Variance in business process can lead to various changes and modifications of business requirements, strategies and functionalities since it is a valuable source of organizational intellectual capital and represents a preferred and successful work practice. It is important to provide an effective method to analyze the similarity between these variants since it can bring benefits for organization productivity. Through this paper, we propose an efficient approach for undertaking the structural similarity analysis and subsequently providing a formula to compute the degree of similarity between the structural relationships of the variants in a systematic way. We hope that the systematic method introduced in this paper can be applied successfully to solve the ambiguity issue in defining and measuring the structural similarity between the process variant.
This paper addresses the problem of managing variance in process instances for business process modeling. In business work practice, variance is a valuable source of organizational intellectual capital that needs to be captured and capitalized as it represents a preferred and successful work practice. Therefore, it is important to provide an effective method to analyze the similarity between these variants since it can bring benefits for organization productivity and provide consistency. Through this paper, we propose a systematic approach to deal with the complexity of business process variants by analyzing the structure relationship and the execution construct in order to measure the similarity degree of the variants.
Evidence from business work practice indicates that variance from prescribed business process models is not only inevitable and frequent, but is in fact a valuable source of organizational intellectual capital that needs to be captured and capitalized, since variance is typically representative of preferred and successful work practice. In this paper, we present a framework for harnessing the value of business process variants. An essential aspect of this framework is the ability to search and retrieve variants. This functionality requires variants to be matched against a given criteria. The focus of this paper is on the structural criteria which is rather challenging as query process structures may have different levels of similarity with variant process structures. The paper provides methods for undertaking the similarity matching and subsequently providing ranked results in a systematic way, as well as a reference architecture within which the methods may be deployed.
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