Post on 11-May-2015
description
Zbigniew Paszkiewicz Department of Information Technology
Poznań University of Economics, Poland
zpasz@kti.ue.poznan.pl
October 16th, 2013, Tokyo, Japan
Analysis of collaborative processes
through process mining and social network analysis
Expanding innovations by joining strengths
Agenda
Process mining Current research Future research Other activities
2
Process mining
Commercials vs. reality
Commercial What we eat
4
Commercial Reality
Image by Fluxicon
Also true for processes
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Commercial Reality
Wrong information leads to wrong decisions
6
Image by Fluxicon
Workshops, models de jure, documents
7
Image by Fluxicon
Exceptions and adaptation
8
Image by Fluxicon
Nobody sees the whole picture
9
Image by Fluxicon
Processes are complex
10
Image by Fluxicon
Big Data
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Big Data
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Process mining
13
Data visualization
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Scope
Discovery
Conformance checking
Social network/organizational mining
Case prediction
History-based recommendation
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Organizational x-ray
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Current research
Modeling collaboration
Business Process Model
Social Network
Collaboration
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Social protocols
Business Process Model
Social requirements
From repeatable to collaborative processes
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Operational support for collaborative processes
Description of context
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Operational support for collaborative processes
Description of context
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Research issues
Representation as service protocols
Context modeling
Recommendation of activity patterns in unstructured processes
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Identification of parts of a collaborative process that have a predictable structure and those which have ad-hoc character
Application areas
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Selection of business partners
Identification and promotion of best practices
Construction management
Future research
Service protocols conformance check
• Research issues – Mining
– Modeling
– Predicting
• Application areas – Process monitoring
– Process adaptation
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68%
Mutual influences of social networks and processes
• Research issues – Mining
– Simulating
– Predicting
• Application areas – Process participants selection
– Process adaptation
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Interdependent networks
• Research issues – Modeling
– Mining
– Simulating
– Predicting
• Application areas – Smart cities
– Multi-modal transport
– Construction management
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Other activities
IEEE Task Force on Process Mining
www.win.tue.nl/ieeetfpm/
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Polish Process Mining Group
www.processmining.pl
www.twitter.com/processminingpl
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Cooperation and initiatives
• Cooperation with business sector
• BPI Challenge 2013 for Volvo IT
• Unleashing Operational Process Mining, Dagstuhl Seminar
• Courses on process mining for students and open workshops
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http://www.fluxicon.com/disco/
Software
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http://www.promtools.org/prom6/ http://ergo.kti.ue.poznan.pl/
Consultancy knowledge
Summary
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Process mining
is a mature
technology
Operational
support based on
process mining
Mutual impact of
social networks
and processes
Discovery of
collaboration
schemes
Chosen publications (1)
• Picard, W., 2013. A Formalization of Social Requirements for Human Interactions with Service Protocols, Information Sciences, IF: 3.643, DOI: 10.1016/j.ins.2013.02.005
• Paszkiewicz, Z., 2013. Process Mining Techniques in Conformance Testing of Inventory Processes: An Industrial Application, Springer Verlag, Heidelberg
• Paszkiewicz, Z., W. Picard, 2013. Analysis of the Volvo IT Incident and Problem Handling Processes using Process Mining and Social Network Analysis, Business Process Intelligence Workshop Proceedings (CEUR Proceedings)
35
Chosen publications (2)
• Picard, W., 2012. Agile Service-Oriented E-Business in a Collaborative Networked Environment, in Strategic and Pragmatic E-Business: Implications for Future Business Practices, IGI Global, DOI: 10.4018/978-1-4666-1619-6.ch001
• Picard, W., 2012. Semantic Modeling of Virtual Organizations with Service Network Schemata, New Generation Computing, IF: 0,941, DOI: 10.1007/s00354-012-0201-0
• Paszkiewicz, Z., W. Cellary, 2012. Computer Supported Collaboration of SMEs in Transnational Market, Journal of Transnational Management
36
Thank you for your attention
Zbigniew Paszkiewicz Department of Information Technology
Poznań University of Economics, Poland
zpasz@kti.ue.poznan.pl
This work has been partially supported by the Polish National Science Center. Grant no. DEC-2011/01/N/ST6/04205