SLA Dashboard
For example, if a customer reports fraudulent activity in their bank account, this is treated as a critical request. The bank’s dispute resolution team works under a defined SLA where all critical issues are resolved within 24 hours. To adhere to the SLA, the team works around the clock and offers the support provided.
Failure to resolve the issue within the defined timeframe results in an SLA breach. While occasional violations may be handled and addressed internally, repeated violations raise red flags.
The SLA dashboard provides an overview of the SLA violated tickets to help the managers quickly understand the issue and take action.
Each department may have its own set of workflows and SLAs, but the SLA dashboard offers a comprehensive view of how SLAs are being managed across the organization. Managers can monitor important metrics to get visibility, ensure timely resolution, maintain operational efficiency, and ultimately improve customer satisfaction.
- SLA violated tickets - Number of tickets that violated the SLA.
- SLA violations - Number of instances when the SLA targets were violated. For example, if an SLA target is violated twice in a ticket and once in another ticket, the consolidated number is calculated as three.
- Average residual time - Shows the time remaining before the SLA is due. Average time between when a ticket is closed and its SLA deadline. For example, if a ticket is resolved at 2 PM and the SLA deadline is 5 PM, the residual time is 3 hours. It indicates how much earlier the issue was resolved before the SLA deadline.
- Average violation time - Average time a ticket exceeds the SLA. For example, if a ticket is resolved at 4:30 PM but the SLA was set to 4 PM, the violation time is 30 minutes. It indicates how late the resolution was provided, violating the SLA.
The SLA dashboard includes seven important components:
- SLA violated tickets
- Adherence vs violated tickets
- Adherence vs violated instances
- Violations by - SLA and Agents
- Violation by time
- Violation by status
- Violation by channel
Filtering the SLA dashboard
The dashboard can be customized to view specific data by using the below mentioned filters.
- SLA Name
- Violation type - first response, response, or resolution
- Teams
- Agents
- Duration
- Last 24 Hours
- Today
- Yesterday
- Last 7 days
- Last 30 days
- Current week
- Last week
- Current month
- Last month
- Custom
SLA violated tickets
The SLA violated tickets display the number of tickets that were not resolved within the set SLA timeline. This component helps managers identify the root cause for delayed resolution, resource allocation, re-evaluate the SLA targets, enhance effective team collaboration, and workflow management.
For example, if a customer support team has an SLA as 4 hours to resolve a high priority ticket but the manager notices in the dashboard that the SLA for high priority tickets is frequently violated and the average time taken is 6 hours.
Support managers can assess the type of requests that come in as high-priority and analyze the reason for delay to modify the SLA by setting more achievable timeline.
The graph displays the ticket count and the time when the tickets were raised. Hovering on the graph will display the ticket count for that specific hour.
Adherence vs violated tickets
The overall percentage of tickets that were resolved within the SLA timeline versus the ones that violated the SLA will be displayed. More number of violations can indicate inefficiencies in ticket resolution. Improving the ticket handling processes, addressing bottlenecks can help address the concern.
Adherence vs violated instances
The percentage of instances when tickets were resolved within the SLA timeline versus instances of violations. The number of tickets contributing to each instance can also be monitored.
Violations by - SLA and Agents
Each department can have multiple SLAs, which can be filtered by SLA name and agent. For each SLA the data shows the number of times it was applied, violated, or achieved.
Violations by time
This graph provides a visual representation of the number of tickets that violated the SLA hourly. It helps managers identify peak times when violations are more, helping them reassign agents as per requirements to improve response times and reduce SLA violations.
For example, if the duration is selected as last week, and the maximum number of tickets that violated the SLA is at 2 PM, managers can reassign agents from other shifts to cover this peak hour.
This ensures that adequate support is provided during high-violation hours, reducing the chances of SLA violations.
Violation by status
This graph helps identify which status across all departments is experiencing the highest number of SLA violations.
For example, the telecom service team has a transition status Pending Activation with an SLA of 24 hours from when a customer requests service activation.
An SLA violation occurs if the status is not updated to Service Activated within 24 hours.
This graph tracks the number of service activation tickets that violated the SLA, helping managers streamline the activation process.
Violation by channels
Channel-wise SLAs allow optimum resource allocation and allow improvisation of ticket deflection to the right team and department by considering the inflow of tickets.
Some channels, like email and chat, are preferred mode of communication and can see higher influx, therefore SLAs can wisely used to meet FRTs and reduce violations.
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