EURO 2024 Copenhagen
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349. Advancing Business Process Evaluation: The Value of Integrating Process Mining and Propensity Score Analysis

Invited abstract in session MD-45: Emerging Trends in Decision Analysis, stream Decision Support Systems.

Monday, 14:30-16:00
Room: 30 (building: 324)

Authors (first author is the speaker)

1. Pavlos Delias
Business School, Democritus University of Thrace
2. GIANNOULA FLOROU
Accounting and Finance,
3. Nikolaos Mittas
Chemistry, International Hellenic University

Abstract

Ensuring the efficacy of business process interventions is essential for informed decision-making and sustained improvements. This study focuses on a pragmatic approach that integrates process mining and the strengths of propensity score analysis to enhance precision and reliability in evaluating business process interventions. Drawing from our prior work, we present a practical methodology tailored for organizations seeking an effective solution.
We aim to construct a framework that utilizes both event logs and observed characteristics to address confounding factors, thereby enhancing the validity of conclusions in observational studies. Our work is complemented by a prototype tool designed to assist practitioners in selecting appropriate weighting methods, evaluating group balance, and assessing covariate balance. Through an applied case study on a simulated claims management process dataset, we illustrate how these techniques synergize to measure and enhance business process effectiveness and efficiency.
This study not only underscores the integration of process mining, business process management, and causal inference but also scrutinizes the inherent limitations and challenges. By providing a comprehensive view, our goal is to offer organizations actionable insights, implementation guidance, and an understanding of how this synergy can advance business process evaluation.

Keywords

Status: accepted

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