JSM 2005 - Toronto

Abstract #303598

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 177
Type: Topic Contributed
Date/Time: Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor: Business and Economics Statistics Section
Abstract - #303598
Title: Discovery, Visualization, and Performance Analysis of Enterprise Workflow
Author(s): Ping Zhang*+ and Patrick H. Tendick
Companies: Avaya Labs Research and Avaya Labs Research
Address: 233 Mt Airy Rd, Basking Ridge, NJ, 07920, United States
Keywords: Data visualization ; Business Process ; Queueing system ; Mixture model ; Cure model
Abstract:

This work was motivated by a recent experience where we needed to develop enterprise operational reports when the underlying business process is not entirely known, a common situation for large companies with sophisticated IT systems. We learned that instead of relying on human knowledge or business documentation, it is much more reliable to learn the workflow structure from data. In this paper, we developed an algorithm to discover and visualize workflows from audit trail data, and argued that workflow discovery is a prerequisite for rigorous performance analysis. We also carried out a detailed performance analysis based on the discovered workflow using data from a remote technical support center. We found service time fits the profile of a log-mixture distribution. It takes at least two parameters to describe such a distribution, which leads to the proposed method of using two metrics for service time reporting.

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Revised March 2005