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.