Abstract
The present article aims to present a rules based decision making model for a crucial business impact analysis task, namely the non-arbitrary criticality ranking of an individual business function. The model aims to serve as a classifier for the specific task. The components of the developed classifier are the inducted decision trees based on a data set and their supporting business rules. Moreover a business process representation with the Business Object Relation Modeling approach is included. The data set for creating the classifier has been based on computations of specific recovery complexity parameters. The parameters are included in the proposed by the author business continuity points method for estimating the recovery complexity of a business function, which, in its turn, stems from the use case points approach for software complexity estimation. The current work includes primary results of computations based on the default recovery case.
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Notes
- 1.
Based on the Use Case Points no units are used for the UBFRP, TRF, URF, ERF and ABFRP.
- 2.
Apart from the default classification path, alternative recovery cases are developed by the author. The derivation of the results regarding the statistical tests for the standardization of these paths are still in progress.
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Podaras, A. (2017). A Rules Based Decision Making Model for Business Impact Analysis: The Business Function Criticality Classifier. In: Pergl, R., Lock, R., Babkin, E., Molhanec, M. (eds) Enterprise and Organizational Modeling and Simulation. EOMAS 2017. Lecture Notes in Business Information Processing, vol 298. Springer, Cham. https://doi.org/10.1007/978-3-319-68185-6_8
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