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Portada de Novática Special 2013-2014

Process Mining

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                                                    Full Issue
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Errata Notice (31th January, 2015) -- see below            


Editorial Section [PDF: 1 page, 125 KB]

ATI: Boosting the Future  2
Dídac López Viñas (President of ATI)

From the Chief Editor's Pen
Process Mining: Taking Advantage of Information Overload   2
Llorenç Pagés Casas (Chief Editor of Novática)

Monograph: "Process Mining"

Guest Editors: Antonio Valle-Salas and Anne Rozinat

Presentation. Introduction to Process Mining   4
Antonio Valle Salas, Anne Rozinat
[PDF: 2 pages, 183 KB]

Process Mining: The Objectification of Gut Instinct - Making Business Processes More Transparent Through Data Analysis   6
Anne Rozinat, Wil van der Aalst
[Summary][PDF: 4 pages, 522 KB]

Process Mining: X-Ray Your Business Processes  10
Wil van der Aalst
[Summary][PDF: 8 pages, 1,081 KB]

The Process Discovery Journey  18
Josep Carmona
[Summary][PDF: 4 pages, 467 KB]
Errata Notice (31th January, 2015) --  Table 1 on page 20 was  inadvertedly published incomplete in our first version. That error has been corrected.
We apologize to the author and to readers for the resulting inconvenience.

Using Process Mining in ITSM  22
Antonio Valle-Sales
[Summary][PDF: 8 pages, 905 KB]

Process Mining-Driven Optimization of a Consumer Loan Approvals Process  30
Arjel Bautista, Lalit Wangikar, Syed M. Kumail Akbar
[Summary][PDF: 9 pages, 752 KB]

Detection of Temporal Changes in Business Processes   39
Daniela Luengo, Marcos Sepúlveda
[Summary][PDF: 8 pages, 691 KB]

Articles Summary

Monograph: "Process Mining"

Guest Editors

Antonio Valle-Salas is Managing Partner of G2 and a specialist consultant in ITSM (Information Technology Service Management) and IT Governance. He graduated as a Technical Engineer in Management Informatics from UPC (Universitat Politécnica de Catalunya) and holds a number of methodology certifications such as ITIL Service Manager from EXIN (Examination Institute for Information Science), Certified Information Systems Auditor (CISA) from ISACA, and COBIT Based IT Governance Foundations from IT Governance Network, plus more technical certifications in the HP Openview family of management tools. He is a regular collaborator with itSMF (IT Service Management Forum) Spain and its Catalan chapter, and combines consulting and project implementation activities with frequent collaborations in educational activities in a university setting (such as UPC or the Universitat Pompeu
Fabra) and in the world of publishing in which he has collaborated on such publications as IT Governance: a Pocket Guide, Metrics in IT Service Organizations, Gestión de Servicios TI. Una introducción a ITIL, and the translations into Spanish of the books ITIL V2 Service Support and ITIL V2 Service Delivery.

Anne Rozinat has more than ten years of experience with process mining technology and obtained her PhD cum laude in the process mining group of Prof. Wil van der Aalst at the Eindhoven University of Technology in the Netherlands. Currently, she is a co-founder of Fluxicon and blogs at <>.

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Process Mining: The Objectification of Gut Instinct - Making Business Processes More Transparent Through Data Analysis
Anne Rozinat (1), Wil van der Aalst (2)
(1) Co-founder of Fluxicon, The Netherlands; (2) Technical University of Eindhoven, The Netherlands

Big Data existed in the 19th Century. At least that might be the conclusion you would draw by reading the story of Matthew Maury. We draw a parallel with the first systematic evaluations of seafaring logbooks and we show how you can quickly and objectively map processes based on the evaluation of log files in IT systems.

Keywords: Big Data, Case Study, Log Data, Process Mining, Process Models, Process Visualization, Systematic Analysis.

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Process Mining: X-Ray Your Business Processes
Wil van der Aalst
Technical University of Eindhoven, The Netherlands

Abstract: Recent breakthroughs in process mining research make it possible to discover, analyze, and improve business processes based on event data. Activities executed by people, machines, and software leave trails in so-called event logs. Events such as entering a customer order into SAP, checking in for a flight, changing the dosage for a patient, and rejecting a building permit have in common that they are all recorded by information systems. Over the last decade there has been a spectacular growth of data. Moreover, the digital universe and the physical universe are becoming more and more aligned. Therefore, business processes should be managed, supported, and improved based on event data rather than subjective opinions or obsolete experiences. The application of process mining in hundreds of organizations has shown that both managers and users tend to overestimate their knowledge
of the processes they are involved in. Hence, process mining results can be viewed as X-rays showing what is really going on inside processes. Such X-rays can be used to diagnose problems and suggest proper treatment. The practical relevance of process mining and the interesting scientific challenges make process mining one of the "hot" topics in Business Process Management (BPM). This article provides an introduction to process mining by explaining the core concepts and discussing various applications of this emerging technology.

Keywords: Business Intelligence, Business Process Management, Data Mining, Management, Measurement, Performance, Process Mining.

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The Process Discovery Journey
Josep Carmona
Software Department, Technical University of Catalonia, Spain

Abstract: Process models are an invaluable element of an IT system: they can be used to analyze, monitor, or improve the real processes that provide the system’s functionality. Technology has enabled IT systems to store in file logs the footprints of process executions, which can be used to derive the process models corresponding with the real processes, a discipline called Process Discovery. We provide an overview of the discipline together with some of the alternatives that exist nowadays.

Formal Methods, Process Discovery, Software Engineering.

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Using Process Mining in ITSM
Antonio Valle-Salas
Managing Partner of G2

Abstract: When it comes to information systems, ranging from copiers to surgical equipment or enterprise management systems, all the information about the processes executed using those systems are frequently stored in logs. Specifically for IT Service Management processes (ITSM), it is quite common for the information systems used to execute and control those  processes to keep structured logs that maintain enough information to ensure traceability of the related activities. It would be interesting to use all that information to get an accurate idea of ??how the process looks like in reality, to verify if the real process flow matches the previous design, and to analyze the process to improve it in order to become more effective and efficient. This is the main goal of process mining. This paper exploresthe different capabilities of process mining and its applicability in the IT Service Management area.

Keywords: Change Management, ITSM, Process Management Tools, Process Mining, Service Desk, Services.                                                                                                                                                                                                                                                                                                            
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Process Mining-Driven Optimization of a Consumer Loan Approvals Process
Arjel Bautista, Lalit Wangikar, S.M. Kumail Akbar
CKM Advisors, 711 Third Avenue, Suite 1806, New York, NY, USA

Abstract: An event log (262,200 events; 13,087 cases) of the loan and overdraft approvals process from a bank in the Netherlands was analyzed using a number of analytical techniques. Through a combination of spreadsheet-based approaches, process mining capabilities and exploratory analytics, we examined the data in great detail and at multiple levels of granularity. We present our findings on how we developed a deep understanding of the process, assessed potential areas of efficiency improvement and identified opportunities to make  knowledge-based predictions about the eventual outcome of a loan application. We also discuss unique challenges of working with such data, and opportunities for enhancing the impact of such analyses by incorporating additional data elements.

Keywords: Big Data, Business Process Intelligence, Data Analytics, Process Mining.             

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Detection of Temporal Changes in Business Processes Using Clustering Technique
Daniela Luengo, Marcos Sepúlveda
Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Santiago (Chile)

Abstract: Nowadays, organizations need to be constantly evolving in order to adjust to the needs of their business environment. These changes are reflected in their business processes, for example: due to seasonal changes, a supermarket’s demand will vary greatly during different months of the year, which means product supply and/or re-stocking needs will be different during different times of the year. One way to analyze a process in depth and understand how it is really executed in practice over time, is on the basis of an analysis of past event logs stored in information systems, known as process mining. However, currently most of the techniques that exist to analyze and improve processes assume that process logs are in a steady state, in other words, that the processes do not change over time, which in practice is quite unrealistic given the dynamic nature of organizations. This document presents in detail the proposed technique and a set of experiments that reflect how our proposal delivers better results than existing clustering techniques.

Concept Drift, Clustering, Process Mining, Temporal Dimension.

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Last updated on 18th December 2014 Autor: Llorenç Pagés Casas
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