Predicting the severity of an active support ticket

US9785918B2 · kind B2 · utility

Assignee

• SAP SE · DE

Inventors

• Gabriele Bodda · Palo Alto, US
• Ryan Currier · Cupertino, US
• Venkitesh Subramanian · Palo Alto, US
• Prerna Makanawala · Palo Alto, US
• Rei Kasai · San Mateo, US
• Devasena Rajamohan · Palo Alto, US
• Amith Manoharan Chithambaram · Palo Alto, US
• Terence Chesire · Palo Alto, US
• Kiran Karadi · Palo Alto, US

Key dates

• Filing date: Sep 19, 2014
• Grant date: Oct 10, 2017
• Expiry date: Oct 28, 2035

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q10/20
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

An issue tracking system capable of predicting the likelihood that an outcome of interest will occur during the lifecycle of an active support ticket. The likelihood can be represented as a severity index score. The issue tracking system can apply a predictive algorithm on attributes of the active support ticket to generate the severity index score. The predictive algorithm to use can depend on the outcome of interest while the correlation factors used to configure the predictive algorithm can depend on support tickets that have already been completed.