SLA Rules

Index

1. What is it and what is it for?
2. How to configure an SLA rule?
3. Real-time monitoring
4. Performance analysis (Service Report)
5. Ticket-based analysis (Service History)
6. How are SLA indicators calculated?

What is it and what is it for?

SLA rules are sets of time-based goals that you can configure to track whether your operation’s deadlines are being met.

Within an SLA rule, you can set achievement targets for one or more operational metrics: waiting time (TME), first response time (TMR1), and handling time (TMA). Each SLA rule must be assigned to at least one queue and can be set as the default for all queues.

When you configure an SLA rule, Blip automatically compares the actual ticket times with the targets you’ve set. This allows you to generate visual alerts and detailed reports about your team’s performance against the established goals.

IMPORTANT: This feature is currently available in Beta. If you’re interested in participating in the testing, please contact the CSM responsible for your account.

How to configure an SLA rule?

1. Access the Blip Portal;
   
   
2. Select a service bot;
   
   
3. Go to the "Service" tab;
   
   
4. Open the "SLA Rules" menu;
   
   
5. Click "New Rule";
   
   
6. Give your SLA rule a name;
   
   
7. Select the queues where the rule will be applied (or leave it as the default rule for all queues);
   
   
8. Enable the metrics you want to track:
   
   
   1. Average Waiting Time (TME)
      
      
   2. Average First Response Time (TMR1)
      
      
   3. Average Handling Time (TMA)
      
      
9. Set the target time for each selected metric;
   
   
10. Save the configuration.
    
    

Done! From now on, you’ll be able to monitor the achievement of the expected times for the main operational metrics. See below an example of the SLA rule creation screen.

IMPORTANT: Although you can create multiple SLA rules, only one rule can be applied per queue. All tickets directed to a queue with an assigned rule will be evaluated based on the targets defined in that rule — it’s not possible to disable a rule (or its targets) for individual tickets.

Real-time monitoring

Whenever a ticket exceeds an SLA target, it will be visually highlighted on the monitoring screen. The highlight appears over the specific metric that was exceeded ("Time in Queue," "First Response Time," or "Handling Time").

You can view the notification in the ticket details section, under the "Assigned/In Progress" and "Tickets in Queue" tabs, as shown in the image below:

The visual notification for assigned tickets without a first response from the agent will still appear highlighted in the monitoring screen, but in yellow and only over the "Handling Time" column, as long as the status text "Waiting" is displayed:

Performance Analysis (Service Report)

The SLA tracking section, available in the service report, gathers indicators that help managers monitor the operation’s performance against the configured targets. In this section, you can clearly view:

• The overall SLA achievement rate;
  
  
• Tickets that did not meet the defined targets;
  
  
• Tickets with an assigned SLA rule;
  
  
• Average exception time;
  
  
• SLA target achievement by metric type (Waiting Time, First Response Time, and Handling Time).
  
  

See below the SLA tracking section within the service report.

This view allows managers to quickly identify bottlenecks in the operation and make strategic decisions based on this data.

In addition to the overall view by queue and by metric type, the service report also displays the SLA achievement rate by agent. This way, besides the general overview, managers can also track the individual performance of the team in relation to the configured rules — identifying who is meeting expectations and who might be facing challenges.

TIP: In addition to the achievement rate shown in the "Agents" section, it is possible to view more detailed individual performance of agents or by queues in the SLA indicators section by applying a filter and selecting a specific agent or queue:

With this data, it is possible to provide more precise feedback, offer personalized support, or reassess the distribution of tickets among agents.

Ticket-based Analysis (Service History)

In addition to real-time visual alerts and performance views by team or agents, it is also possible to check how a specific ticket performed against the SLA rules in the service history.

This ticket-based view allows you to understand, for example, which targets were met or missed in each service interaction, what the actual time recorded was compared to the configured target, and at which point in the flow any excess occurred.

With this, the manager can analyze specific cases more deeply, support feedback conversations, investigate process deviations, and justify operational decisions based on objective data.

How are SLA indicators calculated?

Overall Achievement: Count of tickets with an assigned and active SLA rule that met ALL THE TARGETS defined in the rule.
For example: In a certain queue, an SLA rule is assigned with time targets for Waiting (10 minutes) and First Response (3 minutes). Three tickets from this queue were handled during the day, as shown in the table below.

 

Notice that ticket number #00001 met the waiting time and first response time targets. Ticket number #00002 exceeded the waiting time limit, and ticket #00003 exceeded both targets (waiting time and first response).
Thus, the count of tickets that met 100% of the defined rules (overall achievement) would be 1 (ticket #00001).

Not achieved: Count of tickets that exceeded at least one of the targets defined in the assigned SLA rule (this indicator is the exact opposite of the previous one).
For example: Considering the previous scenario, the count of tickets that did not meet SLA targets would be 2 (tickets #00002 and #00003).

Tickets with assigned rule: Count of tickets handled in queues where an SLA rule was configured and active.
For example: Suppose a service operation has two different queues registered — queue A and queue B. The first queue (A) does not have an SLA rule assigned, while the second queue (B) has an assigned and active SLA rule.

In the example above, the indicator for tickets with an assigned rule would show the number 203, even though the total tickets handled that day were 468, because only queue B had an assigned and active SLA rule.

Exception time: The target time defined in the specific goal minus the actual time recorded for the ticket.
If the result of this calculation is zero or greater, then the counted value will be zero. If the result is less than zero, then the calculated negative value will be counted.
For example: the handling time target defined for a certain queue was 20 minutes. Ticket number #00008, assigned to that queue, had a handling time (TMA) of 19:53, while ticket #00009, also assigned to the same queue, had a TMA of 27:09.

Ticket number #00008 did not exceed the TMA target (20 minutes) and therefore the exception time will remain zero, even though the calculation results in a non-zero number (00:00:07). In the case of ticket #00009, applying the rule (00:20:00 - 00:27:09) shows that the total exception time is below zero, so the calculated value itself is counted (00:07:09).

Average exception time: The sum of the exception times for targets exceeded by tickets (regardless of metric type), divided by the number of times a target exceeded the defined SLA.
For example: consider that three tickets exceeded the SLA targets defined for them, as shown in the table below.

In the example above, there were four targets exceeded (across three different tickets). The average exception time would be calculated as follows:

Average exception time = (
  Exception of TMA for ticket #00011 +
  Exception of TME for ticket #00012 +
  Exception of TME for ticket #00013 +
  Exception of TMR1 for ticket #00013
) / 4

Average exception time = (00:39:00 + 00:11:00 + 00:08:13 + 00:03:49) / 4
Thus, the value shown in the average exception time indicator would be 00:15:30 (fifteen minutes and thirty seconds).

SLA achievement rate by target: Number of tickets that met the specific target (TME/TMR1/TMA), divided by the number of tickets that had that same metric assigned.
In this case, the calculation is done individually by target/metric type. Therefore, if the SLA rule assigned to the queues does not have an active target for one of the operational metrics, the graph for that metric will show zero.
For example: the SLA rule defined for the queues had active targets for TME and TMA.

Assuming the tickets in the table above represent all the service interactions during the period with an active SLA rule, the achievement rate per target would be as follows:

• Waiting Time (TME): 1 ticket met the target / 5 tickets assigned the target (20%)
  
  
• First Response Time (TMR1): no tickets had this target assigned (0%)
  
  
• Handling Time (TMA): 3 tickets met the target / 5 tickets assigned the target (60%)
  
  

SLA achievement rate (agents): Number of tickets by the agent that met all SLA targets / Number of tickets by the agent that had the same assigned rule.
For example: assuming agent João handled 10 tickets during the day, all with an active SLA rule, and met all SLA targets in 7 of those tickets, his achievement rate for the day would be 70%.

For more information, check out the discussion on this topic in our community or watch the videos on our channel. 😃