Calculate agent efficiency and workload based on standard WFM metrics.
Total scheduled time minus breaks and meetings.
Occupancy Rate0%
Total Workload (Handle Time)0 min
Available / Idle Time0 min
Analysis–
How to Calculate Occupancy Rate in a Call Center
In the world of Workforce Management (WFM), the Occupancy Rate is one of the most critical Key Performance Indicators (KPIs) for assessing operational efficiency. It measures the percentage of time agents spend actively handling customer interactions compared to their total available time while logged in.
Unlike "Utilization," which often accounts for paid time (including breaks, meetings, and training), Occupancy specifically focuses on the time an agent is available to take calls versus the time they are actually working on them.
The Occupancy Rate Formula
To calculate the occupancy rate manually, you need to aggregate three specific work components and divide them by the total logged-in time. The formula is:
Occupancy Rate % = ( (Talk Time + Hold Time + After Call Work) / Total Logged-In Time ) × 100
Here is a breakdown of the variables:
Talk Time: The total minutes spent speaking with customers.
Hold Time: The total minutes customers spent on hold during active calls.
After Call Work (ACW): Also known as Wrap-Up time, this is the time spent documenting the call or performing necessary transactions immediately after the call disconnects.
Total Logged-In Time: The total duration the agent was signed into the queue and available to receive work (excluding offline statuses like "Break" or "Training").
Understanding the Results
Interpreting your occupancy rate is a balancing act between efficiency and employee well-being.
1. The "Danger Zone" (Under 70%)
If your occupancy rate is consistently below 70%, it generally indicates that your call center is overstaffed. Agents are spending a significant amount of time waiting for calls (idle time). While this ensures immediate answer times for customers, it is not cost-effective.
2. The "Sweet Spot" (75% – 85%)
Most industry standards consider 75% to 85% to be the optimal range. At this level, agents are kept busy enough to be productive but still have small pockets of "breathing room" between calls (micro-breaks) to reset mentally.
3. The "Burnout Zone" (Above 85-90%)
While a 95% occupancy rate might look good on a finance spreadsheet, it is detrimental to long-term operations. Rates consistently above 85-90% mean agents have almost zero downtime between calls. This leads to:
High Attrition: Agents burn out quickly and quit.
Lower CSAT: Exhausted agents provide poorer customer service.
Increased AHT: Agents may intentionally extend calls to avoid getting the next one immediately.
Example Calculation
Imagine an agent works an 8-hour shift (480 minutes). They take 60 minutes of break/lunch (unpaid/offline), leaving 420 minutes of Logged-In Time.
During the day, their metrics are:
Talk Time: 280 minutes
Hold Time: 20 minutes
ACW: 40 minutes
Total Handle Time: 280 + 20 + 40 = 340 minutes.
Calculation: (340 / 420) × 100 = 80.95%.
This agent is operating squarely in the optimal efficiency zone.
function calculateOccupancy() {
// 1. Get input values
var talkTimeInput = document.getElementById('talkTime').value;
var holdTimeInput = document.getElementById('holdTime').value;
var acwTimeInput = document.getElementById('acwTime').value;
var loggedInTimeInput = document.getElementById('loggedInTime').value;
// 2. Parse values to floats, default to 0 if empty
var talkTime = parseFloat(talkTimeInput) || 0;
var holdTime = parseFloat(holdTimeInput) || 0;
var acwTime = parseFloat(acwTimeInput) || 0;
var loggedInTime = parseFloat(loggedInTimeInput) || 0;
// 3. Validation
if (loggedInTime loggedInTime) {
// We allow calculation but show a warning usually. For this specific calc, we will proceed.
}
// 5. Calculate Occupancy Percentage
var occupancyRate = (totalHandleTime / loggedInTime) * 100;
// 6. Calculate Idle Time
var idleTime = loggedInTime – totalHandleTime;
// 7. Determine Status and Colors
var statusText = "";
var statusColor = "";
var analysis = "";
if (occupancyRate = 70 && occupancyRate 85 && occupancyRate <= 90) {
statusText = "High Load";
statusColor = "#fd7e14"; // Orange
analysis = "Efficiency is high, but risk of agent fatigue is increasing.";
} else {
statusText = "Critical / Burnout Risk";
statusColor = "#dc3545"; // Red
analysis = "Agents have zero downtime. High risk of burnout and error.";
}
// 8. Update the DOM
document.getElementById('finalOccupancy').innerText = occupancyRate.toFixed(2) + "%";
document.getElementById('totalHandleTime').innerText = totalHandleTime.toFixed(1) + " min";
document.getElementById('idleTime').innerText = idleTime.toFixed(1) + " min";
document.getElementById('analysisText').innerText = analysis;
var badge = document.getElementById('statusBadge');
badge.innerText = statusText;
badge.style.backgroundColor = statusColor;
// Show results
document.getElementById('results').style.display = 'block';
}