Developing a biological understanding of organizational knowledge

Developing a biological understanding of
organizational knowledge
Access my research papers from Google Citations
A unique area in
the state space of the
Mandlebrot set
An attractor
Presentation for Knowledge Management Leaders
Forum, 24 July 2013
Attribution
CC BY
William P. Hall
President
Kororoit Institute Proponents and Supporters
Assoc., Inc. - http://kororoit.org
Principal
EA Principals – http://eaprincipals.com
william-hall@bigpond.com
http://www.orgs-evolution-knowledge.net
definition

My Background
 Early life: physics / natural history / cytogenetics / evolutionary
biology (PhD Harvard, 1973)
 1981-1989: Computer literacy journalism, technical
communication, commercial software, banking
 1990-2007: Documentation and knowledge management systems
analyst and designer for Tenix Defence/$ 7 BN ANZAC Ship
Project
– Tenix grew to be Australia’s largest defence engineering prime
contractor and then failed.
– How did Tenix succeed and why did it fail?
 2001-now: Researcher trying to understand what organizational
knowledge is and why organizations have such major problems
managing and applying it
2

 Company formed 1987
 Oct. 1989 won $7 BN stringently fixed price contract to build 10 frigates for
Aus. & NZ , with many difficult warranty/ liquidated damages milestones.
 Project completed 2007
– every ship delivered on-time
– on-budget
– company profit
– happy customers
 Mid 2004 began a $500 M fixed-price “Protector” contract to build 7 ships to
commercial standards for New Zealand, to be completed in 2007
 By 2007 only one ship delivered (with substantial defects). Tenix costs were so
far above contract value that Tenix auctioned Defence assets to highest bidder
 Management assumed Tenix knew how to build ships. Policies blocked social
transfer of personal knowledge re problems/solutions from ANZAC staff to
new staff hired for Protector.
Success & failure of Tenix Defence
3
 10
Hall, W.P., Richards, G., Sarelius, C., Kilpatrick, B. 2008. Organisational management of project and
technical knowledge over fleet lifecycles. Australian Journal of Mechanical Engineering. 5(2):81-95.
Hall, W.P., Nousala, S., Kilpatrick B. 2009. One company – two outcomes: knowledge integration vs
corporate disintegration in the absence of knowledge management. VINE: The journal of information
and knowledge management systems 39(3), 242-258

My own major success in the company
 Delivery of engineering tech data and maintenance knowledge into
relationally based maintenance management system
– (2000 ship specific maintenance routines x 10 ships) + (engineering technical
data on all systems/components x 10 ships)
 Correct and consistent for the points of use
 Applicable/Effective
 Available to those who need it, when and where it is needed
 Useable
– Conventional authoring and information systems could not meet requirement
 Cost blowout to fix
 Schedule slippage
 Liquidated damages (multi $M)
– Implemented structured authoring and product data management
 Solution substantially improved quality of data, information and
knowledge delivered for substantially reduced labour cost
– 80% reduction in number of documents managed
– 98% reduction in documents delivered
– further 50-70% reduction in managed text down the line
 10 ships delivered on time, on budget, for corporate profit4
Savings: $50 M - $100 M ??

How Tenix closed the ANZAC knowledge building
circles
5

Developing the biological understanding
 Only scratching the surface - see papers for
details
 Human biology
– Origins of culture and social organization
– Adaptation
– Genetic vs cultural heredity (knowledge transfer)
 Karl Popper’s evolutionary epistemology
 Autopoiesis
 Foundations of organizational knowledge
 Enterprise Knowledge Architecture
6

Biological basis of
human individual and
social knowledge
Basically we are bipedal apes who
became top predators on the African
savannah
Hall, W.P. 2013. Evolutionary origins of Homo sapiens.
Extract from Application Holy Wars or a New Reformation: A
fugue on the theory of knowledge [in preparation] -
http://tinyurl.com/kqrcxsf

We are all apes
 Our close primate cousins, orangutans, gorillas, chimpanzees and
bonobos live in organized social groups that make and use tools
– Orangutans live in small single mum families but are effective tool users and
teachers
 Another video shows mother taking boat to raid a fish trap for a meal
– Chimpanzees work in larger social groups with a lot of interaction
8
Attenborough: Amazing DIY
Orangutans - BBC Earth -
http://tinyurl.com/avl8yby
Charlotte Uhlenbroek
Chimpanzees' sophisticated
use of tools - BBC wildlife –
http://tinyurl.com/lj8ejt2

Comparative genomics provides detailed geneologies
9
From Locke et al. (2011)

10
Our family tree
White et al’s (2009) depiction of the adaptive plateaus achieved by the different species
grade shifts in the Pliocene radiation of hominins as our ancestors became more adapted
to more open and arid environments. CLCA = chimpanzee-human last common ancestor.
 CLCA was a forest ape using simple natural and biodegradable tools to increase
dietary range probably a lot like today’s chimps and bonobos
 Changing climates broke up forest into grassy woodlands. Ardipithecus adapted
by developing bipedal locomotion and use of tools for self-protection and to
harvest wider dietary range.
 Australopithecus became a successful savannah dweller
 Homo became top carnivore in Africa and Eurasia

 Grave risk of predation by big cats & other
carnivores on savanna
 Gangs of chimps can cooperate to deter cats
 Anthropoid apes aren’t the only primate tool users
– See Capuchin nut-cracking industry - http://tinyurl.com/mky2b3l
Pleiocene climate change forced some apes onto a
savanna – a tough neighbourhood to survive in!
11
From Tattersall (2010)
Masters of the Planet, p. 49
see Kortlandt 1980. How might
early hominids have defended
themselves against large
predators and food competitors?
Journal of Human Evolution 9,
79-112 –
http://tinyurl.com/l5z5vu2

Cultural knowledge transfer and adaptation to the
savanna opened new worlds
12
 Guthrie (in Roebroeks 2007) speculated that a tiny
technological improvement was all that was needed
for a more effective defence than waving big sticks
– Any cat running into a thorn branch will have its eyes
torn to shreds. Cats “know” this
– Easy step from thorn branch to spear for hunting

13
Increasing tool complexity in archaeological record
• Development of increasingly
complex stone tools (after Stout
2011), correlates with increasing
brain capacity (and more social
intelligence?)
• Exponential growth in
technology continues up to
today with development of
cognitive tools: speech,
writing, printing, computers
and the internet.
• Today computing technology is
growing hyper-exponentially
See extract from my draft book

Genetic vs cultural heredity (mechanisms for
knowledge transfer)
 Shared heritage defines the species/group
 Adaptation = change through time
 Natural selection eliminates entities with maladaptive
genes/knowledge
– Genetic heritage slow to change)
– Cultural heritage (can lead to more rapid change)
 More plastic but may not durable unless reenforced
 Can be shared laterally
 Tacit vs explicit sharing & transfer
 Capacity for language is very recent
 Linguistically expressed language can be criticized & peer reviewed
 Self-selection / criticism to eliminate errors
– Memory of and learning from history
– Speech, writing
14

Karl Popper’s Evolutionary
Epistemology
In his later work, Popper applied
evolutionary biology to his theory of
knowledge
• Popper, K.R. 1972. Objective Knowledge – an Evolutionary
Approach. Oxford University Press / Routledge.
• Popper, K.R. 1994. Knowledge and the Body-Mind Problem –
in Defence of Interaction. Routledge.
• Hall, W.P. 2003. Managing maintenance knowledge in the
context of large engineering projects - Theory and case
study. Journal of Information and Knowledge Management,
Vol. 2, No. 2 - http://tinyurl.com/3yqh8j

Sources for evolutionary approach to epistemology
16
 Charles Darwin (1859) On the Origin of Species
 Konrad Lorenz – 1973 Nobel Prize (animal cognition / knowledge)
 Donald T. Campbell (1960, 1974)
– (1960) Blind Variation and Selective Retention…. (paper)
– (1974) Evolutionary Epistemology (chapter in Schilpp)
 Sir Karl R. Popper ( 1972 – knowledge is solutions to problems)
– (1972) Objective Knowledge – An Evolutionary Approach
– (1974) “The main task of the theory of knowledge is to
understand it as continuous with animal knowledge; and … its
discontinuity – if any – from animal knowledge” p 1161,
“Replies to my Critics”
– (1994) Knowledge and the Body-Mind Problem
 Knowledge revolutions
– Thomas Kuhn (1960) The Structure of Scientific Revolutions
– Stephen J. Gould (and Eldridge 1972) - Punctuated equilibria

Karl Popper's first great idea from Objective Knowledge:
Knowledge = solutions to problems
17
Pn a real-world problem faced by a
living entity
TS a tentative solution/theory.
Tentative solutions are varied
through serial/parallel iteration
EE a test or process of error
elimination
Pn+1 changed problem as faced by an
entity incorporating a surviving
solution
The whole process is iterated
 All knowledge claims are constructed, cannot be proven to be true
 TSs may be embodied as “structure” in the “knowing” entity, or
 TSs may be expressed in words as hypotheses, subject to objective criticism; or as
genetic codes in DNA, subject to natural selection
 Objective expression and criticism lets our theories die in our stead
 Through cyclic iteration, sources of errors are found and eliminated
 Solutions/theories become more reliable as they survive repetitive testing
 Surviving TSs are the source of all knowledge!
Karl Popper, Objective Knowledge – An Evolutionary Approach
(1972), pp. 241-244

Popper's second great idea:
“three worlds” ontology
18
Energy flow
Thermodynamics
Physics
Chemistry
Biochemistry
Cybernetic
self-regulation
Cognition
Consciousness
Tacit knowledge
Genetic heredity
Recorded thought
Computer memory
Logical artifacts
Explicit knowledge
Reproduce/Produce
Develop/Recall
World 1 – External
Reality
World 2
Organismic/personal/
situational/subjective/tacit
knowledge in world 2 emerges
from world 1
World 3
The world of “objective”
knowledge
“living
knowledge”
“codified
knowledge”
The real
world

Why people who should know better ignore Popper
 Popper’s intellectual arrogance
– Ignored or denigrated those he disagreed with (e.g., Polanyi)
– Irritated many academic philosophers (ref Wittgenstein & Polanyi
affairs), especially ex positivists and constructivists
 Popper’s “negative attitude towards definitions” facilitated
misunderstanding (reaction to Wittgenstein)
– Undefined language created paradigmatic barriers between schools
 Popper’s use of ‘objective’ in the title Objective Knowledge
apparently caused those who believed knowledge could not be
objective (i.e., “objective” in that it was verifiably true) to reject
the book without reading it (ref constructivists)
– Popper used “objective” in the very different sense that knowledge
could be objectively codified in tangible objects, e.g:
 "the world of the logical contents of books, libraries, computer
memories, and suchlike" (1972: p. 74)
 our theories, conjectures, guesses (and, if we like, the logical content of
our genetic code)" (1972: p. 73)19

The autopoietic
organization
Knowledge and life are inseparable.
With a proper definition of life,
knowledge-based organizations are
seen to be living
• Maturana, H.R., Varela, F.J. 1980. Autopoiesis and Cognition
– the Realization of the Living. Kluwer.
• Nelson, R.R., Winter, S.G. 1982. An Evolutionary Theory of
Economic Change, Harvard Uinv. Press.
• Kauffman, S.A. 1993. The Origins of Order – Self-
organization and Selection in Evolution. Oxford Univ. Press
• Hall, W.P. 2005. Biological nature of knowledge in the
learning organization. The Learning Organization 12(2):169-
188.

21
What makes a system living?
 Autopoiesis
– Self-regulating, self-sustaining, self-(re)producing dynamic entity
– Fundamentally cyclical, continuation depends on the structure of the state in
the previous instant to produce autopoiesis in the next instant (ref Popper;
Maturana & Varela)
– Selective survival builds knowledge into the system one problem solution at a
time
 Imperatives for continuation of
autopoiesis Constraints and boundaries, regulations determine what is physically allowable
Energy (exergy)
Component recruitment
Materials
Observations
Entropy/Waste
Products
Departures
Actions
ProcessesProcesses
"universal" laws governing component interactions determine physical capabilities
The entity's imperatives and goals
The entity's history and present circumstances
HIGHER LEVEL SYSTEM / ENVIRONMENT
SUBSYSTEMS / COMPONENTS
Constraints and boundaries, regulations determine what is physically allowable
Energy (exergy)
Component recruitment
Materials
Observations
Entropy/Waste
Products
Departures
Actions
ProcessesProcesses
"universal" laws governing component interactions determine physical capabilities
The entity's imperatives and goals
The entity's history and present circumstances
HIGHER LEVEL SYSTEM / ENVIRONMENT
SUBSYSTEMS / COMPONENTS
0 0 0 0 0 0 0 0
0 0 1 2 1 0 0 0
0 0 1 1 2 1 0 0
0 1 3 5 3 2 0 0
0 1 1 3 2 2 0 0
0 1 2 3 2 1 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 1 2 1 0 0
0 0 0 1 1 2 1 0
0 0 1 3 5 3 2 0
0 0 1 1 3 2 2 0
0 0 1 2 3 2 1 0
0 0 0 0 0 0 0 0
1-1 1-2 1-3 1-4
2-1
0 0 0 0 0 0 0 0
0 0 1 2 1 0 0 0
0 0 1 1 2 1 0 0
0 1 3 5 3 2 0 0
0 1 1 3 2 2 0 0
0 1 2 3 2 1 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 1 2 1 0 0
0 0 0 1 1 2 1 0
0 0 1 3 5 3 2 0
0 0 1 1 3 2 2 0
0 0 1 2 3 2 1 0
0 0 0 0 0 0 0 0
1-1 1-2 1-3 1-4
2-1
Self producing entity in Conway’s Game of Life
cellular automaton
Autopoietic system

22
Spontaneous co-emergence of autopoiesis and
knowledge
 The dynamic vectors of the present instant result from causal
events in past instants as reflected in the adjacent possibles of
the immediately prior instant
– Historical connections (heritage) determine the vectors in state
space of the present instant.
 Attractor basins: convergent paths may become coherently
autopoietic, such that the ensemble structure of a convergent
state in one instant generates an ensemble structure that
remains convergent in the next instant.
 Chaos: divergent paths lead to incoherent structures that dis-
integrate and lose the historical thread of successful autopoiesis
 Ensembles that remain convergent through the selective
elimination of divergent outcomes retain structural knowledge
that solved a problem of survival to retain convergent structure
Hall, W.P., Else, S., Martin, C., Philp, W. 2011. Time-based frameworks for valuing knowledge: maintaining strategic knowledge. Kororoit
Institute Working Papers No. 1: 1-28.
Hall, W.P. 2011. Physical basis for the emergence of autopoiesis, cognition and knowledge. Kororoit Institute Working Papers No. 2: 1-63

23
 Knowledge-based
“adaptive” systems
exist at several
hierarchical levels of
structural organization
– Nation
– State
– Council
– Community group
– Person
– Body cell
 For effective action,
flows of knowledge,
decision and action
must pass through
several hierarchical
levels
Scalability and the complex hierarchy
Hall, W.P. 2006 Emergence and growth of knowledge and diversity in
hierarchically complex living systems. Workshop "Selection, Self-
Organization and Diversity CSIRO Centre for Complex Systems Science and
ARC Complex Open Systems Network, Katoomba, NSW, Australia 17-18 May
2006.

24
Six necessary and sufficient criteria for
recognizing an autopoietic system
 Bounded
– System components identifiably demarcated from environment
– E.g., organizational badges, logos, reception desks, gates, etc.
 Complex
– separate and functionally different subsystems exist within boundary)
 Mechanistic
– System dynamics driven by self-sustainably regulated economic cash flows or
dissipative “metabolic” processes
 Self-defining
– System demarcation intrinsically produced
– E.g., employment policies, procedures, etc.
 Self-producing
– System intrinsically produces own components
– E.g., recruitment & training programs
 Autonomous
– self-produced components are necessary and sufficient to produce the
system.

Foundations of
organizational knowledge
Understanding organizational knowledge
and how to manage it flows naturally
from the biological point of view
• Hall, W.P., Dalmaris, P., Nousala, S. 2005. A biological
theory of knowledge and applications to real world
organizations. Knowledge Management in Asia Pacific,
Wellington, N.Z. 28-29 November 2005
• Vines, R., Hall, W.P. 2011. Exploring the foundations of
organizational knowledge. Kororoit Institute Working
Papers No. 3: 1-39

Personal vs organizational knowledge
 Important difference
– individual knowledge (in any form) is known only by a person
– organizational knowledge is available and physically or socially
accessible to those who may apply it for organizational needs
– Even where explicit knowledge exists, individual knowledge may be
required to access it within a useful response time.
 People know:
– what knowledge the organization needs,
– who may know the answer,
– where in the organization explicit knowledge may be found,
– why the knowledge is important or why it was created,
– when the knowledge might be needed, and
– how to apply the knowledge
 This human knowledge is critical to the organization
 Snowden, D. 2002. Complex acts of knowing: paradox and
descriptive self-awareness. J. Knowledge Management 6:100-111
– Personal knowledge is volunteered; it cannot be conscripted.
– People always know more than can be told, and will tell more than
can be written down.
– People only know what they know when they need to know it.26

27
OODA system of systems in the socio-technical
knowledge-based organization
ORIENT (PROCESS)
PEOPLE
CULTURE &
PARADIGMS
INFRASTRUCTURE
“CORPORATE MEMORY”
SENSE
ANALYSIS
SYNTHESIS
PEOPLE
PEOPLE
GENETIC HERITAGE
DATA CONTENT
LINKS
RELATIONS
ANNOTA-
TIONS
OBSERVE DECIDE, ACT
DOCS RECORDS
Boyd 1996 see Osinga, F.P.B. (2005) Science, Strategy and War: the strategic theory of John Boyd. Eburon Academic Publishers,
Delft, Netherlands [also Routledge, Taylor and Francis Group (2007)] - http://tinyurl.com/26eqduv

Personal (i.e., human) knowledge
28
●Sense making
– W2 process
constructing tacit
understanding in
context
– We only know what we
know when we need to
know it
Nickols, F. 2000. The knowledge in knowledge management (KM).
in J.W. Cortada and J.A. Woods, eds. The Knowledge Management
Yearbook 2001-2002. Butterworth-Heinemann
(W2) (W2) (W3)
(W2) (W2/W3)

Building and processing knowledge in the
organization / community
IFK
(W2)
FK
CK
EK
}Semantics of explicit
knowledge are only
available via World 2
processes
Code:
EK – Explicit Knowledge
CK – Common Knowledge
FK – Formal Knowledge
IFK – Integrated Formal
Knowledge
For the purposes of this diagram
CK and FK are expressions
of explicit knowledge (EK)
WORLD 1
WORLD 2
PERSONAL
KNOWLEDGE
WORLD 3
KNOWLEDGE
BUILDING
PROCESSES
KNOWING
ORGANIZATION
(including organizational tacit knowledge)
ENVIRONMENTAL
CONTEXTS
SEMIPERMEABLE
BOUNDARY
●
●
DRIVE & ENABLE
ANTICIPATE & INFLUENCE
OBSERVE, TEST & MAKE SENSE
KNO
W
LEDG
E
FLO
W
S
&
EXCHANG
ESIFK
(W2)
FK
CK
EK
}Semantics of explicit
knowledge are only
available via World 2
processes
Code:
EK – Explicit Knowledge
CK – Common Knowledge
FK – Formal Knowledge
IFK – Integrated Formal
Knowledge
For the purposes of this diagram
CK and FK are expressions
of explicit knowledge (EK)
WORLD 1
WORLD 2
PERSONAL
KNOWLEDGE
WORLD 3
KNOWLEDGE
BUILDING
PROCESSES
KNOWING
ORGANIZATION
(including organizational tacit knowledge)
ENVIRONMENTAL
CONTEXTS
SEMIPERMEABLE
BOUNDARY
●
●
DRIVE & ENABLE
ANTICIPATE & INFLUENCE
OBSERVE, TEST & MAKE SENSE
KNO
W
LEDG
E
FLO
W
S
&
EXCHANG
ES
Vines, R., Hall, W.P. 2011.
Exploring the foundations of
organizational knowledge.
29

Cyclic interactions between personal (W2) and
explicit (W3) knowledge
30

31
Formal organizational knowledge from personal
knowledge
Personal
Accessible and
shared in group Organizational
Error reduction in new knowledge claims
Knowledgequalityassurancethroughcriticismandrealitytesting
WORLD 3
Formal
knowledge
WORLD 3
Explicit
knowledge
WORLD 3
Common
knowledge
Knowledgeexchange
Review
processing
Error reduction in new knowledge claims
Knowledgequalityassurancethroughcriticismandrealitytesting
WORLD 3
Formal
knowledge
WORLD 3
Explicit
knowledge
WORLD 3
Common
knowledge
Knowledgeexchange
Review
processing

32
Creating and building knowledge is cyclical
 Knowledge is solutions to problems of living
– Iterated cycles of creation and destruction (Boyd, Osinga)
 Creation = assembly of sense data and information to suggest
claims about the world
 Destruction = testing and criticizing claims against the world
to eliminate those claims that don’t work
– Popper: solutions are those claims which prove to work (at
least most of the time)
 Knowledge is mentally constructed
 Cannot logically prove that any claimed solution is actually true
 All claims must be considered to be tentative (i.e., potentially
fallible)
 Follow tested claims until they are replaced by something that
works better
 Knowledge building cycles are endlessly iterated and
may exist at several hierarchical levels of
organization

33
Hierarchy of knowledge building cycles
 3 stages in building reliable knowledge
– Personal/individual
– Group/team
– Peer review/formal publication
W1
Context
Individual
NOOSPHERE
Peer review /
formalization
Rework
Publication
Group/team
review/extension
W1
Context
Individual
NOOSPHERE
Peer review /
formalization
Rework
Publication
Group/team
review/extension
world knowledge-
base
application of
existing knowledge
Knowledge
construction cycle
Vines et al. 2011
Hall, Nousala 2010
Nousala et al. 2010
Hall et al. 2010

Putting theory into
practice
Understanding how to manage
organizational knowledge flows naturally
from the biological point of view
• Hall, W.P., Dalmaris, P., Nousala, S. 2005. A biological
theory of knowledge and applications to real world
organizations. Knowledge Management in Asia Pacific,
Wellington, N.Z. 28-29 November 2005
• Vines, R., Hall, W.P. 2011. Exploring the foundations of
organizational knowledge. Kororoit Institute Working
Papers No. 3: 1-39

Enterprises exist in contexts that must be
addressed as imperatives if they are to survive
 Enterprises are living entities
 No enterprise or subsidiary component should be
considered in isolation from its existential contexts
– What are its imperatives for continued existence?
 to maintain survival and wellbeing
 to maintain resource inputs necessary to survival
 to produce and distribute goods necessary to survival
 to survive environmental changes
 to minimize risk
 to maintain future wellbeing
– Organizational systems satisfying imperatives must track
continually changing contexts with observations, decisions
and actions
35

36
Building and maintaining an adaptive KM
architecture to meet organizational imperatives
DRIVERS
ENABLERS &
IMPEDIMENTS
PEOPLE
PROCESS
STRATEGY
DEVELOPMENT
STRATEGIC
REQUIREMENTS
OBSERVATION
OF CONTEXT & RESULTS
ORIENTATION & DECISION
ENACTED
STRATEGY
In competition
 Win more
contracts
 Perform better
on contracts won
 Minimise losses
to risks and
liabilities
 Meet statutory
and regulatory
requirements
 Operational
Excellence
 Customer
satisfaction
 Stakeholder
intimacy
 Service delivery
 Growth
 Sustainability
 Profitability
 Risk mitigation
 Knowledge audit
 Knowledge
mapping
 Business
disciplines
 Technology &
systems
 Information
disciplines
 Incentives &
disincentives
 Etc.
 Internal /
external
communication
 Taxonomies
 Searching &
retrieval
 Business process
analysis &
reengineering
 Tracking and
monitoring
 Intelligence
gathering
 QA / QC
 Strategic
management
 Architectural
role
 Communities of
Practice
 Corporate
communications
 HR practices
 Competitive
intelligence
 IT strategy
 Etc.
… ITERATION …

Where to next?
Developing an
enterprise KNOWLEDGE architecture
See EA Principals (http://eaprincipals.com)

An EA definition from Gartner
 Enterprise architecture is the process of translating business
vision and strategy into effective enterprise change by
creating, communicating and improving the key principles and
models that describe the enterprise's future state and enable
its evolution.
 The scope of the enterprise architecture includes the people,
processes, information and technology of the enterprise, and
their relationships to one another and to the external
environment.
 Enterprise architects compose holistic solutions that address
the business challenges of the enterprise and support the
governance needed to implement them.
(http://www.e.govt.nz/enterprise-architecture)
 Note focus on information management.
 Powerful methodology but needs to focus on knowledge in the
biological organization
38

What is an EA Framework?
 Framework (from American Heritage Dictionary)
1. A structure for supporting or enclosing something else,
especially a skeletal support used as the basis for
something being constructed.
2. An external work platform; a scaffold.
3. A fundamental structure, as for a written work.
4. A set of assumptions, concepts, values, and practices that
constitutes a way of viewing reality.
 EA Framework
– All of these definitions apply to the kinds of frameworks
used in EA.
– The value of a framework is determined by the degree to
which it provides positively useful guidance to the
architect, minus the degree to which adherence to its
strictures limits the architect’s ability to see and think
about possibly bigger pictures.
– Frameworks may be applied at several architectural levels.
39

Enterprise solutions architecture builds models &
blueprints
 Identifies interrelationships among
– Components forming the “business”
– Data and information systems
– Supporting technologies
 Two perspectives joined by modeling relationships
– “As is”
– Understanding and modeling how to get from the before to the after
– “To be”
 Primary components of models
– Business architecture (how the business works)
– Applications architecture (software)
– Technology architecture (hardware)
– Solutions architecture (how it all fits together to deliver business
outcomes)
– To add: knowledge architecture (data, information, knowledge
requirements to support business decisions & processes)
 Other components
– Security architecture
– Human capital architecture40

Where EA’s approaches apply
 Problem Space  {Modeling Space}  Solution
Space
– EA should begin with understanding problems the
enterprise faces (i.e., “business” problems) and then design
deliverable solutions (in the solution space) to solve them
– The Architect works in a Modeling Space between the
Problem Space and Solution Space to rationally define the
problems and to identify and specify interventions that map
back to provide practical solutions in the problem space (all
too often seen to be IT implementations)
 Root causes of problems are often related to
personnel, processes, or knowledge – not just
technological inefficiency.
– IT implementations focused on technology often fail to
solve original problems and may create new ones
– The wise architect is aware of and considers non-
technological issues in proposed solutions41

TOGAF provides a proven methodology
 The Open Group Architecture Framework
 Phases:
– Preliminary
 Charter & mobilization
– A. Architectural vision
 scope, stakeholders, vision & approvals
– B. Business architecture
 business architecture to support agreed
vision
– C. Information systems architecture
 includes data and application
architectures
– D. Technology architecture
– E. Opportunities & solutions
 delivery vehicles and implementation
planning
– F. Migration planning
 sequence of transition architectures with
implementation & migration plans
– G. Implementation governance
– H. Architecture change management
– Requirements management (throughout)42

Community knowledge
management
See EA Principals (http://eaprincipals.com)

New tools extending human cognition introduce radical
capabilities for knowledge infrastructure
 “Instant” observation/communication/decision/action
possible
– Every smart phone in a hand is an intelligent sensing node also
capable of organizing and supporting action
– Polling & voting (e.g., SurveyMonkey)
– Acting (e.g., Mechanical Turk)
 Crowd sourcing tools for assembling knowledge
– wiki
– databases
 Unlimited access to knowledge resources
– cloud computing
– Google Scholar / Google Translate
 > 50% world knowledge available free-on-line via author archiving
 > 95% available via research library subscriptions
– University of Melbourne accesses 105,000 eJournals
– Scholar offers direct access from search result to university
subscription
 Etc. – beyond imagining44

Sample community action groups
45
Click picture
to open link
See: Hall, W.P.,
Nousala, S., Best, R.
2010. Free technology
for the support of
community action
groups: theory,
technology and practice.

Some references on relevant technology for building
knowledge infrastructures for sustainability
 Hall, W.P., Nousala, S., Best, R., Nair, S. 2012. Social networking tools for knowledge-
based action groups. (in) Computational Social Networks - Part 2: Tools, Perspectives and
Applications, (eds) Abraham, A., Hassanien, A.-E. Springer-Verlag, London, pp. 227-255
 Nousala, S., Hall, W.P., Hadgraft, R. 2011. Socio-technical systems for connecting social
knowledge and the governance of urban action. 15th WMSCI, CENT Symposium, July 19-
22, 2011, Orlando, Florida, USA.
 Vines, R., Hall, W.P., McCarthy, G. 2011. Textual representations and knowledge support-
systems in research intensive networks. (in) Cope, B., Kalantzis, M., Magee, L. (eds).
Towards a Semantic Web: Connecting Knowledge in Academic Research. Oxford: Chandos
Press, pp. 145-195.
 Hall, W.P., Nousala, S., Best, R. 2010. Free technology for the support of community action
groups: theory, technology and practice. Knowledge Cities World Summit, 16-19, November
2010, Melbourne, Australia
 Hall, W.P., Nousala, S. 2010. What is the value of peer review – some sociotechnical
considerations. Second International Symposium on Peer Reviewing, ISPR 2010 June 29th
- July 2nd, 2010 – Orlando, Florida, USA
 Hall, W.P., Nousala, S., Vines, R. 2010. Using Google’s apps for the collaborative
construction, refinement and formalization of knowledge. ICOMP'10 - The 2010
International Conference on Internet Computing July 12-15, Las Vegas, Nevada, USA
 Nousala, S., Miles, A., Kilpatrick, B., Hall, W.P. 2009. Building knowledge sharing
communities using team expertise access maps (TEAM). International Journal of Business
and Systems Research 3(3), 279-296.
46

Developing a biological understanding of organizational knowledge

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