data → the hours are reviewed and processed → they are accepted or rejected according to the approved policy.
This allows Dawmt to support more than one overtime management scenario instead of forcing every company to follow the same workflow.
After overtime hours are recorded and approved, the next important step is determining the amount payable for those hours.
It is important to distinguish between the number of overtime hours and the value of an overtime hour. The amount due does not depend on the number of hours alone. It can also depend on the type of overtime, the company’s policies, and the approved calculation settings.
The calculation may vary depending on the nature of the overtime, such as:
Overtime during daytime hours.
Overtime during nighttime hours.
Overtime on rest days.
Overtime during holidays.
Different calculation multipliers depending on the type of overtime and the company’s applicable policy.
Therefore, the system needs to know more than the fact that an employee worked two additional hours. It needs to identify the type of hours and the rules that apply to them so that the corresponding amount can be calculated correctly.
For companies that use different calculation multipliers, such as 1.5 or 2, the multiplier can be associated with the overtime type and the company’s approved settings rather than applying one rate to every situation.
This is where automation becomes valuable. Instead of requiring HR employees to manually calculate every case, the system can process overtime according to the defined rules and settings.
The way overtime is handled may vary depending on when it is performed.
Some company policies distinguish between daytime and nighttime overtime, meaning that the calculation may differ according to the rule adopted by the company.
Therefore, analyzing overtime requires more than knowing the total number of hours. It is also important to know:
Were the hours worked during the day or at night?
Did they occur on a regular working day or a rest day?
Were they related to a specific shift?
Were they approved in advance?
Were the hours processed after they were recorded?
These details help provide a more accurate calculation of employee entitlements.
Another important situation occurs when an employee works during a holiday or rest day.
In such cases, compensation may take the form of financial payment or compensatory leave, depending on the company’s policy and applicable rules.
Dawmt provides a compensatory overtime feature that allows overtime hours or days to be recorded and converted into compensatory leave balances.
This means overtime management does not stop at calculating the value of additional hours. It can also extend to managing the impact of those hours on employee leave balances.
For example, if an employee works on a holiday according to the approved policy, the entitlement can be processed through the system and converted into a compensatory leave balance when that is the company’s approved approach.
This connects overtime, leave, and attendance within one workflow instead of handling each component through separate systems.
HR management needs to know when employees actually arrive and leave, not just their scheduled working hours.
The difference between scheduled and actual working time can reveal overtime, lateness, early departures, or changes in working patterns.
In Dawmt, actual working hours and overtime are managed through Attendance and Departure Management, with attendance data also supporting HR and payroll processes.
This makes attendance data a key source for analyzing overtime rather than recording it separately.
For example:
Scheduled working time: 8 hours.
Actual working time: 10 hours.
The hours exceeding the defined working hours may appear as overtime data and can then be processed according to company policy and approval procedures.
The workflow becomes:
There is a direct financial aspect to overtime.
As overtime hours increase, the need to calculate, review, and approve them within the payroll cycle also increases according to applicable policies and regulations.
Problems can arise when overtime is recorded in one place, attendance is managed somewhere else, and payroll is calculated in a separate file.
This increases the possibility of discrepancies that require manual review.
When the data is connected, approved overtime hours can move into the payroll calculation process as part of an integrated workflow.
Dawmt’s Payroll Management connects payroll with attendance and leave-related processes and supports automated calculation of employee entitlements. The platform also connects attendance, overtime, and payroll processes.
There is no single number that can be considered a universal threshold for every company.
A company operating with shifts may have completely different overtime patterns from a business operating fixed office hours. Operating requirements also vary from one industry to another.
However, several indicators can make overtime more important to analyze.
If a limited number of employees record most of the overtime hours, the company may be relying too heavily on them.
This can create continuous pressure on those employees while the rest of the workforce is not being utilized at the same level.
If one department consistently records the highest overtime rate, it is important to understand why.
Is the workload higher?
Is there a shortage of employees?
Are tasks distributed unevenly?
Do peak hours match employee availability?
Each question may lead to a different management decision.
If overtime increases only during a specific season, the reason may be related to a temporary increase in workload.
In this case, seasonal workforce planning may be more appropriate than permanently increasing the number of employees.
If overtime increases at the same time as lateness, absenteeism, shift-change requests, and declining productivity, there may be a broader operational issue that requires analysis.
Overtime should not be viewed as an isolated indicator.
A shortage of employees is one of the obvious causes of increased overtime.
When the workload exceeds the capacity of the available team, employees may extend their working hours to complete the required tasks.
However, the company should first confirm that the issue is genuinely a staffing shortage rather than a problem with task distribution or scheduling.
A company may have an adequate number of employees, but some employees may carry a disproportionately large share of the workload.
This can result in higher overtime among certain employees while the rest of the team does not experience the same increase.
Analyzing working hours by employee, department, and project can help identify this pattern.
Some businesses are affected by specific seasons.
Orders may increase during a particular period of the year, projects may become more demanding, or operations may require intensive work for a limited time.
In these situations, increased overtime may be expected. The problem begins when the company does not have a plan to manage these periods in advance.
In shift-based organizations, an inappropriate schedule can increase the need for overtime.
If there are not enough employees available during peak hours, employees who are already working may need to extend their shifts.
Connecting working-hours management with shift planning helps management understand the relationship between actual schedules and overtime hours.
Sometimes a company becomes dependent on a particular employee to complete specific tasks.
Over time, this can lead to a continuous increase in that employee’s working hours.
Although this may initially appear positive because the employee consistently delivers results, it can become an operational risk if the company becomes unable to distribute those responsibilities among other employees.
Overtime analysis should not start with the total number of hours alone.
The data should be divided into several levels that help management identify the underlying cause.
Which employees record the highest number of overtime hours?
Are they in the same department?
Do they have the same job title?
Are they working on the same project?
Do their overtime hours repeat every month?
These questions help identify patterns.
Comparing departments helps management identify where the issue is concentrated.
A company may have high total overtime, while the actual cause comes from only one department.
This allows for more targeted intervention.
It is important to compare overtime hours weekly and monthly because an annual average may hide important increases during specific periods.
For example, overtime may increase at the end of every month, indicating pressure related to closing operations or delivering reports.
In companies that rely on shifts, comparing shifts can reveal whether one shift carries a greater workload than others.
This makes schedule and attendance data essential parts of the analysis.
Employee Self-Service makes overtime management clearer because employees do not need to rely on paper requests or separate messages to submit their requests.
Through Dawmt’s Employee Self-Service Application, employees can access attendance services, view shift schedules, request shift changes, and submit overtime requests, along with other employee services.
At the same time, managers or responsible personnel can process overtime requests through their designated approval workflow.
This creates a clear separation between:
Do not wait until the end of the year to discover that a department has been relying on overtime continuously.
Monthly reviews help management intervene early.
Comparing departments helps identify where operational issues may exist.
A simple schedule adjustment may be enough to reduce the need for overtime.
If a limited number of employees are carrying most of the workload, the company may need to redistribute responsibilities.
Connecting attendance data with payroll reduces manual data entry and makes entitlement calculations more organized.
Reports should not only display numbers. They should help management understand trends and make data-driven decisions.
Dawmt treats overtime as part of an integrated workflow connecting attendance, payroll, shifts, leave, and Employee Self-Service.
Through Attendance and Departure Management, actual working hours can be recorded and overtime can be calculated automatically, while Employee Self-Service allows employees to submit overtime requests and track their requests.
At the management level, overtime requests can be processed, along with overtime hours that appear based on attendance data. These hours can then be approved or rejected according to the company’s procedures.
Approved overtime can also be connected to payroll so that the hours are included in the entitlement calculation process instead of being manually transferred from one file to another. Dawmt connects attendance, working hours, and overtime with payroll processing.
When a company uses compensatory leave as a form of compensation, overtime hours or days can be converted into compensatory leave balances through the system.
Dawmt’s HR Management Plans include features such as overtime processing, approval levels, shift scheduling, and compensatory leave within the integrated HR management system.
This makes the overtime workflow clearer:
No.
It is a mistake to consider overtime a problem in itself.
Overtime may be necessary in certain situations, especially when there is a temporary operational need, a project that requires quick completion, or a season when demand increases.
The problem is not the existence of overtime, but when it becomes the normal way of completing essential work.
If a company continuously relies on overtime to cover core tasks, it is worth reviewing the operating model rather than treating the situation as normal.
Temporary overtime is usually linked to a clear event:
A specific season.
A new project.
A temporary increase in demand.
A specific delivery period.
Temporary employee absences.
In these situations, the company can plan in advance for the workforce requirements of that period.
Recurring overtime occurs when additional hours continue without a clear temporary reason.
This raises deeper questions:
Is the team smaller than required?
Are tasks distributed unevenly?
Is there a scheduling problem?
Are certain employees being relied on too heavily?
Are there peak periods when the appropriate number of employees is not available?
Does the company need to review its overtime approval process?
Can some overtime hours be handled as compensatory leave according to company policy?
These questions turn overtime into a tool for understanding the company’s workforce rather than simply another item on the payroll statement.
Data alone is not enough if it is not transformed into indicators that management can understand.
Management needs reports showing:
Total overtime hours.
Average overtime per employee.
Departments with the highest overtime.
Employees recording the most overtime hours.
Monthly changes in overtime.
The relationship between overtime and attendance.
The relationship between overtime and shifts.
Overtime costs.
Approved and rejected overtime hours.
Overtime compensated through leave.
Dawmt provides reports and dashboards that help monitor attendance and working-hours data while supporting more organized HR data processing and analysis.
This type of analysis helps HR management move from asking:
to a more important question:
Workforce planning is not simply about determining how many employees the company needs to hire.
It is about understanding workload, timing, and workforce distribution in a way that helps the company achieve its goals without placing continuous pressure on a particular team.
If the data shows that a specific department consistently records high overtime, this may be a reason to review the department’s staffing needs.
However, before opening a new position, the company should analyze:
Workload volume.
Current employee numbers.
Distribution of working hours.
Schedules and shifts.
Seasonal demand.
Productivity.
Overtime costs.
Overtime approved in advance.
Overtime that appeared after work was performed and was processed afterward.
In some cases, the solution may be hiring new employees. In others, the better solution may be redistributing tasks or adjusting shifts.
Not necessarily.
Increased overtime may increase the number of hours worked, but it does not automatically mean productivity increases at the same rate.
If an employee consistently works long hours, work quality, concentration, and the ability to maintain the same level of performance may be affected.
Therefore, working hours alone should not be used to evaluate team performance.
It is more useful to compare working hours with achieved results, workload volume, performance quality, and operational requirements.
The best way to manage overtime is not to view it only as a cost.
It is also a valuable source of information.
High overtime can tell you where pressure exists, when it occurs, who is carrying it, and whether it is temporary or ongoing.
When this information is connected with attendance, shifts, payroll, and leave data, management can build a clearer picture of workforce distribution and operational efficiency.
This is where an integrated system becomes valuable. HR management does not need to move between multiple files to determine whether overtime was approved, how it was recorded, whether it should be included in payroll, or whether the employee will receive compensatory leave.
Recurring overtime is not simply a number that appears at the end of the month in payroll data. It can be an important indicator of the reality of the company’s workforce.
It may reveal employee shortages, poor task distribution, seasonal pressure, scheduling issues, or over-reliance on a limited number of employees.
However, identifying the real cause requires accurate data and integrated overtime management.
With Dawmt, companies can manage the overtime cycle from submitting and approving overtime requests in advance, to processing hours that actually appear after work is performed, and then reviewing, accepting, or rejecting those hours according to the approved procedures.
The approved hours can then be connected to attendance and payroll data, with different overtime types handled according to the company’s settings and policies, whether in terms of the timing of the hours or their calculation multiplier.
Where applicable, overtime hours or days can also be converted into compensatory leave instead of being treated as a financial entitlement, according to company policy.
This makes the workflow clearer:
Therefore, when you notice an increase in overtime within your company, do not ask only:
Start with the more important question:
Recurring overtime refers to employees consistently working beyond their regular working hours on a regular basis, rather than only due to a temporary situation or exceptional circumstance.
Not necessarily. The cause may be a shortage of employees, but it can also result from poor task distribution, unsuitable shift schedules, or seasonal workload pressures. Therefore, overtime data should be analyzed before making a hiring decision.
Employees can use Dawmt’s self-service features to submit an overtime request, which is then routed through the appropriate administrative workflow for review and processing.
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