A MODEL FOR KNOWLEDGE MANAGEMENT

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1 Ry Stephen Mrum A MODEL FOR KNOWLEDGE MANAGEMENT IN AN ARCHITECTURAL ENTERPRISE Submitted in partial fulfilment f the requirements fr the Master f Design Management Degree. UNITEC Institute f Technlgy, New Zealand March 2005 Page 1

2 ABSTRACT Knwledge Management deals with the critical prcesses f transfrming the knwledge f individuals int grup knwledge, and the knwledge f grups int rganisatinal knwledge. T put knwledge int actin, we must understand the prcesses thrugh which managers can embed knwledge in rganisatinal systems, prcesses, and values. This dissertatin lays ut a cmprehensive creative structure fr Knwledge Management systems in a hierarchy f levels, rienting each level t wrk structure in the Architectural prfessin -- s that a clear picture f integratin pssibilities is presented. Cultural barriers, technical implementatin, pprtunities and examples are explred t illustrate the verall structure. Sme prcesses and techniques used in the Architectural prfessin are analysed, including the generatin, visualisatin, capture, and sharing f ideas and infrmatin. This dissertatin will explre the attitudes, knwledge and skills essential fr effective Knwledge Management (in the Architectural prfessin in particular). It is prpsed that these are cntained within the cntextual realms f Purpse, Peple, Resurces, Lcatin, Prcess and Practice. All these elements have aspects that are qualitative and intangible r are subject t mre precise definitin and measurement. T explit KM as a strategic asset, an enterprise must excel in all six realms. Althugh many f the principles described herein are applicable t general Knwledge Management, this dissertatin fcuses n general Architectural practice. The Knwledge Base in Architecture is enrmus, s, fr the purpse f this dissertatin, it will be mapped ut in brad utline - t the secnd r third level nly. The authrs understanding is that Explicit Knwledge is bjective and factual, and encmpasses the data which can be catalgued, filed and srted and this knwledge can be captured and shared by practical and tangible means Tacit Knwledge is encmpassed by man's intellect and includes the accumulatin f knwledge, experience, bservatins, discvery and interactin and it is acquired and transferred by experiencing, ding and participating. T attempt t devise a system that can cntain all knwledge present and future, is impssible, s it is necessary t design a prcess that cntinues t grw, prmtes reuse, imprves cnstantly, and avids redundancy. T achieve this, the infinite vlume f knwledge has t be prcessed thrugh a filter r frmula which is reiterative, nt static, and this is the essence f Knwledge Management. The wrking mdel fr Architectural KM prpsed in this dissertatin is a creative apprach t the prblem and the essential questin cnfrnted is hw t design and implement an effective KM prcess fr an architectural enterprise. The wrk end with the initiatin stages f the intrductin f the mdel, develped as a result f this research, int a specific architectural practice. Page 2

3 INDEX Table f Cntents ABSTRACT 2 TABLE OF CONTENTS 3 INDEX 3 1. INTRODUCTION DEFINITIONS OF KM THE ESSENTIAL RESEARCH QUESTION KM DEVELOPMENT KNOWLEDGE MANAGEMENT THROUGH HISTORY LANDMARKS IN KNOWLEDGE DEVELOPMENT CURRENT KM PRACTICE CURRENT KM THEORIES CULTURAL ASPECTS OF KM BEHAVIOUR AND WORK PROCESS IN KM THE POLITICS OF KM THE TECHNOLOGY OF KM THE CAPITAL VALUE OF KM THE NEED FOR KM IN ARCHITECTURE A KM CONCEPTUAL ONTOLOGY 36 Page 3

4 4.1 CULTURAL METAPHORS TOWARDS A CONCEPTUAL ONTOLOGY FOR KM THE NATURE OF KNOWLEDGE NEURAL NETWORKS IN ARCHITECTURAL KM THE FRACTAL MODEL IN CONTEXT IMPLEMENTATION OF THE FRACTAL MODEL THE ARCHITECTURAL WORK PROCESS ENTERPRISE WORK DYNAMICS PROJECT WORK BREAKDOWN STRUCTURE (WBS) KM CONTEXTUAL REALMS A KNOWLEDGE MANAGEMENT MODEL ARCHITECTURAL WBS DATABASE FIELDS KNOWLEDGE BASE STRUCTURE & DELIVERY KM MODEL TEMPLATES/ SEEDS KNOWLEDGE MANAGEMENT TOOLS THE KNOWLEDGE BASE SEED TOOLS OF EFFECTIVE KNOWLEDGE MANAGEMENT DIGITAL TOOLS FOR KNOWLEDGE MANAGEMENT INFORMATION COLLECTION, STORAGE & ACCESS IMPLEMENTATION OF THE MODEL KM STRUCTURE AND ACCESS 95 Page 4

5 7.7 CASE STUDY CONCLUSION ADDENDA 102 LIST OF TABLES AND ILLUSTRATIONS Fig Future Wisdm(See Reference)...17 Fig Reasns fr Adpting KM (See Reference)...18 Fig Knwledge Management Benefits...37 Fig The Metcalfe Curve...38 Fig Fractal Images generated by Ry Mrum (using iteratins f the Mandelbrt Fractal)...40 Fig The Mandelbrt Fractal...40 Fig Aperidic Neural Netwrks...41 Fig The Glden Rectangle (graphic by the Authr)...42 Fig Metaphrs (Surce Astrin Architects)...42 Fig An iteratin f a Phenix Fractal. Nte hw the reiterative pattern repeats in sub-branches alng the main spiral path...44 Fig The 3-dimensinal nature f the Fractal frmula...46 Fig An iteratin f the Phenix fractal...47 Fig Netwrked Reslutin f the KM Seed...48 Fig Graphic images f Pittsburgh, PA...51 Fig A Mdel f the Wrk Dynamics f an Architectural Enterprise...52 Fig Wrk Breakdwn Structure...53 Fig Prject WBS...54 Fig Knwledge Management Cntextual Realms...55 Fig An iteratin f the Carr 1625 fractal frmula (public dmain) Fig An iteratin f the Mandelbrt Fractal...57 Fig Representatin f the KM Mdel...61 Page 5

6 Fig The KM Hierarchical database structure...63 Fig The Architectural Wrk Structure Matrix...63 Fig The Digital Dashbard a fractal Representatin f the structure (cnstructed with Fractal PC and adapted)...67 Fig Tree representatin f the Data Base File Structure...67 Fig The Fractal GUI representatin f the Administrative Structure...69 Fig An example f dcument cding in the Administratin database structure Fig The Fractal GUI representatin f level A Fig.6.09 Prject Website: Mathena Cultural Arts Center Princetn, West Virginia...71 Fig The Fractal GUI representatin f Level A Fig Design Develpment Spiral (frm Inquiry by Design Jhn Zeisel (1981)) and Phenix Fractal cmparisn Fig The Fractal GUI representatin f Level A Fig The Fractal GUI representatin f Level A Fig The Fractal GUI representatin f Level A Fig The Fractal GUI representatin f Level A Fig The Fractal GUI representatin f Level A Fig The Fractal GUI representatin f the CSI level...82 Fig The defining factrs in determining the Knwledge Base Seed...84 Fig Diagram illustrating the cncepts f the Intranet and the Extranet Fig. 7.03The Infrmatin Seed -- An iteratin f the Fractal Mdel...91 Fig The Cntent Management Seed...92 Fig Illustratin f a Database Management System Architecture...93 Fig Cmputer Aided Engineering in the Cnstructin Industry...93 Fig The Phenix Fractal and the 7-step prcess...94 Fig The ETB hme page...98 Acknwledgements I wish t thank the fllwing peple fr their assistance and advice during the preparatin f this dissertatin: Patti J Mrum, my wife, fr her patience and advice. David Rees, my UNITEC supervisr, fr his guidance. Page 6

7 1. Intrductin Bruce E. Blackmer (FAIA), in the American Institute f Architects Jurnal f Architecture (Nv. 2004) 1, stated that we live in an era when success is measured mre by what we knw than by any ther means. As knwledge management is applied, understanding reaches higher levels, data transfrms frm explicit int tacit knwledge and we becme mre valuable t ur firms, ur clients and ur cmmunities. Knwledge Management (KM) is mre than just anther industry buzzwrd, as it has existed frm the day man first used his emerging sentience t educate, develp, utilise, and pass n the fruits f learning, human intelligence and experience. Knwledge has been stred, managed and passed n in many frms thrughut histry. In the mdern Internet Age, it als includes (but is nt dminated by) the sphisticated use f the latest sftware and electrnic tls and the applicatin f the Internet tgether with the cncepts f Grupware, Intranet, Extranet, Business Intelligence, Data Markets, Message Cllabratin, E-Cmmerce, E- Business, Search Engines -- amngst thers. The effective use f Knwledge Management assets in an enterprise can empwer wrkers t make crrect and speedy decisins t gain cmpetitive advantage. It is imprtant, that KM is defined within the cntextual realms f Purpse, Peple, Resurces, Lcatin, Prcess and Practice using parameters that are qualitative and intangible and als subject t mre precise definitin and measurement. T explit KM as a strategic asset, an enterprise must excel in all six realms. 1.1 DEFINITIONS OF KM The field f Knwledge Management is diverse and has many definitins. In the peer reviewed Harvard Business Review n Knwledge Management 2, Peter Drucker states that Infrmatin is Data endwed with relevance and purpse. Cnverting Data int Infrmatin thus requires Knwledge. A cmmn (but, in the writer s pinin, fallacius) definitin states Knwledge management technlgies deliver the right infrmatin t the right persn at the right time. (Authr unknwn) This implies that human intelligence and experience can be reduced t technlgical slutins. It becmes necessary t differentiate between Explicit Knwledge, which is bjective and factual, and Tacit Knwledge, which is mre challenging t capture as it is based n a cmplex accumulatin f knwledge, experience, bservatins, discvery and interactin. The frmer can be captured and shared via infrmatin technlgy, in wrds, diagrams and numbers -- while tacit knwledge is acquired and transferred by experiencing, ding and participating. Page 7

8 Ygesh Malhtra 3, funder, chairman and CKO f the Brint Institute in Frt Lauderdale, Flrida, USA, gruped varius interpretatins f KM int three paradigms: The Inputs-Driven Paradigm, which cnsiders Infrmatin Technlgy and KM as synnymus. The Prcessing-Driven Paradigm f KM, which has its fcus n best practices, training and learning prgrams, cultural change, cllabratin, and virtual rganisatins. The Outcmes-Driven Paradigm f KM which has its primary fcus n business perfrmance. Here are examples f KM definitins which fall int these categries: RESOURCE OR INPUT DRIVEN KNOWLEDGE MANAGEMENT "Knwledge management systems (KMS) refer t a class f infrmatin systems applied t managing rganizatinal knwledge. That is, they are IT-based systems develped t supprt and enhance the rganizatinal prcesses f knwledge creatin, strage/retrieval, transfer, and applicatin." (Alavi and Leidner, ) Knwledge management is the generatin, representatin, strage, transfer, transfrmatin, applicatin, embedding, and prtecting f rganizatinal knwledge. (Schultze & Leidner ) "Fr the mst part, knwledge management effrts have fcused n develping new applicatins f infrmatin technlgy t supprt the capture, strage, retrieval, and distributin f explicit knwledge." (Grver and Davenprt, ) Knwledge has the highest value, the mst human cntributin, the greatest relevance t decisins and actins, and the greatest dependence n a specific situatin r cntext. It is als the mst difficult f cntent types t manage, because it riginates and is applied in the minds f human beings." (Grver and Davenprt, 2001) "Knwledge management uses cmplex netwrks f infrmatin technlgy t leverage human capital. The integratin f user-friendly electrnic frmats facilitates inter-emplyee and custmer cmmunicatin; a central requirement fr successful KM prgrams." (emarketer ) "In cmpanies that sell relatively standardized prducts that fill cmmn needs, knwledge is carefully cdified and stred in databases, where it can be accessed and used--ver and ver again by anyne in the rganizatin." (Hansen and Nhria, ) PROCESS DRIVEN KNOWLEDGE MANAGEMENT "KM entails helping peple share and put knwledge int actin by creating access, cntext, infrastructure, and simultaneusly reducing learning cycles.. (Massey et al., ) "Knwledge management is a functin f the generatin and disseminatin f infrmatin, develping a shared understanding f the infrmatin, filtering shared understandings int degrees f ptential value, and string valuable knwledge within the cnfines f an accessible rganizatinal mechanism." (CFP fr Decisin Sciences special issue n Knwledge Management, 2002) "In cmpanies that prvide highly custmized slutins t unique prblems, knwledge is shared mainly thrugh persn-t-persn cntacts; the chief purpse f cmputers is t help peple cmmunicate." (Hansen and Nhria, 1999) Knwledge Management (KM) definitin: Knwledge management, r KM, is the prcess thrugh which rganizatins generate value frm their intellectual prperty and knwledge-based assets. KM invlves the creatin, disseminatin, and utilizatin f knwledge. 10 PRACTICE OR OUTCOME DRIVEN KNOWLEDGE MANAGEMENT "Knwledge Management refers t the critical issues f rganizatinal adaptatin, survival and cmpetence against discntinuus envirnmental change. Essentially it embdies rganizatinal prcesses that seek synergistic cmbinatin f data and infrmatin prcessing capacity f infrmatin technlgies, and the creative and innvative capacity f human beings." (Malhtra 1998a, ) New cmpetencies and instruments fr cmmunicatin and netwrking have been made pssible by the Digital Age, althugh sme may cntend that the majr impact f the digital age has been t increase the Page 8

9 quantity and nt the quality f data. Carl Hildebrand, in her article Des KM = IT 12 expldes the myths that infrmatin technlgies can deliver, stre and distribute human intelligence and experience. She states that the fact f infrmatin in a database desn't ensure that peple will see r use the infrmatin and that mst f knwledge management technlgy cncentrates n efficiency and cnsensus with ratinal and static data withut cntext. In such systems, there is n accunting fr renewal f existing knwledge and creatin f new knwledge. Knwledge Management deals with the prcesses f transfrming the knwledge f individuals int grup knwledge, and the knwledge f grups int rganisatinal knwledge. T effectively utilize knwledge, we must understand the prcesses thrugh which knwledge can be structured, managed, and accessed in rganisatinal systems, prcesses, and values. KM is a prcess that prmtes a cllabrative and integrative apprach t the creatin, capture, rganisatin, access, and use f infrmatin assets, including the tacit knwledge f peple. The best learning ccurs in exchanges between peple and is enhanced, but nt cntrlled, by the establishment f databases, methds fr measuring intellectual capital, building crprate libraries, building intranets, sharing best practices, installing grupware, leading training prgrams, leading cultural change, fstering cllabratin and creating virtual rganizatins. The cncept f treating rganisatinal knwledge capital as a valuable asset has been ppularised by many mdern management and rganisatin specialists. In rder t remain cmpetitive, rganisatins are advised that they must effectively and efficiently lcate, create, capture, and share their rganisatin's knwledge and have the ability t use that knwledge and expertise t reslve specific prblems and develp pprtunities. Traditinal perfrmance measures are nt sufficient t gauge perfrmance and guide rganisatins in the mdern rapidly changing and cmplex business sciety. If perfrmance measurement is linked t strategy in an rganisatin, it must measure perfrmance in ways that prmte bth psitive results and reflect past experience and perfrmance. With the abve in mind, the definitin f Knwledge Management develped by the writer fr this treatise is as fllws: KM is a reiterative business management practice delivering tacit and explicit knwledge t the right persn at the right time using creative cnceptual and technlgical tls and techniques t capture, rganise, transfer and maintain a dynamic knwledge base. Page 9

10 1.2 THE ESSENTIAL RESEARCH QUESTION This dissertatin fcuses n hw the discipline f Knwledge Management can be utilized t becme a creative and dynamic asset fr an architectural enterprise. This leads t the fllwing essential questin: Hw can an apprpriate mdel, suited t architectural practitiners be develped and hw this mdel can be placed in cntext? This can be brken dwn int the fllwing elements: Definitin f requirements fr KM in an Architectural Enterprise. Analysis f essential tls and skills are required fr KM in Architecture. Methds f implementatin f KM in an architectural enterprise. Systems that can be adpted t keep the system dynamic and avid stagnatin. 1 Blackmer, Bruce E. (FAIA). Knwledge Defined and Delivered. The AIA Jurnal f Architecture (Nv. 2004). 2 Drucker, Peter F. The cming f the New Organizatin in the Harvard Business Review n Knwledge Management. Harvard Business Schl Press. Cpyright Malhtra, Ygesh Integrating Knwledge Management Technlgies in Organizatinal Business Prcesses. Accepted fr publicatin in the Jurnal f Knwledge Management (Emerald) Special Issue n Knwledge Management and Technlgy, Q3, Alavi, M. and Leidner, D. Review: Knwledge Management and Knwledge Management Systems: Cnceptual Fundatins and Research Issues. MIS Quarterly, v. 25, n1, Mar. 2001, p Alavi and Drthy E. Leidner. 5 Schultze, U. and Leidner, D. Studying Knwledge Management in Infrmatin Systems Research: Discurses and Theretical Assumptins. MIS Quarterly, Vl. 26, N. 3, September 2002, pp Grver, V. And Davenprt, T.H. General Perspectives n Knwledge Management: Fstering a Research Agenda. Jurnal f Management Infrmatin System. Summer 2001, Vl. 18, N. 1, pp emarketer. Knwledge Management: Executive Brief. Page 10

11 URL: 8 Hansen, Mrten T. and Nhria, Nitin. What's Yur Strategy fr Managing Knwledge Harvard Business Review, Mar-Apr 1999, pp Massey, A.P., Mntya-Weiss, M.M. and Hlcm, K. Re-engineering the custmer relatinship: leveraging knwledge assets at IBM. Decisin Supprt Systems vl. 32, n. 2, December 2001, pp Malhtra, Y., Is Knwledge Management Really an Oxymrn? Unravelling the Rle f Organizatinal Cntrls in Knwledge Management, In D. White (Ed.), Knwledge Mapping and Management, Hershey, PA: Idea Grup Publishing, 1-13, 2002b. URL: 12 Hildebrand, Carl Des KM=IT Sept. 15, 1999 Issue f CIO Enterprise Magazine. Page 11

12 2. KM Develpment This sectin deals with a literature review in the frm f a study f the develpment f KM thrugh histry up t mdern times in an attempt t identify leaders and trends in this field -- frm the ancient philsphers t mdern times. 2.1 KNOWLEDGE MANAGEMENT THROUGH HISTORY A key element in knwledge management has been hw t deal with the limitatins f capacity and the rganisatin f an infinite knwledge resurce. Philsphers and thinkers have, thrugh the ages, pndered n the nature and extent f mankind s search fr knwledge. These thinkers include Aristtle, Plat, Dante, Grtius, Pufendrf, Russeau, Berkeley, Hume, Hbbes, and Jhn Lcke. The fllwing deals with sme f the principles espused by these great men. THE NATURE OF KNOWLEDGE Explicit Knwledge is bjective and factual, and encmpasses the data which can be catalgues, filed and srted and this knwledge can be captured and shared by practical and tangible means Tacit Knwledge is encmpassed by man s intellect and includes the accumulatin f knwledge, experience, bservatins, discvery and interactin and it is acquired and transferred by experiencing, ding and participating. The ratinalists (frm Descartes n) had claimed that the fundatins f human knwledge are fund in Reasn - i.e. ideas innate in human nature. Jhn Lcke (1690) had questined this assertin and cncluded instead that knwledge was merely the cmplex cmbinatin f ideas that had been acquired thrugh the senses. In An Enquiry Cncerning Human Understanding, David Hume 13 ( ) presented the simple query: What are the limits f human knwledge? He divided prpsitins between tw types: thse which are "relatins f ideas" (analytic) and thse which are "matters f fact" (synthetic). The first type is acquired withut knwledge f anything in the wrld but slely frm reasning; the secnd type is acquired nly thrugh experience. Gerge Berkeley (1710) refuted the divisin between qualities: ur knwledge is nt pictures f reality but pictures, perid. They have n necessary cnnectin t reality and merely exist in ur head. Thus, Berkeley denied cmpletely Lcke's thery that knwledge was merely the cmplex cmbinatin f ideas that had been acquired thrugh the senses. Knwledge cmmunities can be defined as grups f peple with a shared passin t create, use, and share new knwledge fr tangible business purpses 14. The medical prfessin was the first f the knwledge cmmunities as far back as the time f Hippcrates, fllwed by the sciences as they develped thrugh the Renaissance. Page 12

13 The authrs J. J. O'Cnnr and E. F. Rbertsn 15 write: - Aristtle (384 t 322 BC) was nt primarily a mathematician but made imprtant cntributins by systematising deductive lgic. He wrte n physical subjects and sme parts f his Analytica psterira shw an unusual grasp f the mathematical methd. Primarily, hwever, he is imprtant in the develpment f all knwledge. Aristtle prmted the sharing f knwledge, as the authr J. Barnes 16 writes: - His wn researches were carried ut in cmpany, and he cmmunicated his thughts t his friends and pupils, never thinking t retain them as a private treasure-stre. He thught, indeed, that a man culd nt claim t knw a subject unless he was capable f transmitting his knwledge t thers, and he regarded teaching as the prper manifestatin f knwledge. Benjamin Jwett, in his translatin f Plat s The Republic 17 stated that Plat was perhaps the greatest metaphysical genius whm the wrld has seen; and in him, mre than in any ther ancient thinker, the germs f future knwledge are cntained. Plat indicates that there is benefit in the sharing f knwledge Prithee, friend, d nt keep yur knwledge t yurself; we are a large party; and any benefit which yu cnfer upn us will be amply rewarded. Plat speaks f fur classes f gds (human activity) and he places Justice and Knwledge in the highest class. A "guild" (als spelled "gild") was, in medieval times, an assciatin f craftsmen r merchants, frmed fr mutual aid and prtectin and t further their wn prfessinal interests. The medieval guilds were f tw types, the merchant guilds and the craft guilds. Mdern prfessinal rganizatins can be likened t ancient guilds... the keepers and prtectrs f knwledge. The best knwn f guilds is that f the Freemasns, which has survived thrugh the ages, and the imprtance f prtecting prfessinal knwledge was well understd in such rganisatins, althugh the Freemasns have nw lst their direct relatinship t the building prfessins. This secretiveness develped thrugh the need t safeguard the knwledge f craft skills (r knwledge capital) fr their wn members. KNOWLEDGE MANAGEMENT METHODOLOGY Dante said, Knwledge dth cme f learning well retained, Unfruitful else. 18 which reinfrces the fact that knwledge is useless unless it can be structured and stred fr re-use and imprvement. Thmas Hbbes ( ), in Leviathan, 19 writes f the reiterative quality f cnsequences and dependencies f Knwledge Management; And whereas sense and memry are but knwledge f fact, which is a thing past and irrevcable, science is the knwledge f cnsequences, and dependence f ne fact upn anther; by which, ut f that we can presently d, we knw hw t d smething else when we will, r the like, anther time: because when we see hw anything cmes abut, upn what causes, and by what manner; when the like causes cme int ur pwer, we see hw t make it prduce the like effects. Page 13

14 THE COMPLEXITY OF KNOWLEDGE SEARCH PATTERNS It will becme evident later in this dissertatin hw strngly search patterns influence KM and hw the cncept f knwledge dividing int branches can frm the basis f a Knwledge Management methdlgy. Reiteratin takes place when, metaphrically speaking, the utcmes (leaves) becme nutrients fr the knwledge netwrk (branches/ rts). An understanding f this is imprtant when cnsidering the essential questin psed by this dissertatin. Jean-Jacques Russeau 20, ( ) wrte f the intricacy f knwledge search patterns: When a persn has any real taste fr the sciences, the first thing he perceives in the pursuit f them is that cnnectin by which they mutually attract, assist, and enlighten each ther, and that it is impssible t attain ne withut the assistance f the rest. Thugh the human understanding cannt grasp all, and ne must ever be regarded as the principal bject, yet if the rest are ttally neglected, the favurite study is generally bscure. I was cnvinced that my reslutin t imprve was gd and useful in itself, but that it was necessary I shuld change my methd; I, therefre, had recurse t the encyclpaedia. I began by a distributin f the general mass f human knwledge int its varius branches, but sn discvered that I must pursue a cntrary curse, that I must take each separately, and trace it t that pint where it united with the rest; thus I returned t the general synthetical methd, but returned thither with a cnvictin that I was ging right. 2.2 LANDMARKS IN KNOWLEDGE DEVELOPMENT Here fllws a brief tur thrugh histry t bring us t the present. The Dark Ages are generally cnsidered t be a time f technlgical and intellectual stagnatin, but Mnasteries remained repsitries f knwledge, cpying, and preserving knwledge in bund and illuminated bks fr psterity. Thurw 21 writes that when we hear that term, we are inclined t think f a perid in histry during which little innvatin ccurred; during which knwledge remained stagnant, dgmatic, and dctrinaire; and during which barbarians destryed the glry f the Rman Empire and its technlgical and engineering marvels yet Thurw cnsiders that n such perid ever really existed. Lacey and Danziger 22 write that knwledge in the year 1000 rarely came frm bks nly a small minrity culd read and they retained data withut the help f filing cabinets r mechanical strage systems. They had learned everything by bserving and imitating. and by memrising everything they needed t survive and enrich their lives. Alfred the Great, wh came t the thrne f Wessex in 871, cmmissined schlars t start the first histry f England and the English language, the Angl-Saxn Chrnicle, which recrded events great and small thrugh the centuries up t the year 1154, when the last unfinished (mysteriusly terminated) entry was Page 14

15 made. 23 This recrding f knwledge became ne f England s unifying factrs. The s-called dark ages were cming t an end and Eurpe began reaching a perid f relative certainty when knwledge culd be supprted by authenticated fact. The fifteenth century saw the inventin f printing frm mvable type by Gutenberg. The painstaking handcpying f bks in the Middle Ages gave way t the printing press and a flurishing f literature. The faster spread f knwledge in the Renaissance may never have been pssible withut Gutenberg's inventin and this was as significant t the spread f knwledge as are the digital inventins f mdern times. The era called the Renaissance spanned the 17th and 18th centuries and this perid saw significant changes in the way Western man viewed his wrld. The flwering f knwledge in the Renaissance was aided by the rediscvery f classical knwledge and manifested itself in the arts and sciences -- leading t the restratin f a high view f man and his intellectual capacity. Jhn Adams ( ) wrte: The preservatin f the means f knwledge amng the lwest ranks is f mre imprtance t the public than all the prperty f all the rich men in the cuntry. As civilisatin mved thrugh the Industrial revlutin twards the mdern age, a significant landmark in KM was the wrk f Charles Babbage 24 ( ), British mathematician and inventr, wh designed and built mechanical cmputing machines n principles that anticipated the mdern electrnic cmputer. The digital age had its birth with the develpment f the cmputer, frm the mechanical Difference Engine by Babbage, thrugh a lineage that included the ABC by J.V. Atansff, ENIAC and the persnal cmputer. This age advanced as Tim Berners-Lee 25 invented the infrmatin superhighway knwn as the Web 26, which allws anyne with a cmputer and brwser t use the Internet. It was his dream t devise a means t link all the infrmatin stred n cmputers everywhere s that there wuld be a single glbal infrmatin space. T turn his dream int reality, in 1980 he wrte a prgram that allwed cmputers t share infrmatin- t link t each ther- and in less than ten years this became the Wrld Wide Web pening up a vast resurce fr the disseminatin f knwledge. It has becme a gal in business practice t devise means f managing and prcessing this vast resurce f knwledge and the term Knwledge Management has begun t be recgnised as a specialist discipline. Sectin Tw will nw deal with Current Knwledge Management Practice with reference t current writings and recgnised mdern leaders in KM. Page 15

16 13 Hume, David. An Enquiry Cncerning Human Understanding (Public Dmain). 14 Page 6 -- Btkin, Dr Jim. Smart Business: hw knwledge cmmunities can revlutinize yur Cmpany. (The Free Press, NY) O'Cnnr J. J. and Rbertsn E. F. Aristtle -- Article Internet surce: 16 Barnes, J. Aristtle. (Oxfrd Press), Bk II f The Republic by Plat. (427 t 347 BC) -- translated by Benjamin Jwet Publisher - EurekaMultimedia's Classic Wrks f Literature (2002) 18 Alighieri, Dante. The Divine Cmedy: Paradise. translated by Henry F. Cary (Public Dmain). 19 Hbbes, Thmas ( ) Leviathan (Public Dmain). 20 Russeau, Jean-Jacques. The Cnfessins f Jean-Jacques Russeau Bk I. [ ] translated by W. Cnyngham Mallry. (Public Dmain). 21 Thurw, L. C. The Future f Capitalism: Hw Tday's Ecnmic Frces Will Shape Tmrrw's Wrld. (St Lenard s, Australia: Allen and Unwin) Lacey, Rbert and Danziger, Danny. The Year (G. K. Hall and C. Thrndike, Maine) (ISBN ). 23 This is based n the dcument published as The Angl-Saxn Chrnicle (Everyman Press, Lndn,) (Public Dmain in USA). Internet surce: 24 Internet surce: 25 Internet develpment infrmatin btained frm Hbbes' Internet Timeline v7.0 by Rbert H'bbes' Zakn - Zakn Grup LLC -- Internet surce: 26 Investigatin int cmputer netwrking technlgy began in 1969 as a prject fr the Pentagn s Defence Advanced Research Prjects Agency (DARPA). Page 16

17 3. Current KM Practice Sectin 3 is a literature review f current KM practice, identifying a few current philsphies in rganisatinal strategy and thinking. The fcus f this treatise is n the Architectural enterprise, but is necessary t identify general appraches in KM management thery and practice in general terms befre narrwing the field. 3.1 CURRENT KM THEORIES Fig Future Wisdm(See Reference 27 ) Russel Ackff, alng with Emery (1972) characterised human systems as purpseful systems whse members are als purpseful individuals wh intentinally and cllectively frmulate bjectives and are parts f larger purpseful systems. M.I.T.'s Nichlas Negrpnte 28 describes the difference between physical prducts and infrmatin prducts in the digital age as the difference between mving atms arund (physical prducts such as cars and cmputers) and mving bits arund (electrnic prducts such as financial analyses and news bradcasts). Prducers f bits can use the Internet t reduce their delivery times t practically zer. Prducers f atms still can't beam the physical bjects thrugh space, but they can use bit speed--digital crdinatin f all kinds--t bring reactin time dwn dramatically. Davenprt 29 (1997) suggested that the elements f knwledge management shuld include Culture, Behaviur, Plitics, and Technlgy. Capital value is als an intrinsic part f the KM prcess and warrants separate mentin. It is under the fllwing headings that current practice is nw studied -- with reference t writings by a number f prfessrs in the field f Knwledge Management Culture Values f and beliefs abut KM; benefits and pitfalls that can affect KM. Behaviur and wrk prcesses - Hw peple actually use KM, Skills, and Attitudes. Plitics Leadership, Cmmunicatin, Management rles, Relatinships Technlgy - KM management systems, Tls, Perfrmance, and Strategy. Capital Value Infrmatin Ownership, Security, Knwledge-Based Ecnmy, Knwledge Sharing, and Intellectual Prperty -- Legalities and Ethics Knwledge Cmmunities the value f Cmmunities f Practice Page 17

18 3.2 CULTURAL ASPECTS OF KM Cultural Acceptance Knwledge Wrkers can be defined as peple wh wrk mainly with knwledge intangibles rather than with their hands t prduce value. Frances Hribe, President f VisinArts, Inc. in Canada, specialises in assisting rganisatins with the human and rganisatinal sides f investing in Intellectual Capital. In her bk Managing Knwledge Wrkers 30, she states that Organisatins that can harness the intellectual capital f knwledge wrkers will be successful in the infrmatin age. The driver f success in New Ecnmy is knwledge, with the fld f infrmatin cming at light speed. Fig Reasns fr Adpting KM (See Reference 31 ) 3.3 BEHAVIOUR AND WORK PROCESS IN KM Implementatin Strategies Thmas A. Stewart, in his bk The Wealth Of Knwledge, bserved that knwledge wrk des nt necessarily fllw the linear path that physical labur ften des and here lies much f the difficulty in understanding the reiterative nature f KM. search patterns. In Knwledge Management Strategies 32, Jerry Hneycutt prvides guidelines fr IT decisin makers and prvides an infrmatin fundatin fr tp cmpany management. Digital technlgy is changing the fundatins f hw business is cnducted tday and hw it will be cnducted tmrrw. Three fundamental elements f all businesses -- the relatinships between businesses and their custmers, infrmatin flw between wrkers and departments within businesses, and business prcesses themselves are underging rapid transfrmatin. Page 18

19 Cultural barriers within rganisatins are imprtant factrs t cnsider in the implementatin f any prject. Mst impediments t KM adptin are "prcess, culture and behaviur based," says Mark Tucker, senir analyst with The Delphi Grup, a research and cnsulting firm in Bstn, Mass. "There's never been a technlgy invented t make smene d smething they're nt culturally inclined t d. 33 " In the white paper Overcming the Cultural Barriers t Sharing Knwledge, 34 the questin addressed is -- What makes a culture that supprts knwledge sharing? The answer ffered is: Share knwledge t slve practical business prblems; execute KM in a way that matches the style f the rganisatin; build n the cre values f the rganisatin; and many mre. Thus, t create a knwledge-sharing culture, ne shuld make a visible cnnectin between sharing knwledge and practical business gals, prblems, r results. It is far mre imprtant t match the verall style f rganisatin than t directly cpy the practices develped by best-practice rganisatins. Withut Purpse, KM has n value and withut prper cnsideratin f Peple (influenced by culture) KM becmes irrelevant. In The Knwing-Ding Gap: Hw Smart Cmpanies Turn Knwledge int Actin 35, the authrs Pfeffer and Suttn cnfrnt the challenge that cmpanies nw face in their battle t turn knwledge int prductive actin. They identify the causes f The Knwing-Ding Gap and explain hw t clse it. The bk is a useful hw-t guide fr managers lking t make changes. Yet, as Pfeffer and Suttn pint ut, it takes mre than reading their bk r discussing their recmmendatins. It takes actin. The authrs questin why, when market fr business knwledge is bming, and cmpanies lking t imprve their perfrmance pur billins f dllars int training prgrams, cnsultants and executive educatin, there are s many gaps between what firms knw they shuld d and what they actually d? Why d s many cmpanies fail t implement the experience and insight they ve wrked s hard t acquire? Firms that turn knwledge int actin avid the smart talk trap. Cmpanies that act n their knwledge eliminate fear, ablish destructive internal cmpetitin, measure what matters, and prmte leaders wh understand the wrk peple d in their firms. They give many examples f cmpanies that have vercme this knwledge-actin gap and they are highlighted in the bk. The authrs describe the mst cmmn bstacles t actin---such as fear and inertia---and prfile successful cmpanies that vercme them. Other case studies include thse cmpanies that tried, but failed, and yet ther rganisatins that managed t avid the gap frm the beginning. Cmpanies which Pfeffer and Suttn say d it right include: General Electric, the Men s Wearhuse, SAS Institute, Suthwest Airlines, Tyta, and British Petrleum. Chris Argyris and Dnald Schön s 1978 bk Organizatinal Learning despite being written 26 years ag, remains relevant in tday s Digital Age. They write abut the persnal transfrmatin that precedes individual learning and enables rganisatinal learning and the differences between Page 19

20 knwledge used fr understanding, and knwledge used fr actin. T bridge the gap between rganisatinal learning thery and practice, we need t fcus nt nly n implementable validity but als, as Argyris ntes in an interview, n usability. In an interview with Chris Argyris cnducted by Mary Crssan 36, he emphasised the need fr bth managers and educatrs (frm business schls as well as the crprate wrld) t fcus n the engine f inquiry the capacity t think. He suggests that what is needed is nt nly a willingness t engage the ideas, but a capacity t think critically and wrk thrugh the prblems. She states that Argyris is hpeful that infrmatin systems, because they can make data available t supprt prductive thinking, may serve as a catalyst fr change. She ges n t state that the sceptic might disagree: withut critical thinking t drive the analysis and interpretatin, infrmatin systems will simply reinfrce single-lp learning and prcesses. Reiterative, as ppsed t single lp Prcesses in KM becmes a strng theme later in this dissertatin the metaphr f an upward infinite spiral as ppsed t a clsed circle. This reiterative Prcess is prmted as being a slutin t ne the cre prblems facing KM, that f stagnatin. Creativity The authrs Kulpuls and Frappal 37 (1999) cnnect knwledge and creativity in suggesting that creativity is the applicatin f knwledge in cmpletely new ways. Thurw, in Building Wealth 38 (1999) stated that, Any sciety that values rder abve all else will nt be creative, but withut the right degree f rder, creativity disappears as if int a black hle. This idea supprts ne f the cre principles prmted in this treatise, Creative Prcess -- that t be effective, KM must be free f creative restrictins, but it requires rder and Prcess t be effective. Skills and Attitudes Francis Hribe 39 (1999) states that as the amunt f knwledge available grws by leaps and bunds, wrkers must gain new skills t master a particular niche. Knwledge capital is nly f value if it cntinues t grw and enterprises need t encurage cntinuus learning t meet changing needs. The elements f Resurce management, Prcess and Practice shuld therefre have built-in renewal r reiterative systems which encurage and reinfrce the change/ grwth dynamic. 3.4 THE POLITICS OF KM Leadership in KM Page 20

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