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421-672 Management of Technological Enterprises
Managing Knowledge in Technological Enterprises (I)William P. (Bill) Hall (PhD)Evolutionary Biology of Species and Organizationshttp://www.orgs-evolution-knowledge.net
Ex Documentation and KM Systems AnalystTenix Group Head Office, Williamstown, Vic. 3016(retired July 2007)
National FellowAustralian Centre for Science, Innovation and SocietyMelbourne UniversityUni Office: ICT 5.59, 111 Barry St., CarltonPhone: +61 3 8344 1530 (Mon, Tue, Thurs only)
Email: [email protected]
18 March 2009
Bill's background - an early vision: 'Spruce Goose' (largest aircraft ever made)
My Background
Childhood ambition: aerospace engineeringMajored in physics, but dyslexic with numbersHands on with all generations of computersPhD 1973 Harvard Univ. in evolutionary biologyMigrated to Australia in 1980, & bought a PC prototypeTurned to computer literacy teaching and tech writing:
– Software development & banking through 1989 Joined Tenix 1990 beginning $7 bn ANZAC Ship Project
– Participated in many commercial and eng KM activities through entire design/engineering/production/in-service support cycle
– Retired July 2007 Since 2000 combined practice and fundamental
research in engineering knowledge management
To err is human!
High tech organizations are fallible, because people, processes and products are all fallible!– Major role of management is to minimise errors and
to remedy those made before they propagateOrganizations are complex dynamic systems
– Difference between complex and complicated• Organizations have minds of their own (my research area)• Cannot be predicted, can only be constrained
– Depend on "system of systems" to manage knowledge
– System of systems components include• People• Processes• Infrastructure
Why is knowledge important to the enterprise?
Tech enterprises and engineering products are knowledge intensive– to design– to manufacture– to operate
Errors are minimised by learning and knowing:– what knowledge is needed– who may know the answer– where the explicit knowledge may be found– why the knowledge is important or why it was
created– when the knowledge was last needed or may be
needed in the future– how to apply the knowledge
KM systems in the high-tech enterprise
PeopleProcess
PeopleTechnology
infrastructure
People
Peop
le
Pro
cess
Infra
stru
ctu
re
Organizational knowledge
Leave one of the legs off, and the stool will fall over
What happens when a leg is missing?
Swiss federal Institute of technology in Zurich analysed 800 cases of structural failure in which 504 people were killed, 592 people injured, and millions of dollars of damage incurred– Insufficient knowledge 36%– Underestimation of influence 16%– Ignorance, carelessness, negligence 14%– Forgetfulness, error 13%– Relying upon others without sufficient control 9%– Objectively unknown situation 7%– Imprecise definition of responsibilities 1%– Choice of bad quality 1%– Other 3%
http://www.matscieng.sunysb.edu/disaster/
What happens when a leg is missing?
Sections from Westgate Bridge at Monash Uni's department of Civil Engineering, Clayton
What can go wrong? (most boil down to KM failures)– For example: (Wikipedia is a good place to start)
• Bhophal insecticide plant (India) - many thousands killed• Chernobyl nuclear power plant explosion - hundreds killed• Piper Alpha - 167 killed• Kansas City Hyatt Regency Hotel Walkway Collapse - 114 killed (see also)• Petrobras P36 Offshore Oil Platform Sinking - 11 killed• Three Mile Island Reactor Meltdown - no deaths but major economic loss
– Closer to home• Westgate Bridge - 35 killed, many injured• HMAS Westralia - 4 killed• Longford gas plant - 2 killed (see also)• Sea King Helo Nias Island - 9 killed
What happens when a leg is missing?
And then there are the economic failures!– Cost overruns– Schedule blowouts– Legal actions– Reputational damages– Again, most could be avoided by better KM
Auditor's reports provide good examples– Australian National Audit Office see especially:
• Management of the M113 APC Upgrade Project• Amphibious Transport Ship Project• Management of Major Equipment Acquisition Projects • New Submarine Project• Jindalee Operational Radar Network
Tacit, Implicit and Explicit
HUMAN MEMORY
HAS IT BEENARTICULATED
?
CAN IT BEARTICULATED
?
EXPLICIT
TACIT
YES YES
NO NO
IMPLICIT
DECLARATIVE PROCEDURAL /CONTEXTUAL
"DESCRIBING" "DOING"
Facts &Things
Tasks &Methods
MotorSkills
MentalSkills
From Nickols 2000
What is knowledge? - Michael Polanyi
Michael Polanyi - a scientist turned philosopher– Epistemology: knowledge is personal not objective
• Knowledge is justified true belief• The ultimate authority for deciding the truth of a claim to
know is the individual's subjective (religious) faith and belief
– The concept of "tacit" knowledge• "We can know more than we can tell"• Skill, know-how, working knowledge, and expertise are
inherent in the individual and cannot readily be verbalised
– Much of the KM discipline, following Nonaka and Sveiby, bases its theory almost entirely on Polanyi
• The only knowledge that counts is what is in peoples' heads• If it is explicit, it is only information.
– Stenmark clearly reflects this view, Sveiby is extreme
Michael Polanyi - a scientist turned philosopher– Epistemology: knowledge is personal not objective
• Knowledge is justified true belief• The ultimate authority for deciding the truth of a claim to
know is the individual's subjective (religious) faith and belief
– The concept of "tacit" knowledge• "We can know more than we can tell"• Skill, know-how, working knowledge, and expertise are
inherent in the individual and cannot readily be verbalised
– Much of the KM discipline, following Nonaka and Sveiby, bases its theory almost entirely on Polanyi
• The only knowledge that counts is what is in peoples' heads• If it is explicit, it is only information.
– Stenmark clearly reflects this view, Sveiby is extreme
What is knowledge? - Karl Popper
Karl Popper - a philosopher who studied science– "All life is problem solving"
–Knowledge is solutions to problems– Epistemology summary
• Knowledge is fundamentally based on external reality• The ultimate authority for deciding the truth of a claim to
know is its correspondence with external reality - but....– All claims to know are fallible (Firestone & McElroy 2003)
• Claims to know are cognitively constructed by the entity• Impossible to prove any claim to know is true (or false)
– Any number of favourable tests are falsified by a single failure– But... any falsification can be "immunised" by auxiliary
hypotheses
Popper more appropriate for engineering than Polanyi
What is knowledge?
Popper's evolutionary theory of knowledge
Pn a real-world problem faced by an entity
TS a tentative solution/theory.Tentative solutions are varied
EE a process of error elimination (i.e., selection)
Pn+1 changed problem faced by an entity incorporating a surviving solution
The whole process is iterated
TS1
TS2
•••••
TSm
Pn Pn+1EE
TS1
TS2
•••••
TSm
Pn Pn+1EE
TS1
TS2
•••••
TSm
P Pn+1EE
Knowledge is constructed by living systems TSs may be tacitly embodied in in the structural dispositions of the individual
entity, or TSs may be explicitly expressed in words as a hypothesis subject to intersubjective
criticism Objective expression and criticism lets our theories die in our stead Through cyclic iteration, tested solutions can approach reality
iteration
Where can knowledge be found?
Popper's three worlds
EnergyThermodynamics
PhysicsChemistry
Biochemistry
Cyberneticself-regulation
CognitionConsciousness
HeredityRecorded thought
Expressed languageComputer memoryLogical artifacts
Reproduction/Production
Development/Recall
Drive/Enab
le
Reg
ulate/Control In
ferr
ed lo
gic
Des
crib
e/Pr
edic
t
TestObserve
Existence/RealityWorld 1
World 3
The world ofexplicit/ objective knowledge
Produced /evaluated byworld 2processes
World 2
World of mental orpsychological states and processes, subjective experiences
Emerges from world 1processes.
Tacit organismic/personalknowledge
Polanyi's epistemology of personal knowledge encompassed within Popper's World 2
What are organisations?
A level of complexity in a hierarchically complex world
Emergentproperties
• Synthesis cannot predict higher level properties
• Behaviour isuncomputable
• Boundary conditions & constraints select
• Analysis can explain• Stanley Salthe (1993) Development and Evolution: Complexity and Change in Biology
HI GH LEVEL SYSTEM / ENVI RONMENT
SYSTEMSYSTEM SYSTEM
SUBSYSTEMS
boundaryconditions,
constraints,
regulations
FOCAL LEVEL
Possibilities
initiatingconditions
universallaws
"material -causes"
The organisation is a self-sustaining complex system in the environment
Processes (which may be complex subsystems in their own rights) are necessary responses to imperatives:
– Survival– Self-maintenance of the processes themselves
Constraints and boundaries(laws of nature determine what is possible)
The organisation's imperatives and goals
Hall, W.P. 2006 Emergence and growth of knowledge and diversity in hierarchically complex living systems.
ProcessesProcesses
Energy (exergy)
Recruitment
Materials
I ncome
Observations
Entropy/Waste
Products
Departures
Expenses
Actions
How is knowledge acquired, used and improved?
Achieving strategic power depends critically on learning more, better and faster, and reducing decision cycle times compared to competitors. See http://www.belisarius.com.
AO
OBSERVE
(Results of Test)
OBSERVATION
PARADIGMEXTERNAL
INFORMATION
CHANGING CIRCUMSTANC
ES
UNFOLDING ENVIRONMENTAL
RESULTS OF ACTIONS
ORIENT
D
DECIDE
(Hypothesis)
O
CULTURE PARADIGM
S PROCESSES
DNA GENETIC
HERITAGE
MEMORY OF HISTORY
INPUTANALYSIS SYNTHESI
S
ACT
(Test)
GUIDANCE AND CONTROL
PARADIGM
UNFOLDING INTERACTION
WITH EXTERNAL
ENVIRONMENTJohn Boyd's OODA Loop process
PROCESS
PEOPLE
Implementing OODA system of systems in the organization
CULTURE & PARADIGMS
INFRASTRUCTURE
“CORPORATE MEMORY”
INPUT
ANALYSIS SYNTHESIS
PEOPLEPEOPLE
GENETIC HERITAGE
DATA CONTENTLINKS
RELATIONSANNOTA-
TIONS
OBSERVE DECIDE, ACT
DOCS RECORDS
© William P. Hall
Building and maintaining an adaptive KM architecture to meet organisational imperatives
DRIVERS ENABLERS &
IMPEDIMENTS PEOPLE PROCESS
STRATEGY DEVELOPMENT
STRATEGICREQUIREMENTS
OBSERVATIONOF CONTEXT & RESULTS ORIENTATION & DECISION
ENACTEDSTRATEGY
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 …
Limits to knowledge and organisation
Rationality in making decisions (key part of OODA loop)“A decision making effort that exhausts all potentially relevant [knowledge] in order to make decisions in a transparently logical and objective fashion.” (Else 2004)
Organizations and people have limited capability (subsystem laws)
– Bounded rationality (Simon 1957). Models of Man Limits on decision making caused by limits on costs, human abilities, time, technology, and availability of [knowledge].
Boundaryless Careers - Arthur & Rousseau (1996)– People belonging to organisations are not owned by them– People have careers outside of any one organisation
Limits of Organization - Arrow (1974 - see Else 2004)– As limited by bounded rationality of individual people– As limited by organisational structure, governance, etc
Limits to knowledge and organisation
Concept of satisficing (Simon 1957)– “Satisficing is an alternative to optimization for cases where
there are MULTIPLE and COMPETITIVE objectives in which one gives up the idea of obtaining a "best" solution. In this approach one sets lower bounds for the various objectives that, if attained, will be "good enough" and then seeks a solution that will exceed these bounds. The satisficer's philosophy is that in real-world problems there are too many uncertainties and conflicts in values for there to be any hope of obtaining a true optimization and that it is far more sensible to set out to do "well enough" (but better than has been done previously).”
Engineers also have an ethical responsibility to say NO!– When none of the alternatives are good enough– When risks are too high– Dithering and no decision is also a decision
Limits to knowledge and organisation
Governance– Steven Else (2004):
• [G]overnance [is] the act of affecting decision making and oversight of a high-value program through the identification and appointment of a top team of talented, subject matter experts to provide dedicated, long-term vision, strategy and direction for the program. In general, governance comprises the traditions, institutions and processes that determine how power is exercised, how stakeholders are given a voice, and how decisions are made on issues of enterprise-wide concern.
Bounded rationality and limits to organisation:Steve Else (2004)
Steven Else (2004) Organization Theory and the Transformation of Large, Complex Organizations -- Donald H. Rumsfeld and the U.S. Department of Defense, 2001-04, PhD Thesis, Denver University– people are limited - 'bounded rationality' (H. Simon 1955,
1957)– best decision the organisation can strive for is 'just good enough',
or 'satisficing' rather than optimising ; (K. Arrow 1974)
My take:– Overcentralisation of decision making is a recipe for disaster
• bounded rationality puts upper limit on observation• overloaded central decision maker loses touch with reality
– Orgs must delegate decisions to periphery as they grow• Need to balance between ability to observe and make effective
decisions• The management style and management of knowledge both must
change as the organisation grows in order to maintain balance
People issues
recruitmenttraining and career developmentfacilitation and incentivesnetworking and community buildingregistering skillsmapping and tracking knowledgesharing and transferring knowledgeetc.
Process issues
overall project managementqualification and biddingsimulation and modellingdesign and stage reviewschange managementproblem managementdocument authoring, production and
publishingtest and trialtechnical regulatory frameworksetc.
Infrastructure issues
business analysispersonal productivity toolsproduct data, configuration and change
managementCAD, text authoring and simulation systemsworkflow enactmentplanning and controlproduction management and trackingauditproduct engineering and maintenance support
Learning from our mistakes as managers
Introduction to Part II of the Columbia Accident Investigation Board Report:
Many accident investigations do not go far enough. They identify the technical cause of the accident, and then connect it to a variant of “operator error” – the line worker who forgot to insert the bolt, the engineer who miscalculated the stress, or the manager who made the wrong decision. But this is seldom the entire issue. When the determinations of the causal chain are limited to the technical flaw and individual failure, typically the actions taken to prevent a similar event in the future are also limited: fix the technical problem and replace or retrain the individual responsible. Putting these corrections in place leads to another mistake – the belief that the problem is solved.
http://www.nasa.gov/columbia/home/CAIB_Vol1.html
Issues
Failure to appropriately manage knowledge relating to any of the above issues (and others!) can lead to project failure.
This week’s tutorial will discuss some project failures following on from poor knowledge management.
