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Automated Findings represent sets of filters, constraints and discovery rules that can be applied to a Process Model to uncover process and workflow problems, as well as opportunities for improvement.   Examples of Automated FIndings include:

Filters

  • Issues containing the step, or transition, from Open to Pending

  • Issues having Priority = 'Critical'

Constraints

  • Issues where the Resolved to Closed duration is > 7 days

  • Issues that were in Pending status more than 2 times

Discovery Rules

  • Variants containing more than 2 loops

  • Steps where the standard deviation is less than 2 hours

Defining Filters is detailed at Process Optimizer - Control Panels - Filters, defining Constraints at Process Optimizer - Control Panels - Constraints, and Discovery Rules at Process Optimizer - Control Panel - Discovery Rules

The Process Optimizer contains numerous pre-defined Automated Findings, both generic, and specific to commonly used issue types.    This effectively means that once a Process Model is built, the findings can be loaded and the Process Optimizer will tell you what your process and workflow problems are.  This is discussed in detail at Process Optimizer - Visualizations - Findings

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There are 2 core types of automated findings.  The first are 'Generic', in that they apply to all issue types.  The second type of finding relates to a specific issue type.

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The definition of an Automated Finding consists of the issue type, the finding name, or short description, the category  (Performance, Compliance, Workflow or Quality), the  the activity related to the finding e.g. status, assignment group, priority  (refer Configuration - Activities) and the detailed definition of the Automated Finding, stored as a JSON field containing the specific filters, constraints and discovery rules

Recommendations

An Automated Finding can also contain one or more Recommendations to address the problems found and improvement opportunities.  Recommendations are created and edited via accessing Options -> Recommendations.

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To create a new recommendation, click the 'Create' button.  The definition of a recommendation includes the following fields:

 

Field

Description

Recommendation

A short description of the recommendation

Recommendation Type

One of the following values:

  • Automation

  • Workflow Configuration

  • Knowledge Base

  • Training

  • Root Cause Analysis

Details

A detailed descrioption of the recommendation to be implemented to resolve the automated finding

Creating and Editing

Automated Findings can be created in any Process Model once filters, constraints or discovery rules are applied.   They can be saved as a 'Generic' finding or specific to the issue type selected for the process model.

The underlying definition of an automated finding can be edited by accessing the 'Options' -> 'Edit', and then modifying the JSON associated with the finding.

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There is also the ability to delete and copy Automated Findings.  Note that if an Automated Finding is deleted that is has been saved in a Process Model, then the Finding will not be deleted from the Process model.

 

 

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