5. PROCESS DISCOVERY Flashcards

1
Q

4 main tasks of process discovery

A
  1. Defining the setting: assembling a team
  2. Gathering information: building an understand of the process through discovery
    methods
  3. Conducting the modeling task: actual creation of the process model
  4. Assuring process model quality: consideration of quality criteria and establishing trust
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2
Q

2 fundamental roles of process discovery

A
  1. Process analysts:
    responsible for gathering information with process modeling languages
  2. Domain experts:
    intimate knowledge of how a process is performed, typically process participants, not proficient in process modeling
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3
Q

challenges

A
  1. Fragmented process knowledge:
    - info from different domain experts
    - diverging assumptions likely to surface
    - iterative approach
  2. Thinking of a processes on a case level
    - Domain experts have problems responding to general questions
    - questions need to reverse-engineer the conditions that govern the routing decisions of a process
  3. Lack of familiarity with process modeling languages
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4
Q

Process discovery methods

A
  • evidence-based discovery:
    1. document analysis
    2. observation
    3. automated process discovery

-interview-based discovery

-workshop-based discovery

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5
Q

document analysis

A
  • documents point to existing roles, activities, and business objects

-issues:
○ not process-oriented
○ too abstract or detailed
○ outdated or idealistic

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6
Q

observation

A

-follow the execution of individual process instances and then abstract active and passive roles

-issues:
○ no big picture (active)
○ non-natural behavior (passive)

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7
Q

automated process discovery

A

-use of event logs and process execution data

-issues:
○ unavailability
○ selection bias
○ hard to understand

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8
Q

Interview-based discovery

A
  • based on interviewing multiple domain experts to inquire about how a process is executed
  • phases:
    1. interview
    2. process modeling
    3. model validation
  • basic strategies:
    1. forward –> follow the natural process flow
    2. backward –> start with process outcomes
  • issues:
    ○ rests on the assumption that process analysts and domain
    experts use the same technology
    ○ discrepancies between domain experts
    ○ shows tendency towards neglecting exceptional behaviour
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9
Q

Workshop-based discovery

A
  • 2 roles:
    1. facilitator → coordination of verbal contributions
    2. process modeler → creation of the process model
  • allows the perspective of multiple domain experts at the same time
  • issues:
    ○ simultaneous availability of domain experts
    ○ speech time of talkative participants
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10
Q

process modeling steps

A
  1. Identify process boundaries (definition of start and end events)
  2. Identify activities and (intermediate) events
  3. Identify resources and their handoffs (pools, lanes and sequence flows)
  4. Identify control flow
  5. Identify additional elements
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11
Q

Quality assurance

A
  • syntactic quality
  • semantic quality
  • pragmatic quality
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12
Q

syntactic quality

A
  • Conformance of a process model to the structural rules and behavioral rules of the modeling language used
    -structural correctness
    -behavioral anomalies
    -soundness
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13
Q

structural correctness

A
  1. Element-level rules:
    activities, events, flows and gateways
  2. Model-level rules:
    all flow nodes must be on a path from a start to an end event
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14
Q

Behavioral anomalies

A

-Deadlock: a running process instance is not able to progress any further

-Livelock: a process instance keeps cycling in a loop

-Lack of synchronization: 2 or more tokens are in the same sequence flow

-Dead activity: an activity can never be executed in any instance of the
process

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15
Q

soundness

A

-Option to complete
-Proper completion –> at the moment of completion, each token of the process instance must be in a different end event
-No dead activities

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16
Q

semantic quality

A

-adherence of a process model to its real-world process

-visual and logical structures
-meaningful labels

17
Q

2 criteria of semantic quality

A
  1. validity: all statements that one can make from the model are correct and relevant
  2. completeness: model contains all relevant statements about the corresponding process
18
Q

Pragmatic quality

A

-usability of a process model:
1. understandability
2. maintainability
3. learning

-modeling conventions:
○ Vocabulary → avoiding certain elements
○ Structure → limiting the model structure
○ Semantics → avoiding certain element meanings
○ Appearance → restricting the model appearance in terms of labels, layout, and notation

19
Q

7 Process Modeling Guidelines (7PMG)

A
  1. Use as few model elements as possible
  2. Minimize the routing paths per element
  3. Use one start event for each trigger and one end event for each outcome
  4. Model as structured as possible
  5. Avoid OR gateways where possible
  6. Use verb-object activity labels
  7. Decompose a model with 30+ elements