[Paper Review] An overview of process model quality literature - The Comprehensive Process Model Quality Framework

Philippe De Meyer, Jan Claes|arXiv (Cornell University)|Aug 23, 2018

Business Process Modeling and Analysis9 references7 citations

TL;DR

This paper proposes the Comprehensive Process Model Quality Framework (CPMQF), a systematic, tertiary-level synthesis of existing research on process model quality. By analyzing 39 quality dimensions, 21 metrics, 28 drivers, and 64 realization initiatives, the framework offers a unified, structured overview that integrates diverse findings into a cohesive instrument for researchers and practitioners aiming to improve process model quality across organizational benefits.

ABSTRACT

The rising interest in the construction and the quality of (business) process models resulted in an abundancy of emerged research studies and different findings about process model quality. The lack of overview and the lack of consensus hinder the development of the research field. The research objective is to collect, analyse, structure, and integrate the existing knowledge in a comprehensive framework that strives to find a balance between completeness and relevance without hindering the overview. The Systematic Literature Review methodology was applied to collect the relevant studies. Because several studies exist that each partially addresses this research objective, the review was performed at a tertiary level. Based on a critical analysis of the collected papers, a comprehensive, but structured overview of the state of the art in the field was composed. The existing academic knowledge about process model quality was carefully integrated and structured into the Comprehensive Process Model Quality Framework (CPMQF). The framework summarizes 39 quality dimensions, 21 quality metrics, 28 quality (sub)drivers, 44 (sub)driver metrics, 64 realization initiatives and 15 concrete process model purposes related to 4 types of organizational benefits, as well as the relations between all of these. This overview is thus considered to form a valuable instrument for both researchers and practitioners that are concerned about process model quality. The framework is the first to address the concept of process model quality in such a comprehensive way.

Motivation & Objective

• To address the lack of consensus and overview in the growing literature on process model quality.
• To synthesize fragmented research findings into a coherent, comprehensive framework.
• To balance completeness with relevance in representing the state of the art in process model quality.
• To provide a structured instrument for both researchers and practitioners to guide quality improvement in process models.
• To identify and map key components such as quality dimensions, metrics, drivers, and organizational benefits.

Proposed method

• Conducting a tertiary-level Systematic Literature Review (SLR) to aggregate and analyze existing studies on process model quality.
• Performing a critical analysis of 39 quality dimensions, 21 quality metrics, 28 quality (sub)drivers, and 44 (sub)driver metrics.
• Mapping 64 realization initiatives and 15 concrete process model purposes to four types of organizational benefits.
• Structuring the relationships between all components into a single, integrated framework.
• Using a synthesis approach to ensure completeness while maintaining relevance and usability.
• Validating the framework's comprehensiveness through systematic integration of findings from diverse academic sources.

Experimental results

Research questions

• RQ1 What are the key dimensions that define process model quality in the current literature?
• RQ2 How are quality metrics and (sub)drivers related to specific process model purposes and organizational benefits?
• RQ3 What is the current state of consensus and fragmentation in process model quality research?
• RQ4 How can disparate findings on process model quality be systematically integrated into a unified framework?
• RQ5 What are the most effective realization initiatives for improving process model quality in practice?

Key findings

• The framework identifies 39 distinct quality dimensions that collectively define process model quality.
• A total of 21 quality metrics are mapped to these dimensions, enabling quantitative assessment.
• 28 quality (sub)drivers and 44 (sub)driver metrics are identified as key influences on model quality.
• 64 realization initiatives are proposed to improve quality, linked to specific drivers and metrics.
• 15 concrete process model purposes are associated with four types of organizational benefits, enhancing practical relevance.
• The framework is the first to comprehensively integrate all these components into a single, structured, and actionable instrument.