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Note KM performance measurement

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Knowledge Management Performance measurement
Knowledge management (KM) is one of the emerging topics of academic and
professional discourse in many fields of knowledge, including cognitive sciences,
sociology, management science, computer science, information science , knowledge
engineering, artificial intelligence, and economics ([Dalkir, 2005], [Martin, 2008],
[Sinotte, 2004], [Rowley, 2007] .The importance of managing knowledge is also
getting more and more attention in all types of organizations, including businesses,
government bodies, research institutes, Non-Governmental Organizations (NGOs),
and international development and financial institutions ([Blair, 2002] and [Chua,
2009]), since beginning of nineties, it is recognized as a significant factor in gaining a
competitive advantage in our competitive business environment [Nonaka and
Takeuchi, 1995].
Evidently, there is a tendency by the different professions interested in KM, as well as
different researcher to present and interpret what constitutes KM from their own
perspective and their own profession ([Dalkir, 2005], [Ekbia and Hara, 2007], [Hlupic
et al., 2002], [Jashapara, 2005], [Liao et al., 2004], [McInerney, 2002], [Sarrafzadeh
et al., 2006] and [Widén-Wulff et al., 2005]). Consequently, developments in KM are
influenced by the different professions interested in knowledge ([Dalkir, 2005],
[Jashapara, 2005], [Martin, 2008], [Rowley, 2007], [Sarrafzadeh et al., 2006] and
[Sinotte, 2004]). This has resulted in different theories as well as different models,
definitions, terminology but among them and commonly, KM can be defined as a
multi-disciplined approach for achieving organizational objectives by making the best
use of knowledge which is divided into tacit and explicit knowledge.
This knowledge may be viewed in term of culture , structure and technology and
that’s compose the Three pillar of KM which were named by Minonne as :
Organizational learning management OLM , Organizational knowledge Management
OKM and Intellectual capital management ICM [Minonne and Turner , 2010].
Maintaining these pillars is a powerful means to improve the level of the whole
performance of an organization. Thus, companies should invest in knowledge
management projects in order to amplify the creation, the sharing and the transfer of
explicit and tacit knowledge. Several techniques can be considered to develop and
implement knowledge management and organizational memory systems, according
to the type of organization, its needs, and its culture as well as the nature of
knowledge to be capitalized. From this need , emerge several topics and object of
research that should contribute to this field development ,among them we can list :
Knowledge Management Systems &Applications , knowledge-based approaches,
Knowledge Representation and Ontology , Knowledge Sharing and Exchange
,Knowledge Acquisition and Evolution, Uncertainty and Vagueness in Knowledge
Modeling , Knowledge Integration ,Agent-based Approaches to Knowledge
Management , KM for Collaboration and Decision Support ,Knowledge Management
Maturity Models , Case-based Reasoning for KM (CBR) , Collective and
Collaborative Intelligence ,Knowledge Management and Social Computing , KM in
Web2.0 and the Semantic Web , Knowledge Visualization , Knowledge and
Business Process Modeling , Evaluation and Measurement of Required Knowledge ,
KM in Collaborative Software Development
One of the most challenging issues on the field of KM is that of measurement, « that
which doesn’t get measured, doesn’t get managed » [Redman, 1998],
Organizations success are becoming increasingly dependent on knowledge that its
strategic success rely on the effective management of its knowledge assets, for this
an effective way of assessing performance is a must , [Turner and JacksonCox,2002], and Metrics that measure the performance of KM integration are
needed , to justify KM initiatives , budgets as well as guiding future strategic firms .
On establishing these set of KPI and metrics , should resist to the temptation to
focus on what is measurable « Tangibles assets » to outcomes that meet really
organizational need, such as intellectual capital ,which are more likely to represent
KM effectiveness dimension than efficiency [Sveiby , 2010 , intangibles assets]
A common starting point of each measurement method is the categorization of
different forms of KM integration and especially for intangibles assets which
represent a high difficulty to measure.
One of the most cited model for KM integration, identify four complementary
integration forms, these are: Cultural Integration, Organizational integration,
Methodical integration and procedural integration [Turner and Minonne 2009]
Then coming methods to define pertinent targets as well as setting appropriate
quantitative or qualitative key performances indicators, this task have the difficulty to
come with appropriate targets according to strategy, and choose between
reductionistic/additive measures to combinatorial ones for definition of the whole KM
index performance.
Over the last thirty years , many framework and measuring system were introduced ,
from Balance scoreboard system by Kaplan and Norton (1992), the most widely
system taking account of non financial data , to knowledge management Monitor
KM2 framework , last years are seeing a new breed of measurement system on
which intellectual capital is center stage .
On our Work, we will try to make the inventory of main relevant measurement
methods and systems developed for evaluating KM performance, our study will focus
on the efficiency of each method with a comparative and critical sight
Having the novelty and emergency of this field, We aim beyond this paper , to
constitute a reference paper that incorporate all works regarding this subject, that
provide to scholar , practitioner and researcher a global view of state and progress of
the measurement of Knowledge management performance , with the added value of
concision , and improvement axis for each of studied system.
References:
Dalkir, 2005 K. Dalkir, Knowledge management in theory and practice, Elsevier Butterworth-Heinemann,
Burlington (2005).
Martin, 2008 B. Martin, Knowledge management, C. Blaise, Editor, Annual review of information science and
technology (ARIST), vol. 42, Information Today, Inc., Medford, NJ (2008), pp. 371–424.v
Sinotte, 2004 M. Sinotte, Exploration of the field of knowledge management for the library and information
profession. Libri, 54 (2004), pp. 190–198.
Rowley, 2007 J. Rowley, The wisdom hierarchy: Representations of the DIKW hierarchy. Journal of Information
Science, 33 2 (2007), pp. 163–180.
Chua, 2009 A.Y.K. Chua, The dark side of knowledge management initiatives. Journal of Knowledge
Management, 13 4 (2009), pp. 32–40.
Blair, 2002 D.C. Blair, Knowledge management: Hype, hope, or help?. Journal of the American Society for
Information Science and Technology, 53 12 (2002), pp. 1019–1028.
Ikujiro Nonaka and Hirotaka Takeuchi,1995, The Knowledge-Creating Company: How Japanese Companies
Create the Dynamics of Innovation (New York: Oxford University Press, 1995)
Ekbia and Hara, 2007 H.R. Ekbia and N. Hara, The quality of evidence in knowledge management research:
Practitioner versus scholarly literature. Journal of Information Science, 34 1 (2007), pp. 1–17.
Jashapara, 2005 A. Jashapara, The emerging discourse of knowledge management: A new dawn for information
science research?. Journal of Information Science, 31 2 (2005), pp. 136–148.
Hlupic et al., 2002 V. Hlupic, A. Pouloudi and G. Rzevski, Towards an integrated approach to knowledge
management: ‘Hard’, ‘soft’ and ‘abstract’ issues. Knowledge and Process Management, 9 2 (2002), pp. 90–102.
Liao et al., 2004 S.S. Liao, J.W. He and T.H. Tang, A framework for context information management. Journal of
Information Science, 30 6 (2004), pp. 528–539.
McInerney, 2002 C. McInerney, Knowledge management and the dynamic nature of knowledge. Journal of the
American Society for Information Science and Technology, 53 12 (2002), pp. 1009–1018.
Sarrafzadeh et al., 2006 M. Sarrafzadeh, B. Martin and A. Hazeri, LIS professionals and knowledge management:
Some recent perspectives. Library Management, 27 9 (2006), pp. 621–635.
Widén-Wulff et al., 2005 G. Widén-Wulff, D. Allen, E. Macevičiūtė, C. Moring, R. Papik and T. Wilson, Knowledge
management/information management, Leif Kajberg, Leif Lørring, Editors , European curriculum reflections on
library and information science education, The Royal School of Library and Information Science, Copenhagen
(2005), pp. 121–130.
Minonne, C and Turner, G.,2010 “Evaluating Knowledge Management Performance” Electronic Journal of
Knowledge Management Volume 7 Issue 5 (pp583 - 592), available online at www.ejkm com
Turner, G. and Jackson-Cox, J. (2002), "If management requires measurement how may we cope with
knowledge?", Singapore Management Review, Vol. 24, No. 3, pp 101-111
Sveiby, K.E. (2010), "Methods for measuring intangible assets", [online],
www.sveiby.com/articles/IntangibleMethods.htm, accessed 24th April 2010
Turner, G. and Minonne, C. (2009), "Measuring the effects of knowledge management practices", Conference
proceedings of the 10th European Knowledge Management Conference, Vicenza, Italy, September..
Notes:
"Introduction to Knowledge Management". Unc.edu.
http://www.unc.edu/~sunnyliu/inls258/Introduction_to_Knowledge_Management.html. Retrieved 15 January
2010.
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