Abstract
Business process activities and their outcomes rely on data that is commonly stored in databases. If the stored data is not accurate, namely, it does not reflect the relevant real world values, the process execution might be disrupted and the process might not be able to reach its goal. Detection of such cases and analysis of their causes may help redesign processes to reduce the potential risks. In this research, we aim to develop a semi-automated method that will enable detection, assessment, and mitigation of risks related to data inaccuracy in business processes. The method will be built on and evaluated with real cases from the industry.
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Acknowledgment
This research is partially supported by the Israel Science Foundation under grant 856/13.
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Tsoury, A., Pnina, S., Reinhartz-Berger, I. (2015). Detecting, Assessing, and Mitigating Data Inaccuracy-Related Risks in Business Processes. In: Fournier, F., Mendling, J. (eds) Business Process Management Workshops. BPM 2014. Lecture Notes in Business Information Processing, vol 202. Springer, Cham. https://doi.org/10.1007/978-3-319-15895-2_47
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DOI: https://doi.org/10.1007/978-3-319-15895-2_47
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