Examples of Custom metrics

The following are some examples of custom metrics that can be applied in your IBM Process Mining project.

Define SLA based on the priority custom field

The following custom metric computes the Case SLA in milliseconds based on the priority field, which makes it suitable for the ticketing process.

Data type: Duration


case when max(priority) = 'High' then 1*24*60*60*1000
else case when max(priority) = 'Medium' then 2*24*60*60*1000
else 5*24*60*60*1000
end
end

Group by: Case ID

Data type is set to Duration to automatically display the metric as a duration instead of a number.
Keep last event for each case is enabled to consider the last value for each case. For more information, see Configuring widgets.

Count the number of specific deviations per case

The following custom metric computes the number of activities with the word change in their name.

Data type: Numeric


count(activity)

Group by: Case ID

Where:


activity LIKE '%Change%'

Where filter applies the filtering only on activities with a specific naming.

Compute the case risk by basing it on the occurrences of some activities

The following custom metric computes case risk by basing it on the Count the number of specific deviations per case custom metric.

Data type: Numeric


SQL_MIN (7*count_changes,100)

Group by: Case ID

Many deviations might violate the SLA of your project or return a negative outcome.

Define the positive or negative outcome by basing it on occurrences of a specific activity

The following custom metric returns true if the activity Resolution Rejected occurs.

Data type: Boolean


case when listagg(activity) LIKE '%Resolution Rejected%' then 1 else 0
end

Group by: Case ID

listagg(activity) requires Resolution Rejected to be written inside the LIKE function.