Steps:

1. The Major Incident Prediction capability monitors whether the pre-configured number of newly created tickets reaches the defined threshold (Ticket Volume Trigger) before the pre-configured time limit expires. If yes, an engine pulls all tickets created during the time frame and identifies clusters of similar tickets that meet the Cluster Size threshold.
2. The extension creates a Major Incident proposal for each cluster, based on the related tickets. The Active Major Incident Proposals widget at Service Desk > Home shows a new proposal.
3. The user opens the list of active Major Incident proposals.
4. The user opens one of the list entries and reviews the incident and the related tickets.
5. The user clicks Accept Proposal. 
6. Optionally, the user adds the incident to the Service Availability Center.

Expected outcome: The Major Incident Prediction feature creates a Major Incident proposal. It converts to a Major Incident and gets updated in the Open Major Incidents widget.

Reject Proposal for Major Incident

Scenario: Based on parameters set by the user, the Major Incident Prediction feature detects a potential Major Incident in the environment.

Steps:

1. The Major Incident Prediction checks if the pre-configured ticket volume reaches the defined threshold within the pre-configured time frame. If yes, an engine pulls all tickets created during the time frame and identifies clusters of similar tickets that meet the Cluster Size threshold.
2. The extension creates a Major Incident proposal. The Active Major Incident Proposals widget at Service Desk > Home shows a new proposal.
3. The user opens the list of active Major Incident proposals.
4. The user opens one of the list entries and reviews the incident and the related tickets.
5. The user clicks Reject Proposal. 

Expected outcome: The Major Incident proposal is declined.

KBA Proposals

Review and Accept a KBA Proposal

Scenario: Based on parameters set by the user, the KBA Gap detection feature identifies recurring issues across similar tickets that are not covered by existing Knowledge Base content and can be addressed with a new Knowledge Base article.

Set parameters:

• Initial Analysis Lookback Period (months): 6
• Recurring Analysis Ticket Threshold: 200

Steps:

1. The KBA Gap analysis runs each time 200 tickets have been closed since the previous run*. A portion of these tickets is related to issues with accessing emails from a specific browser. The system compares the ticket content against the existing Knowledge Base articles and discovers that none sufficiently address this specific issue. As a result, a knowledge gap is identified.
   *The initial run analyzes all closed tickets from the past 6 months.
2. The feature creates a KBA Proposal based on ticket resolutions
3. Using the KBA Proposals widget, the Service Desk user reviews the suggestion and changes the state from Draft to Final to make the KB Article available for the configured Audience.