Decision-enabled dynamic process management for networked enterprises |
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Authors: | Amit V Deokar Omar F El-Gayar |
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Affiliation: | (1) Dakota State University, Madison, SD, USA |
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Abstract: | Enterprises in today’s networked economy face numerous information management challenges, both from a process management perspective
as well as a decision support perspective. While there have been significant relevant advances in the areas of business process
management as well as decision sciences, several open research issues exist. In this paper, we highlight the following key
challenges. First, current process modeling and management techniques lack in providing a seamless integration of decision
models and tools in existing business processes, which is critical to achieve organizational objectives. Second, given the
dynamic nature of business processes in networked enterprises, process management approaches that enable organizations to
react to business process changes in an agile manner are required. Third, current state-of-the-art decision model management
techniques are not particularly amenable to distributed settings in networked enterprises, which limits the sharing and reuse
of models in different contexts, including their utility within managing business processes. In this paper, we present a framework
for decision-enabled dynamic process management that addresses these challenges. The framework builds on computational formalisms,
including the structured modeling paradigm for representing decision models, and hierarchical task networks from the artificial
intelligence (AI) planning area for process modeling. Within the framework, interleaved process planning (modeling), execution
and monitoring for dynamic process management throughout the process lifecycle is proposed. A service-oriented architecture
combined with advances from the semantic Web field for model management support within business processes is proposed. |
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