For the third time, the Business Process Intelligence workshop hosted the Business Process Intelligence Challenge. The goal of this challenge is twofold. On the one hand, the challenge allows researchers and practitioners in the eld to show their analytical capabilities to a broader audience. On the other hand, the challenge (and it's data) allows for researchers to prove that their techniques work on real-life data sets.
Every year, the challenge organizer's look for a real-life event log which contains event-data of one or more operational business processes of an organization. This data is provided to the participants as-is, without any pre-processing or ltering (other than anonymization). The logs are made publically available and are given a DOI for future reference.
In contrast to authors of scienti c papers, challenge participants are not asked to write scienti c descriptions of algorithms, techniques or tools, nor are they asked to provide scienti cally well set-up case studies. Instead, the participants are asked to analyze the provided log data using whatever techniques available, focusing on one or more of the process owner's questions or proving other unique insights into the process captured in the event log.
A jury consisting of academic and industry members with a strong background in business process analysis assesses the submitted reports on completeness of the analysis, presentation of the results and on originality. Finally, the jury decides on a winner who receives a prize o ered by one of the challenge's sponsors: Fluxicon - Process mining for professionals. The process mining technology in Fluxicon's products can automatically create smart ow diagrams of your process. All you need are event logs that are already on your IT systems. Because our products work with this objective information, you no longer need to rely on belief or hearsay you will know what's going on. Perceptive Software. Through the recent purchase of Pallas Athena, Perceptive Software has become a world-leading Business Process Management Software (BPM) and Solutions provider. Their innovative software platforms and user-friendly designs are well known and recognized throughout the industry.
For the 2013 edition of the BPI challenge an event log was provided by Volvo IT Belgium. The log contains events from an incident and a problem management system called VINST. The primary goal of the incident management process is restoring a customer's normal service operation as quickly as possible when incidents arise ensuring that the best possible levels of service quality and availability are maintained. The problem management system includes the activities required to diagnose the root cause(s) of incidents and to secure the resolution of those problems to enhance the quality of ITservices delivered and/or operated by Volvo IT.
The data contained events related to the two processes as well as di erent
organisational entities and was separated into three event logs:
Incidents [
Closed Problems [
Open Problems [
The process owner was particularly interested in four di erent questions. Push to Front (incidents only). Is there evidence that cases are pushed to the 2nd and 3rd line too often or too soon? Ping Pong Behavior. How often do cases ping pong between teams and which teams are more or less involved in ping-ponging? Wait User abuse. Is the \wait user" substatus abused to hide problems with the total resolution time? Process Conformity per Organisation. Where do the two IT organisations di er and why?
While the rst BPI challenge in 2011 attracted only three submissions and the
second BPI challenge in 2012 attracted six, a total of 12 submissions were
received for assessment by the jury this year. In this section, all submissions are
presented. For each submission, a short abstract is included followed by a
selection of the jury's comments on that submission in italics.
M. Arias and E. Rojas, Ponti cia Universidad Catolica de Chile,
Chile [
A. Bautista, S. Akbar, A. Alvarez, T. Metzger and M. Reaves, CKM
Advisors, USA [
The Jury: It is very interesting to analyze the data at product and country granularities, in order to suggest possible candidates as root causes of bottlenecks. In general, the number of variables taken into account is remarkable and this suggests long and accurate work on actual data.
S. vanden Broucke, J. Vanthienen and B. Baesens, KU Leuven,
Belgium and University of Southampton, UK [
The Jury: I particularly liked how carefully and consistently the potential biases were revealed, and that interpretations (particularly concerning individual employees) were given with caution. It's very important to keep in mind that the actual root cause of what can be observed behind a process often lies outside of the data analyst's view (e.g., \Is this team slow or just deals with the more complicated cases?").
E. Dudok and P. van den Brand, Perceptive Software, The
Netherlands [
F. van Ge en and R. Niks, Rabobank, The Netherlands and O&I
Management Consultants, The Netherlands [
The Jury: The report is less of a classical solution to the BPI challenge, but a case study on conducting a DMAIC (De ne, Measure, Analyze, Improve, Control) Analysis from the Six Sigma Toolkit in a faster and more objective way through the use of Process Mining tools. The BPI challenge data is used as an exemplary case study to support this idea. The paper is a nice testimonial about the usefulness of process mining techniques in the context of BPM improvements e orts such as Six Sigma.
The purpose of this document is to answer the questions raised by Volvo IT Belgium. In addition, an attempt is made to capture the incident and problem management processes in the form of BPMN models.
The Jury: The submission addresses all questions of the process owner using Disco, Excel, Word and Enterprise Architect. The report does not comprise any additional analyses, but provides process documentation in form of BPMN models.
J. Hevia and C. Saint-Pierre, Ponti cia Universidad Catolica de
Chile, Chile [
The Jury: In general, this report tends to make excessive use of process mining techniques even when simple data analysis would su ce to answer the clients questions. However, in one particular instance, such approach allowed the authors to discover unexpected behaviour which may be important for the client to know (regardless of their initial questions). This is the case of the push-to-front question, where the authors discovered an escalation of some incidents from level 1 directly to level 3, which might not be desirable.
C. J. Kang, Y. S. Kang, Y. S. Lee, S. Noh, H. C. Kim, W. C. Lim, J.
Kim and R. Hong, Myongji University, Korea [
A professional application of Process Mining has been established in the context of a methodology as de ned by a consultancy rm. The results of the research show where in the context of consultancy Process Mining is used and how clients can bene t from expertise and standardized work.
The Jury: This report attempts to diligently answer, one by one, all questions from the client. I appreciate a consultant taking time to perform such a report, and I do encourage the author to continue in this direction.
Z. Paszkiewicz and W. Picard, Poznan Unviersity of Economics,
Poland [
The Jury: The authors frequently state an hypothesis and then prove or disprove it. This is very good. There is an interesting mix of tools deployed, data inconsistencies are addressed, and assumptions are clearly stated. It's a detailed and good-quality analysis. The chord diagrams are an innovative and interesting contribution.
S. Radhakrishnan and G. Anantha, SolutioNXT Inc., US [
The Jury: All the analyses are performed with Disco and a graphical fuzzy
model is used to respond to all questions. The work nishes with three interesting
business-level suggestions.
P. Van den Spiegel, L. Dieltjens and L. Blevi, KPMG Advisory,
Belgium [
The Jury: I like the mapping of statuses on the standard ow. This really bridges the gap between the data in the event log and the provided process model. Furthermore, the authors make good use of their experience in the business domain and include interpretations from a business level perspective beyond the questions asked by the process owner in the case description. Overall, it's a solid contribution with a good focus on business level insights.
Using the jury's scores as initial ranking of the 12 submissions, we obtained a clear top three: { A. Bautista, S. Akbar, A. Alvarez, T. Metzger and M. Reaves, CKM Advisors,
USA { E. Dudok and P. van den Brand, Perceptive Software, The Netherlands { C.J. Kang, Y.S. Kang, Y.S. Lee, S. Noh, H.C. Kim, W.C. Lim, J. Kim and R.
Hong, Myongji University, Korea
All these submissions were praised for their thoroughness, completeness and presentation. However, one winner had to be selected and the decision was made to select, as winner of the BPI Challenge 2013:
C.J. Kang, Y.S. Kang, Y.S. Lee, S. Noh, H.C. Kim, W.C. Lim, J. Kim and R. Hong,
Myongji University, Korea
Their report was found to be complete, repeatable and thorough, while maintaining a proper mix between general data analysis techniques and real business process intelligence techniques. During the BPI workshop 2013, the prizes were handed over to the rst author of the submission as shown in Figure 1.
The BPI challenge has proven to be a succesful way to let practitioners and researchers come together and share their capabilities and techniques. The various reports have signi cantly increased in quality over the years and this year's result shows how mature the business process intelligence eld has become.
With the help of the community, we hope to organize many succesful challenges in the future.