=Paper=
{{Paper
|id=Vol-2703/paperDC4
|storemode=property
|title=Interactive Data-Driven Business Process Simulation (Extended Abstract)
|pdfUrl=https://ceur-ws.org/Vol-2703/paperDC4.pdf
|volume=Vol-2703
|authors=Gerhardus van Hulzen
|dblpUrl=https://dblp.org/rec/conf/icpm/Hulzen20
}}
==Interactive Data-Driven Business Process Simulation (Extended Abstract)==
https://ceur-ws.org/Vol-2703/paperDC4.pdf
Interactive Data-Driven Business Process
Simulation (Extended Abstract)
Gerhardus van Hulzen
Research group Business Informatics
Hasselt University
Hasselt, Belgium
0000-0001-8962-9515
I. I NTRODUCTION individual BPS model components to make it usable to
support CM decisions.
Today, healthcare systems worldwide are under constant
2) Enabling interactive data-driven process simulation:
pressure. On the one hand, increasing population numbers,
Domain knowledge should be closely integrated during
ageing populations, lifestyle factors, and new technologies are
the discovery of BPS models to ensure the reliability
increasing the yearly expenses on healthcare. On the other
and usability of the discovered simulation models.
hand, budgets are under pressure due to economic austerity [1].
In order to provide high-quality care to all patients, healthcare III. P LANNED R ESEARCH ACTIVITIES
managers are forced to improve their care processes. Efficient
The following subsections give an overview of the planned
Capacity Management (CM) is one of the key aspects to ensure
research activities for the two research objectives.
this. This involves, amongst others, determining the suitable
resource levels – i.e. staff size, equipment, and facilities [2]. A. Extended Support for Key BPS Modelling Tasks
Business Process Simulation (BPS) can be used to support
Based on a systematic literature review, we concluded
managers during CM decisions. BPS uses a (computer) model
that defining the control-flow, entity arrival rates, activity
to imitate the behaviour of a business process. This approach
execution times, gateway routing logic, entity types, queueing
allows evaluating the effects of changes before implementing
disciplines, resource schedules, resource requirements, and
them [3]. For instance, BPS can be used to determine suitable
resource roles are the most important modelling tasks to
equipment levels, e.g. by simulating the effect of an additional
support CM decisions via simulation. These tasks correspond
X-ray scanner on patient waiting times, throughput rates, and
to a subset of modelling tasks given by [7]. Most attention
staff workload.
of PM research has been dedicated to control-flow definition
In Process Mining (PM) the emerging field of data-driven
[7]. However, for creating a simulation model for supporting
process simulation provides promising first results to generate
CM decisions, we believe that all aforementioned tasks are
simulation models from information captured in event logs [4].
required – albeit some tasks are more important than others.
These “discovered” models can form the basis to compare
In PM, only limited amount of work has been devoted
the operational effects of various capacity levels. The main
to integrating the various tasks needed to build a simulation
advantage of data-driven process simulation over “traditional”
model. The authors in [8] were the first to generate an initial
simulation model development is the availability and objec-
simulation model from data. They included the process-flow,
tivity of event logs compared to information sources, such as
gateway routing logic, and resource pools. Later, the authors
interviews, process documentation, and observations [5]. How-
extended their work with activity durations and entity inter-
ever, some challenges remain in the field of automated BPS
arrival times [5]. Nevertheless, the authors emphasise that the
discovery. Most importantly, the lack of domain knowledge
derived initial model still has to be verified and – if required
makes it challenging to extract a reliable and usable simulation
– augmented by domain experts to ensure validity.
model. In addition, event logs often suffer from data quality
In [9], a PM approach is proposed to generate BPS models
issues, which strongly affects the reliability of the simulation
for short-term KPI prediction. A similar approach as in [5] is
results [6]. Therefore, it is imperative to take these problems
used. However, the resource perspective is left aside, assuming
seriously.
an infinite amount of resources is available [9].
II. R ESEARCH O BJECTIVES Control-flow, resources, activity durations, and gateway
routing logic are supported by the approach in [10]. In
Given the context outlined above, this PhD research pursues addition, they also support inter-arrival times and resource
the following two objectives: schedules. However, the latter have to be defined manually
1) Extended support for key BPS modelling tasks: While by the domain expert.
the field of automated BPS discovery renders promising None of the aforementioned studies tried to integrate all
results; there are still challenges ahead to discover elements into a single, simulation-ready model. This is where
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Simod [11] extends the work on data-driven process simu- expert should immediately obtain an estimation of the impact
lation. Simod is a tool which automatically discovers BPS of the changed parameter, instead of having to wait until the
models from event logs. In addition, Simod is also capable of simulation has finished running, which could – depending on
measuring the accuracy of the obtained simulation model and the complexity of the model – take quite a while.
allows to optimise the accuracy using hyper-parameters [11]. The third cycle of the framework involves the actual model
While the initial results of data-driven BPS algorithms are validation. The calibrated model is simulated extensively, and
promising, there are still challenges to automatically derive the domain expert validates the simulation results. If needed,
a simulation model for supporting CM decisions from event the parameters of the simulation model can be altered again
logs. Especially the resource perspective is crucial for CM to obtain more realistic results. The validated model can be
decisions. Incorrect resource requirements, pools, and sched- used for further analyses and to evaluate different scenarios.
ules make the results of the model unreliable, resulting in The goal of this part of the PhD research is to develop a
inaccurate capacity requirement estimations. The state-of-the- prototype which supports the interactive development of data-
art still has limitations when it comes to defining the resource driven simulation models.
perspective. Part of this PhD research will be dedicated to IV. C ONCLUDING R EMARKS
improving the support of the resource perspective in data-
This PhD will mainly focus on the resource aspect of data-
driven BPS.
driven BPS and how domain experts can be interactively
B. Enabling Interactive Data-Driven Process Simulation involved in the discovery of simulation models. This should
As mentioned earlier, data quality issues should be taken culminate in the development of a prototype tool which allows
seriously to ensure the reliability of the data-driven simulation interactive data-driven generation of BPS models based on
model. Detecting these issues often requires domain knowl- event logs and domain knowledge. The derived simulation
edge. Therefore, it would be beneficial to involve the domain model will form the basis for supporting CM decisions in
experts as early as possible to detect and handle data quality healthcare. Nevertheless, the prototype would also be usable in
issues before integrating everything into a single simulation many other applications in different fields besides healthcare,
model. Especially in stochastic models, such as simulation, a such as production planning in manufacturing, supply chain
problem in one part of the model may have a profound impact logistics, and transportation.
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