SLA Consumption Tracking by Agent

The current SLA (Service Level Agreement) system in Freshservice tracks the overall time taken to resolve a ticket but does not provide insight into how much of the SLA was consumed by individual agents who handled the ticket. This can lead to a lack of accountability and visibility when multiple agents are involved.

Proposed Feature: SLA Consumption by Agent Breakdown

This feature aims to track and report the SLA consumption per agent on a ticket. When a ticket is handled by multiple agents, the system will calculate and report how much of the total SLA time was consumed by each agent during their ownership of the ticket. This will help provide a more detailed view of team performance and individual contributions.

Key Features:

1. SLA Time Tracking Per Agent:

   • The system will automatically track the time each agent has ownership of a ticket. The SLA will be split and calculated per agent.
   • For each ticket, a detailed log will show the duration the ticket was with each agent and how much SLA time was consumed during their ownership.

2. Ownership Transfer Handling:

   • When the ownership of a ticket is transferred from one agent to another, the SLA timer for the current agent stops, and it resumes for the next agent once they take ownership.
   • The system will ensure the remaining SLA time is recalculated correctly for the subsequent agents.

3. SLA Consumption Report:

   • A new reporting feature will show SLA consumption by agent, detailing:
     • Total time the ticket was in each agent’s queue.
     • The percentage of SLA consumed by each agent.
     • Total SLA time used up by the team in resolving the issue.

4. Enhanced Accountability:

   • By assigning SLA consumption to specific agents, it will improve accountability and allow teams to identify bottlenecks, inefficiencies, or areas for additional support or training.

5. Integration with Current SLA and Reporting Tools:

   • The feature will integrate with the existing SLA and reporting systems, allowing users to generate reports that compare SLA performance between agents.
   • Custom filters can allow users to sort tickets based on the highest or lowest SLA consumption by specific agents.

Use Case Example:

• Ticket #12345 was handled by three agents:
  • Agent A owned the ticket for 2 hours (consuming 30% of the SLA).
  • Agent B owned the ticket for 4 hours (consuming 50% of the SLA).
  • Agent C resolved the ticket after 1 hour (consuming 20% of the SLA).

In the final report, you can see exactly how the SLA was split across each agent and identify if one agent consumed more time than expected or if another agent quickly resolved the issue.

Benefits:

• Improved Visibility: Managers can see who contributed to the SLA consumption and pinpoint where delays are occurring.
• Fair Evaluation: Agents will be evaluated more fairly based on their actual contribution to the ticket's SLA, not just the final resolution.
• Better Resource Allocation: The data can help reassign tickets to the right agents or improve response times based on historical performance.