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Models vs. Reality. dr.ir . B.F. van Dongen Assistant Professor Eindhoven University of Technology b.f.v.dongen @ tue.nl. Process Mining. Discovering processes How do people behave? Compliance oriented Where and why do people deviate from standards / rules / regulations?

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Models vs reality

Models vs. Reality

dr.ir. B.F. van Dongen

Assistant Professor

Eindhoven University of Technology

[email protected]


Process mining
Process Mining

  • Discovering processes

    • How do people behave?

  • Compliance oriented

    • Where and why do people deviate from standards / rules / regulations?

  • Performance oriented

    • Where are bottlenecks in my processes?


Aligning models to observed behavior
Aligning models to Observed Behavior

Starting point for conformance checking is a process model and a log

What is the most likely execution of the model, corresponding to a trace observed in the log?


Introduction alignments
Introduction: Alignments

  • Alignments are used for conformance checking

  • Alignments are computed over a trace and a model:

    • A trace is a (partial) order of activities

    • A model is a labeled Petri labeled with activities

  • An alignment explains exactly where deviations occur:

    • A synchronous move mean that an activity is in the log and a corresponding transition was enabled in the model

    • A log move means that no corresponding activity is found in the model

    • A model move means that no corresponding activity appeared in the log


  • E xample
    Example

    model:

    ABDE

    log


    Logged a aligns nicely to model
    Logged “A” aligns nicely to model

    model:

    A

    A

    ABDE

    log


    Logged b aligns nicely to model
    Logged “B” aligns nicely to model

    model:

    A

    B

    A

    B

    ABDE

    log


    Logged d does not fit the model
    Logged “D” does not fit the model

    model:

    A

    B

    A

    B

    D

    ABDE

    log


    C was probably executed but was not logged
    “C” was probably executed, but was not logged

    model:

    C

    A

    B

    A

    B

    D

    ABDE

    log


    Logged e aligns nicely to model
    Logged “E” aligns nicely to model

    model:

    E

    C

    A

    B

    E

    A

    B

    D

    ABDE

    log


    Alignment shows where deviations occurred
    Alignment shows where deviations occurred

    Alignment:

    The best way to fit the trace in the model

    model:

    E

    C

    A

    B

    E

    A

    B

    D

    ABDE

    log


    Alignments
    Alignments

    • Alignments specify exactly where deviations occurred when comparing logs to models

    • Alignments can be used for:

      • Fitness/precision computations

      • Performance analysis

      • Model repair

      • ...

      • Compliance analysis


    Use of alignment techniques in compliance
    Use of alignment techniques in compliance

    ?

    compliance improvement

    compliance checking and analysis

    implement compliance measures

    formalize compliance rules

    elicit compliance rules

    13


    Automated compliance checking
    Automated compliance checking

    business process

    compliance requirement

    compliancespecification

    diagnostic information

    compliance checker


    Automated compliance checking1
    Automated compliance checking

    business process

    Log

    compliance requirement

    B

    F

    diagnostic information

    A

    B

    alignment

    compliance checker

    compliance

    Petri net pattern

    Ƭ

    F


    Specifying compliance rules
    Specifying Compliance Rules

    rule repository

    Log

    Which compliance pattern?

    compliance checker

    How to prune the Petri net pattern?

    precise

    Petri net pattern

    compliance specifier


    Implementation

    Patient registration

    Patient registration

    X-Ray

    Implementation

    ProM6 (www.promtools.org/prom6)

    Compliance Checking Using Conformance Checking

    Elicit Compliance Rule

    Patient registration

    X-ray

    others


    Conclusions
    Conclusions

    Alignments provide a powerful method to explain where operational processes deviated from models

    Using the right models, alignments can detect (and predict) possible violations of compliance rules

    Alignments provide guarantees on non-deviating cases


    Future directions
    Future directions

    Current challenges:

    Representation and extraction of multi-dimensional event data for deviation detection

    Representation and management of deviations

    Detection and diagnosis of deviations

    Online, real time deviation prediction

    Integration of prototypes applicable to high-volume data

    Application on real-life cases



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