What business process modelers can learn from programmers

Gruhn, Volker; Laue, Ralf

doi:10.1016/j.scico.2006.08.003

Cited by 48 publications

(36 citation statements)

References 14 publications

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“…Four of the recent verification studies [11][12][13]15] use Event-driven Process Chain (EPC) business process models as input. Therefore, we briefly introduce EPCs and some potential correctness issues of their control flow.…”

Section: Formal Errors Of Process Modelsmentioning

confidence: 99%

“…The decomposition approach identifies all those deadlocks and lack of synchronization that are defined in the heuristics. Reduction Another heuristic for checking the correctness of process models is used in [15]. The authors identify reduction rules for structured EPC models and heuristics to correct simple connector mismatch errors.…”

Section: Verification Approachesmentioning

confidence: 99%

“…On the other hand, there are clearly quality issues with real-world process models. Recent studies report a significant rate of models with control flow errors in industry process model collections [11][12][13][14][15]. The mentioned lack of V&V features in tools as well as the lack of modeling competence in large-scale modeling projects [8] contribute to such high error rates.…”

Section: Introductionmentioning

confidence: 99%

“…Against this background, this paper aims to compare five recent studies on process model verification for real-world model collections, namely [11][12][13][14][15]. Such a comparison is beneficiary for the process verification community.…”

Section: Introductionmentioning

confidence: 99%

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Empirical Studies in Process Model Verification

Mendling

2009

Transactions on Petri Nets and Other Models of Concurrency II

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Abstract. Despite the large body of knowledge on formal analysis techniques for process models, in particular Petri nets, there has been a notable gap of empirical research into verification. In this paper we compare the few studies that report results from applying verification techniques to real-world process model collections. For this comparison we are particularly interested in the different approaches, their computational performance, and the number of errors found. Our comparison reveals that most of the samples have error rates of 10% to 20%. Some of the studies have established a connection between error probability and process model metrics, as well as between model understanding and both metrics and modeling competence of the model reader. Based on these results, we discuss implications and directions for future research.

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Section: Formal Errors Of Process Modelsmentioning

confidence: 99%

Section: Verification Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Empirical Studies in Process Model Verification

Mendling

2009

Transactions on Petri Nets and Other Models of Concurrency II

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“…Because of this, guidelines for good process models are unorganized and dispersed in different papers (e.g. [5,6,[13][14][15][16][17][18]), and there is no view on how complete this set of guidelines is.…”

mentioning

confidence: 99%

A systematic literature review of studies on business process modeling quality

de¹,

Snoeck²,

Reijers³

et al. 2015

Information and Software Technology

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Document VersionPublisher's PDF, also known as Version of Record (includes final page, issue and volume numbers) Please check the document version of this publication:• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication Citation for published version (APA):Moreno-Montes de Oca, I., Snoeck, M., Reijers, H. A., & Rodríguez-Morffi, A. (2015). A systematic literature review of studies on business process modeling quality. Information and Software Technology, 58, 187-205. DOI: 10.1016/j.infsof.2014.07.011 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. b s t r a c tContext: Business process modeling is an essential part of understanding and redesigning the activities that a typical enterprise uses to achieve its business goals. The quality of a business process model has a significant impact on the development of any enterprise and IT support for that process.Objective: Since the insights on what constitutes modeling quality are constantly evolving, it is unclear whether research on business process modeling quality already covers all major aspects of modeling quality. Therefore, the objective of this research is to determine the state of the art on business process modeling quality: What aspects of process modeling quality have been addressed until now and which gaps remain to be covered? Method: We performed a systematic literature review of peer reviewed articles as published between 2000 and August 2013 on business process modeling quality. To analyze the contributions of the papers we use the Formal Concept Analysis technique. Results: We found 72 studies addressing quality aspects of business process models. These studies were classified into different dimensions: addressed model quality type, research goal, research method, and type ...

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Effort based performance measurement in business process management

Glykas

2011

Knowl Process Manag

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Aegean Technopolis, The Technology Park of the Aegean RegionThis paper presents a holistic methodology and associated toolset for business process modelling and analysis. The importance of integrating performance measurement (PM) indicators and tools in business process management has been identified in the literature as well as contemporary approaches that attempt to give a solution to this problem. However, most of these approaches propose solutions based on theories and techniques used in other disciplines or research fields which approach the issue of performance measurement in BPR from their individualistic perspective. In the majority of cases the proposed theories and techniques prove to be inadequate to measure performance holistically and integrate, organizational, human resource management, process management and workflow management concepts. The resulting methodology and toolset is based on business analysis ratios that define and measure key performance indicators in qualitative and quantitative terms and identify the relationships between them. These ratios allow enterprises to achieve a performance evaluation tool for continuous improvement in their attempt to respond and adapt quickly to turbulent markets. The performance measurement toolset (called ADJUST) is used for (1) planning different reorganization scenarios for the achievement of desired performance, (2) for assessing real time performance and (3) reporting deviations from desired planned performance. In order to monitor and assess real time performance the ADJUST software tool provides interfaces to three kinds of management tool categories, namely:Process management tools (PMT): business models, cycle time, primitive cost, etc. Human resource management (HRM) tools: job descriptions, performance measures, etc. Workflow management (WFM) tools: transactions, business rules, workflow models, etc.The ADJUST business analysis engine is based on employee effort analysis and provides meta-analysis of data analysed in PMT and HRM tools. Data like activity sequencing, cycle times, primitive costing, etc. from PMT tools are analysed in ADJUST in order to assess the percentage of high-business and low value added activities, mission-non mission activities, concentration analysis, etc. Knowledge management elements are integrated to job descriptions and associated with performance measures and workflow elements. Similarly, job descriptions and performance measurement data that are provided by HRM tools are analysed further in terms of cost to manage, principal-agent analysis etc. In the case of WFM tools the ADJUST system provides not only meta-analysis of workflow processes, transactions and document flows but also dynamic monitoring of their performance in real time.

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What business process modelers can learn from programmers

Cited by 48 publications

References 14 publications

Empirical Studies in Process Model Verification

Empirical Studies in Process Model Verification

A systematic literature review of studies on business process modeling quality

Effort based performance measurement in business process management

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