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.netEx 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: bhall-u@dis.unimelb.edu.au

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 prototype

Turned 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 propagate

Organizations 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

PeopleProcessPeopleTechnology

infrastructurePeople

People

Process

Infrastructure

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

TS 1TS 2

•••••

TS m

Pn Pn +1EE

TS 1TS 2

•••••

TS m

Pn Pn +1EE

TS 1TS 2

•••••

TS m

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 thoughtExpressed languageComputer memoryLogical artifactsReproduction/Production

Development/Recall

Drive/Enable

Regulate/Control

Inferred logic

Describe/Predict

TestObserve

Existence/RealityWorld 1

World 3The 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

HIGH LEVEL SYSTEM / EN VIRO N M EN T

SYSTEMSYSTEM SYSTEM

SUBSYSTEM S

boundaryconditions,constraints,regulations

FO CAL 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)

Recruitm ent

M aterials

Incom eO bservations

Entropy/W aste

Products

Departures

ExpensesActions

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)

OBSERVATIONPARADIGM

EXTERNAL INFORMATION

CHANGING CIRCUMSTANCES

UNFOLDING ENVIRONMENTAL RESULTS OF ACTIONS

ORIENT

D

DECIDE(Hypothesis)

O

CULTURE PARADIGMS PROCESSES

DNA GENETIC HERITAGE

MEMORY OF HISTORY

INPUT ANALYSIS SYNTHESIS

ACT(Test)

GUIDANCE AND CONTROLPARADIGM

UNFOLDING INTERACTION

WITH EXTERNAL ENVIRONMENT

John 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 CONTENT LINKSRELATIONS

ANNOTA-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 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 …

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 publishing

test and trialtechnical regulatory frameworksetc.

Infrastructure issues

business analysispersonal productivity toolsproduct data, configuration and change management

CAD, 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.