Intelligent agent supported business process and exception management
Student thesis: Doctoral Thesis
Related Research Unit(s)
|Award date||15 Feb 2005|
In recent years businesses around the world have been facing the challenges of a rapidly changing business and technology environment. As a result, organizations are paying more attention to supporting business process management by adapting to the dynamic environment. The unpredictability of business activities requires that business applications support exception management to achieve improved performance of systems. However, traditional approaches to business process and exception management are based on workflow technology. They model and manage business processes and anticipated exceptions based on a predefined logical procedure of activities from a centralized perspective, which offer little support for the dynamic environment. In order to solve the problem, an intelligent agent supported cognitive approach to business process and exception management has been investigated in this research. It contains three separate, but interrelated parts. The first part depicts an agent-based cognitive approach to manage business activities based on situational awareness and real-time decisions on activities (Wang et al. 2004d). Business activities are delegated to a number of cognitive and collaborative agents. Each agent can perceive its environment by capturing events and monitoring the state of tasks and resources. Based on the continuous perception of the environment, business rules concerning process routing, operational constraint, exception handling and business strategy are used by such software agents to perform appropriate actions. The mechanism of this approach is investigated, and the agent-based framework is elaborated. The proposed approach is compared with workflow approaches, and its validity and benefits are demonstrated. The second part uses the agent-based cognitive approach to deal with the complex processes in exception management, in which multiple organizations and mixture of human activities and automated tasks may be involved (Wang et al. 2004c). Relevant data are extracted from existing applications to the exception management agents for detection and diagnosis, and resolutions of exceptions are sent back to legacy systems for repair actions. Moreover, web services technique is adopted for more scalability and interoperability in network-based business environment. By integrating agent technology with web services and using the advantages from both, this approach leads to a more intelligent, flexible, and collaborative business exception management. The third part presents a prototype system of exception management in securities trading using the approach proposed in the second part (Wang et al. 2004b). The prototype aims to automate the identification and resolution of exceptions to assist securities industry to gain quicker competitive advantage. The development of the prototype illustrates how the proposed approach is applied to a real world application. The effectiveness of this system is evaluated through a use case and demonstration feedback. The results reveal the success in using web services and agent-based technique for exception management in business activities. There are two major contributions of this research. Firstly, an agent-based cognitive approach to adaptive process and exception management is proposed. Compared with traditional workflow technology, the cognitive approach is characterized by i) continuous perception of business environment, ii) real time and decision-based control of business activities, iii) extension from process logic to business logic for process management. Secondly, the mechanism of agent application in complex business process and exception management is investigated, especially in the context of flexible task management and knowledge engineering. Based on this mechanism, an agent-based framework for a cognitive approach to complex process and exception management is proposed.
- Management, Workflow, Management by exception