Business Process Performance Mining with Staged Process Flows

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Business Process Performance Mining with Staged Process Flows Hoang Nguyen, Marlon Dumas, Arthur H.M. ter Hofstede, Marcello La Rosa, and Fabrizio Maria Maggi CAISE’2016

Transcript of Business Process Performance Mining with Staged Process Flows

Business Process Performance Mining

with Staged Process Flows

Hoang Nguyen, Marlon Dumas, Arthur H.M. ter Hofstede,

Marcello La Rosa, and Fabrizio Maria Maggi

CAISE’2016

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Process Performance Mining (PPM)

/

event log

live event stream

database

process model

conformanceanalysis

processperformance…

if A then B

extract process

knowledge

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Model-Based PPM Techniques

Performance

Analysis with

Petri net

Disco

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Issues with Model-Based PPM Techniques

Based on process maps that are sometimes too complex.

Only show a snapshot of process performance aggregated over a period of

time, not how the performance evolves over time.

Animation does not provide a precise measurement, often requires close

human inspection.

Q1: How does the overall process performance evolve over time?

Q2: How formation and dissolution of bottlenecks affects overall

performance?

Q3: How do changes in demand and capacity affect overall process

performance?

The following questions have not been well addressed:

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“Business Process Performance Analysis with Staged Process Flows”

Process flows are key to:

- Managing customer satisfaction

- Managing service quality

- Managing work load

Companies wish to make their process flows: smooth, predictable and efficient

How to measure the performance of process flows?

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Approach - Staged Process Flows

Kanban BoardWaiting PatientsSecurity check

Arrival

Departure

(Knock-out)

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Flow Performance Measurement

t t +

Case 1

Case 2

Case 3

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Measurement Tools

Cumulative Flow DiagramTime Series Chart

Summary Table

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Evaluation

Q1: How does the overall process performance evolve over time?

Q2: How formation and dissolution of bottlenecks affect overall performance?

Q3: How do changes in demand and capacity affect overall process performance?

• Process stages are based on the

helpdesk lines

• Size: ~ 8,000 IT requests

• Period: 2 years

BPIC 2012: Loan Origination Process BPIC 2013: IT Incident Handling Process

• Process stages are based on

processing stages of loan applications

• Size: ~ 13,000 applications

• Period: 6 months

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BPIC 2012: Loan Origination Process

Q1: How does the overall process performance evolve over time?

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BPIC 2012: Loan Origination Process

Q2: How formation and dissolution of bottlenecks affect overall performance?

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BPIC 2012: Loan Origination Process

Q3: How do changes in demand and capacity affect overall process performance?

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Process Performance Analysis with Petrinet Plugin

Spaghetti Model Filtered Model

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Disco

Spaghetti Model Filtered Model

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Disco Animation

(Open and play the recoded movie file)

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Conclusion

Strengths

– Novel performance measures precisely capture process evolution

– Visual analytics showing time-oriented patterns, to support performance

investigation, e.g. bottleneck detection through formation, evolution and

dissolution

Limitations and Future work

– Only applicable to processes where key stages can be detected

– Linear stage model

– Manual identification of stages

– Manual detection of process patterns

– Linear stage model

– Manual identification of stages

– Manual detection of process patterns

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Thank you!

Q&A