- 13 Dec 2024
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WFM Metrics
- Updated on 13 Dec 2024
- 6 Minutes to read
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Understanding performance metrics is key to managing your team’s productivity. Let’s review the key metrics used in Dialpad WFM, helping you track progress, spot areas for improvement, and keep your team on track.
Who can use this
Dialpad WFM is available to all Dialpad users.
Contact your Customer Success Manager to discuss adding Dialpad WFM to your plan.
Utilization
‘Utilization’ shows how much time an agent was scheduled for service activities in the selected period.
This metric provides a view of how well utilized agents were on service, and can be used to add context to other metrics.
For example, an agent with low utilization is likely to work on much fewer tickets than an agent with high utilization.
Note
Service activities are activities that are linked to a queue.
Utilization is calculated by dividing the time an agent spends actively working on customer tasks by the total time they were scheduled to work. The result is then multiplied by 100 to get a percentage.
For example, if an agent is scheduled to work 8 hours and spends 4 hours on customer interactions, their utilization rate would be 50%
Total Closed
‘Total Closed’ measures total output, counting the total number of tickets with a 'closed' status.
This data will change slightly depending on whether you're viewing the metric per agent or per activity.
When viewing metrics at the agent level, the data is calculated based on the specific agent who closed the ticket.
When viewing metrics at the activity level, the data is calculated based on the type of activity that was closed, regardless of the specific agent involved.
Note
For Zendesk integrations, "Total closed" = number of "Closed" and "Solved" tickets.
Closed per Hour
‘Closed per hour’ highlights an agent's productivity and impact on overall team performance. It measures the average number of tickets closed per scheduled hour, providing insights into workload management and efficiency.
Closed per hours is calculated by dividing the number of tickets closed by the number of hours worked.
For example, if an agent closed 20 tickets over 8 hours, their Closed per hour score would be 2.5.
This is particularly helpful when measuring BPOs or analyzing cost-to-serve.
Closed per Service Hour
‘Closed per Service Hour’ displays the average number of tickets closed for each hour that was specifically scheduled for service activities.
This metric provides a fairer, unbiased measure of productivity by removing any time that was not scheduled on service — this is helpful when agent's utilization varies.
‘Closed per Service Hour’ is calculated by dividing the number of tickets closed by the number of hours scheduled for service activities.
For example, an agent’s shift was 8 hours, and 4 hours were scheduled on service activities. They closed 20 tickets during their shift, so their ‘Closed per Service Hour’ score is 5.
Time-on-task
‘Time-on-task’ represents the percentage of total scheduled hours that were spent on-task.
This metric is an alternative to the industry standard of "adherence", and indicates how well the agent actively followed their schedule across the entire shift.
Unlike other tools, Dialpad WFM verifies if the agent is actively working by using tracked activity from linked customer service platforms, rather than relying on shallow data such as status.
‘Time-on-Task’ is calculated by subtracting off-task time from total scheduled time, then dividing the result by the total scheduled time and multiplying by 100.
For example, if an agent is scheduled for 8 hours but spends 1.5 hours off-task, their actual work time is 6.5 hours. To calculate their time-on-task percentage, we divide their work time (6.5 hours) by their total scheduled time (8 hours) and multiply by 100. This results in a time-on-task percentage of 81.25%.
What is on-task?
When agents are scheduled on service activities, their activity is tracked within the linked customer service platform (e.g. Zendesk).
If no activity is tracked, then an agent will be marked as 'off-task', and this time will be detracted from their score.
When agent's are scheduled on non-service activities, breaks, or meetings, it is expected that they won't be working in the customer service platform (e.g. Zendesk), so no activity is classed as 'on-task'.
This definition applies to both time-on-task and occupancy.
Occupancy
‘Occupancy’ is the percentage of the total hours scheduled for service activities that were actually spent on-task.
This metric helps to focus in on time spent on-task while agents were scheduled on service, removing any time lost at other times, e.g. a meeting overran, or the agent went to lunch late.
‘Occupancy’ is calculated by subtracting off-task hours from the total scheduled hours on service activities, then dividing the result by the total scheduled hours on service activities, and finally multiplying by 100 to get a percentage.
For example, an agent is scheduled to work 8 hours, with 4 hours allocated for service activities. However, due to breaks or other off-task time, they only spend 3 hours on service activities.
To calculate the occupancy percentage, we first determine the on-task hours:
On-task hours = Scheduled service hours - Off-task hours
On-task hours = 4 hours - 1 hour = 3 hours
Then, we calculate the occupancy percentage:
Occupancy = (On-task hours / Scheduled service hours) 100
Occupancy = (3 hours / 4 hours) 100 = 75%
In this scenario, the agent's occupancy is 75%, meaning 75% of their scheduled service time was spent actively working on customer tasks.
Average Interaction Time (AIT)
‘Average interaction time’ (also known as as AIT), measures the average time it took agents to complete each interaction. An interaction is an event related to a ticket, i.e. a comment was added/sent, or the status of the ticket changed (e.g. open -> closed).
This metric provides insight into the average duration of each customer interaction, helping to identify areas for efficiency improvement and better resource allocation.
Average Interaction Time is calculated by dividing the total time scheduled on interactions by the number of interactions.
For example, if an agent handles 20 interactions in a day, spending a total of 400 minutes, the average interaction time would be 20 minutes (400 minutes ÷ 20 interactions).
Average Conversation Time
‘Average conversation time’, (also known as ACT), measures the average total active working time spent to close a ticket, removing waiting or idle time.
This metric is an alternative to the industry standard of "average handle time" (AHT)
Traditional methods of measuring average handle time (AHT) often rely on tracking the time from ticket creation to closure. However, this approach can be misleading, especially for asynchronous channels like email and chat. These channels often involve extended wait times between responses, which can artificially inflate AHT metrics.
To address this limitation, Dialpad WFM uses a more accurate approach that focuses on actual agent handling time. This ensures that staffing requirements are based on realistic workload assessments and avoids unnecessary overstaffing.
When we build an activity timeline, we group related interactions on the same ticket into "ticket sessions" to get a more accurate picture of actual handling time. Once a ticket is closed, we combine all its session durations to calculate the total conversation time.
The average conversation time is then determined by calculating the average of all closed ticket conversation times within a specific timeframe (e.g., daily, weekly).
For example, Ben exchanges 3 messages with a customer on live chat. The customer then stops responding. These 3 messages form 1 ticket session that lasted 300s.
The customer responds again after work and the 2 more messages are sent, then the conversation is closed. These 2 messages form another ticket session that lasted 240s.
There are now 2 ticket sessions on this ticket, from open to close. These are added together to create a Conversation Time of 540s.