Utilization Rate in professional services is the percentage of time spent on billable projects versus the total time worked. In other words, it measures how busy employees are.
Utilization in consulting is a crucial metric because management needs to understand how much time staff members are spending doing billable tasks versus non-billable tasks. Billable utilization and average hourly rate are mission-critical for the financial health of a company.
Many organizations distinguish between Billable Utilization and Productive Utilization (overall utilization including marketing, sales, general management, training, internal projects, etc.).
Utilization is the key to overall organizational profitability and productivity. Utilization should be examined in conjunction with overall revenue and profit per person. Usually, the biggest driver of capacity utilization is the maturity of the business development process (marketing, sales and recurring revenue).
We recommend tracking utilization at the granular level and over time. For example, utilization could go down by 5% during the year, which is significant for a company with 30 employees (30 × 2,000 × 0.05 = 3,000 hours).
Utilization measurement helps to answer the following questions:
- Who are the most productive employees?
- Which person might be burned out and in need of a vocation?
- Which department has better productivity?
In Metric.ai, there are options to configure hours calculation:
Besides the time period, you are able to choose which employees to use to calculate the time:
- All employees
- Billable employees
- Internal (non-billable) employees
And you can choose whether to include or exclude time off (defines as a project with billing type internal and Time-off option chosen).
Utilization can be calculated based on available capacity or based on total hours.
You can see multiple types of utilization in Metric.ai:
Logged, which is based on a time reflected in timesheets (inputted in Metric.ai or via time tracking software).
Planned is calculated from Allocations (could be imported from a resource scheduling tool like Float via integration or internal resource allocation functionality in Metric.ai).
Forecasted consist of logged utilization before today and planned utilization after today.
To learn more about the analytics view of Metric.ai, please read Analytics overview help documentation.