Jan Claes Process Mining

1. FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION
Process Mining
Get your processes out of the black box!
Faculty of Economics and Business Administration Jan Claes | Confenis DC 2012
Department of Management Information and Operations Management 21 September, 2012

2. A plane crashed... What happened?
Analyse the ‘black box’
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 2 / 11

3. Event log
Black box in a plane
Detect causes
Log book on a ship
Find optimal routes
Event log file in a company
Analyse business processes
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 3 / 11

4. Process modeling
The world is complex Organizations are complex We make models
Models contain errors
Organizations use software Software record traces We generate models
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 4 / 11

5. Process modeling
Process mining
Your organization...
… uses software ...
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 5 / 11

6. Process mining
A A A A
A B C D E
B C B
A C B D E
B C
A B C D E C B C
A B C E D D D
A C B D E E E E E
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 6 / 11

7. Types of process mining
Process Discovery Process Conformance
Process Process
Discovery Conformance
Models Event logs Models Event logs
Process Extension
Process
Extension
Models Event logs
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 7 / 11

8. 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 Jan Claes | Confenis 2012
Department of Management Information and Operations Management 8 / 11

9. 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 Jan Claes | Confenis 2012
Department of Management Information and Operations Management 9 / 11

10. Process mining in Disco (www.fluxicon.com)
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 10 / 11

11. Contact information
Jan Claes
jan.claes@ugent.be
http://processmining.ugent.be
Twitter: @janclaesbelgium
Faculty of Economics and Business Administration Jan Claes | Confenis 2012
Department of Management Information and Operations Management 11 / 11