A
Framework for Discovering KM Forces: The Fifth Element
Khalid
Samara, London South Bank Uiversity
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
Keywords: Knowledge
Management, Evidence Based Practice, SECI Model, Tacit Knowledge, 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; Olszak and Ewa, 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) 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 Le May, 2004; Galiè et al, 2004; Russel 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 Nonaka’s SECI matrix (Nonaka, 1994; Nonaka and Takeuchi, 1995) of knowledge creation. This paper presents a critic of key empirical aspects of Nonaka’s 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.
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. Nonaka’s theory of knowledge capturing and creation is an extension of Michael Polanyi. In Polanyi’s (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. Knowledge 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 extemsively examined in various areas of health e.g. dermatology, (Grindlay et al, 2006), neonatal hearing (Moorjani and Fortnum, 2004), and nursing (Hsia 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 patient’s 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 and organisational cultural issues, plus 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 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 clinicians that 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.
3. Defining Heterogeneous
Knowledge 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. Nonaka’s
Theory Of Knowledge Creation
The SECI process and ba together
form the dynamic environment where knowledge can be created and converted (Nonaka, 1994; Nonaka et al, 2000a
and 2000b) 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, 2000a and 2000b).
Figure 1.
Adapted From Nonaka (1994-1995) SECI model
The following SECI
elements in Figure 1 are the processes of knowledge creation:
Ø
Socialisation
is the world where
individuals share feelings, emotions, experiences and mental model.
Ø
Externalisation requires the expression of
tacit knowledge and its translation into comprehensible forms
that can be understood by others.
Ø
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.
In the compound of Nonaka (2000a and 2000b) 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.
Nonaka’s 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; Nonaka and Takeuchi, 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 Nonaka’s 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 within the 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:
Ø Barriers between the individual and the KM systems (i.e. portals, collaboration tools, ontology’s)
Ø Barriers between diverse specialist domains (increasing accessibility to users representing other sections of the same field)
Ø
Evidence-based health care
knowledge must stem from both tacit knowledge and codified explicit knowledge
Ø
Barriers between the individual
and learning enabling environment
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 organization
4.
identify
the forces and obstacles for tacit knowledge.
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 firm’s 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.
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) becomes also a pivotal “enabler” to the success of KM to turn highly unstructured research information into clinical knowledge.
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
et al, 2005) It is also understandable that the role of IT in supporting KM
initiatives varies for different categories of organisations
(Ghosh 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 purposeful action make
collaborative 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 Nonaka’s 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
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Contact the Author:
Khalid Samara, MSc MBCS CITP MIET, Phd Student, Centre For Information Management and E-Business, Room 330, London South Bank University, London SE1 OAA; Tel: 020 8868 4362; Email: samarakb@lsbu.ac.uk