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Towards a Technological, Managerial, and Socio-Technical Well-Balanced KM Initiative Strategy Within Organizations Michel Grundstein MG Conseil, Nogent sur Marne, France LAMSADE Paris Dauphine University, Paris, France mgrundstein@mgconseil.fr Abstract: In this paper, following a constructivist approach that is deeply rooted in our pragmatic experience within a large industrial Company, we argue that Knowledge is not manageable as if it was data or information. This leads to suggest KM as <strong>the</strong> management <strong>of</strong> activities and processes that help organization’s support and business processes enhancing <strong>the</strong>ir capabilities to utilize and create knowledge, more than focusing on knowledge itself. This change <strong>of</strong> paradigm induces to conceive a technological, managerial, and socio-technical well-balanced KM initiatives strategy. This pragmatic vision needs thinking about <strong>the</strong> architecture <strong>of</strong> an Enterprise’s Information and Knowledge System (EIKS), which must be a basis <strong>of</strong> discussion during <strong>the</strong> strategic orientation phase <strong>of</strong> a general KM initiative. Keywords: Knowledge Management (KM), individual’s tacit knowledge, commensurability <strong>of</strong> individual’s interpretative frameworks, strategic KM Initiative orientations phase, information tacit and explicit knowledge process (DITEK process) 1. Introduction In <strong>the</strong> foreword <strong>of</strong> <strong>the</strong> book untitled “The New Age in Knowledge” (O’Dell and Hubert 2011) Larry Prusak describes some <strong>of</strong> <strong>the</strong> main principles focused on knowledge management at <strong>the</strong> beginning days (p. xi): i) Knowledge is a fixed pool, a collection <strong>of</strong> resources that can be measured and used by standard management techniques; ii) Technology is <strong>the</strong> key tool to unlock <strong>the</strong> value <strong>of</strong> this resource – more technology, <strong>the</strong> better; and iii) Individuals are <strong>the</strong> critical unit <strong>of</strong> analysis in working with knowledge – <strong>the</strong> more productive <strong>the</strong> individual is <strong>the</strong> more knowledge is being used. He concludes: “It is now clear in hindsight that <strong>the</strong>se principles were developed with information in mind, not knowledge, and that <strong>the</strong>y were not at all suitable to working with such elusive intangible. It is because <strong>of</strong> <strong>the</strong>se ideas that many knowledge management efforts ran into problems and that <strong>the</strong> whole subject began to fade in <strong>the</strong> minds <strong>of</strong> busy executives.” However, although it does not always get <strong>the</strong> expected outcomes when put at work in organizations, <strong>the</strong> positivist paradigm <strong>of</strong> KM, influenced by computer science and information technology, is <strong>the</strong> most implicit recognized paradigm by researchers and practitioners in KM. From our viewpoint, this paradigm needs to be enlarged to a general view resting on a constructivist paradigm In this paper we put down background <strong>the</strong>ory and assumptions; notably, we introduce <strong>the</strong> concept <strong>of</strong> “commensurability <strong>of</strong> interpretative frameworks,” and we propose an empirical model (DITEK) that attempts to describe <strong>the</strong> transformation process from data to information and from information to tacit and explicit knowledge. Then, we suggest a constructivist paradigm <strong>of</strong> KM within organizations based on three fundamental postulates. This leads to envisage new KM perspectives and to sketch out <strong>the</strong> architecture <strong>of</strong> an enterprise’s information and knowledge system (EIKS). Finally, we propose a wellbalanced KM initiative strategy within organizations 2. Background <strong>the</strong>ory and assumptions 2.1 Research motivations, method, and objectives Our research follows a constructivist paradigm that is deeply rooted in our pragmatic experience in <strong>the</strong> real field. As a practitioner having to manage deployment <strong>of</strong> innovative technologies (such as computer aided design, knowledge based systems, and o<strong>the</strong>rs) in large companies just when <strong>the</strong>se technologies were conceived into universities and laboratories, we observed that we always needed to elaborate a model with socio-technical perspectives, which could be used as a pattern <strong>of</strong> reference for all stakeholders in order to engender <strong>the</strong> essential learning process that leads people to appropriate and use <strong>the</strong>se technologies. Later on, when becoming Associate Researcher in <strong>the</strong> domain <strong>of</strong> KM, we perceived <strong>the</strong> lack <strong>of</strong> general model <strong>of</strong> KM that integrates socio-technical perspectives. This point <strong>of</strong> view is <strong>of</strong>ten disregarded when considering <strong>the</strong> technical approach <strong>of</strong> KM, 200
Michel Grundstein although hundred <strong>of</strong> frameworks can be found in <strong>the</strong> literature (CEN-CWA 14924-1, 2004). As a practitioner we always had to consider <strong>the</strong> constructivist paradigm that underlies <strong>the</strong> creation <strong>of</strong> knowledge, and consequently KM approach. As a researcher we always had to be confronted with <strong>the</strong> positivist paradigm that most <strong>of</strong>ten considers knowledge independently <strong>of</strong> its links with action, and <strong>the</strong> context <strong>of</strong> organizations. Thus, our researches, notably in <strong>the</strong> domain <strong>of</strong> KM, are continuously oriented towards a well-balanced use <strong>of</strong> positivist and constructivist paradigms within organizations. 2.2 The dominant positivist paradigm <strong>of</strong> KM Numerous authors analyzed <strong>the</strong> notions <strong>of</strong> data, information and knowledge. Let us quote notably Davenport and Prusak (1998, pp.1-6), Sena and Shani (1999), Takeuchi, and Nonaka, (2000), Amin, and Cohendet, (2004, pp. 17-30), Laudon and Laudon, (2006, p. 416). Besides, Snowden (2000,) makes <strong>the</strong> following syn<strong>the</strong>sis: “The developing practice <strong>of</strong> knowledge management has seen two different approaches to definition; one arises from information management and sees knowledge as some higher-level order <strong>of</strong> information, <strong>of</strong>ten expressed as a triangle progressing from data, through information and knowledge, to <strong>the</strong> apex <strong>of</strong> wisdom. Knowledge here is seen as a thing or entity that can be managed and distributed through advanced use <strong>of</strong> technology…The second approach sees <strong>the</strong> problem from a sociological basis. These definitions see knowledge as a human capability to act (pp. 241-242).” The dominant positivism paradigm <strong>of</strong> KM is implicit in <strong>the</strong> DIKW (Data-Information-Knowledge- Wisdom) hierarchy model. This model induced numerous computers and information researches. For example, (Rowley, 2007) revisiting <strong>the</strong> DIKW hierarchy by examining <strong>the</strong> articulation <strong>of</strong> <strong>the</strong> hierarchy in a number <strong>of</strong> widely read textbooks in information systems and knowledge management preferably published in 2003 and later, noted that “<strong>the</strong>re is a consensus that data, information and knowledge are to be defined in terms <strong>of</strong> one ano<strong>the</strong>r, although data and information can both act as inputs to knowledge; <strong>the</strong> tangle <strong>of</strong> concepts can be explored at two levels – <strong>the</strong> relationship between data and information, and <strong>the</strong> relationship between information and knowledge p.174);” and she raised <strong>the</strong> question: “Is <strong>the</strong>re a sharp divide between data, information and knowledge, or do <strong>the</strong>y lie on a continuum with different levels <strong>of</strong> meaning, structure and actionability occurring at different levels (p. 175)?” More recently, (Muller and Maasdorp 2011) point out <strong>the</strong> dominance <strong>of</strong> <strong>the</strong> DIK model in information science. They have three conjectures as to why knowledge management practitioners and authors prefer <strong>the</strong> DIK model. The first one concerns information <strong>the</strong>ory background, <strong>the</strong> second one is about simplicity, and <strong>the</strong> third one rests on accumulative worldview. Their ideas are closely akin to ours. Let’s quote some <strong>of</strong> <strong>the</strong>ir conjunctures: “<strong>the</strong> first possible explanation for <strong>the</strong> dominance <strong>of</strong> <strong>the</strong> DIK model in KM is that it is an effect <strong>of</strong> background in information <strong>the</strong>ory or communication <strong>the</strong>ory <strong>of</strong> <strong>the</strong> practitioner or <strong>the</strong> author; <strong>the</strong> second conjecture is that simplicity counts in management and that this has <strong>the</strong> effect <strong>of</strong> privileging a <strong>the</strong>oretical position that is clearly linked to a working and productive legacy in information system but more importantly, clears up <strong>the</strong> messy situation <strong>of</strong> exactly understanding <strong>the</strong> notion <strong>of</strong> knowledge in organizations; <strong>the</strong> third conjecture is painted on an even broader canvas. If one has a worldview that is cumulative and sees <strong>the</strong> world as consisting <strong>of</strong> innumerable little bits (now not in <strong>the</strong> technical sense) <strong>of</strong> matter that all add up to <strong>the</strong> while by <strong>the</strong> process <strong>of</strong> accumulation and simple organization and categorization, <strong>the</strong>n a data information knowledge model would make sense…That means that a mechanistic and positivist worldview is to be found at <strong>the</strong> base <strong>of</strong> <strong>the</strong> easy acceptance <strong>of</strong> <strong>the</strong> DIK model.” In fact, we think that, beyond all <strong>the</strong>se studies, we have to position our thoughts in <strong>the</strong> contextual field where <strong>the</strong> notion <strong>of</strong> data, information, and knowledge are used: in our case, <strong>the</strong> field <strong>of</strong> enterprises and more generally organizations. That leads to conceive how <strong>the</strong> transformation process should be envisaged using <strong>the</strong> concept <strong>of</strong> commensurability <strong>of</strong> interpretative frameworks highlighted by (Tsuchiya 1993). 2.3 The concept <strong>of</strong> commensurability <strong>of</strong> interpretative frameworks 2.3.1 Creation <strong>of</strong> individual’s tacit knowledge Our approach is built upon <strong>the</strong> assumption emphasized by Tsuchiya concerning knowledge creation ability. He states, “Although terms ‘datum’, ‘information’, and ‘knowledge’ are <strong>of</strong>ten used 201
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Proceedings <stron
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Contents Paper Title Author(s) Page
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Paper Title Author(s) Page No. Main
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Paper Title Author(s) Page No. Know
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Preface These proceedings represent
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TU Dortmund, Germany, ); Wing Bun L
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William Halal is Prof</stro
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Evgeny Blagov has obtained a specia
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science and mathem
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George Majdalany is a PhD candidate
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Joyce Nesamani Simson is a PhD cand
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Manpower Discipline Based on Knowle
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Peyman Akhavan et al. brains, knowl
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Peyman Akhavan et al. showed that o
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Peyman Akhavan et al. appropriate l
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Peyman Akhavan et al. sources for c
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Attitudes Towards Changes and Organ
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Ruth Alas et al. During the
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Professional inter
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Ruth Alas et al. Table 4: Correlati
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Research was supported by ETF Grant
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Rivadávia Correa Drummond de Alvar
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5. Conclusions Rivadávia Correa Dr
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Toward a Meta-Synthe</stron
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Xiaomi An et al 2.3 Reasons for dev
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Xiaomi An et al PTC works closely w
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Xiaomi An et al The first is an adm
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Xiaomi An et al policy reflections
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Figure 1: Transmission gear Marko A
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Marko Anzelak et al. knowledge basi
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Marko Anzelak et al. 72% recognise
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Marko Anzelak et al. virtually all
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Gabriel Prananingrum Aryanindita an
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Rita Babiliūtė and Kęstutis Kri
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Knowledge Management, Cultural Know
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Leonard Barnett and Edward Carter 2
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Leonard Barnett and Edward Carter p
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Leonard Barnett and Edward Carter p
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Leonard Barnett and Edward Carter d
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Impact of Knowledg
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Bob Barrett shorter product life-cy
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Bob Barrett 6. Concept of</
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Bob Barrett Brown, J.S. and Duguid
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Aurilla Aurelie Bechina and Eli Hus
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Lorne Booker et al. Knowledge is us
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Figure 1: Business Valuation Knowle
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3.4 Practitioner knowledge market L
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4. Implications Lorne Booker et al.
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Strategic Thinking Dimensions in Em
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Constantin Bratianu et al. shows <s
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Constantin Bratianu et al. Academy
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Constantin Bratianu et al. cases wi
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Constantin Bratianu et al. Pinker,
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Delio Ignacio Castañeda and Sandra
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Quality in Teacher Education: A Sys
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Rajendra Chetty The mechanism <stro
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Academic leadership Rajendra Chetty
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Rajendra Chetty There must be a re-
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Developing Personal Knowledge Manag
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Thirathep Chonmait
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Thirathep Chonmait
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The Relationship Between Knowledge
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Samuel Kai Wah Chu et al. A knowled
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Samuel Kai Wah Chu et al. negative
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Samuel Kai Wah Chu et al. Questionn
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Samuel Kai Wah Chu et al. few done
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Value Creation Through Collaborativ
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Ridha Derrouiche et al. level for e
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Ridha Derrouiche et al. best, <stro
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Ridha Derrouiche et al. experience
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Ridha Derrouiche et al. Of course,
Page 171 and 172: Organizational Learning and Transfo
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Page 179 and 180: Knowledge Acquisition and Sharing:
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Page 187 and 188: Eva Eckenhofer cou
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Page 191 and 192: Eva Eckenhofer The
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Page 195 and 196: 1.2 Intellectual capital and innova
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Page 233 and 234: Intellectual Property Valuation Dec
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Page 239 and 240: Acknowledgements Hezlin Harris et a
Page 241 and 242: Managing an Assessment Process <str
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Page 245 and 246: Shaheed Hartley Table 3: OEQ respon
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Page 257 and 258: Eli Hustad and Aurilla Aurelie Bech
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Nurul Indarti Arrow, K. J. (1969).
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Organizational Learning in Pr<stron
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Brigita Janiunaite et al. learn and
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Brigita Janiunaite et al. given dif
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Brigita Janiunaite et al. empowered
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Brigita Janiunaite et al. A statist
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Brigita Janiunaite et al. learning
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Balancing the Ince
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Giedrius Jucevičius safeguard and
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Giedrius Jucevičius nature <strong
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Giedrius Jucevičius motivating fac
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Giedrius Jucevičius Ghosh, T. (200
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Palmira Juceviciene and Vyda Mozuri
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Robertas Jucevicius relations shoul
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Robertas Jucevicius do not know whe
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Robertas Jucevicius and innovation
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Robertas Jucevicius Lawton Smith, H
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Annukka Jyrämä et al. knowledge c
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Annukka Jyrämä et al. Respondents
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Annukka Jyrämä et al. various cit
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Annukka Jyrämä et al. example hea
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Managing Information Overload - Tea
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Harri Ketamo conceptual structure a
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Harri Ketamo limited to YouTube, Fl
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Harri Ketamo Figure 8: Visualizatio
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Farmers’ Knowledge Management in
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2.1 Farmer knowledge Le Nguyen Doan
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Le Nguyen Doan Khoi days needed for
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Le Nguyen Doan Khoi dosage. Moreove
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Le Nguyen Doan Khoi use homemade in
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Developing Human Capital through Ne
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Eric Kong organisation as individua
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Eric Kong As described by Tosey and
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Eric Kong Craft, A. (2001) "Neuro-l
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Sophie Le Bellu and Benoit Le Blanc
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Results Sophie Le Bellu and Benoit
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Pornpen Lertthasanawong and Nopasit
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2. Literature review Ya-Hui Ling 2.
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Ya-Hui Ling action of</stro
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Intellectual Capital Intellectual C
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Ya-Hui Ling Hitt, M.A., Hoskisson,
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Maksim Maksimovic et al paper prese
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Maksim Maksimovic et al 4. Lean kno
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Maksim Maksimovic et al of<
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Maurizio Massaro and Andrea Moro <s
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Maurizio Massaro and Andrea Moro Pr
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Maurizio Massaro and Andrea Moro hi
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Maurizio Massaro and Andrea Moro Si
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Helen Mitchell and Dennis Viehland
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Figure 1: KMS Framework for collabo
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Mohd Zali Mohd Nor et al. Ano<stron
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Mohd Zali Mohd Nor et al. Table 4:
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Mohd Zali Mohd Nor et al. KQ8 provi
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Maria Cristina Morariu economy and
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Table 1: Literature review summary
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Maria Cristina Morariu ATO = Turnov
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4.2 Correlation analysis Maria Cris
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4.3 Regression analysis Maria Crist
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Table 13: Regression analysis_M6 Mo
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The Arrival of <st
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Bertrand Pauget and Ahmed Dammak Mo
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Bertrand Pauget and Ahmed Dammak no
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Bertrand Pauget and Ahmed Dammak th
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Bertrand Pauget and Ahmed Dammak Sa
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Wannapa Pipattanawong et al. cannot
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Wannapa Pipattanawong et al. 3.2 Do
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Wannapa Pipattanawong et al. Moreov
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The Dark Side of S
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Siwarit Pongsakornrungsilp vans, ro
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Siwarit Pongsakornrungsilp Kreng Ja
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Siwarit Pongsakornrungsilp Lave, J.
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