Business Process Impact Visualization and Anomaly Detection

Abstract

Business operations involve many factors and relationships and are modeled as complex business process workflows. The execution of these business processes generates vast volumes of complex data. The operational data are instances of the process flow, taking different paths through the process. The goal is to use the complex information to analyze and improve operations and to optimize the process flow. In this paper, we introduce a new visualization technique, called VisImpact that turns raw operational business data into valuable information. VisImpact reduces data complexity by analyzing operational data and abstracting the most critical factors, called impact factors, which influence business operations. The analysis may identify single nodes of the business flow graph as important factors but it may also determine aggregations of nodes to be important. Moreover, the analysis may find that single nodes have certain data values associated with them which have an influence on some business metrics or resource usage parameters. The impact factors are presented as nodes in a symmetric circular graph, providing insight into core business operations and relationships. A cause-effect mechanism is built in to determine ‘good’ and ‘bad’ operational behavior and to take action accordingly. We have applied VisImpact to real-world applications, fraud analysis and service contract analysis, to show the power of VisImpact for finding relationships among the most important impact factors and for immediate identification of anomalies. The VisImpact system provides a highly interactive interface including drilldown capabilities down to transaction levels to allow multilevel views of business dynamics.

Keywords

Business intelligence visual data mining visualization technique

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