Process Mining - Chapter 13 - Cartography and Navigation
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Transcript of Process Mining - Chapter 13 - Cartography and Navigation
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Chapter 13Cartography and Navigation
prof.dr.ir. Wil van der Aalstwww.processmining.org
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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
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Business process maps
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The first geographical maps date back to the 7th Millennium BC. Since then cartographers have improved their skills and techniques to create maps thereby addressing problems such as clearly representing desired traits, eliminating irrelevant details, reducing complexity, and improving understandability.
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Example of a map
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Road map of The Netherlands. The map abstracts from smaller cities and less significant roads; only the bigger cities, highways, and other important roads are shown. Moreover, cities aggregate local roads and local districts. Also not use of color, size, etc.
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Tripfacts
are releasedfor accounting
Plannedtrip
is approved
TravelExpenses
Advancepayment
Needto correctplanned
tripis transmitted
Unrequestedtrip
has takenplace
Tripfacts
and receiptshave
been released for checking
Approvedtrip
has takenplace
Tripcosts
statementis transmitted
Entryof tripfacts
Entryof a
travelrequest
Accountingdate
is reached
Paymentamount
transmittedto bank/payee
Cancellation
Tripcostsmust
be includedin cost accounting
Amountsliable
to employmenttax transmitted
to payroll
Amountsrelevant
to accountingtransmitted
to payroll accounting
Needfor trip
has arisen
Paymentsmust
be released
Tripis requested
Approvalof tripfacts
Paymentmust
be effected
Approvalof travelrequest
Tripexpenses
reimbursementis rejected
Plannedtrip
mustbe canceled
Tripadvance
is transmitted/paid
Tripexpenses
reimbursementmust
be canceled
Tripis canceled
Tripcosts
cancelationstatement
is transmitted
Plannedtrip
is rejected
Approvalof tripfacts
is transmitted
A
B
CE
D
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PAGE 5
Highlights more important paths
More significant nodes are emphasized
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PAGE 6
AggregationClustering of coherent, less significant structures
AbstractionRemoving isolated, less significant structures
More to learn from maps...
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Illustrating the problem
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a
cb d
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Classical top level view: low level connections still exist
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p3
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Seamless zoom
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a
cb d
e
f
g h
i
j
k l
Threshold: 0.3
a
b
e
f
g h
i
j
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Threshold: 0.4
a
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k
Threshold: 0.6
a
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Threshold: 1.0
x
x y z
x y z
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x y z
y z
x y z
x y z
x y z
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Example: Reviewing papers(100 cases generating 3730 events)
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WF-net discovered using the α-algorithm
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Fuzzy miner: two views on the same process
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fuzzy model showing all activities
color and width of arc
indicates significance
of connection
fuzzy model showing only two activities
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Balancing between both extremes
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aggregated node containing 10 activities
inner structure of aggregated node
fuzzy model showing all activities
color and width of arc
indicates significance
of connection
fuzzy model showing only two activities
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Not a single map!
PAGE 13
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Projecting dynamic information on business process maps
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Projecting traffic jams on maps
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Business process movies
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Navigation
• Whereas a TomTom device is continuously showing the expected arrival time, users of today’s information systems are often left clueless about likely outcomes of the cases they are working on.
• Car navigation systems provide directions and guidance without controlling the driver. The driver is still in control, but, given a goal (e.g. to get from A to B as fast as possible), the navigation system recommends the next action to be taken.
• Operational support provides TomTom functionality for business processes.
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PAGE 18
Predict: When will I be home? At 11.26!
Recommend: How to get home ASAP? Take a left turn!
Detect: You drive too fast!
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Relating the process mining framework to cartography and navigation
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information system(s)
current data
“world”people
machines
organizationsbusiness
processes documents
historic data
resources/organization
data/rules
control-flow
de jure models
resources/organization
data/rules
control-flow
de facto models
provenance
expl
ore
pred
ict
reco
mm
end
dete
ct
chec
k
com
pare
prom
ote
disc
over
enha
nce
diag
nose
cartographynavigation auditing
event logs
models
“pre mortem”
“post mortem”