Ideas@Work Open House Seminar 2011

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

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

Presentation for Ideas@Work - Tutorial from Fluxicon ©
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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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Example Scenario

Customer service process

Call center

1

CRM

2

Customers Front Line Back Line

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Outline

1. Example Scenario
2. Roadmap
3. Process Mining Session
4. Take-away Points

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Example Scenario

Customer service process

Call center

1

CRM

2

Customers Front Line Back Line

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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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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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Roadmap

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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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Roadmap

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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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Roadmap

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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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Roadmap

Focus of today’s session

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Hands-on Session

Let’s get started!

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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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Step 0 - Inspect Data

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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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Step 1- Construct Log

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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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Step 2 - Inspect Log

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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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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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Step 4 - Add Start and End

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Choose ‘Mining ➞ Filtered
ExampleLog.mxml.gz (Advanced filter)
➞ Heuristics miner’ from menu

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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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Step 6 - Compare Process

Not allowed
Not allowed

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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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Step 7 - Construct New Log

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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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Step 8 - Inspect New Log

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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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Step 9 - Drill Down

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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
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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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Step 11 - Tune Level of Detail

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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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Step 12 - Animate Process

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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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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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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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Social Network Analysis

Shows case transfers between agents

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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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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

My research

CSV Event
Data Log

CSV Event
Data Log

Event
Log

Presentation for Ideas@Work - Research of Jan Claes
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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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Contact information

Jan Claes
jan.claes@ugent.be
http://processmining.ugent.be

FEB08, Tweekerkenstraat 2
9000 Gent, Belgium

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Ideas@Work Open House Seminar 2011

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