Decision Noise Instrument (DNI): Estimating Decision Noise in Business Processes

Marcus Dees; P. H. G. Berkhout; Claudio Di Ciccio; Hajo A. Reijers

doi:10.1007/978-3-032-15140-7_9

Decision Noise Instrument (DNI): Estimating Decision Noise in Business Processes

Marcus Dees^*
, P. H. G. Berkhout
, Claudio Di Ciccio
, Hajo A. Reijers

^*Corresponding author for this work

Sub Process Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

Abstract

Business processes in which decisions are made by human resources suffer from noise. Noise is unwanted variability, which leads to inconsistent and unrepeatable decisions and impacts trust negatively. In this paper, we present the Decision Noise Instrument (DNI) to quantitatively estimate the noise that can be attributed to unknown factors affecting the actors who carry out the business process. For our estimation, we solely use readily available data from business information systems that support the execution of the process. In our method, we limit the influence of factors that cannot be attributed to actors. The DNI makes it possible to compare the noise levels between and within business processes. Based on that comparison, further investigation into the problem and noise reduction efforts can be prioritized. We evaluate the DNI on a claim handling process of UWV, a public service provider in the Netherlands. Our results show that we can estimate differences between the noise levels of several decisions within the selected process of UWV. By drilling down on a decision, the subgroups that have the most impact on the noise level are identified.

Original language	English
Title of host publication	Enterprise Design, Operations, and Computing
Subtitle of host publication	29th International Conference, EDOC 2025, Lisbon, Portugal, September 9-12, 2025, Revised Selected Papers
Editors	Alessandro Gianola, Renata Guizzardi, José Borbinha, Miguel Mira da Silva, José Barateiro
Publisher	Springer
Pages	156-172
ISBN (Electronic)	978-3-032-15140-7
ISBN (Print)	978-3-032-15139-1
DOIs	https://doi.org/10.1007/978-3-032-15140-7_9
Publication status	Published - 3 Feb 2026

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	16213
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-032-15140-7_9

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Dees, M., Berkhout, P. H. G., Ciccio, C. D., & Reijers, H. A. (2026). Decision Noise Instrument (DNI): Estimating Decision Noise in Business Processes. In A. Gianola, R. Guizzardi, J. Borbinha, M. M. da Silva, & J. Barateiro (Eds.), Enterprise Design, Operations, and Computing: 29th International Conference, EDOC 2025, Lisbon, Portugal, September 9-12, 2025, Revised Selected Papers (pp. 156-172). (Lecture Notes in Computer Science; Vol. 16213). Springer. https://doi.org/10.1007/978-3-032-15140-7_9

Dees, Marcus ; Berkhout, P. H. G. ; Ciccio, Claudio Di et al. / Decision Noise Instrument (DNI): Estimating Decision Noise in Business Processes. Enterprise Design, Operations, and Computing: 29th International Conference, EDOC 2025, Lisbon, Portugal, September 9-12, 2025, Revised Selected Papers. editor / Alessandro Gianola ; Renata Guizzardi ; José Borbinha ; Miguel Mira da Silva ; José Barateiro. Springer, 2026. pp. 156-172 (Lecture Notes in Computer Science).

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abstract = "Business processes in which decisions are made by human resources suffer from noise. Noise is unwanted variability, which leads to inconsistent and unrepeatable decisions and impacts trust negatively. In this paper, we present the Decision Noise Instrument (DNI) to quantitatively estimate the noise that can be attributed to unknown factors affecting the actors who carry out the business process. For our estimation, we solely use readily available data from business information systems that support the execution of the process. In our method, we limit the influence of factors that cannot be attributed to actors. The DNI makes it possible to compare the noise levels between and within business processes. Based on that comparison, further investigation into the problem and noise reduction efforts can be prioritized. We evaluate the DNI on a claim handling process of UWV, a public service provider in the Netherlands. Our results show that we can estimate differences between the noise levels of several decisions within the selected process of UWV. By drilling down on a decision, the subgroups that have the most impact on the noise level are identified.",

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Dees, M, Berkhout, PHG, Ciccio, CD & Reijers, HA 2026, Decision Noise Instrument (DNI): Estimating Decision Noise in Business Processes. in A Gianola, R Guizzardi, J Borbinha, MM da Silva & J Barateiro (eds), Enterprise Design, Operations, and Computing: 29th International Conference, EDOC 2025, Lisbon, Portugal, September 9-12, 2025, Revised Selected Papers. Lecture Notes in Computer Science, vol. 16213, Springer, pp. 156-172. https://doi.org/10.1007/978-3-032-15140-7_9

Decision Noise Instrument (DNI): Estimating Decision Noise in Business Processes. / Dees, Marcus; Berkhout, P. H. G.; Ciccio, Claudio Di et al.
Enterprise Design, Operations, and Computing: 29th International Conference, EDOC 2025, Lisbon, Portugal, September 9-12, 2025, Revised Selected Papers. ed. / Alessandro Gianola; Renata Guizzardi; José Borbinha; Miguel Mira da Silva; José Barateiro. Springer, 2026. p. 156-172 (Lecture Notes in Computer Science; Vol. 16213).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

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AB - Business processes in which decisions are made by human resources suffer from noise. Noise is unwanted variability, which leads to inconsistent and unrepeatable decisions and impacts trust negatively. In this paper, we present the Decision Noise Instrument (DNI) to quantitatively estimate the noise that can be attributed to unknown factors affecting the actors who carry out the business process. For our estimation, we solely use readily available data from business information systems that support the execution of the process. In our method, we limit the influence of factors that cannot be attributed to actors. The DNI makes it possible to compare the noise levels between and within business processes. Based on that comparison, further investigation into the problem and noise reduction efforts can be prioritized. We evaluate the DNI on a claim handling process of UWV, a public service provider in the Netherlands. Our results show that we can estimate differences between the noise levels of several decisions within the selected process of UWV. By drilling down on a decision, the subgroups that have the most impact on the noise level are identified.

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