Hourly Employees

How to plan for hourly employees in Jirav

Jirav will annualize the salaries for any employee imported with an hourly rate using an assumed average hours per week.

The average number of hours used to annualize the salaries can be found in Settings ⚙️ > Company.

If it does not make sense to annualize the Salaries for all employees using this methodology, Staffing will need to be managed with Excel import. Here are a few options to consider:

Option 1: Custom Table

  1. Import Employees to Staffing: Import hourly employees to staffing for headcount reporting, but set their salaries to $0.

  2. Utilize Custom Table and Drivers: Create a custom table with the following inputs for each hourly employee:

    • Hours per Month: Input the expected hours worked per month.
    • Pay Rate: Use an assumption or create a custom line for pay rate.
    • Hourly Wages: Calculate using the formula: Hours per Month * Pay Rate.
  3. Link to OpEx: Ensure to link the Hourly wage lines back to OpEx as needed.

Consider consolidating this process for all hourly employees if pay rates, depts, and # of hours are similar. Otherwise, repeat this pattern for each employee.

Option 2: Annualize in Excel

Before importing employee data into Jirav, you can manually annualize salaries in Excel. For example, calculate one person's annualized salary using Hourly Rate * 40 Hours per Week * 52 and another person's using Hourly Rate * 35 Hours per Week * 52.

This option works well when hours worked are fairly consistent with minimal variability month-to-month.

Option 3: Manual Adjustment

Manually adjust calculated salaries by month in OpEx to reflect variations. While this is the most straightforward option, it may become tedious to maintain over time.

Considerations

Evaluate each option based on your organization's specific needs, considering factors such as accuracy, efficiency, and ease of maintenance. By choosing the most suitable method, you can effectively plan for hourly employees within Jirav and ensure accurate financial forecasting.