Lost in Models? Structuring Managerial Decision Support in Process Mining with Multi-criteria Decision Making

TL;DR

This paper proposes a multi-criteria decision-making approach using AHP to evaluate and prioritize process models in process mining, addressing model overload and supporting managerial decision-making.

Contribution

It introduces an MCDM framework incorporating quantitative and qualitative criteria to improve process model selection in process mining.

Findings

MCDM enhances decision-making by balancing operational metrics and managerial needs.

AHP facilitates effective trade-off analysis among process models.

Initial results show improved alignment with organizational objectives.

Abstract

Process mining is increasingly adopted in modern organizations, producing numerous process models that, while valuable, can lead to model overload and decision-making complexity. This paper explores a multi-criteria decision-making (MCDM) approach to evaluate and prioritize process models by incorporating both quantitative metrics (e.g., fitness, precision) and qualitative factors (e.g., cultural fit). An illustrative logistics example demonstrates how MCDM, specifically the Analytic Hierarchy Process (AHP), facilitates trade-off analysis and promotes alignment with managerial objectives. Initial insights suggest that the MCDM approach enhances context-sensitive decision-making, as selected models address both operational metrics and broader managerial needs. While this study is an early-stage exploration, it provides an initial foundation for deeper exploration of MCDM-driven strategies to enhance the role of process mining in complex organizational settings.