These are the slides I used for my talk at the Enterprise Architecture Summer School 2018 in Copenhagen. You can see them with animations here: https://youtu.be/oQbSwr_N1H8. The talk is an overview of the way I practice Enterprise Architecture. It is based on a combination of two ostensibly incompatible paradigms.

1. EA SUMMER SCHOOL
AUGUST 2018, COPENHAGEN
SASSY Architecture
IVO VELITCHKOVArtwork by Vaquyahn

2. Entrepreneur
ManagerManagement Consultant
Enterprise Architect
@kvistgaardvelitchkov
About me

3. sassy
/ˈsasi/
adjective
informal
lively, bold; cheeky.
Oxford Dictionary
sassy
Possessing the attitude of
someone endowed with
an ungodly amount of
cool.
Urban Dictionary
SASSY: Semantic Architecture for Social Systems
SASSY Architecture

4. • 2001 BPM
• 1996 ERP
• 2004 EA
• 2006 ArchiMate
• 2007 EA + Strategy + Performance
• 2008 Process Simulation
• 2009 Whole‐of‐enterprise EA
• 1997 Workflow
• 2011 Systems; Ontologies
• 2013 Taskless BPMN
Lisbon
• 2014 Language & meta‐language for EA
London
• 2017 Productive Paradoxes
Affligem
• 2012 Adaptivity
ArchiMate is a registered trademark of The Open Group

5. PHILOSOPHY Aristotle Nagarjuna
LOGIC Non‐contradiction Paradox
MODEL Network System
FOCUS Information Communication
IDENTITY Given Self‐created
TECHNOLOGY Semantic Glasses
SASSY

6. PM Fair 2017
What kind of Enterprise do we want?
What kind of Enterprise do we have?

7. AGILE
COHERENT
EFFICIENT
ENTERPRISE
QUALITIES

8. PM Fair 2017
ENTERPRISE
QUALITIES
AGILE COHERENT EFFICIENT
ENTERPRISE
PRINCIPLES
ENTERPRISE
DESCRIPTIONS
Enterprise Architecture Principles
support
Enterprise Architecture Descriptions
support
are
qualities
of

9. PM Fair 2017
ENTERPRISE
QUALITIES
AGILE COHERENT EFFICIENT
ENTERPRISE
PRINCIPLES
ENTERPRISE
DESCRIPTIONS
Enterprise Architecture Principles
support
Enterprise Architecture Descriptions
support

10. PM Fair 2017
Core EA principle example:
Solutions are coherent, interoperable,
extensible and allow independence from the
future strategy or fate of a particular vendor.
Solutions are consistently connected, and necessary to
support the processes of <name of organisation> . They are
designed to fit together and interact smoothly ‐ physically,
operationally and semantically. All solution dependencies on
vendors can be efficiently replaced on request.
Interoperability Principle

11. Express unambiguously structures, operations, definitions, EA principles
and governance rules (for both humans and machines).
EXPRESSIVE
EXTENSIBLE
EXECUTABLE
Re‐use and extend other Enterprise Descriptions, and give sense to them
using decentralised network of knowledge models.
Be consistent, infer new knowledge, execute models (e.g. use reference
architecture descriptions for actual validations).
ENTERPRISE
ARCHITECTURE
DESCRIPTIONS

12. Reusing and extending
other ontologies
ENTERPRISE
ARCHITECTURE
DESCRIPTIONS
ENTERPRISE
DESCRIPTIONS
Ontologies (OWL)
give sense to; is
Governance (SHACL)
validates; is
Enterprise
Knowledge Graph

13. PM Fair 2017
Semantic Architecture
TECHNOLOGIES:
SASSY
How to name things?
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
URI
How to represent facts?
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
RDF
How to ask questions?
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
SPARQL
How to give sense?
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
OWL
How to validate?
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
SHACL

14. PM Fair 2017
What kind of Enterprise do we want?
What kind of Enterprise do we have?
AGILE
COHERENT
EFFICIENT

15. a
a
a
a
a
a
a
The data models of the
applications, developed or
acquired by most enterprises, are:
in the physical implementation
layer, and
separate for each application.
M
M
M
M
M
MM
ENTERPRISE
DESCRIPTIONS
What kind of Enterprise do we have?
The interpretation of data
is hidden in the application code.

16. Enterprise Knowledge Graph
The data models are part of
the knowledge graph:
They are shared and linked
M
M
M
M
M
M
M
M
M
M
M
M
MM
ENTERPRISE
DESCRIPTIONS

17. Linked Enterprise Data
Enterprise
Knowledge Graph
ENTERPRISE
DESCRIPTIONS

18. Semantic Architecture =
3 in 1:
SASSY

19. PM Fair 2017
Structure and behaviour
A car has a horn. Horns can honk.

20. PM Fair 2017
Structure and behaviour
A car has a horn. Horns can honk.
Enterprise Knowledge Graph
Car
Horn
Honking
has part
is part of
Capability
is a

21. COREONTOLOGIES
DOMAIN
ONTOLOGY
DOMAIN
ONTOLOGY
DOMAIN
ONTOLOGY
DOMAIN
ONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY
AONTOLOGY

23. PM Fair 2017

24. PM Fair 2017

25. PM Fair 2017

26. PM Fair 2017

27. PM Fair 2017
simple structure and
behaviour
emergent
properties
self‐
organisation enterprise
social
system

28. SASSY:
Semantic Architecture for Social Systems

29. In short about
• Tool
• Reasoning
• Theory
• Applications

30. lens frame
made to fit…
The Brilliant metaphor

31. Three years ago in Hasselt
Essential Balances in Organisations
essentialbalances.com

32. autonomy | cohesion
stability | diversity
exploitation | exploration

33. Social System Glasses
Look at the enterprises “as” Social Systems

34. Enterprise architect describes enterprise.

35. Hm, not always...
• Mathematics
• Biology
• Sociology
Theory
Calculus of Indications (George Spencer‐Brown)
Autopoiesis (Humberto Maturana and Francisco Varela)
Social Systems Theory (Niklas Luhmann)

36. Autopoiesis

37. communications
Social Systems

38. Notation
=

39. Structural Coupling

40. decisions
Organisations

41. decisions
communications
1
2
3

42. The paradoxes of decisions
"Only those questions which are in principle undecidable, we can decide“
Heinz von Foerster
1/3

43. The paradoxes of decisions
what a decision is is a decision
2/3
Find more in “The Undecidability of Decision” by Niels Åkerstrøm Andersen

44. The paradoxes of decisions
t1 t2
enable
produce
3/3

45. Some practical imp/app‐lications
• Managing constraints
• Cultivating habits for decision‐contraint patterns
• Starting away from requirements
• Discovering hidden dependancies

46. Managing constraints
Deconstructing constraint “molecules”
Suspending constraints to enable innovation
Range of realistic expectations
Configuration of constraints
Natural limitation
Decision-based limitation

47. constraints
constrained by
options
excluded due to
consideredalso feasible
… … …

49. Starting away from requirements
• Requirements‐oriented architecture
 solution‐bias
 justification of decisions that are already made
 not analysing the problems created by the solution
 atention to how, not to way: risk of wrong design decisions
• Better: problem‐oriented approach
• Even better: understanding the decision topology

50. time
power
Solution: To implement “Business Analysis Dashboard” (BAD)
Approved “BAD” business case
“BAD” investment approved
by the High IT Board
“BAD” selected, using SWOT
Prefer Buy to Build
Trust Gartner
reports
Use SWOT in
business cases,
decided by X
Recruit X,
decided by B
B can recruit,
decided by A
Start “BAD” project

51. Example:
Reducing the “local optimum” risk
Project metrics Enterprise metrics

52. Describes change in:
• Capabilities
• Processes
• Data
…
COHERENT
AGILE
EFFICIENT
REFERENCE
ARCHITECTURE
EA Principles Business Case
(Investment Proposal)
Solution Architecture

53. We suggest management to be the various ways
of reintroducing the organisation’s environment
into the organisation, while –rather ambivalently
– both accepting and changing the existing states
of the organisation itself.
Dirk Baecker, “The Form of the Firm”
The role of Enterprise Architecture
is to reintroduce the enterprise into
the efforts of changing parts of the
enterprise.

54. LOGIC Laws of thought
A=A, ¬(A ∧ ¬A), A∨¬A
Self‐reference
a≠a, a ∧ ¬a, a∨a
MODEL Graph
enterprise knowledge graph
System
closed network of processes
FOCUS Information
represented as s‐p‐o triples
Communication
more specifically decisions
IDENTITY Given
assigned unique IDs to all entities
Self‐created
internally maintained
TECHNOLOGY Semantic
URI, RDF, OWL, SPARQL, SHACL
Glasses
habits to observe observations
SASSY

55. SASSY Architecture
@kvistgaardvelitchkov
You can watch this presentation with
animations here.