From a superficial perspective, the meaning of the term "Knowledge Management" is deceptively self-evident;however, the simplicity of the term belies the complexity of its description and the scope of its application. Knowledge Management (KM) represents the convergence of many seemingly disparate disciplines, with the goal of superceding barriers imposed by organizational structures, format restrictions, and conceptual limitations, so that the creation, storage, retrieval, dissemination, transformation, application, and accumulation of "Knowledge" can be facilitated.
Our examination of KM will serve to provide an overview and focus on several core subtopics:
The increasing emphasis on KM as a critical success factor reflects the evolution of organizational value paradigms. The term "Knowledge Worker" is generally attributed to Peter Drucker, a renowned management visionary. Increasing use of the term accompanies the transition from traditional views of capital assets, products and productivity, to knowledge as both an asset and a product. Knowledge workers are life-long learners whose skills and knowledge sets are critical to improving organizational structures and dynamics as well as competing effectively in the present volatile external environment.
T. Kanti Srikantaiah describes three themes central to KM as organizational learning (OL), document management (DM), and information technology (IT). In terms of its evolution, KM can be viewed partly as an expansion of the mechanistic concepts and processes that were once the domain of IT specialists. As the organization's world view is expanded beyond data and information to encompass KM, the primary role of IT is to provide the infrastructure for KM, including the networks, databases, hardware, and software. The other side of KM evolution reflects preexistent information structures and practices. OL specialists bring a different set of "soft" skills and approaches to the table, expanding the realm of KM to include the tacit, unstructured knowledge held by workers themselves, as well as consideration of how well organizational structures and processes promote collaboration, learning, communication, and sharing of knowledge. DM specialists focus on explicit knowledge components. Their domain includes libraries, information centers, record centers, archives, collections, with emphasis on collections and policies.
In terms of organizational functions, KM is largely an outgrowth of record management (explicit knowledge). William Saffady described the organizational evolution to KM and its core dilemma in Knowledge Management: A Manager's Briefing (1998):
(Records management) encompasses the creation or receipt, through its processing, distribution, organization, storage, and retrieval to the ultimate disposition of recorded information. However, records--which have tangible manifestations in paper, photographic, or electronic media-are easier to conceptualize and identify than knowledge resources. Broadly defined, a knowledge resource is one that contains or embodies knowledge, but that definition does not sufficiently distinguish knowledge from recorded information.
Basically, KM addresses all types of knowledge within an organization.
Boynton has described four steps for getting KM under way in an organization:
Given the dimensions of its scope and pervasiveness in organizations, KM presents a formidable learning topic. With this in mind, this document is meant to serve as a threshold for students entering into the study of KM. A good place to start is with a formal definition of KM. Scott Davidson cites a definition by the Gartner Group that serves well in an organizational context:
Knowledge management promotes an integrated approach to identifying, capturing, retrieving, sharing and evaluating an enterprise's information assets. These information assets may include databases, documents, policies and procedures, as well as the uncaptured tacit expertise and experience stored in individual workers' heads.
Before KM, it's important to have a working understanding of the differences between data, information, and knowledge. Data are basically facts. Facts are numbers or terms that exist either apart or as an attribute label. Information is data associated with contextual relevance. Knowledge is the interrelation and association of information, longitudinally over time.
For the most part, we can distinguish between the three entities intuitively. I won't even attempt to define wisdom.
As stated previously, traditional approaches have focused on the management of Explicit Knowledge (EK). EK can be generally described as structured knowledge that can be easily expressed, communicated, stored, and shared in the form of alphanumeric characters or symbols.
Tacit Knowledge (TK) is highly subjective and personalized. For the most part, it is unstructured, and can be expressed as insights, opinions, intuitions, hunches, experiences, observations, etc.
Knowledge conversion processes represent the mean by which knowledge is transformed for communication, learning, and application. The four conversion processes are:
The goal is to map both knowledge types, and then convert them to EK for facilitation of dissemination, storage, and conversion ultimately to TK.
Srikantaiah lists the steps in the Knowledge Mapping process:
Knowledge Mapping is in essence a comprehensive inventory of knowledge within the organization, and then aligning and applying the information both internally and externally.
To be effective, KM must properly integrate with the organization's structure, technology, people, and procedures.
Organizational culture (OC): Srikantaiah notes that workers' actions and behaviors, influenced by peers, are repeated over time to collectively become cultural norms and formalized modes of action that influence individual attitudes and actions. OC strongly influences how knowledge is managed, both formally and informally.
Organizational Learning (OL) is an aspect of OC that focuses on the ability of an organization to acquire, interpret, and accumulate, and apply knowledge. Two components of OL are:
KM Life Cycle: Nissen et al. emphasize the need for integrating a 6 stage KM life cycle with organizational-level, group-level, and individual-level systems and practices; KM as a component of organizational strategy is largely a work-in-progress:
KM Life Cycle Stages: |
Create |
Organize |
Formalize |
Distribute |
Apply |
Evolve |
As described by Herschel and Nemati, the Chief Knowledge Officer
(CKO) is a recent creation whose purpose is the management of intellectual capital, a
unique organizational asset.
The CKO's role includes:
The KM infrastructure incorporates all of the organizational assets that can be directly or indirectly applied to KM. This includes physical elements, policies, processes, technologies, and layering elements (connections, communications, conversations, and collaborations). As described by Zack, there are four primary resource types:
Internet-based technologies provide an attractive solution for integrating these resources.
Healthcare (HC) is a very knowledge-intensive field in terms of both tacit and explicit knowledge. As we have seen from our study of the Computer-based Patient Record, Decision Support Systems, and Expert Systems, HC organizations are not very well integrated for KM. The effects on the healthcare business organization of dependence on external payer systems, competition and the shift to for-profit long term strategizing; as well as the inherent specialization of the practice of medicine, secularization of knowledge within specialties, and subsequent creation of HC organizational "silos' -- all contribute to fragmentation.
There are mitigating factors, however. The collaborative culture of the caregiver is well established. Evidence-based medicine (EBM) relies heavily on KM principles. The strategic importance of knowledge repositories and refineries has been acknowledged by HC organizations. The next stages involve creation and empowerment of organizational roles to execute and manage the refining process, and standardization of information technologies to support the repositories and processes.