What's Coming Next? Short-Term Simulation of Business Processes from Current State

Fuente: arXiv
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Main Authors: Avramenko, Maksym, Chapela-Campa, David, Dumas, Marlon, Milani, Fredrik
Format: Preprint
Published: 2025
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author Avramenko, Maksym
Chapela-Campa, David
Dumas, Marlon
Milani, Fredrik
author_facet Avramenko, Maksym
Chapela-Campa, David
Dumas, Marlon
Milani, Fredrik
contents Business process simulation is an approach to evaluate business process changes prior to implementation. Existing methods in this field primarily support tactical decision-making, where simulations start from an empty state and aim to estimate the long-term effects of process changes. A complementary use-case is operational decision-making, where the goal is to forecast short-term performance based on ongoing cases and to analyze the impact of temporary disruptions, such as demand spikes and shortfalls in available resources. An approach to tackle this use-case is to run a long-term simulation up to a point where the workload is similar to the current one (warm-up), and measure performance thereon. However, this approach does not consider the current state of ongoing cases and resources in the process. This paper studies an alternative approach that initializes the simulation from a representation of the current state derived from an event log of ongoing cases. The paper addresses two challenges in operationalizing this approach: (1) Given a simulation model, what information is needed so that a simulation run can start from the current state of cases and resources? (2) How can the current state of a process be derived from an event log? The resulting short-term simulation approach is embodied in a simulation engine that takes as input a simulation model and a log of ongoing cases, and simulates cases for a given time horizon. An experimental evaluation shows that this approach yields more accurate short-term performance forecasts than long-term simulations with warm-up period, particularly in the presence of concept drift or bursty performance patterns.
format Preprint
id arxiv_https___arxiv_org_abs_2509_07747
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle What's Coming Next? Short-Term Simulation of Business Processes from Current State
Avramenko, Maksym
Chapela-Campa, David
Dumas, Marlon
Milani, Fredrik
Software Engineering
Business process simulation is an approach to evaluate business process changes prior to implementation. Existing methods in this field primarily support tactical decision-making, where simulations start from an empty state and aim to estimate the long-term effects of process changes. A complementary use-case is operational decision-making, where the goal is to forecast short-term performance based on ongoing cases and to analyze the impact of temporary disruptions, such as demand spikes and shortfalls in available resources. An approach to tackle this use-case is to run a long-term simulation up to a point where the workload is similar to the current one (warm-up), and measure performance thereon. However, this approach does not consider the current state of ongoing cases and resources in the process. This paper studies an alternative approach that initializes the simulation from a representation of the current state derived from an event log of ongoing cases. The paper addresses two challenges in operationalizing this approach: (1) Given a simulation model, what information is needed so that a simulation run can start from the current state of cases and resources? (2) How can the current state of a process be derived from an event log? The resulting short-term simulation approach is embodied in a simulation engine that takes as input a simulation model and a log of ongoing cases, and simulates cases for a given time horizon. An experimental evaluation shows that this approach yields more accurate short-term performance forecasts than long-term simulations with warm-up period, particularly in the presence of concept drift or bursty performance patterns.
title What's Coming Next? Short-Term Simulation of Business Processes from Current State
topic Software Engineering
url https://arxiv.org/abs/2509.07747