Summary

Are you passionate about process mining, data-driven decision making, and cutting-edge
visual analytics? Join us in an exciting collaboration with ARIS, a global leader in Process
Intelligence, to develop innovative solutions in Object-Centric Process Mining (OCPM).
You’ll gain hands-on experience with real-world business questions, contribute to the
evolution of a widely-used process mining tool, learn and work with ARIS, and help shape
the future of process intelligence.

Each of these four projects focuses on a unique challenge in OCPM – ranging from KPI
automation and process variant analysis to visual storytelling and intelligent conformance
checking. You won’t just explore ideas-you’ll build features that can directly contribute
to ARIS’ ongoing OCPM development.

Offered Projects

Automatic KPI Generation for OCPM Analysis

Challenge

How can we automatically compute relevant KPls like cycle time, bottlenecks, or resource
usage from OCPM data?

Goal

The goal of this project is to develop a system that automatically extracts and computes Key
Performance lndicators (KPls) from Object-Centric Process Mining (OCPM) logs. Key metrics
like cycle time, resource utilization, and bottlenecks are essential for evaluating the efficiency
and performance of processes. This project aims to create a dynamic framework that can
adjust and generate KPls based on user needs, ensuring that the computed KPls are tailored to
specific process management goals.

Research Questions

Which KPls are relevant for OCPM processes, such as cycle time, bottlenecks, and
resource utilization?
How can a framework be developed to dynamically generate and adjust KPls based on
the specific needs of users?
What methods can be employed to automate the extraction and computation of KPls
from OCPM logs?

Expected Outcome

This project will result in a module that automatically computes KPls for OCPM data, providing
insights into process performance and enabling informed decision-making. The tool will allow
users to efficiently track and improve operational performance based on real-time data
analysis. The tool will be benchmarked against existing algorithms to assess its performance,
with the goal of improving process conformance detection in real-world scenarios.

Your Contribution to ARIS

You’ll help develop a flexible KPI engine that could become a core part of ARIS’ OCPM
capabilities.

Process Variant Analysis for OCPM: Comparing Multiple Process Executions

Challenge

How can we detect and compare different ways a process is executed using object-centric
data?

Goal

This project focuses on developing a methodology for analyzing and visualizing different
process variants in Object-Centric Process Mining (OCPM). The aim is to identify and compare
multiple executions of a process, particularly focusing on Object-Centric Event Logs (OCEL).
Understanding process variant behavior is crucial for identifying inefficiencies and areas of
improvement in process management. This project will also include interactive visualizations to
intuitively showcase the differences between process variants.

Research Questions

How can different process variants be detected and analyzed to find meaningful
patterns in a large number of variants in an Object-Centric Event Log?
What types of visualizations can effectively highlight the differences between various
process executions?
How can these visualizations be made interactive to allow users to explore process
variants in-depth?

Expected Outcome

The project will deliver a feature for variant analysis, complete with query logic and interactive
visualizations. This will allow users to easily identify different process variants and understand
how variations in execution impact overall process performance. The tool will be benchmarked
against existing algorithms to assess its performance, with the goal of improving process
conformance detection in real-world scenarios.

Your Contribution to ARIS

The outcome will be a variant analysis tool that supports better operational decisions in ARIS.

New lnnovative Visualizations of Process-Oriented Object Interactions Challenge

Challenge

How can we visualize complex object interactions in an intuitive and visually compelling
way?

Goal

This project aims to develop a new approach to visualizing OCPM data.” The goal is to create an
intuitive and visually engaging representation of process objects and their relationships,
incorporating key performance metrics such as cycle time and bottlenecks. The object-centric process visualization should offer a fresh way to explore complex process data, ma king it easier
to identify inefficiencies and optimize operations.

Research Questions

How can process objects and their interrelationships be effectively visualized?
How can key performance metrics like cycle time and bottlenecks be integrated into the
visualization?
How can the complexity of the visualization be automatically adapted to the user’s
needs?

Expected Outcome

The outcome of this project will be a novel visualization for OCPM. This new layout algorithm
and visualization will highlight object relationships and provide an intuitive way for users to
analyze process flows and performance metrics. The new visualization will be benchmarked
against existing ones to assess its performance, with the goal of improving comprehensibility in
real-world scenarios.

Your Contribution to ARIS

You’ll help develop a visually appealing and powerful new way for ARIS users to understand
their processes.

Conformance Checking for Object-Centric Event Logs

Challenge

How can we verify if real-world executions of a process conform to their expected models?

Goal

The goal of this project is to implement a conformance-checking engine for Object-Centric
Process Mining (OCPM) to detect deviations from expected process behavior. The project will
explore the combination of rule-based and data mining approaches to improve the accuracy
and scalability of conformance checking against process models. By benchmarking the
proposed solution against existing algorithms such as in PM4Py, this project will evaluate the
effectiveness of the new conformance-checking engine in real-world applications. The project
should also investigate whether and which specific requirements exist for process models, e.g.
in BPMN notation, in order to use them for an object-centered conformance check.

Research Questions

How can rule-based and data mining-driven conformance checking be effectively
integrated for OCPM?
How does the new approach compare with existing conformance-checking algorithms,
such as in PM4Py?
What are the challenges involved in ensuring process conformance in OCPM – with a
focus on the required process models that prescribe the targeted process execution?

Expected Outcome

This project will produce a prototype engine for conformance checking in OCPM, combining
rule-based and data mining techniques. The tool will be benchmarked against existing
algorithms to assess its performance, with the goal of improving process conformance
detection in real-world scenarios.

Your Contribution to ARIS

You’ll lay the groundwork for a next-generation conformance checker that could be integrated
directly into ARIS.

ARIS

ARIS, the Process Intelligence leader, helps organizations turn their processes into value. By
managing the entire process lifecycle with a single, integrated suite, ARIS enables companies
to define, analyze, simulate, optimize and control their processes. ARIS is consistently
recognized by Gartner and Forrester as a leader in Process Intelligence and Process Mining and
is trusted by thousands of businesses across finance, healthcare, manufacturing, retail and
others to improve and reinvent their business. For more information, visit www.ARIS.com and follow ARIS on LinkedIn.