process mining - chapter 2 - process modeling and analysis

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Chapter 2 Process Modeling and Analysis prof.dr.ir. Wil van der Aalst www.processmining.org

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Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.

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Page 1: Process Mining - Chapter 2 - Process Modeling and Analysis

Chapter 2Process Modeling and Analysis

prof.dr.ir. Wil van der Aalstwww.processmining.org

Page 2: Process Mining - Chapter 2 - Process Modeling and Analysis

Overview

PAGE 1

Part I: Preliminaries

Chapter 2 Process Modeling and Analysis

Chapter 3Data Mining

Part II: From Event Logs to Process Models

Chapter 4 Getting the Data

Chapter 5 Process Discovery: An Introduction

Chapter 6 Advanced Process Discovery Techniques

Part III: Beyond Process Discovery

Chapter 7 Conformance Checking

Chapter 8 Mining Additional Perspectives

Chapter 9 Operational Support

Part IV: Putting Process Mining to Work

Chapter 10 Tool Support

Chapter 11 Analyzing “Lasagna Processes”

Chapter 12 Analyzing “Spaghetti Processes”

Part V: Reflection

Chapter 13Cartography and Navigation

Chapter 14Epilogue

Chapter 1 Introduction

Page 3: Process Mining - Chapter 2 - Process Modeling and Analysis

Productivity improvements

• Adam Smith (1723-1790) showed the advantages of the division of labor.

• Frederick Taylor (1856-1915) introduced the initial principles of scientific management.

• Henry Ford (1863-1947) introduced the production line for the mass production of “black T-Fords”.

• Since 1950 computers and digital communication infrastructures are the most dominant factor influencing business processes and their management.

PAGE 2

Page 4: Process Mining - Chapter 2 - Process Modeling and Analysis

Role of models

• Operations management, and in particular operation research, is a branch of management science heavily relying on modeling.

• Models are used to reason about processes (redesign) and to make decisions inside processes (planning and control).

• A process model may be used to discuss responsibilities, analyze compliance, predict performance using simulation, and configure a WFM system.

PAGE 3

Page 5: Process Mining - Chapter 2 - Process Modeling and Analysis

Problems of models

• The model describes an idealized version of reality.• Inability to adequately capture human behavior.• The model is at the wrong abstraction level.• Therefore, we advocate the use of event data:

− Process mining allows for the extraction of models based on facts.

− Moreover, process mining does not aim at creating a single model of the process.

− Instead, it provides various views on the same reality at different abstraction levels.

− For example, users can decide to look at the most frequent behavior to get a simple model (“80% model”).

− However, they can also inspect the full behavior by deriving the “100% model” covering all cases observed.

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Page 6: Process Mining - Chapter 2 - Process Modeling and Analysis

Transition systems

PAGE 5

[start]

register request

examine thoroughly

examine casually

checkticket

decide

pay compensation

reject request

reinitiate request

[end][c1,c2]

[c1,c4]

[c2,c3]

[c3,c4]

checkticket

examine casually

examine thoroughly

[c5]

Page 7: Process Mining - Chapter 2 - Process Modeling and Analysis

Petri nets

PAGE 6

astart register

request

bexamine

thoroughly

cexamine casually

d

check ticket

decide

pay compensation

reject request

reinitiate request

e

g

h

f

end

c1

c2

c3

c4

c5

t

p

transition

place

token

AND-split AND-join

XOR-joinXOR-split

AND-split

XOR-split

XOR-join

Page 8: Process Mining - Chapter 2 - Process Modeling and Analysis

Reachability graph

PAGE 7

astart register

request

bexamine

thoroughly

cexamine casually

d

check ticket

decide

pay compensation

reject request

reinitiate request

e

g

h

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end

c1

c2

c3

c4

c5

t

p

transition

place

token

AND-split AND-join

XOR-joinXOR-split

AND-split

XOR-split

XOR-join

[start]

register request

examine thoroughly

examine casually

checkticket

decide

pay compensation

reject request

reinitiate request

[end][c1,c2]

[c1,c4]

[c2,c3]

[c3,c4]

checkticket

examine casually

examine thoroughly

[c5]

Page 9: Process Mining - Chapter 2 - Process Modeling and Analysis

How many states?

PAGE 8

t t2

p

i2

t3i3

t4i4

t5i5

t1i1

out

(a) (c)

t

p

(b)

Page 10: Process Mining - Chapter 2 - Process Modeling and Analysis

WF-nets and soundness

PAGE 9

start end

Page 11: Process Mining - Chapter 2 - Process Modeling and Analysis

YAWL

PAGE 10

start

register request

examine thoroughly

examine casually

checkticket

decide

pay compensation

reject request

new information

end

c1

c2

OR-split OR-join

c3

condition (like a place in a Petri net)

task (i.e., an atomic activity)

AND-split

XOR-split

OR-split

AND-join

XOR-join

OR-join

start end

multiple instance task

composite task

cancelation region

Page 12: Process Mining - Chapter 2 - Process Modeling and Analysis

BPMN

PAGE 11

task/activity

AND-splitgateway

XOR-split gateway

OR-split gateway

AND-join gateway

XOR-join gateway

OR-join gateway

startevent

endevent

intermediate events

y

z

x

deferred choice pattern using the event-based XOR gateway

register request

examine casually

examine thoroughly

check ticket

decide

pay compensation

reject request

reinitiate request

start end

Page 13: Process Mining - Chapter 2 - Process Modeling and Analysis

Event-Driven Process Chains (EPCs)

PAGE 12

function

AND-split connector

XOR-split connector

OR-split connector

AND-join connector

XOR-join connector

OR-join connector

startevent

endevent

AND AND

XOR

OR OR

XOR

intermediate event

start

register request

examinethoroughly

examine casually

checkticket

decide

pay compensation

reject request

end

e1

AND

OR

XOR

OR

AND

XOR end

e2

e3

e4 e5

e6

Page 14: Process Mining - Chapter 2 - Process Modeling and Analysis

Vicious cycle paradox

PAGE 13

e1

OR

f1

AND

e3

e2

OR

f2

AND

e4

Page 15: Process Mining - Chapter 2 - Process Modeling and Analysis

Causal nets (C-nets)

PAGE 14

a

register request

b

examine thoroughly

c

examine casually

d

checkticket

decide

pay compensation

reject request

e

g

h

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end

reinitiate request

z

XOR-split AND-split OR-split

XOR-join AND-join OR-join

Page 16: Process Mining - Chapter 2 - Process Modeling and Analysis

Why C-nets?

• Similar to heuristic nets and representation used by genetic miners.

• Fits well with mainstream languages (BPMN, EPCs, YAWL, BPEL, etc.).

• Model XOR, AND, and OR, but no silent steps or duplicate activities needed.

• Loose interpretation (focus on replay semantics rather than execution semantics).

PAGE 15

Page 17: Process Mining - Chapter 2 - Process Modeling and Analysis

Another C-net

PAGE 16

a

start booking

c e

complete booking

bookcar

d

bookhotel

b

bookflight

Page 18: Process Mining - Chapter 2 - Process Modeling and Analysis

WF-net interpretation of C-nets(only valid sequences!)

PAGE 17

bookflight

a

start booking

c

b

d

bookcar

bookhotel

e

complete booking

a

start booking

c e

complete booking

bookcar

d

bookhotel

b

bookflight

Page 19: Process Mining - Chapter 2 - Process Modeling and Analysis

Non-sound C-nets

PAGE 18

a

start booking

c e

complete booking

bookcar

d

bookhotel

b

bookflight

(a) unsound because there are no valid sequences

a

start booking

c e

complete booking

bookcar

d

bookhotel

b

bookflight

(b) unsound although there exist valid sequences

Page 20: Process Mining - Chapter 2 - Process Modeling and Analysis

Unbounded C-net

PAGE 19

a

c

b d e

Page 21: Process Mining - Chapter 2 - Process Modeling and Analysis

Verification

PAGE 20

astart register

request

bexamine

thoroughly

cexamine casually

d

check ticket

decide

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e

g

h

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end

c1

c2

c3

c4

c5

deadlock

c6

Page 22: Process Mining - Chapter 2 - Process Modeling and Analysis

Example: YAWL

PAGE 21

Page 23: Process Mining - Chapter 2 - Process Modeling and Analysis

Performance analysis, e.g., simulation in BPM|one

PAGE 22

Page 24: Process Mining - Chapter 2 - Process Modeling and Analysis

Limitations of model-based analysis

• Verification and performance analysis heavily rely on the availability of high quality models.

• When the models and reality have little in common, model-based analysis does not make much sense.

• There is often a lack of alignment between hand-made models and reality

• Process mining aims to address these problems by establishing a direct connection between the models and actual low-level event data about the process.

• Process discovery techniques allow for viewing the same reality from different angles and at different levels of abstraction.

PAGE 23