Pedro Antunes pedro.antunes @ vuw.ac.nz

Modelling Sensible Business Processes

Building rich process models for knowledge sharing

2016

IntroBusiness process management

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Business transformation

IT c

apab

ility

Workflow

Automation

Servitisation

Design of business

Intro

Process modelling is central to BPM approach Codifying organisational knowledge and behaviour

Enabling computational support

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IntroProcess modelling

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Business transformation

IT c

apab

ility

Workflow

Automation

Servitisation

Design of business

Functionalist view: control data, production data, flows, procedures, consistency

Flexibility: unique cases, loose activities, human interventions

Context awareness, decision making, agility

Coordination view: routing

Intro

Early days

Automation, rationalisation, and coordination

Nowadays

Design of business

Strategy, innovation, through-life services, collaboration, transparency, agility

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Intro

Early days

Easy elicitation-analysis-design cycle

Limited scope, known flows, clear procedures

Expected exceptions, predefined behaviour

Nowadays

Complex knowledge-sharing cycle

Unique cases, human discretion, changing goals

Unexpected exceptions, emergent behaviour

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Problem

How to capture and model process knowledge?

Lack of realism/detail/context

Lost in translation

Lack of flexibility

Lack of agility

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Illustration

Modeller: What do you do when event X arrives?

Domain expert: It depends on so many decisions…

Modeller: Sorry, I need to report ONE activity

Modeller: Which activity follows Y?

Domain expert: I often decide on the spot…

Modeller: Sorry, I need to know ALL conditions

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Example

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MeetingFirst morning flight

Expense report

“Happy” path

Evening flight

Example

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MeetingFly to meeting

Expense report

Unexpected path

Wait 3 days

Check alternatives

Take ferry

Fly back same day

Buy clothes

2 days at sea

Classification of Processes

!11Model

Rich Lean

Mac

hine

con

trol

Hum

an c

ontr

ol

Beha

viou

r

Classification of Processes

!12Model

Rich Lean

Mac

hine

con

trol

Hum

an c

ontr

ol

Beha

viou

r

1 Mechanistic processes

• Behaviour clarity • Predictable • No decision-making • No disturbances • Typical BPM

Classification of Processes

!13Model

Rich Lean

Mac

hine

con

trol

Hum

an c

ontr

ol

Beha

viou

r

2 Ad hoc

processes

• Exceptional events • Workarounds • Human ingenuity • Typical case handling

Classification of Processes

!14Model

Rich Lean

Mac

hine

con

trol

Hum

an c

ontr

ol

Beha

viou

r

3 Generative processes

1 Mechanistic processes

• Evolution • Breeding • Adaptation • Mining

Classification of Processes

!15Model

Rich Lean

Mac

hine

con

trol

Hum

an c

ontr

ol

Beha

viou

r

4 Sensible

processes

• Context sensitivity • Sensemaking • Augmentation • Meta-design

Classification of Processes

!16Model

Rich Lean

Mac

hine

con

trol

Hum

an c

ontr

ol

Beha

viou

r

3 Generative processes

1 Mechanistic processes

2 Ad hoc

processes

4 Sensible

processes

Sensible Business Processes

A definition

Processes that leverage both the human capacity for sensemaking and decision making and the processing capacity of complex information systems

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Sensible Business Processes

Our research questions

What process knowledge would be captured?

What methods and tools would be needed to capture such knowledge?

What would be the effectiveness of these tools and methods?

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Research Paradigm

Design science

Building artefacts

Advancing the knowledge base

Demonstrating utility

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Research Paradigm

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Build EvaluateArtefact

Artefact

Process stories

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Actors

DialogueScenes

Information resources

Narrative

Process Stories

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Process storytelling tool

Process Stories

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A process story in storyboard view

Process Stories

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A process story in structure view

Process Stories

Theoretical foundations

Sensemaking theory

“Sensemaking involves the ongoing retrospective development of plausible images that rationalise what people are doing”

Organisational storytelling theory

“Stories communicate complex ideas and spring people into action using narrative mechanisms”

“Stories bring detailed explanations, contextual information, values, and what-if considerations to knowledge sharing”

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Build-Evaluate Cycles

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Build Evaluate

We needed 3 build-evaluate cycles to answer our research questions

Artefact

Build-Evaluate Cycles

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Build Evaluate

Features Purpose Participants Cases

Cycle 1 Initial tool FormativeLarge organisation

Model existing process

Cycle 2Improved editing

Summative Small teamModel new process

Cycle 3Improved storytelling

SummativeLarge organisation

Model existing process

Cycle 1

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Case Size Data gathering

Cycle 1

Model existing process - Client relationship management

27 participants

1 stage: - Individual storytelling - Informal feedback

Cycle 1

Results (disappointing)

Many difficulties composing scenes (too many steps)

Problems viewing process stories

Wide variations in level of abstraction

Lack of contextual details

Lack of confidence expressing stories

Consequence

Improved tool with fewer clicks and automatic if-then-else

Improved training and instructions to users

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Cycles 2 and 3

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Case Size Data gathering

Cycle 2

Model new process - IT service provisioning

Small team - leader plus 5 members

2 stages: - Individual storytelling - Convergence meeting moderated by leader

Cycle 3Model existing process - administrative

Large organisation - 20 participants

3 stages: - Define reference process (sanctioned

by the organisation) - Modelling sessions (mainly individual) - Conversion of individual stories into

BPMN and comparison with reference

Research Questions

RQ1. Did the subjects create detailed stories?

RQ2. Can workflow be derived from user stories?

RQ3. Did the stories portray emotion?

RQ4. Were unexpected situations depicted?

RQ5. Was contextualised knowledge applied?

RQ6. Did sharing stories help the team better understand the process?

RQ7. Did the gathered stories influence the final adopted practices?

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Detail (Size & Complexity)

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0%

25%

50%

75%

100%

Structural complexity

None Low Medium High Very high

Valu

e A

xis

0%

25%

50%

75%

100%

Number of stories with “x” scenes

None Low Medium High Very high

New Existing

Low [1-4] Medium [5-9] High [10-19] Very high [20-∞]

Detail (Dialogue & Narrative)

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0%

25%

50%

75%

100%

Use of dialogue

None Low Medium High Very high

New process Existing process

0%

25%

50%

75%

100%

Use of narrative

None Low Medium High Very high

Detail

Did the subjects create detailed stories?

Yes - Regarding both size and complexity

Interestingly, size and complexity were higher with a new process

Yes - Regarding narrative

However, existing process had more narrative

Depends - Regarding dialogue

New process had less dialogue

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Workflow

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0%

25%

50%

75%

100%

Workflow elements

No Yes

New and Existing process

Can workflow be derived from user stories?

Yes - Every story had at least one workflow element (activity, condition, flow)

Emotion

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0%

25%

50%

75%

100%

Emotion

No Yes

New process Existing process

Did the stories portray emotion?

Divided results (50% mark) Existing process generated slightly more emotional elements

Surprise

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0%

25%

50%

75%

100%

Surprise

No Yes

New process Existing process

Were unexpected situations depicted?

Depends on type of process Existing process very often described with surprising situations

New process completely focussed on “happy path”

Context

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0%

25%

50%

75%

100%

Context

None Low Medium High Very high

New process Existing process

Was contextualised knowledge applied?

Depends on type of process Existing process highly contextualised

New process had low contextual cues

Understanding & Influence

RQ6. Did sharing stories help the team better understand the process?

RQ7. Did the gathered stories influence the final adopted practices?

To answer these questions, we had to adopt a different approach to data analysis

Chunking the process in logical segments and analysing individual contributions to each segment

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Understanding

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0

4

8

12

16

20

Number of scenes per story

Chunk 1 Chunk 2 Chunk 3 Chunk 40

4

8

12

16

20

Number of scenes in converged story

Chunk 1 Chunk 2 Chunk 3 Chunk 4

New process

Understanding

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0

6

12

18

24

30

Number of activities per individual process

Chunk 1 Chunk 2 Chunk 30

6

12

18

24

30

Number of activities in reference process

Chunk 1 Chunk 2 Chunk 3

Existing process

Understanding

Did sharing stories help the team better understand the process?

Yes - In both cases

The converged story had more scenes than most individual stories (new process)

An excessively detailed story was toned down by the group

The reference process had fewer activities than most individual processes (existing process)

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Influence

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0%

25%

50%

75%

100%

% individual activities appearing in individual stories and converged story

Chunk 1 Chunk 2 Chunk 3 Chunk 4

New process

Influence

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0%

25%

50%

75%

100%

% individual activities appearing in individual stories and converged story

Chunk 1 Chunk 2 Chunk 3 Chunk 4

New process

This story shaped chunk 3 of final story

This story had no influence on chunk 2

Influence

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0%

25%

50%

75%

100%

Influence of individual activities on reference process

Supports Contradicts

No Yes No Yes

Existing process

Influence

Did the gathered stories influence the final adopted practices?

Yes - In both cases

The converged story was significantly influenced by some stories

Those stories exhibited high expertise in specific chunks of the whole process

The reference process was supported by all stories, but also contradicted by some stories

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In a GlanceRQ1. Did the subjects create detailed stories?

YES (size, complexity): New > Existing

YES (narrative): Existing > New

DEPENDS (dialogue): Existing > New

RQ2. Can workflow be derived from user stories?

YES

RQ3. Did the stories portray emotion? Around 50% did

RQ4. Were unexpected situations depicted? DEPENDS: Existing = Yes, New = No

RQ5. Was contextualised knowledge applied? DEPENDS: Existing = High, New = Low

RQ6. Did sharing stories help the team better understand the process? YES

RQ7. Did the gathered stories influence the final adopted practices?

YES

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Discussion

Arguments in favour of sensible processes

Enriching knowledge of existing processes

85% process stories had high context reasoning

75% expressed surprising events

67% expressed emotion

100% activities supported the established process

43% activities contradicted the established process

Enriching knowledge of new processes

83% stories had high detail

66% had high complexity

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Discussion

Enriching knowledge

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This… …versus this

Discussion

Arguments in favour of sensible processes

Balancing the picture

Converged process was balanced when compared to individual process stories

More detail in some chunks, less in others

Reference process was simultaneously supported and contradicted by individual process stories

Better account of reality in some chunks

Integration with existing approaches

Every story contained workflow elements (mechanistic)

Stories identified alternative activities (surprises)

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Discussion

Integration with existing approaches

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Discussion

Domain experts, instead of modelling experts No specialised language or skills required

Collaboration Domain experts can effectively collaborate in building process stories

Process elicitation versus modelling No need for separate activities

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Discussion

Regarding design science Anonymous reviewer

“I understand what you intend, but the RQs are too fuzzy, 'can' can never be falsified. Sure, all you present CAN improve business processes, but it is more relevant whether and to which amount it really improves. There is no baseline/control group for comparison, still I think the results are interesting and should be reported”

Answer?

Design science is more about problem solving

“what”/ “can” type of research questions

Comparison with baseline was possible in one case (229% increase in number of process nodes), but not in others

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Future Work

Alternative ways for capturing process stories

Generic purpose tools?

Quality assessment of process stories Utility/understandability versus correctness/completeness?

Elicitation/modelling method Best practices?

More research needed for theory building

New versus existing processes

Big versus small organisations

Consensus versus divergence

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ReferencesSimões, D., P. Antunes and L. Carriço (2018). “Eliciting and Modelling Business Process Stories.” Business & Information Systems Engineering, 60 (2), pp. 115-132.

Simões, D., P. Antunes and J. Cranefield (2016). Enriching Knowledge in Business Process Modelling: A Storytelling Approach. Innovations in Knowledge Management: The impact of social media, semantic web and cloud computing. L. Razmerita, G. Phillips-Wren and L. Jain. Heidelberg, Springer. 95: 241-267.

Simões, D., N. Thuan, L. Jonnavithula and P. Antunes (2015). Modelling Sensible Business Processes. 2nd International Conference on Future Data and Security Engineering (FDSE). Ho Chi Minh City, Vietnam. T. Dang, R. Wagner, J. Küng, N. Thoai, M. Takizawa and E. Neuhold. Heidelberg, Springer. 9446.

Jonnavithula, L., P. Antunes, J. Cranefield and J. Pino (2015). Organisational Issues in Modelling Business Processes: An Activity-Based Inventory and Directions For Research. 19th Pacific Asia Conference on Information Systems (PACIS), Singapore, AIS.

Antunes, P., D. Simões, L. Carriço and J. Pino (2013). “An End-User Approach to Business Process Modeling.” Journal of Network and Computer Applications, 36 (6), pp. 1466-1479.

Simões, D., P. Antunes and J. Pino (2012). Humanistic Approach to the Representation of Business Processes. 16th IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD), Wuhan, China, IEEE.

Antunes, P. and H. Mourão (2011). “Resilient Business Process Management: Framework and Services.” Expert Systems With Applications, 38 (2), pp. 1241-1254.

Antunes, P. (2011). “BPM and Exception Handling: Focus on Organizational Resilience.” IEEE Transactions on System, Man, and Cybernetics Part C: Applications and Reviews, 41 (3), pp. 383-392.

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