Marlon Dumas

Marlon Dumas
University of Tartu · Institute of Computer Science

Professor of Information Systems at University of Tartu
Putting process mining research into practice

About

507
Publications
247,376
Reads
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25,447
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Introduction
My research interests span across the fields of software engineering, information systems and business process management. My ongoing work focuses on combining data mining and formal methods for analysis and monitoring of business processes. My team has developed state-of-the-art methods for several core process mining problems, such as automated process model discovery (cf. BPMN Miner), business process conformance checking (via behavioral alignment) and predictive business process monitoring.
Additional affiliations
September 2019 - February 2022
Apromore
Position
  • Manager
Description
  • Apromore is a leading provider of open-source solutions for process mining and AI-driven business process improvement. Within Apromore, I am responsible for developing partnerships, including partnerships with research centres and universities.
December 2007 - present
University of Tartu
Position
  • Professor (Full)
September 2000 - March 2009
Queensland University of Technology
Position
  • Professor (Associate)
Education
September 1997 - June 2000
University of Grenoble
Field of study
  • Computer Science

Publications

Publications (507)
Article
Full-text available
Predictive business process monitoring refers to the act of making predictions about the future state of ongoing cases of a business process, based on their incomplete execution traces and logs of historical (completed) traces. Motivated by the increasingly pervasive availability of fine-grained event data about business process executions, the pro...
Article
Full-text available
Robotic process automation (RPA) is an emerging technology that allows organizations automating repetitive clerical tasks by executing scripts that encode sequences of fine-grained interactions with Web and desktop applications. Examples of clerical tasks include opening a file, selecting a field in a Web form or a cell in a spreadsheet, and copy-p...
Article
Full-text available
Simulation is a versatile technique for quantitative analysis of business processes. It allows analysts to estimate the performance of a process under multiple scenarios. However, the discovery, validation, and tuning of business process simulation models is cumbersome and error-prone. It requires manual iterative refinement of the process model an...
Preprint
This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of treatments that maximize the probability of a given outcome. Users classify the attributes in the event log into controllable and non-controllable, where the former correspond to attributes that can be altered during an e...
Article
Full-text available
A generative model is a statistical model capable of generating new data instances from previously observed ones. In the context of business processes, a generative model creates new execution traces from a set of historical traces, also known as an event log. Two types of generative business process models have been developed in previous work: dat...
Chapter
Prescriptive process monitoring approaches leverage historical data to prescribe runtime interventions that will likely prevent negative case outcomes or improve a process’s performance. A centerpiece of a prescriptive process monitoring method is its intervention policy: a decision function determining if and when to trigger an intervention on an...
Chapter
Business process simulation is a versatile technique to predict the impact of one or more changes on the performance of a process. Mainstream approaches in this space suffer from various limitations, some stemming from the fact that they treat resources as undifferentiated entities grouped into resource pools. These approaches assume that all resou...
Preprint
Full-text available
Business Process Simulation (BPS) is a common technique to estimate the impact of business process changes, e.g. what would be the cycle time of a process if the number of traces increases? The starting point of BPS is a business process model annotated with simulation parameters (a BPS model). Several studies have proposed methods to automatically...
Preprint
Full-text available
Business process simulation is a versatile technique to predict the impact of one or more changes on the performance of a process. Mainstream approaches in this space suffer from various limitations, some stemming from the fact that they treat resources as undifferentiated entities grouped into resource pools. These approaches assume that all resou...
Conference Paper
Full-text available
Process mining is a set of techniques to analyze business processes based on event logs extracted from information systems. Existing process mining techniques are designed for intra-organizational settings, as they assume that the entire event log of a process is available for analysis at once. In an intra-organizational process, each party only ha...
Article
Automated process discovery is a process mining operation that takes as input an event log of a business process and generates a diagrammatic representation of the process. In this setting, a common diagrammatic representation generated by commercial tools is the directly-follows graph (DFG). In some real-life scenarios, the DFG of an event log con...
Article
Full-text available
The implementation of data mining projects in complex organisations requires well-defined processes. Standard data mining processes, such as CRISP-DM, have gained broad adoption over the past two decades. However, numerous studies demonstrated that organisations often do not apply CRISP-DM and related processes as-is, but rather adapt them to addre...
Preprint
Full-text available
Business Process Simulation (BPS) is a common approach to estimate the impact of changes to a business process on its performance measures. For example, BPS allows us to estimate what would be the cycle time of a process if we automated one of its activities. The starting point of BPS is a business process model annotated with simulation parameters...
Preprint
Process mining techniques enable analysts to identify and assess process improvement opportunities based on event logs. A common roadblock to process mining is that event logs may contain private information that cannot be used for analysis without consent. An approach to overcome this roadblock is to anonymize the event log so that no individual r...
Preprint
Full-text available
Prescriptive process monitoring approaches leverage historical data to prescribe runtime interventions that will likely prevent negative case outcomes or improve a process's performance. A centerpiece of a prescriptive process monitoring method is its intervention policy: a decision function determining if and when to trigger an intervention on an...
Chapter
Full-text available
Batch processing reduces processing time in a business process at the expense of increasing waiting time. If this trade-off between processing and waiting time is not analyzed, batch processing can, over time, evolve into a source of waste in a business process. Therefore, it is valuable to analyze batch processing activities to identify waiting ti...
Article
Full-text available
Privacy regulations, such as GDPR, impose strict requirements to organizations that store and process private data. Privacy-enhancing technologies (PETs), such as secure multi-party computation and differential privacy, provide mechanisms to perform computations over private data and to protect the disclosure of private data and derivatives thereof...
Article
Full-text available
Process Mining is an active research domain and has been applied to understand and improve business processes. While significant research has been conducted on the development and improvement of algorithms, evidence on the application of Process Mining in organisations has been far more limited. In particular, there is limited understanding of the...
Article
Data mining techniques have gained widespread adoption over the past decades, particularly in the financial services domain. To achieve sustained benefits from these techniques, organizations have adopted standardized processes for managing data mining projects, most notably CRISP-DM. Research has shown that these standardized processes are often n...
Article
Full-text available
Money laundering is a global threat to society nowadays. Governments and governmental authorities fight money laundering, in part, by regulating banks and financial institutions. Financial institutions, in turn, are obligated to implement mechanisms to prevent money laundering. Usually, these prevention mechanisms include automated monitoring syste...
Chapter
Prescriptive process monitoring is a family of techniques to optimize the performance of a business process by triggering interventions at runtime. Existing prescriptive process monitoring techniques assume that the number of interventions that may be triggered is unbounded. In practice, though, interventions consume resources with finite capacity....
Article
Full-text available
Predictive process monitoring is a family of techniques to analyze events produced during the execution of a business process in order to predict the future state or the final outcome of running process instances. Existing techniques in this field are able to predict, at each step of a process instance, the likelihood that it will lead to an undesi...
Preprint
Full-text available
Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems that draws upon trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for...
Preprint
Full-text available
The applicability of process mining techniques hinges on the availability of event logs capturing the execution of a business process. In some use cases, particularly those involving customer-facing processes, these event logs may contain private information. Data protection regulations restrict the use of such event logs for analysis purposes. One...
Preprint
Full-text available
Verifying temporal compliance rules, such as a rule stating that an inquiry must be answered within a time limit, is a recurrent operation in the realm of business process compliance. In this setting, a typical use case is one where a manager seeks to retrieve all cases where a temporal rule is violated, given an event log recording the execution o...
Preprint
Full-text available
Prescriptive process monitoring methods seek to optimize a business process by recommending interventions at runtime to prevent negative outcomes or poorly performing cases. In recent years, various prescriptive process monitoring methods have been proposed. This paper studies existing methods in this field via a Systematic Literature Review (SLR)....
Article
Events recorded during the execution of a business process can be used to train models to predict, at run-time, the outcome of each execution of the process (a.k.a. case). In this setting, the outcome of a case may refer to whether a given case led to a customer complaint or not, or to a product return or other claims, or whether a case was complet...
Article
Full-text available
Process mining is an active research domain and has been applied to understand and improve business processes. While significant research has been conducted on the development and improvement of algorithms, evidence on the application of process mining in organizations has been far more limited. In particular, there is limited understanding of the...
Article
Robotic Process Automation (RPA) is a technology to automate routine work such as copying data across applications or filling in document templates using data from multiple applications. RPA tools allow organizations to automate a wide range of routines. However, identifying and scoping routines that can be automated using RPA tools is time consumi...
Preprint
Prescriptive process monitoring is a family of techniques to optimize the performance of a business process by triggering interventions at runtime. Existing prescriptive process monitoring techniques assume that the number of interventions that may be triggered is unbounded. In practice, though, specific interventions consume resources with finite...
Chapter
Full-text available
The allocation of resources in a business process determines the trade-off between cycle time and resource cost. A higher resource utilization leads to lower cost and higher cycle time, while a lower resource utilization leads to higher cost and lower waiting time. In this setting, this paper presents a multi-objective optimization approach to comp...
Article
Full-text available
The problem of automatically discovering business process models from event logs has been intensely investigated in the past two decades, leading to a wide range of approaches that strike various trade-offs between accuracy, model complexity, and execution time. A few studies have suggested that the accuracy of automated process discovery approache...
Chapter
Die Prozessidentifikation (engl.: process identification) zielt darauf ab, die Geschäftsprozesse eines Unternehmens systematisch zu definieren und klare Kriterien für die Auswahl zu verbessernder Prozesse festzulegen. Das Ergebnis der Prozessidentifikation ist eine Prozessarchitektur, die die Prozesse und ihre Beziehungen darstellt. Diese Prozessar...
Chapter
In den vorangegangenen Kapiteln haben wir gelernt, wie man konzeptionelle Prozessmodelle erstellt und diese für Dokumentations- und AnalysezweckeProzessimplementierung einsetzt. Diese Modelle sind aufgrund ihres Zwecks bewusst abstrakt, d. h. sie enthalten keine Details zur technischen Umsetzung. Das bedeutet, dass konzeptionelle Prozessmodelle sys...
Chapter
In den letztenProzesserhebung beiden Kapiteln haben wir uns mit der Frage beschäftigt, wie man Prozessmodelle erstellt. Dabei sind wir meist von der Annahme ausgegangen, dass es eine textbasierte Beschreibung des Prozesses gibt. In der Praxis ist das aber nur selten der Fall, zumindest wenn ein Prozessmodell zum allerersten Mal erstellt wird. Es gi...
Chapter
In den vorangegangenen Kapiteln haben wir gelernt, wie man qualitative und quantitative Analyseverfahren einsetzt, um Probleme in bestehenden Geschäftsprozessen zu identifizieren. Wir haben auch gesehen, dass viele Prozesse in der Praxis Probleme mit der Durchlaufzeiteffizienz haben. Verschiedene Heuristiken unterstreichen das Potenzial, das im Ein...
Chapter
DieProzessanalyse qualitative AnalyseProzessanalyse ist ein wertvolles Instrument, um systematische Einblicke in einen Prozess zu gewinnen. Die Ergebnisse der qualitativen Analyse sind jedoch manchmal nicht präzise genug, um eine solide Entscheidungsgrundlage zu schaffen. Denken Sie an den Prozessverantwortlichen des Vermietungsprozesses von BuildI...
Chapter
Geschäftsprozessmanagement (engl.: business process management (BPM)) ist die Kunst und Wissenschaft, die Arbeit in einer Organisation so zu gestalten, dass konsistente Ergebnisse sichergestellt und Verbesserungspotenziale genutzt werden. In diesem Zusammenhang kann der Begriff „Verbesserung“ in Abhängigkeit von den Zielen der Organisation untersch...
Chapter
In diesem Kapitel werden wir weiter vertiefen, wie komplexe Geschäftsprozessemit BPMN modelliert werden können. Die hier vorgestellten Elemente bauen auf demerworbenen Wissen von Kap. 3 auf. Wir werden insbesondere näher auf Aktivitäten, Ereignisse und Gatter eingehen. Wir werden Aktivitäten erweitern, um komplexere Formen von Nacharbeit und Wieder...
Chapter
Sobaldwir einen neu gestaltetenGeschäftsprozess implementiert und eingeführt haben, kann es passieren, dass der neue Prozess nicht unseren Erwartungen entspricht. Beispielsweise können bestimmte Arten von unvorhergesehenen Ausnahmen auftreten, die Bearbeitungszeit einiger Aufgaben kann aufgrund dieser Ausnahmen viel höher sein als erwartet, und War...
Chapter
Modelle von Geschäftsprozessen sind in verschiedenen Phasen des BPM-Lebenszyklus von Bedeutung. Bevor wir mit der Modellierung eines Prozesses beginnen, ist es wichtig zu verstehen, warum wir diesen modellieren. Die Modelle, die wir erstellen, werden je nach dem Zweck, für den wir sie erstellen, recht unterschiedlich aussehen. Es gibt viele Gründe,...
Chapter
Die Analyse von Geschäftsprozessen ist sowohl eine Kunst als auch eine Wissenschaft. In dieser Hinsicht ist die qualitative Analyse die künstlerische Seite der Prozessanalyse. Wie in der bildenden Kunst, zum Beispiel in der Malerei, gibt es nicht nur eine einzige Möglichkeit, eine gute Prozessanalyse zu erstellen, sondern eine Reihe von Prinzipien...
Chapter
Die gründliche Analyse eines Geschäftsprozesses bringt eine ganze Reihe von Problemen zu Tage. Beispielsweise verlangsamen Engpässe den Prozess oder die Kosten für die Ausführung sind zu hoch. Diese Probleme deuten auf verschiedene Möglichkeiten zur Prozessverbesserung hin. Das Problem ist jedoch, dass die Verbesserung oft nicht systematisch angega...
Chapter
wir eine Reihe vonMethoden und verwandten Techniken für die Identifizierung, Entdeckung, Analyse, Neugestaltung, Implementierung und Überwachung von Geschäftsprozessen vorgestellt. Entlang der sechs Phasen des BPM-Lebenszyklus haben wir auch Softwarewerkzeuge und -systeme besprochen, die uns bei der Anwendung dieser Methoden für das effektive Manag...
Preprint
Robotic Process Automation (RPA) is a technology to automate routine work such as copying data across applications or filling in document templates using data from multiple applications. RPA tools allow organizations to automate a wide range of routines. However, identifying and scoping routines that can be automated using RPA tools is time consumi...
Preprint
Full-text available
Reducing cycle time is a recurrent concern in the field of business process management. Depending on the process, various interventions may be triggered to reduce the cycle time of a case, for example, using a faster shipping service in an order-to-delivery process or giving a phone call to a customer to obtain missing information rather than waiti...
Preprint
Enterprise information systems allow companies to maintain detailed records of their business process executions. These records can be extracted in the form of event logs, which capture the execution of activities across multiple instances of a business process. Event logs may be used to analyze business processes at a fine level of detail using pr...
Chapter
Data mining techniques have gained widespread adoption over the past decades, particularly in the financial services domain. To achieve sustained benefits from these techniques, organizations have adopted standardized processes for managing data mining projects, most notably CRISP-DM. Research has shown that these standardized processes are often n...
Article
Business process simulation is a versatile technique for quantitative analysis of business processes. A well-known limitation of process simulation is that the accuracy of the simulation results is limited by the faithfulness of the process model and simulation parameters given as input to the simulator. To tackle this limitation, various authors h...
Chapter
Enterprise information systems allow companies to maintain detailed records of their business process executions. These records can be extracted in the form of event logs, which capture the execution of activities across multiple instances of a business process. Event logs may be used to analyze business processes at a fine level of detail using pr...
Preprint
Business process simulation is a well-known approach to estimate the impact of changes to a process with respect to time and cost measures -- a practice known as what-if process analysis. The usefulness of such estimations hinges on the accuracy of the underlying simulation model. Data-Driven Simulation (DDS) methods combine automated process disco...
Preprint
Full-text available
The applicability of process mining techniques hinges on the availability of event logs capturing the execution of a business process. In some use cases, particularly those involving customer-facing processes, these event logs may contain private information. Data protection regulations restrict the use of such event logs for analysis purposes. One...
Article
Full-text available
It is common for business processes to exhibit a high degree of internal heterogeneity, in the sense that the executions of the process differ widely from each other due to contextual factors, human factors, or deliberate business decisions. For example, a quote-to-cash process in a multinational company is typically executed differently across dif...
Book
Dieses Lehrbuch umfasst den gesamten Lebenszyklus des Geschäftsprozessmanagements (BPM), von der Prozessidentifikation bis zur Prozessüberwachung, und die entsprechenden Schritte der Erhebung, Analyse, Verbesserung und Implementierung von Prozessen. Dabei werden Konzepte, Methoden und Werkzeuge der Betriebswirtschaftslehre, der Informatik und der I...
Book
This book constitutes thoroughly reviewed and selected short papers presented at the 25th East-European Conference on Advances in Databases and Information Systems, ADBIS 2021, as well as papers presented at doctoral consortium and ADBIS 2021 workshops. Due to the COVID-19 the conference and satellite events were held in hybrid mode. The 11 full p...
Book
This book constitutes the proceedings of the 25th European Conference on Advances in Databases and Information Systems, ADBIS 2021, held in Tartu, Estonia, in August 2021. The 18 full papers presented together with 3 keynotes were carefully reviewed and selected from 70 submissions. The selected papers span a wide spectrum of topics in databases an...
Preprint
Full-text available
Process mining techniques enable organizations to analyze business process execution traces in order to identify opportunities for improving their operational performance. Oftentimes, such execution traces contain private information. For example, the execution traces of a healthcare process are likely to be privacy-sensitive. In such cases, organi...
Chapter
In this paper, we address the problem of detecting potentially illicit behavior in the context of Anti-Money Laundering (AML). We specifically address two requirements that arise when training machine learning models for AML: scalability and imbalance-resistance. By scalability we mean the ability to train the models to very large transaction datas...
Conference Paper
Full-text available
Robotic Process Automation (RPA) is a technology to develop software bots that automate repetitive sequences of interactions between users and software applications (a.k.a. routines). To take full advantage of this technology, organizations need to identify and to scope their routines. This is a challenging endeavor in large organizations, as routi...
Conference Paper
Full-text available
This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of treatments that maximize the probability of a given outcome. Users classify the attributes in the event log into controllable and non-controllable, where the former correspond to attributes that can be altered during an e...
Preprint
A generative model is a statistical model that is able to generate new data instances from previously observed ones. In the context of business processes, a generative model creates new execution traces from a set of historical traces, also known as an event log. Two families of generative process simulation models have been developed in previous w...
Preprint
Robotic Process Automation (RPA) is a technology to develop software bots that automate repetitive sequences of interactions between users and software applications (a.k.a. routines). To take full advantage of this technology, organizations need to identify and to scope their routines. This is a challenging endeavor in large organizations, as routi...
Article
Full-text available
Blockchain technology enables the execution of collaborative business processes involving mutually untrusted parties. Existing tools allow such processes to be modeled using high-level notations and compiled into smart contracts that can be deployed on blockchain platforms. However, these tools do not provide mechanisms to cope with the flexibility...
Chapter
Business process simulation is a versatile technique for analyzing business processes from a quantitative perspective. A well-known limitation of process simulation is that the accuracy of the simulation results is limited by the faithfulness of the process model and simulation parameters given as input to the simulator. To tackle this limitation,...