Slides of my presentation at Ideas@Work Open House Seminar, 30 March 2011, Brussel, B

1. Process Mining
Open House Seminar
Faculty of Economics and Business Administration Presentation for Ideas@Work
Department of Management Information and Operations Management 30 August, 2011

2. Presentation
This presentation is from Fluxicon as part of
their Academic Initiative
It is used under the Creative Commons
Attribution-NonCommercial-ShareAlike 3.0
Unported License
More information: www.fluxicon.com
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3. Goals of this tutorial
Understand phases of process mining analysis
Be able to get started and play around with
your own data
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4. Example Scenario
Customer service process
Call center
1
CRM
2
Customers Front Line Back Line
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5. Outline
1. Example Scenario
2. Roadmap
3. Process Mining Session
4. Take-away Points
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6. Example Scenario
Customer service process
Call center
1
CRM
2
Customers Front Line Back Line
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7. Example Scenario
Start
Our problem:
Inbound Call Inbound Email
Increased costs:
- More activities
- Lower first call resolution Handle
Handle Email
rate Case
Decreased customer Call Outbound
Email
Outbound
satisfaction:
- Net promotor score (NPS)
Expected
End Process
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8. Example Scenario
Process Mining:
You can’t control what you can’t measure.
Questions:
1) Is the expected process the actual process?
2) Can we find points of improvement to save cost
or increase quality?
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9. Roadmap
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10. Data Extraction
IT Admin of call center performs CRM
SQL Query on the CRM system
 All cases started last month
 For two problematic product
CSV
categories Data
CSV file is starting point for our Session
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11. Roadmap
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12. Event Log Construction
Input data needs to be mapped onto event
sequences
Fluxicon’s tool Nitro makes this easy
Download from
fluxicon.com/nitro
CSV Event
Data Log
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13. Roadmap
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14. Data Analysis
Event log can be loaded in open source
software ProM (We use Version 5.2)
Download from
www.promtools.
Event org/prom5/
Log
Academic toolset that is great to start
experimenting with process mining
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15. Roadmap
Focus of today’s session
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16. Hands-on Session
Let’s get started!
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17. Step 0 - Inspect Data
Open ExampleLog.csv file in Excel and
inspect its contents
You can see information about
• Service instances
• Service operations
• Start and end times
• Additional data..
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18. Step 0 - Inspect Data
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19. Step 1- Construct Log
Start Nitro and load ExampleLog.csv
Assign columns as follows:
Service ID ➞ Case ID
Operation ➞ Activity
Start Date ➞ Set ‘column ignored’
End Date ➞ Timestamp
... ➞ Other
Agent ➞ Resource
Press ‘Start conversion’
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20. Step 1- Construct Log
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21. Step 2 - Inspect Log
Look at ‘Statistics’ tab to see overview
information about event log
Select ‘Explorer’ tab to inspect individual
service instances
Press ‘Export MXML file...’
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22. Step 2 - Inspect Log
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23. Step 3 - Discover Process
Start ProM and open ExampleLog.mxml.gz
Choose ‘Mining ➞ Raw
ExampleLog.mxml.gz (unfiltered) ➞
Heuristics miner’ from menu
Press ‘start mining’
Look at the resulting process model
- Numbers in rectangles are activity frequencies
- Lower number at arcs is frequency of connection
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24. Step 3 - Discover Process
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25. Step 4 - Add Start and End
Go back to log window and select ‘Filter’ tab
Select ‘Advanced’ filter tab
Select ‘Add Artificial Start Task Log Filter’
from list ➞ press ‘add selected filter’
➞ press ‘add new filter’
Select ‘Add Artificial End Task Log Filter’ ...
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26. Step 4 - Add Start and End
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27. Step 5 - Discover Process
Choose ‘Mining ➞ Filtered
ExampleLog.mxml.gz (Advanced filter)
➞ Heuristics miner’ from menu
Press ‘start mining’
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28. Step 5 - Discover Process
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29. Step 6 - Compare Process
Start
Answer question No. 1:
Is the expected process the Inbound Call Inbound Email
actual process?
Observations: Handle
Case
Handle Email
1. Actual process is much
more complex! Email
Call Outbound
Outbound
2. Does not always start with
calls or emails (quality problem)
End
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30. Step 6 - Compare Process
Not allowed
Not allowed
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31. Step 7 - Construct New Log
Goal: We want to see whether quality
problem is in front line (FL) or back line (BL)
Go back to Nitro and change
‘Agent Position’ field from ‘Other’ to
‘Activity’
Press ‘Start conversion’ and ‘Export MXML
file...’
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32. Step 7 - Construct New Log
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33. Step 8 - Inspect New Log
Open new log in ProM
Select ‘Filter’ tab and see how activities are
distinguished between BL and FL
Observation:
In ‘Start Events’ we can see that new cases are started in the
back line (should not happen)
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34. Step 8 - Inspect New Log
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35. Step 9 - Drill Down
Select ‘Inbound Call-BL’ in ‘Start events’
filter to focus on cases that start with this
activity
Go to ‘Summary’ tab in log window and scroll
to bottom to look at ‘Originators’
Actionable result for question No. 2:
Give targeted training: Agents can be asked to re-use existing
service instances
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36. Step 9 - Drill Down
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37. Step 10 - Discover Process
Go to ‘Filter’ tab in log window again, choose
‘Advanced’ filter tab
• Select + add ‘Add Artificial Start Task Log Filter’
• Select + add ‘Add Artificial End Task Log Filter’
Choose ‘Mining ➞ Filtered
ExampleLog.mxml.gz (Advanced filter)
➞ Fuzzy miner’ from menu
Press ‘start mining’
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38. Step 10 - Discover Process
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39. Step 11 - Tune Level of Detail
Move the slider in the ‘Node filter’ tab on
the right (“significance cutoff”) up and
down
Observe how the process can be simplified
and detailed dynamically
Pull the slider down to the bottom
Last step: We will now visualize how individual
cases flow through process
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40. Step 11 - Tune Level of Detail
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41. Step 12 - Animate Process
Go to ‘Animation’ tab and pull ‘Lookahead’
slider to the far left ➞ Press ‘view
animation’
Press ▷ button to start animation
Observe how one service instance after
another moves through the process
Drag needle to end of time line and observe
how most used paths get thicker and thicker
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42. Step 12 - Animate Process
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43. That’s it!
We learned how to discover a process model
and found opportunities to improve service
quality by targeted training
Close the loop: Take action and verify results
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44. Further Steps
Process Mining allows for much more:
• Perform quantitative analysis
• Explicitly check conformance of initial model
• Perform social network analysis
• ...
We could also include additional data sources
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45. Conformance Initial Model
Start
67% of the cases “fit”
Inbound
Inbound Call
Email
Handle Handle
Case Email
Call Email
Outbound Outbound
End
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46. Social Network Analysis
Shows case transfers between agents
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47. Take-away Points
Real processes are often more complex than
you would expect
There is no one “right” model
You can take multiple views on the same data
Process mining is an explorative, interactive
activity
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48. My research
PhD project for Ghent University
Faculty of Economics and Business Administration Presentation for Ideas@Work
Department of Management Information and Operations Management 30 August, 2011

49. My research
CSV Event
Data Log
CSV Event
Data Log
Event
Log
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50. Free data analysis
You are looking for an easy way to jump in?
I am looking for some real case examples.
Let’s work together!
 Free process mining analysis
 Minimal time investment
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51. Contact information
Jan Claes
jan.claes@ugent.be
http://processmining.ugent.be
FEB08, Tweekerkenstraat 2
9000 Gent, Belgium
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