A Framework for Discovering KM Forces

8/8/2019 A Framework for Discovering KM Forces

1/8Electronic copy available at: http://ssrn.com/abstract=983309

Journal of Knowledge Management Practice, Vol. 8, No. 1, March 2007

A Framework for Discovering KM Forces: The Fifth Element

Khalid SamaraLondon South Bank University

Business, Computing and Information Management

Abstract

This paper is an ongoing research in the area of knowledge management (KM) and evidence-based practice (EBP).

This study reveals that when health care organisations in the UK initiate a KM initiative, their success has been

limited by undervaluing the importance of tacit clinical knowledge (non-codified) in practice to use them in theirdecision-making. This research advocates that one of the key failures of evidence-based health care has been

instigated by clinicians who usually work not with explicit codified knowledge (such as guidelines) but directly with

knowledge in practice (tacit-knowledge). This paper focuses on research evidence, drawing on the work of Nonaka

knowledge creation framework that tacit into explicit knowledge contributes, as a matter of social interaction.

However, the respective model has not granted high flexibility to adjust to changing conditions and has not placed

enough clarity neither on evidence based policies or the requirements to lever the barriers and risks during the

configuration of knowledge creation, which heavily impacts on knowledge transformation. By helping to explain the

reasoning behind this, I would add that a fifth element is required onto the SECI model as a force to clarify the

importance of those context, social, cultural and technological barriers. The extension supports the illumination andstructure clustering of heterogeneous knowledge sources by determining the probable forces and barriers that may

influence a KM gap in the organisation.

Keywords: KM, Evidence Based Practice, SECI model, Tacit and Explicit Knowledge

1. Introduction

Knowledge has both tacit and explicit dimensions such that the integration of knowledge has an

important social component. Knowledge management (KM) is commonly associated with knowledge

engineering, which in itself is a field within artificial intelligence concerned in the advancement of

knowledge-based systems as decision support or expert systems (Jianqiang et al., 2005 and Olszak M C,

et al., 2006) Most notable problems that current KM systems contain is the need to improve in handling

heterogeneity and dispersion of knowledge sources, rich and complex information in facilitating better

knowledge acquisition, codification, generation and transfer of knowledge (Jianqiang et al., 2005,

Wakefield, 2005, Celina 2006 ) This is also highlighted within clinical practice as a significant challenge

in how to fuse collective knowledge and experiences into a KM system on an ongoing basis. This

perspective builds upon and extends the evidence based decision-making view, as the integration of KM

systems and evidence based has always been inseparable and directly inclusive to manage clinical

knowledge. The term evidence based is now used widely (Gabbay and May 2004; Gali N, et al. 2004;

Russel J, et al. 2004; Kawamoto et al., 2005; Gilgun, 2005; Heneghan 2005) Knowledge creation is

often theory driven conceptual diagrams such as the widely accepted model of Knowledge transfer based

on the empirical work of Nonakas SECI matrix (1994, 1995) of knowledge creation. This paper presents

a critic of key empirical aspects of Nonakas SECI model of knowledge creation. The research advocates

that one of the fundamental achievements of Knowledge creation is the assimilation and distribution of

EBP. However, the paper argues that the SECI model does not elaborate the richness required for EBP

nor does it contain the requirements to oversee the barriers and risks of the formation of knowledge.


2/8Electronic copy available at: http://ssrn.com/abstract=983309


This research advocates that the SECI model should be treated as a meta-model in the sense that other

models have and can been built from the SECI model. Nonakas theory of knowledge capturing and

creation is an extension of Michael Polanyi. In Polanyis (1966) theory of knowledge creation tacit

knowledge remains personalised deep rooted in the individual even after knowledge develops into

explicit forms (i.e. guidelines) Once again, this may seem to be a problematic notion and raises the

question of how organisations determine best practice once knowledge is transformed.

2. Know ledge Management and Evidence Based Health Care

The dynamics of knowledge transfer (KT) and of evidence-based policy analysis needs to be re-

examined with the current thinking of health care organisations. Hospitals are large organisations and as

they become larger and more multifaceted what is being studied also becomes more complex internally

as well as externally, hence the need to examine all segments as a whole relationship becomes a critical

process. Furthermore, the health care is continually working towards refining and managing information

overload, and has been extensively examined in various areas of health; dermatology (Grindlay et al.,

2006), neonatal hearing (Moorjani and Fortnum, 2004), and nursing (Hsia T L et al., 2006) The

dissemination of information into knowledge (clinical notes, guidelines) underpins the evaluation of

health needs, together with the development of health strategy and monitoring of progress. Knowledge

management combines and investigates data for forecasting and decision-making. Data is no longer

viewed as a collection of names and amounts; value is placed upon the innovative use and application of

the data as information to become an integral part of a knowledge domain. KM in the healthcare

generally provides two types of support: diagnoses support and management support.

KM provides suggestions on how to manage patients condition. Some of the suggestions may involve

tests that have to be carried out, what medication or treatment should be considered. However,information is complex, there are ambiguities, organisational culture, conflicting interest and

uncertainty. For this reason, knowledge creation lies in a holistic approach bounded by concealed

barriers and as a consequence it becomes necessary to identify those barriers, which has unequivocally

limited health care organisations to translate their core knowledge needs into a long term strategic

decision-making process. There are concerns that information overload is one of the major obstacles

that clinicians have to overcome (Hsia T L et al., 2006) The resulting information overload and joint with

insufficient information management capabilities appear to be among the prime causes of important

information being either overlooked or misinterpreted. These factors; could be contributed by cliniciansthat rely on implicit information as apposed to EBP where knowledge is codified into accurate data

through rigorous testing. It is those rigorous guidelines that lay down the ground rules and disseminates

the fuzzy unstructured sources, in turn providing knowledge that are requisites for the sharing and

collective knowledge of both the practitioner and patient with unique preferences, concerns and

expectations. Gabbay and Le May (2004) stresses that the current core knowledge culture in the health

care is the collectively reinforced, internalised, tacit guidelines practiced between practitioners within

their domain. This form of knowledge transfer has ultimately created barriers in clinical knowledge and

increasing heterogeneity and knowledge deficiencies.


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3. Defining Heterogeneous Know ledge Sources

Heterogeneous knowledge sources are the diverse unconnected knowledge domains that are highly tacit

and virtually inaccessible to other domains dispersed internally (i.e. secondary, primary care) or

externally (i.e. suppliers), of highly specific nature and remains virtually inaccessible to users

representing other sections of the same field. The transformation of tacit knowledge into evidence base

or making evidence base a tacit context is an essential condition for the creation of new knowledge. It is

essential for the accessibility of newly codified knowledge as it makes reusability for further knowledge

and increases the likelihood of knowledge durability, for instance best practice.

4. Nonakas theory of Know ledge Creation

The SECI process and ba together form the dynamic environment where knowledge can be created and

converted (Nonaka, 1994 and Nonaka; Toyama; Konno 2000) Knowledge creation consists of three

elements. (1) A knowledge conversion process, SECI (2) Context knowledge ba (3) Knowledge assets.

All three are needed for knowledge creation. However, knowledge cannot be created from nothing. A ba

environment forms part of the SECI as a stimulus for the concentration of the organisation knowledge

and of the individuals who own and create such knowledge (Nonaka, 2000).

Figure 1. Adapted by Nonaka (1994-1995) SECI model

The following SECI elements in figure 1 are the processes of knowledge creation.

Socialisation is the world where individuals share feelings, emotions, experiences and mental model. Externalisation requires the expression of tacit knowledge and its translation into comprehensible

forms that can be understood by others. Internalisation of newly created knowledge is the conversion of explicit knowledge into the

organisation's tacit knowledge. Combination involves the conversion of explicit knowledge into more complex sets of explicit

knowledge. In this stage, the key issues are communication and diffusion processes and the

systemisation of knowledge.

As one cannot be free from context, social, cultural, technological forces it would seem plausible at this

stage to identify were the forces that determine the output and accuracy of that knowledge source.

More importantly the objective of knowledge codification, generation and transfer is the creation of

evidence based and best practice, which necessitates precision during codification. In the SECI model

there seems to be no theory about emerging forces that unequivocally predicts the development of new

knowledge sources.

Socialisation Externalisation

Combination Internalisation


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In the compound of Nonaka (2000) essential assumption of knowledge creation is the dynamics of

individual and group communication processes. However, the lever for new and codified knowledge is

fused only when those forces and barriers are constantly sieved within the knowledge creation process.

As newly created knowledge sources become operational and part of the knowledge domain there are

existing forces impinging on the evolutionary process of tacit into explicit sources. Therefore, care

should be taken not to underestimate or underemphasize the importance of barriers and the internal or

external forces that may intrude on the process of knowledge creation within an organisation.

Nonakas SECI model describes the requirements of knowledge creation, but overlooks what may impose

that creation itself. Nonaka attempts to describe the individual inside a dynamic process when

transforming tacit into explicit knowledge as individuals become amplified and part of the knowledge

network (Nonaka, 1994,1995) Except the SECI model fails to represent the fundamental and fluid nature

of forces (risks, barriers) that may interrupt the knowledge creation process. Such as in the context of

health care were majority of failures with KM systems to a certain extent has been due to strategic and

organisational structures; those failures have not been theoretically or empirically examined within the

framework of knowledge management. In the health care knowledge is mostly ambiguous and messy

hence, a mechanism, for exemplifying the internal and external forces in knowledge creation is essential.

5. SECI Fifth Element

In figure 2, is an extension of Nonakas SECI model of knowledge creation. In between the elements I

have added forces as a fifth and primary element as part of the knowledge creation process. The

extension allows and easily facilitates the fusion of heterogeneous knowledge sources given that the

forces determine the flow and synthesis of those diverse knowledge sources. Then ultimately the diverse

and unconnected knowledge domains that are highly tacit become accessible to other domains withinthe organisation. As forces are normally constant to return knowledge creation should be viewed as an

iterative process. The fifth element will determine the following forces:

Barriers between the individual and the KM systems (i.e. portals, collaboration tools, ontologys)

Barriers between diverse specialist domains (increasing accessibility to users representing other

sections of the same field)

Evidence-based health care knowledge must stem from both tacit knowledge and codified explicit

knowledge Barriers between the individual and learning enabling environment


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Secondly cluster structure and the diversity of highly complex knowledge sources must be tamed in

order to support the fusion of heterogeneous knowledge sources to (1) enable a stable knowledge

learning environment, (2) identify a KM representation or allocating a KM repository, (3)

increase accessibility between other sections in the organisation and (4) identify the forces

and obstacles for tacit knowledge.

Wicked/Tame

Figure 2.SECI Fifth Element

5. Knowledge Management Framework

The health care unlike other industries is not prone to indulge in high competition or forming strategic

alliances or even prone to indulge into high tech innovative technologies. Unlike the health care majority

of firms are more open to meet the opportunities and threats in the organisations external and internal

environment and have included KM as part of the firms asset therefore utilised and nurtured for further

tactical solutions.

It is extensively reported that the health care in the UK are yet challenging to find ways to improve its

KM strategy as a fundamental part of its clinical manoeuvre especially when this should be exploited

further to improve the implementation of EBP and to decrease the heterogeneity among practitioners

(Andre et al., 2002; Gabbay and Le May 2004; McCaughan 2005; Heneghan 2005) A significant part of

the knowledge exists inside the human mind and the tacit knowledge plays a large role in the health

care processes and can be made explicit only under particular conditions. These conditions must be

applied within certain rules and once these rules are functional we can explore possibilities for KM and

the forces that may impinge upon them.

Socialisation Externalisation

Forces

Internalisation Combination


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It is inevitable as forces and barriers increase the knowledge gap within the health care also increases.

This is due to a number of reasons one which could be encountered by dynamic changes and nature of

the industry itself. In figure 3, the KM framework is a generic conceptualisation of the proposed fifth

element that represents the probable forces and barriers that may influence a KM gap in the

organisation. The strategic health executive seeking to develop an edge to enhance KM can use this

model to better understand the context in which the organisation operates. The framework is meant to

raise questions and facilitate discussion concerning the strategising facets that may or may not be in

place within an organisation.

Figure 3. Knowledge Management Framework (Fifth Element)

6. KM Representation

The forces of technologies and innovation that determine the direction of a firm are the same forces that

direct and govern the health care industry because technologies are rapidly changing forces influencing

the functioning of individual and in turn the organisation. Information technologies enhance efficiency of

decision-making and has the requisites necessary to identify and analyse aspects concerning the

leveraging and codification of knowledge as it heavily directs its focus on the relational aspects of the

user in the product and knowledge development cycle (Williams, 2006) Purposeful information and

knowledge are likely to be tacit sources, and so, the integration of information technology (IT) becomesalso a pivotal enabler to the success of KM to turn highly unstructured research information into

clinical knowledge.

KNOW-HOW

Knowledge domain competence

Expertise, knowledge, skill of KM

Human capital, asset Identify key knowledge

Support towards knowledge communities

KM representation: technologies,knowledge groupware, ontology,knowledge model technologies

KNOWLEDGE TRANSFER

Data management

Information management

Comprehension of tacit/explicitknowledge

LEARNING & MEMORY

Organisational memory

Individuals memory

Learning organisation

Individual learning

CHANGE

Embrace change

Change to knowledge intensiveorganisation

Change to risk knowledge monitoringorganisation

Change towards a robust evidence basedpractice


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Whilst IT has recreated the concept of KM and plays a major part in the heightening and alleviation in

the management of heterogeneous knowledge sources, the key KM challenges facing organisations are

determining what robust KM systems to implement, which user friendly processes and practices to

institute that are not cumbersome (Chinho Lin et al., 2005) It is also understandable that the role of IT

in supporting KM initiatives varies for different categories of organisations (Gosh and Scott, 2005) This

may imply that the knowledge enablers for health care need to support the KM culture, while capturing

best practices and knowledge from clinical work. Collaborative technologies structuring through virtual

systems and purposful action make collabrative technologies particularly appropriate for the context of

KM.

For this reason when developing a system in this area of KM it maybe necessary to rely on systems for

groupware, which provide generic functions. However, knowledge groupware, ontology and web based

DSS may not carry much weight if the KM culture as whole does not maintain the dynamic forces which

shape the direction of the organisation.

7. Conclusion

This paper presented the relationships between the individual action and KM structure, which needs to

be studied as a shared relationship. Moreover, the ability to deliver reliable EBP requires the integration

of both explicit research evidence and non-research knowledge and to determine the forces that impinge

on knowledge creation. The proposed framework helped to identify an extension yet critical element

adapted from Nonakas SECI model. The extension promotes awareness of forces and barriers that may

impinge during the knowledge creation process as key performers within a KMS infrastructure. Also, to

allow the capturing of knowledge without impairing the autonomy of each domain and heterogeneity

involved a high level unified KM framework to support awareness for structure clustering and

sustainability of heterogeneous knowledge sources is needed.

This paper advocates that organisations need to constantly identify KM forces and barriers, as forces are

normally constant to return. These improvements would guide individuals to transform their knowledge

using technologies and to identify key knowledge to create a synthesis, integration and collection of

ideas, to discover and relate them to relevant information by identifying different knowledge sources.

The framework encourages individuals to go through a process of self-learning and develop an

organisation wide interest in KMS. Furthermore, this research is an ongoing study in the context of KM

centred on the UK health care. The initial conceptual model presented in this paper is a generic model

and still in development to be examined specifically surrounding health care organisations.


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A Framework for Discovering KM Forces