Configure automated finding definitions

  • Release version: Washingtondc
  • Updated February 1, 2024
  • 1 minute to read
  • Configure automated finding definitions to view the insights specified by you in your Summary and Insights dashboard.

    Before you begin

    • You can create one configuration per table for each project based on a process.
    • Role required:
      • The sn_process_optimization_admin and sn_process_optimization_power_user roles can create a finding definition for a project.
      • The sn_process_optimization_analyst role can view a finding definition for a project, but can’t create, edit, or delete a definition.

    About this task

    Automated findings are configured for a table in the process configuration. These findings can be imported into any project based on that table for generating improvement opportunities.

    Procedure

    1. Navigate to All > Process Mining > Process Configurations.
    2. Select the table that you want to use for your findings.
    3. In the Automated Finding Definitions tab, select New.
    4. Fill in the fields in the Automated Finding Definition form.
      Table 1. Automated Finding definition fields
      Field Description
      Name Title for the insight. This text appears at the top of the insight card on the Summary and Insights dashboard.
      Active Whether the finding definition is active.
      Type Type of finding. You can select from the list available. Three options are available:
      • Rework: Refers to a repeating step or activity in the process. It happens when a process step must be redone or revisited.
      • Ping-Pong: Refers to a repetitive pattern where a record bounces between two process steps or activities without interruption, indicating a loop.
      • Extra step: Compares each route to identify the existence of different routes that deviate in only one step, thus pinpointing process steps where unnecessary transitions occur.
      • Repeating patterns: Detects unnecessary repeating sequence of steps.
      • Extreme duration: Finds records with a very long transition time compared to other transition records.
      • Extreme repetition: Finds records with a very high number of arc repetitions compared to other records on the same arc.
      • Slow transition: Identifies situations where there is a cluster of records with similar durations, and this cluster has a higher average duration compared to other group of records. This detector also offers a breakdown of the significance of the identified cluster, providing further insights into the root cause.
      Category Category for this finding definition.
      • Quality
      • Automation
      • Conformance
      • Performance
      Field A field on which the finding definition is used.
      Select impacted KPIs Select the related KPIs to link with the finding definition.
      Note:
      This field is populated from the PA Indicator table.
    5. Select Submit.