Developing a biological understanding of organizational knowledge
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Developing a biological understanding of organizational knowledge

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Gaining his PhD from Harvard as an evolutionary biologist, amongst other career twists and turns, Bill had the opportunity to play with all generations of computer technology, spent two postdoctoral ...

Gaining his PhD from Harvard as an evolutionary biologist, amongst other career twists and turns, Bill had the opportunity to play with all generations of computer technology, spent two postdoctoral years studying the history and epistemology of his science, and the last 17½ years prior to his redundancy/retirement in July 2007 working for what was for part of that time Australia's largest defence contractor. In his "retirement" Bill is again studying and writing academic papers.

In this latter stage of his career Bill confronted the KM requirements of a large and complex engineering project management and shipbuilding organization head-on as he was involved in the entire span of this company's involvement in completing the $7 BN ANZAC Ship Project to build 10 frigates for Australia (8) and New Zealand (2). In the first 10 years of his employment there, amongst other roles he designed the system for authoring, content management and delivery of the more than 20,000 individual maintenance procedure (including both human and computer readable components) into the relationally-based computerized maintenance management system that still helps keep the ships operational today. Thanks in good part to the successful development and management of the body of knowledge relating to the ships’ engineering, mainitenance and operations, this project finished with every ship delivered on-time, on-budget, with a healthy company profit and happy customers against a stringently fixed-price contract signed in 1989. By around 2000 the major KM issues relating to the ANZAC Project had been solved, and Bill was transferred to corporate Head Office as a KM analyst, where he helplessly watched the rigid command and control hierarchy at the executive and line management levels stifle the problem solving and knowledge sharing culture that produced a uniquely successful outcome for the ANZAC Project. Consequently, Tenix performed so poorly on the next significant project (~$500 M to build 7 smaller and simpler ships to commercial standards) that the owners decided to auction "all or part" the company to get out from under huge cost and schedule overruns.

Bill's experience and frustrations with this company led him to combine the diverse threads from his career in an attempt to understand both theoretically and practically how this beast of a company could at various times during its short life-span be both so good and so bad at managing knowledge that was vital to its existence. Given his background in biology, Bill could not help but to do this from his backgrounds in biology and epistemology. In this talk, Bill will discuss some highlights and lessons learned from his work with a number of students and colleagues, and point to a number of published papers that describe the experiences and findings in more detail. The publications to be discussed are all available on Bill's web site: http://www.orgs-evolution-knowledge.net/Index/PapersandPresentations.htm.

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Developing a biological understanding of organizational knowledge Developing a biological understanding of organizational knowledge Presentation Transcript

  • 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