=Paper=
{{Paper
|id=Vol-3216/paper_243
|storemode=property
|title=A Tool for Assisted Business Process Redesign
|pdfUrl=https://ceur-ws.org/Vol-3216/paper_243.pdf
|volume=Vol-3216
|authors=Tobias Fehrer,Dominik A. Fischer,Sander J.J. Leemans,Maximilian Röglinger,Moe T. Wynn
|dblpUrl=https://dblp.org/rec/conf/bpm/FehrerFLRW22
}}
==A Tool for Assisted Business Process Redesign==
https://ceur-ws.org/Vol-3216/paper_243.pdf
A Tool for Assisted Business Process Redesign
Tobias Fehrer1,2,* , Dominik A. Fischer1,2 , Sander J.J. Leemans3 ,
Maximilian Röglinger1,2 and Moe T. Wynn4
1
Research Center Finance & Information Management, University of Bayreuth, Bayreuth, Germany
2
Branch Business & Information Systems Engineering of the Fraunhofer FIT, Bayreuth, Germany
3
RWTH University, Aachen, Germany
4
Queensland University of Technology, Brisbane, Australia
Abstract
The continuous optimization of business processes remains a critical success factor for companies. The
assisted business process redesign (aBPR) concept guides users in improving business processes based on
redesign patterns. Depending on the process data at hand, it generates four types of recommendations
that differ in their level of automation. This paper presents a tool implementation of the aBPR concept as
a stand-alone desktop application that has been successfully used in several case studies. The aBPR tool
uses BPMN diagrams, redesign best practices, and simulation experiments to guide the user to improved
process designs in a modeling application.
Keywords
Business Process Redesign, User Guidance, Simulation
1. Introduction
Transforming business processes at an accelerating pace is essential for companies to meet
increasing competition and customer needs [1]. Business process redesign (BPR) is concerned
with improving business processes [2]. It is considered an essential phase in the business
process management (BPM) lifecycle since it entails significant economic value by introducing
innovation, reducing costs, as well as improving quality, productivity, and customer experience
[3, 4]. Despite its importance, BPR lacks clear guidance and often “happens in a black box”
([5, p. 217]). Often, organizations conduct workshops with consultants and stakeholders to
analyze process challenges as well as opportunities and manually generate options for process
improvements [5]. Even when supported by data-driven approaches such as process mining,
the quality and the effectiveness of BPR depend on the creativity and the expertise of the project
team to find valuable solutions, which is both time-consuming and costly. Automation of process
redesign could thus hold great potential for long-term organizational success, as it could be
more efficient with less dependence on human creativity. Several approaches have already dealt
Proceedings of the Best Dissertation Award, Doctoral Consortium, and Demonstration & Resources Track at BPM 2022
co-located with the 20th International Conference on Business Process Management, Sept. 11–16, 2022, Münster, Germany
*
Corresponding author.
$ tobias.fehrer@fim-rc.de (T. Fehrer); dominik.fischer@fim-rc.de (D. A. Fischer); s.leemans@bpm.rwth-aachen.de
(S. J.J. Leemans); maximilian.roeglinger@fim-rc.de (M. Röglinger); m.wynn@qut.edu.au (M. T. Wynn)
0000-0002-8798-5724 (T. Fehrer); 0000-0002-5218-6463 (D. A. Fischer); 0000-0002-5201-7125 (S. J.J. Leemans);
0000-0003-4743-4511 (M. Röglinger); 0000-0002-7205-8821 (M. T. Wynn)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
97
with how partial aspects of process improvement can be automated. However, to the best of
our knowledge, there is no holistic approach that provides end-to-end support and integrates
the user into the decision-making process where necessary.
The assisted business process redesign (aBPR) tool was developed as a stand-alone desktop
application that guides users in improving process models using an assisted approach and
redesign recommendations. Focusing on incremental process improvement, it facilitates the
popular method of process redesign patterns and a four-step procedure to generate redesign
options: step 1) select suitable redesign patterns, step 2) identify suitable process parts, step
3) create alternative models, and step 4) evaluate the performance of these alternative models.
Executing these four steps leads to redesign options that, after thorough evaluation, may be
suitable for improving the process under investigation. The presented aBPR tool integrates
this four-step procedure. The literature shows that individual steps and combinations of these
steps can be (partially) automated, leaving the finalization of the redesign options with the
human user [6]. This is by no means a weakness of related work in this area, but often because
the approaches work with assumptions for which data may be missing in the execution. From
the possible combinations of automatable and manual steps, four types can be defined with an
increasing automation level (AL). The aBPR tool supports this typology so that increasingly
specific recommendations for process improvement are proposed to the user, who can adopt
them whole or finalize them manually, depending on their type.
In the remainder of this manuscript, we present the aBPR tool with its innovation and
characteristics in Section 2, discuss its maturity by describing the measures and outcomes used
to evaluate the tool (in Section 3), and conclude in Section 4.
2. Innovation and characteristics
In the aBPR tool, a blank canvas can be used as a starting point to model a process or an
existing business process modeling and notation (BPMN) diagram can be imported. The process
model is the central starting point for process improvement and can therefore be enriched with
far-reaching information that provides a comprehensive picture of the as-is state. The aBPR
tool provides support for interactively editing the process model and integrates improvement
recommendations for the generation of redesign options. A four-step procedure is repeated
until satisfaction with the process is achieved and the improved process model is exported.
Because of its good usability, we used the Camunda Modeler1 , which is widely used in research
and practice, as a starting point for tool development. Figure 1 shows the tool’s GUI.
Modeling and simulation In addition to traditional control flow descriptions and considering
events, documents, organizations, and lanes, a custom extension of the BPMN metamodel
captures simulation configuration, performance data, and aBPR-specific annotations. This
allows information to be stored consistently in the model and imported and exported as a .
simubpmn file. When importing a basic BPMN diagram, event arrival rates, resources with their
costs and timetables, activity durations, routing probabilities, resource timetables, and further
properties are initialized with a default configuration to ensure valid models and a convenient
1
https://github.com/camunda/camunda-modeler
98
Figure 1: General tool overview with the major GUI components (1) the diagram editor and lint tab, (2)
the performance objective selection, and (3) the list of recommendations.
experience for the user. The available element shapes in the process modeler are restricted to a
set supported by the redesign handlers. Via static model analysis, the tool identifies modeling
errors, detects misconfigurations or missing properties, and provides visual feedback to fix
the model. The simulation package Scylla [7] is embedded in the aBPR tool and facilitates
the simulation of the as-is process model and redesign options. The results of the simulation
experiments can be compared side by side to estimate the effects.
Redesign recommendations After modeling the initial process model and validating its
real-world fidelity with initial simulation studies, a redesign performance objective, such as time,
cost, flexibility, or quality, is selected. Using the process model and the performance objective
as an input, the tool then generates redesign recommendations by invoking recommendation
providers that contain the logic to execute (parts of) the four-step procedure for applying
redesign patterns. A recommendation provider may return more than one recommendation
and several recommendation providers might provide recommendations for the same redesign
pattern. In the graphical user interface (GUI), each recommendation is characterized with
its corresponding process aspect, the pattern category, a distinct name, a description, and,
optionally, the expected impact and affected process elements. How a recommendation can
be applied varies per AL. The aBPR tool supports all patterns from Reijers and Mansar [8] in
varying automation levels (AL). The triage and activity automation patterns are implemented
on AL3, the parallelism, and extra resources patterns are implemented on AL4, whereas the
remaining are implemented as AL1 and AL2 recommendations. In case of full automation
(AL4), the aBPR tool generates process models in the background with feasible implemented
redesign options, such as parallelized task: The developed heuristic checks whether sequential
99
Figure 2: Implementation of two redesign patterns
activities can be parallelized or are interdependent (see Figure 2 b). The different models are
then simulated simultaneously to reveal effects on performance. The result of this simulation is
then integrated into the recommendation and shown to the user. In contrast, at the lowest level,
only a general recommendation is made that a redesign pattern can help achieve a performance
goal. In the intermediate levels (AL2&3), user input is requested in addition to the automated
checks to determine, for example, the applicability of the triage pattern (see Figure 2 a): After
selecting activities that are potentially suitable for triage, the user models the new process
manually or is guided by a wizard.
To diversify good recommendations in terms of their estimated impact and place them on
top of the list of recommendations a 𝐴* heuristic is implemented. Users can accept or reject
recommendations and evaluate their impact via simulation experiments and own judgment.
3. Tool maturity & evaluation
The stand-alone aBPR tool can be downloaded2 for Windows PCs and tried, e.g., with a sample
process provided in a tutorial3 . The aBPR tool is the result of a design science research (DSR)
project [6] and has been evaluated in terms of operationality, feasibility, and applicability in
artificial and naturalistic settings. During the development phase, the tool was interactively
demonstrated in eight expert interviews to evaluate the aBPR’s feasibility and operationality,
based on an artificial service request process that is also demonstrated in a screencast of the
tool’s functionality4 . In a second evaluation, we conducted two case studies with professionals
engaged in real-world BPR projects in an artificial setting. In the first case, we involved three
consultants from a process consulting firm. For the second case, we involved a consultant and a
process owner. In a real-world case study with Germany-based industrial automation solutions
provider KUKA, the aBPR tool was tested in a workshop where the prototype was utilized to
develop process improvement ideas that reduce cycle time by 30 %. Further details on the case
studies and the evaluation of the aBPR tool can be found in Fehrer et al. [6].
2
download: https://dtdi.github.io/assisted-bpr-modeler/
3
tutorial: https://github.com/dtdi/assisted-bpr-modeler/blob/gh-pages/aBPR%20Tutorial.pdf
4
screencast: https://www.youtube.com/watch?v=HwXtz2mDHLw
100
4. Conclusion
In this paper, we introduced the aBPR tool that supports practitioners in improving business
processes by guiding them to creating process redesign options and simulating the impact
of process changes. The tool is available for download and can be extended with additional
redesign heuristics. In future research, we plan to enhance the tool by (a) implementing further
redesign heuristics in advanced levels of automation, (b) improving the guidance through the
act of process redesign, and (c) integrating additional sources for developing an understanding
of the as-is business process, such as event logs.
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