An introduction to Process Mining

Diogo R. Ferreira

diogo.ferreira@tecnico.ulisboa.pt

DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018

Introduction

• Example of a business process

• sequence of activities

• branching and parallel behavior

• process model vs. process instances

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 2

a. Fill out request

b. Approve request

c. Archive request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request

Requisitionapproved?

Yes

No

+ +

Introduction

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 3

a. Fill out request

b. Approve request

c. Archive request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request

Requisitionapproved?

Yes

No

+ +

a b ca b d e f g ha b d e g f ha b d g e f h

Introduction

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 4

a. Fill out request

b. Approve request

c. Archive request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request

Requisitionapproved?

Yes

No

+ +

a b ca b d e f g ha b d e g f ha b d g e f h

Introduction

• Possible questions• what is the most frequent path?

• how many requests (%) get approved?

• how much time does the process (or each activity) take?

• does every instance comply with the model?

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 5

a. Fill out request

b. Approve request

c. Archive request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request

Requisitionapproved?

Yes

No

+ +

Introduction

• Task allocation

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 6

ha a

bb b d g

fe f

ce

dgha

cb

u3 u4 u5 u6 u7 u8u2u1

tasks

users

a. Fil l out request

b. Approve request

c. Archive request

a. Fil l out request

b. Approve request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request+ +

a. Fil l out request

b. Approve request

c. Archive request

a. Fil l out request

b. Approve request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request+ +

Introduction

• More possible questions• what is the distribution of work, i.e. who does what?

• how do users interact and collaborate with each other?

• what is the performance of each user in each activity?

• are certain resources being overloaded?

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 7

ha a

bb b d g

fe f

ce

dgha

cb

u3 u4 u5 u6 u7 u8u2u1

tasks

users

a. Fil l out request

b. Approve request

c. Archive request

a. Fil l out request

b. Approve request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request+ +

a. Fil l out request

b. Approve request

c. Archive request

a. Fil l out request

b. Approve request

d. Order product

e. Receive product

f. Updatestock

g. Handle payment

h. Close request+ +

Event logs

• Example of an event log

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 8

Event logs

• Process mining perspectives• control-flow perspective (task column)

• organizational perspective (user column)

• performance perspective (timestamp column)

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 9

• Task transitions within each case id

Control-flow perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 10

• Transition matrix

Control-flow perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 11

a b c d e f g h

a 3

b 1 2

c

d 1 1

e 2

f 1 1

g 1 1

h

• Transition graph

Control-flow perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 12

• Transition graph for a larger event log

• percentage of approvals: 5683 / (1866 + 5683) ≈ 75%

Control-flow perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 13

• Improving the visualization• edge thickness

• activity counts

• node coloring

Control-flow perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 14

• Handover of work

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 15

• Transition matrix

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 16

u1 u2 u3 u4 u5 u6 u7 u8

u1 1

u2 1 1

u3 1 1

u4 1

u5 1

u6 1 2

u7 2

u8 1 1

• Transition graph

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 17

• Transition graph for a larger event log

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 18

• Working together

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 19

• Number of cases where each pair of users have worked together

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 20

u1 u2 u3 u4 u5 u6 u7 u8

u1 3 2 1 1 2 2 2

u2 3 2 1 1 2 2 2

u3 2 2 1 2 2 2

u4 1 1

u5 1 1 1 1 1 1

u6 2 2 2 1 2 2

u7 2 2 2 1 2 2

u8 2 2 2 1 2 2

• Number of cases where each pair of users have worked together

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 21

• Number of cases where each pair of users have worked together

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 22

• Distribution of work

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 23

• Distribution of work

Organizational perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 24

• Timestamp difference between events

Performance perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 25

• Timestamp difference between events

Performance perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 26

• Timeline of events

Performance perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 27

• Relative time

Performance perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 28

• Activity duration

Performance perspective

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 29

Conclusion

• Where to go from here• process mining books

• A Primer on Process Mining: Practical Skills with Python and Graphviz, D. R. Ferreira (Springer, 2017)

• Process Mining: Data Science in Action, W. van der Aalst (Springer, 2016)

• process mining courses• Process Mining: Data Science in Action

https://www.coursera.org/learn/process-mining

• Introduction to Process Mining with ProMhttps://www.futurelearn.com/courses/process-mining

• process mining website• http://www.processmining.org

• process mining tools: ProM, Disco, etc.

© 2018 Diogo R. Ferreira DELix – Lisbon Winter School on Data Science and Engineering | February 15-17, 2018 30