Effects of Quantitative Measures on Understanding Inconsistencies in Business Rules

Nagel, Sabine; Corea, Carl; Delfmann, Patrick

doi:10.24251/hicss.2019.019

Cited by 5 publications

(4 citation statements)

References 18 publications

(43 reference statements)

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“…As observed, business rules are utilized to govern the business process (Nagel et al, 2019). These business rules are widely used to control and influence the behaviour of a business in an information system context (De Jesus & De Melo, 2014;Ezekiel et al, 2018;Nagel et al, 2019). Generally, institutional policies and procedures function as business rules.…”

Section: Issues With Existing Quality Assurance Systems and Prevailin...mentioning

confidence: 99%

Business Rules Driven Automated Quality Assurance Governance System for Higher Education

Pushpakumara,

Jayaweera,

Wanniarachchige

2023

S. Asian J. Bus. Insights

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Although higher education institutes have paid serious attention to quality assurance, implementation issues have been reported frequently. Since the existing information systems do not adequately support automatic verification, manual verification of quality assurance compliances has become a challenge. Therefore, this study first analysed the prevailing higher education quality assurance context to identify the prevailing issues. Secondly, Quality Assurance Governance System integrated with a quality assurance rule manipulation mechanism was designed based on the business rules concept to address the identified issues. Thirdly, the key modules of the proposed Quality Assurance Governance System were developed as a proof-of-concept. Finally, the proposed quality assurance rules manipulation mechanism and modules of the Quality Assurance Governance System were evaluated. The study found that one of the main issues in the existing systems is the lack of integration among various modules and a rule manipulation mechanism. Therefore, the study concludes that quality assurance requirements could be better captured as rules using the proposed rule templates, while rule manipulations and compliance could be verified in real-time through the proposed Quality Assurance Governance System. Nevertheless, the results of the evaluation suggest that rigid rule implementations may make the system inflexible and create stakeholder resistance. Thus, this can be mitigated by implementing the proposed rule enforcement levels.

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Section: Issues With Existing Quality Assurance Systems and Prevailin...mentioning

confidence: 99%

Business Rules Driven Automated Quality Assurance Governance System for Higher Education

Pushpakumara,

Jayaweera,

Wanniarachchige

2023

S. Asian J. Bus. Insights

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“…Thus, culpability measures can pinpoint the actual causes of inconsistencies in WFMS cases as a driver for resolving modeling errors [6]. Nagel et al (2019) could show that such inconsistency metrics are associated with a better understanding of inconsistencies. In light of the unique big data challenges in WFMS, not only these (quantitative) insights themselves but also the speed of their use become important to foster the innovative and sustainable development of WFMS [19].…”

Section: Figure 1 Exemplary Business Process and Business Rulesmentioning

confidence: 99%

“…During the pretest, we found that one major problem was the lack of trust in the inconsistency metrics, as many participants preferred to double-check the implication of the quantitative insights manually. As a result of this, we refined the introductory slides in order to build more trust in the values, as our focus was an investigation of different visualization approaches, and the general advantage of the values themselves has already been evaluated in [15].…”

Section: Participantsmentioning

confidence: 99%

Effects of Visualization Techniques on Understanding Inconsistencies in Automated Decision-Making

Corea¹,

Nagel²,

Delfmann³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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The automation of business processes and decision-making has received major interest from practice and academia. As automation allows us to execute more processes (cases), monitoring automated decision-making is currently evolving into a big data analytics problem for companies. Thus, not only monitoring insights themselves, but also an effective use of such insights become important. In this context, the speed and ability to interpret data is closely related to the visualization of metrics and data. While various approaches for quantitative insights on automated decision-making have been proposed, there is currently no evidence as to how the specific visualization of such metrics helps companies to create more value from their data. In this report, we therefore present the results of an empirical experiment analyzing the cognitive effects of different visualization techniques for quantitative insights on understanding inconsistencies in automated decisionmaking data.

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“…DMN has mainly been adopted in business process management (BPM) literature, which moves towards accommodating decision management into the paradigms of Separation of Concerns (SoC) and Service-Oriented Architecture (SOA), by externalising decisions and encapsulating them into separate decision models [2,[9][10][11][12][13]. Hence, the decisions are implemented as externalised services.…”

Section: Introductionmentioning

confidence: 99%

Decision model change patterns for dynamic system evolution

et al. 2020

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In the modern digital era, information systems must operate in increasingly interconnected and dynamic environments, which force them to be changeable yet consistent. Such modern information systems are usually decision-and knowledge-intensive. A recently introduced standard, the Decision Model and Notation (DMN), has been adopted in both industry and academia as a suitable method for modelling decisions and decision rules. Noteworthy is that, despite the dynamic nature of modern knowledge-intensive systems, DMN was only studied and implemented in a static fashion, as decision schema change patterns have not received any attention so far. This paper identifies and analyses the change patterns that can occur in a DMN decision model. A change in the decision model can require the triggering of other changes in order to safeguard consistency. As such, this paper will also investigate for each change pattern which further changes should be performed to ensure model consistency. The patterns presented in this paper will not only facilitate the understanding of decision change management and within-model consistency, but can also be capitalised on for developing and implementing flexible decision management systems. To illustrate this, we present a modelling environment prototype that provides modelling support when applying the proposed change patterns.

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Effects of Quantitative Measures on Understanding Inconsistencies in Business Rules

Cited by 5 publications

References 18 publications

Business Rules Driven Automated Quality Assurance Governance System for Higher Education

Business Rules Driven Automated Quality Assurance Governance System for Higher Education

Effects of Visualization Techniques on Understanding Inconsistencies in Automated Decision-Making

Decision model change patterns for dynamic system evolution

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