Ideas@Work Open House Seminar 2011

Faculty of Economics and Business Administration Department of Management Information and Operations Management

Presentation for Ideas@Work9 April 2023

Process MiningOpen House Seminar

Presentation for Ideas@Work - Tutorial from Fluxicon ©2 / 51

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

http://fluxicon.com/


Goals of this tutorial

Understand phases of process mining analysis

Be able to get started and play around with your own data



Example Scenario

Call center

Customer service process

CRM

Front Line Back LineCustomers

1

2



Outline

1. Example Scenario

2. Roadmap

3. Process Mining Session

4. Take-away Points



Example Scenario

Call center

Customer service process

CRM

Front Line Back LineCustomers

1

2



Example Scenario

Increased costs:- More activities- Lower first call resolution rate

Decreased customer satisfaction:- Net promotor score (NPS)

Expected Process

Our problem:

Email Outbound

Email OutboundCall OutboundCall Outbound

Handle EmailHandle EmailHandle Case

Handle Case

StartStart

EndEnd

Inbound CallInbound Call Inbound EmailInbound Email



Example Scenario

Questions:1) Is the expected process the actual process?2) Can we find points of improvement to save cost

or increase quality?

Process Mining: You can’t control what you can’t measure.



Roadmap



Data Extraction

IT Admin of call center performs SQL Query on the CRM system

All cases started last month For two problematic product

categories

CRM

CSVData

CSV file is starting point for our Session



Roadmap



Event Log Construction

Input data needs to be mapped onto event sequences

Fluxicon’s tool Nitro makes this easy

CSVData

EventLog

Download from fluxicon.com/nitro

http://fluxicon.com/nitro/

http://fluxicon.com/nitro/



Roadmap



Data Analysis

Event log can be loaded in open source software ProM (We use Version 5.2)

Academic toolset that is great to start experimenting with process mining

Download from www.promtools.org/prom5/Event

Log

http://www.promtools.org/prom5/

http://www.promtools.org/prom5/



Roadmap

Focus of today’s session



Hands-on Session

Let’s get started!



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..



Step 0 - Inspect Data



Step 1- Construct Log

Start Nitro and load ExampleLog.csvAssign columns as follows:

Service ID Case ID➞Operation Activity➞Start Date Set ‘➞ column ignored’End Date Timestamp ➞... Other➞Agent Resource➞

Press ‘Start conversion’



Step 1- Construct Log



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...’



Step 2 - Inspect Log



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






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’ ...



Step 4 - Add Start and End




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







Step 6 - Compare Process

Answer question No. 1:Is the expected process the actual process?

Observations:1. Actual process is much more complex!2. Does not always start with calls or emails (quality problem)

Email Outbound

Email OutboundCall OutboundCall Outbound

Handle EmailHandle EmailHandle Case

Handle Case

StartStart

EndEnd

Inbound CallInbound Call Inbound EmailInbound Email



Not allowedNot allowed

Step 6 - Compare Process



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...’



Step 7 - Construct New Log



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)



Step 8 - Inspect New Log



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



Step 9 - Drill Down




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







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



Step 11 - Tune Level of Detail



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



Step 12 - Animate Process



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



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



Conformance Initial Model

67% of the cases “fit”

Email Outbound

Email Outbound

Call Outbound

Call Outbound

Handle Email

Handle Email

Handle Case

Handle Case

StartStart

EndEnd

Inbound CallInbound Call Inbound Email

Inbound Email



Social Network Analysis

Shows case transfers between agents



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


Faculty of Economics and Business Administration Department of Management Information and Operations Management

Presentation for Ideas@Work9 April 2023

My researchPhD project for Ghent University

Presentation for Ideas@Work - Research of Jan Claes49 / 51

My research

CSVData

EventLog

CSVData

EventLog

EventLog


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


Contact information

Jan [email protected]://processmining.ugent.be

FEB08, Tweekerkenstraat 29000 Gent, Belgium