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Analysis of collaborative processes through process mining and social network analysis
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Transcript of Analysis of collaborative processes through process mining and social network analysis
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Zbigniew Paszkiewicz Department of Information Technology
Poznań University of Economics, Poland
October 16th, 2013, Tokyo, Japan
Analysis of collaborative processes
through process mining and social network analysis
Expanding innovations by joining strengths
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Agenda
Process mining Current research Future research Other activities
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Process mining
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Commercials vs. reality
Commercial What we eat
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Commercial Reality
Image by Fluxicon
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Also true for processes
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Commercial Reality
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Wrong information leads to wrong decisions
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Image by Fluxicon
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Workshops, models de jure, documents
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Exceptions and adaptation
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Nobody sees the whole picture
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Image by Fluxicon
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Processes are complex
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Image by Fluxicon
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Big Data
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Big Data
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Process mining
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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
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Modeling collaboration
Business Process Model
Social Network
Collaboration
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Social protocols
Business Process Model
Social requirements
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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
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Application areas
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Selection of business partners
Identification and promotion of best practices
Construction management
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Future research
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Service protocols conformance check
• Research issues – Mining
– Modeling
– Predicting
• Application areas – Process monitoring
– Process adaptation
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68%
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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
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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
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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
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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)
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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
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Thank you for your attention
Zbigniew Paszkiewicz Department of Information Technology
Poznań University of Economics, Poland
This work has been partially supported by the Polish National Science Center. Grant no. DEC-2011/01/N/ST6/04205