Can I Trust My Simulation Model? Measuring the Quality of Business Process Simulation Models
Not on the map. Why?
Abstract (arXiv)
Business Process Simulation (BPS) is an approach to analyze the performance of business processes under different scenarios. For example, BPS allows us to estimate what would be the cycle time of a process if one or more resources became unavailable. The starting point of BPS is a process model annotated with simulation parameters (a BPS model). BPS models may be manually designed, based on information collected from stakeholders and empirical observations, or automatically discovered from execution data. Regardless of its origin, a key question when using a BPS model is how to assess its quality. In this paper, we propose a collection of measures to evaluate the quality of a BPS model w.r.t. its ability to replicate the observed behavior of the process. We advocate an approach whereby different measures tackle different process perspectives. We evaluate the ability of the proposed measures to discern the impact of modifications to a BPS model, and their ability to uncover the relative strengths and weaknesses of two approaches for automated discovery of BPS models. The evaluation shows that the measures not only capture how close a BPS model is to the observed behavior, but they also help us to identify sources of discrepancies.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 2 of its 25 references that are in the map. First posted on arXiv 30 Mar 2023.
Builds on
2 of 25 references.
References · 2
Built on by
Citing papers per year: 2024: 5; 2025: 1.
6 papers.
- 2024AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulationcited by 8
- 2024Discovery and Simulation of Data-Aware Business Processescited by 2
- 2024Control-flow Reconstruction Attacks on Business Process Modelscited by 1
- 2024Business Process Simulation: Probabilistic Modeling of Intermittent Resource Availability and Multitasking Behaviorcited by 0
- 2024Generating the Traces You Need: A Conditional Generative Model for Process Mining Datacited by 0
- 2025A Divide-and-Conquer Approach for Modeling Arrival Times in Business Process Simulationcited by 0
- 2025A Divide-and-Conquer Approach for Modeling Arrival Times in Business Process Simulation28 May 2025
- 2024Generating the Traces You Need: A Conditional Generative Model for Process Mining Data4 Nov 2024
- 2024Business Process Simulation: Probabilistic Modeling of Intermittent Resource Availability and Multitasking Behavior22 Oct 2024
- 2024Control-flow Reconstruction Attacks on Business Process Models17 Sep 2024
- 2024Discovery and Simulation of Data-Aware Business Processes24 Aug 2024
- 2024AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation16 Aug 2024