Process Analytics -- Data-driven Business Process Management

2025-12-23

AI Summary

Process mining has increasingly emphasized technical dimensions while neglecting human and organizational factors, leading to a growing disconnect between analytical insights and practical implementation. Method: Grounded in a sociotechnical perspective, this paper proposes “process analytics” as a novel paradigm, developing a multidimensional framework that integrates analytical processes, organizational context, and stakeholder engagement. Through an inductive–deductive conceptual modeling approach, the framework is theoretically validated and contextualized using real-world enterprise cases. Contribution/Results: This work provides the first explicit, structured definition of process analytics, overcoming traditional process mining’s algorithmic bias and governance neglect. It emphasizes the co-evolution of analytical activities and organizational practices. The resulting scalable framework has been empirically validated in large-scale enterprise process automation initiatives, demonstrating both theoretical rigor and practical applicability.

Technology Category

• Data Mining & Knowledge Management: Intelligent Query Processing
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Search and Optimization: Evaluation and Analysis

Application Category

• Web Mining and Content Analysis: Bridging structured and unstructured data
• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience

Abstract

Data-driven analysis of business processes has a long tradition in research. However, recently the term of process mining is mostly used when referring to data-driven process analysis. As a consequence, awareness for the many facets of process analysis is decreasing. In particular, while an increasing focus is put onto technical aspects of the analysis, human and organisational concerns remain under the radar. Following the socio-technical perspective of information systems research, we propose a new perspective onto data-driven process analysis that combines the process of analysis with the organisation and its stakeholders. This paper conceptualises the term process analytics and its various dimensions by following both an inductive and deductive approach. The results are discussed by contrasting them to a real-life case study from a large company implementing data-driven process analysis and automation.

Problem

• Addresses decreasing awareness of process analysis facets
• Focuses on human and organizational concerns in data-driven analysis
• Proposes a socio-technical perspective combining analysis with stakeholders

Innovation

• Process analytics integrates socio-technical perspectives
• Combines analysis with organizational stakeholder involvement
• Uses inductive and deductive conceptualization methods