An Effective Practical Approach for Business Process Modeling and Simulation in Service Industries

• Published date: 01 January 2016
• Author: Arsalan Safari
• DOI: http://doi.org/10.1002/kpm.1496
• Date: 01 January 2016

■Research Article

An Effective Practical Approach for

Business Process Modeling and

Simulation in Service Industries

Arsalan Safari*

Qatar University, Doha, Qatar

Simulation imitates the behavior of real systems by applying different methods and applications. Business process

modeling and simulation is a new quantitative approach to model, analyze, and improve the efficiency and effective-

ness of business processes in a structured manner.Because there is a lack of practical framework or process to provide

sequential steps of process simulation in a more comprehensive and structured way, this paper develops a new stan-

dard and practical process for effective process simulation in service industries, proposing differentmodeling and an-

alytical approaches and discussing the methods that can be utilized in each step. This model has been implemented in

several business areas in a large financial institution with exceptional results of cost saving and process improvement.

Copyright © 2016 John Wiley & Sons, Ltd.

INTRODUCTION

Business process modeling and simulation is a stan-

dard quantitative approach for modeling, analyz-

ing, and improving business processes in all types

of industries. There is a lack of practical process or

guideline in the current articles or textbooks to pro-

vide the sequential steps of process simulation in a

more structured way and to cover all components

of a successful end-to-end process simulation pro-

ject in service industries. The main purposes of this

paper are to develop effective guidelines and meth-

odology for process modeling and simulation in ser-

vice industries and to discuss the effective methods

and tools that can be utilized for each step. The pa-

per provides a practical end-to-end process, and it

elaborates a real project in the banking industry as

a case study.

Simulation can be used to model a process as a

system for the purpose of understanding the pro-

cess behavior or evaluating different strategies or

operation models for learning purposes or decision

making (Aguilar-Saven, 2004). As many authors

confirm (e.g., Hlupic and Robinson, 1998; Padilla

et al., 2011), the growing popularity of simulation

has resulted in its widespread usage for systems

modeling and analysis in all science, engineering,

and business areas (e.g., manufacturing, service in-

dustries, finance, logistics and transportation, tele-

communication, health care, and pharmacy). One

of the key areas for applying simulation is business

process management (BPM) in which the simulation

method is applied to analyze, improve, and rede-

sign the processes and increase productivity

(Laguna and Marklund, 2013; Van der Aalst, 2015).

As many authors argue, the key BPM or any pro-

cess improvement project failure reasons are the dif-

ficulty in predicting the results of a radical change,

inability to evaluate the effects of designed solutions

before implementation, lack of creativity in the fu-

ture state process redesign, inability to accurately

predict the costs of implementing the new process,

difficulty in identifying the dynamic nature of the

processes, lack of senior management commitment

and executive level support, and employee involve-

ment (Paolucci et al., 1997; Hlupic and Robinson,

1998; Miers, 2006; Wong et al., 2014). If an organiza-

tion does not have enough capabilities to solve these

issues ahead of time, the problems arise once the

new processes have been implemented, when it is

usually hard and costly to fix an incorrect decision

(Greasley, 2006). Therefore, it is important to recog-

nize and prevent any mistake, or failure may

emerge by executing the redesigned processes.

Using process simulation, we are able to incorporate

stochastic conditions in the model. This method

*Correspondence to: Arsalan Safari, College of Business &

Economics, Qatar University, Doha, Qatar.

E-mail: asafari@qu.edu.qa

Knowledge and Process Management

Volume 23 Number 1 pp 31–45 (2016)

Published online 2 February 2016 in Wiley Online Library

(www.wileyonlinelibrary.com) DOI: 10.1002/kpm.1496

Copyright © 2016 John Wiley & Sons, Ltd.