Published: June 2, 2022
It’s common for local governments to incur overtime costs, which can be significant if you provide critical or emergency services. You know that you need strong controls to ensure your government pays out overtime appropriately, but are you also verifying that the costs are reasonable and meet your expectations?
Monitoring your overtime costs allows you to detect irregularities, such as a mistake or system glitch that might have resulted in overpayments. You can also see if the overtime that employees are working is significant and then assess whether it is sustainable. If it’s not, then you can explore ways to reduce overtime and potentially lower your costs. Alternatively, if overtime is reasonable, you have another point of reference that your internal controls appear to be working.
Before you start monitoring your overtime costs, you first need to establish expectations for a reasonable range of overtime activity. Then, compare your expectations to the actual data and follow up on any variances. Here are a few ways you can monitor your overtime data.
Compare overtime by using an overtime percentage
The overtime percentage is the ratio between the number of overtime hours and the number of regular hours worked for a particular period. The ratio will tell you how much more employees are working beyond their regular workweek.
For example, the calculation for an employee who worked eight hours of overtime during a 40-hour regular workweek would be ((8/40) x 100), which comes to a 20 percent overtime ratio. The same holds true for monthly calculations if they worked 32 overtime hours with 160 regular hours in a month (32/160 x 100 = 20 percent). You can calculate this figure for each department and for your organization as a whole using any period you wish.
This example chart details overtime percentages by department over a two-month period.
|Department||Overtime percent, January||Overtime percent, February||Percent change|
In our example above, you can see that Department B’s employees worked 20% more than they were regularly scheduled. If this exceeds your expectations, then you can follow up and ask questions or request more detailed reports.
Monitor how many employees earn overtime
You can also evaluate how many employees in each department earned overtime compared to the total number of employees. In our example below, you’ll notice that more than half the employees in this department worked overtime in April. Based on this data, you might have additional questions for the department about what occurred that month to almost double the number of employees with overtime hours.
|Month||Number of employees working overtime||Total number of employees||Percent of employees working overtime|
The reverse can also happen, where a few employees in a department earned the majority of the overtime. This, too, may raise questions, as there could be a concern that a department is not using an equitable basis to award overtime opportunities.
Identify your high overtime earners by position
Some employees may choose to work more overtime than others, so it’s a good idea to identify and monitor those high-dollar overtime earners. In our example below, we’ve listed a few employees with their overtime payments compared to their base salary. As you can see, the first employee on our list is earning an additional 71 percent of their regular pay in overtime.
|Month||Overtime earnings (YTD)||Base salary (YTD)||Percent of overtime to base salary|
If certain employees work significant overtime over an extended period, you may want to ask some of these questions: Are these employees truly working the extra hours? Are there safety risks? Is relying on overtime hours sustainable for our government and the employee? It may be that you should consider bringing on additional staffing to meet your long-term needs.
Monitor the extent of your high overtime earners
You can also sort the data to find out how many employees are earning a high percentage of their pay in overtime. If you are dealing with large data sets, this might be a better starting place than focusing on individual records.
Let’s look at the hypothetical results for one department:
|Overtime percent of base salary||Employee count, 2 years ago||Employee count, 1 year ago||Employee count, current year|
|50% or higher||4||6||9|
|40 – 49%||6||7||7|
|30 – 39%||3||4||4|
|20 – 29%||15||10||17|
In this case, we see an increase in the number of employees earning more than 50 percent of their salary in overtime in the current year. You might also have questions about the number of employees earning more than 30 or 40 percent, even though the numbers are stable or the total number of employees earning overtime because it has grown in the current year. For example, you might ask what is driving this upward trend in the over 50 percent category and why the department relies heavily on a handful of employees to work so much. You might review documentation to verify this represents work actually completed. Again, you might consider whether the overtime practices in this department are sustainable and whether there is a lower-cost solution to accomplish the work.
At the end of the day, analytics like these can only provide you high-level information that might indicate red flags from a data set. It’s up to you to ask questions and take action where needed to make these analytics effective. In some cases, overtime might be entirely justified, but in other instances, a change might be in order. The important thing is that you are actively monitoring and following up on your overtime payments.
For more ideas about how you can improve your payroll processes, check out SAO’s Payroll Guide.
Remember, we are here to help. If you have specific technical accounting questions, please submit them using our HelpDesk in the client portal.
We also have financial management specialists at SAO’s Center for Government Innovation available to talk with you about best practices, resources or internal controls. For assistance, reach out to us at Center@sao.wa.gov.