process mining by jan claes
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Faculty of Economics and Business Administration Department of Management Information and Operations Management
FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION
Jan Claes | Confenis DC 2012 21 September, 2012
Process Mining
Get your processes out of the black box!
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 2 / 11
A plane crashed... What happened?
Analyse the ‘black box’
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 3 / 11
Event log
Event log file in a company Analyse business processes
Log book on a ship Find optimal routes
Black box in a plane Detect causes
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 4 / 11
Process modeling
The world is complex Organizations are complex We make models Models contain errors
Organizations use software Software record traces We generate models
Your organization...
… uses software ... Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 5 / 11
Process modeling Process mining
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 6 / 11
Process mining
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Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 7 / 11
Types of process mining
Process Discovery
Event logs Models
Process Discovery Process Conformance
Process Conformance
Event logs Models
Process Extension
Event logs Models
Process Extension
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 8 / 11
Process mining project
Three iterative (!) steps
Collect data (from files and databases)
Structure data (case id, activity, timestamp)
Use miners (e.g., Fuzzy Miner, Heuristics Miner)
Main drawbacks are about finding and preparing the (right) data
Main benefits are objectivity, completeness and speed (once data is present)
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 9 / 11
Process mining in ProM (www.promtools.org)
Audit trail, database fields, csv log file ProM Analyses
ProM Log File
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 10 / 11
Process mining in Disco (www.fluxicon.com)
Faculty of Economics and Business Administration Department of Management Information and Operations Management
Jan Claes | Confenis 2012 11 / 11
Contact information
Jan Claes jan.claes@ugent.be http://processmining.ugent.be Twitter: @janclaesbelgium
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