Model-based Analysis of Data Inaccuracy Awareness in Business Processes

Problem definition: Data errors in business processes can be a source for exceptions and hamper business outcomes. Relevance: The paper proposes a method for analyzing data inaccuracy issues already at process design time, in order to support process designers by identifying process parts where data...

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Veröffentlicht in:Business & Information Systems Engineering 2022-04, Vol.64 (2), p.183-200
Hauptverfasser: Evron, Yotam, Soffer, Pnina, Zamansky, Anna
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container_title Business & Information Systems Engineering
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creator Evron, Yotam
Soffer, Pnina
Zamansky, Anna
description Problem definition: Data errors in business processes can be a source for exceptions and hamper business outcomes. Relevance: The paper proposes a method for analyzing data inaccuracy issues already at process design time, in order to support process designers by identifying process parts where data errors might remain unrecognized, so decisions could be taken based on inaccurate data. Methodology: The paper follows design science, developing a method as an artifact. The conceptual basis is the notion of data inaccuracy awareness – the ability to tell whether potential discrepancies between real and IS values may exist. Results: The method was implemented on top of a Petri net modeling tool and validated in a case study performed in a large manufacturing company of safety–critical systems. Managerial implications: Anticipating consequences of data inaccuracy already during process design can help avoiding them at runtime.
doi_str_mv 10.1007/s12599-021-00709-9
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subjects Business and Management
Data analysis
Design
Errors
IT in Business
Petri nets
Research Paper
Safety management
title Model-based Analysis of Data Inaccuracy Awareness in Business Processes
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