Business Value of Process Mining

Abstract

Process mining (PM) has evolved from a set of algorithms for discovering, checking, and enhancing processes from event data into a broader organizational capability for continuous improvement and value creation. Yet organizations and researchers repeatedly report a gap between insights and impact: while PM often uncovers bottlenecks, deviations, and compliance issues, it remains unclear when, how, and for whom these analytics translate into tangible business value. This thesis addresses the general research question: How can we improve the current understanding of process mining value? The work integrates cross-domain business-value concepts, systematically reviews the PM value literature, theorizes about negative contingencies that hinder value realization, and designs a holistic maturity model for PM. The thesis develops a cross-domain conceptualization of business value that can be systematically applied to process mining. Drawing on systematic literature reviews in information systems (IS), business intelligence (BI), and business process management (BPM), it synthesizes a multidimensional, multilevel view of business value across operational, financial, strategic, and stakeholder outcomes. Using the Context– Intervention–Mechanism–Outcome (CIMO) lens, the thesis distinguishes contextual conditions, interventions, value-creation mechanisms, and outcomes. It proposes an integrative business value framework suitable for analyzing digital initiatives such as This framework is then applied to the process mining literature. A systematic review of PM studies that explicitly discuss value shows that existing research concentrates on process-level operational gains and transparency, with limited attention to strategic or ecosystem-level outcomes and few explicit accounts of mechanisms linking PM to broader business value. The mapping reveals notable gaps around AI-enabled features, value inhibitors, cross-process stakeholder perspectives, and intermediate outcomes. To explain why PM initiatives often fall short of their promised benefits, the thesis theorizes and empirically identifies negative contingencies that undermine value realization. Based on qualitative analysis of multiple PM projects and narratives, it develops a typology of nine recurring contingencies across data, tooling, organizational, and ecosystem dimensions, showing how PM interventions can fail and how value-creation mechanisms are weakened or blocked. Actively managing these contingencies is argued to be essential for closing the PM value gap. The thesis also designs and evaluates a Holistic Process Mining Maturity Model (HP3M) using a design science research approach. HP3M specifies maturity levels and dimensions that characterize the evolution of PM from isolated experiments to an embedded, value-oriented capability. Multi-method evaluation and an industry case study illustrate how HP3M can be used to diagnose PM maturity, identify capability gaps, align PM ambition with organizational context, and relate maturity to value realization. Conceptually, the thesis sharpens the foundations of business value for process mining and embeds PM within a mechanism-oriented, context-sensitive framework. Methodologically, it demonstrates a CIMO-based synthesis across domains, a structured protocol for reviewing PM value studies, a qualitative and sentiment-aware approach to identifying negative contingencies, and a design science process for developing a maturity model. Practically, it offers a structured vocabulary for scoping PM value, a map of current value patterns and gaps, a contingency-based diagnostic, and a holistic maturity model to guide organizations from ad hoc PM projects toward a mature, value-driven PM capability.