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
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
5
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
11
Big Data
12
Process mining
13
Data visualization
14
Scope
Discovery
Conformance checking
Social network/organizational mining
Case prediction
History-based recommendation
15
Organizational x-ray
16
Current research
Modeling collaboration
Business Process Model
Social Network
Collaboration
18
Social protocols
Business Process Model
Social requirements
From repeatable to collaborative processes
20
Operational support for collaborative processes
Description of context
21
Operational support for collaborative processes
Description of context
22
Research issues
Representation as service protocols
Context modeling
Recommendation of activity patterns in unstructured processes
23
Identification of parts of a collaborative process that have a predictable structure and those which have ad-hoc character
Application areas
24
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
26
68%
Mutual influences of social networks and processes
• Research issues – Mining
– Simulating
– Predicting
• Application areas – Process participants selection
– Process adaptation
27
Interdependent networks
• Research issues – Modeling
– Mining
– Simulating
– Predicting
• Application areas – Smart cities
– Multi-modal transport
– Construction management
28
Other activities
IEEE Task Force on Process Mining
www.win.tue.nl/ieeetfpm/
30
Polish Process Mining Group
www.processmining.pl
www.twitter.com/processminingpl
31
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
32
http://www.fluxicon.com/disco/
Software
33
http://www.promtools.org/prom6/ http://ergo.kti.ue.poznan.pl/
Consultancy knowledge
Summary
34
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
This work has been partially supported by the Polish National Science Center. Grant no. DEC-2011/01/N/ST6/04205
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