Each organization has its own unique knowledge management strategy (KM) and modeling.
You would agree that it really helps to understand if the strategy addresses the strategic needs of the organization.
Knowledge itself is the ability to apply the tacit and explicit information in problem-solving, decision making or effecting an improvement within the core values of an organization.
A KM model is a structured way to look at the process of KM used by an organization in order to investigate its properties and tailoring it to the organization’s specific needs. All models basically have four parts:
- Information capture
- and use
Some models like the Nonaka Model elaborates more on the “Use” and “creation” parts while the Zack Model concentrates more on the customization part or the refinement of the information.
At first, the information captured needs to be processed to distill only the business critical knowledge, also called strategic knowledge, which has to be verified and validated by key stakeholders.
This information stored in usable formats has become Knowledge. This knowledge has to be distributed to the relevant target group and enables the user to solve problems for example. This process of converting information into knowledge that can be used is called the Knowledge Management Cycle.
The 4 comprehensive and widely used KM models are elaborated here:
Nonaka and Takeuchi Model
Here the focus is on knowledge creation. In order for innovation to take place, the bar has to be raised, first, in the sphere of knowledge creation. The model defines and elaborates on the 2 types of knowledge, the explicit knowledge which is well documented and tacit knowledge which is a result of years of experience and hence is likely to unconsciously reside at the back of the mind of the expert using this knowledge.
Since knowledge creation is a continuous process and occurs in both a planned and accidental way across the organization, this model considers the capture of this knowledge as the key to continuous improvement.
Nonaka also specifies the 4 methods of knowledge conversion:
- Socialization (tacit to tacit)
- Externalization (tacit to explicit)
- Combination (explicit to explicit) and
- Internalization (explicit to tacit)
Explicit knowledge can be processed by either a human or computer whereas tacit information can only be processed by the person who holds it. Let’s now look at each of the methods of knowledge conversion.
Socialization: This is where knowledge sharing takes place through presentations, demonstrations, one-on-ones etc. It can be between two individuals over coffee or a formal open-up session. It may also take the form of a mentorship program where the objective itself is the systematic download of tacit information onto a successor.
Externalization: Here knowledge is stored to disseminate in a planned manner e.g. through publication, presentations in seminars and conferences etc. Academic institutions and research and development centers have this as their priority as they are viewed as the source of information dissemination.
Internalization: Simply put this is training with a purpose. If you need to fix your water heater, you first “internalize” or learn the “explicit” knowledge which the user manual may contain in order to then use this knowledge to troubleshoot. Similarly, an organization may need experts to pore over certain documented information to troubleshoot a manufacturing line to reduce rejections or streams of financial data to plug profitability leaks.
Combination: Here knowledge enhancement and adaptation takes place. The tacit information is combined with explicit information to create knowledge adapted or enhanced to tackle a specific problem or about a particular project.
ZACK Knowledge Management Model
The model put forward by Meyer and Zack defines the various stages of a KM cycle emphasizing the “refinery”. The stages of information collection to conversion into usable knowledge have been enumerated as; acquisition, refinement, storage and retrieval, distribution and presentation or use.
Each of these stages is networked using pure logic in order to facilitate analysis of the knowledge repository and clear mapping of each of the stages of the KM cycle. Let’s look at these stages a little more closely:
Acquisition of Data or Information
At the information, stage focus is given to the quality and accuracy of the information. This in the context of where our materials come from and what specifications they carry can range from, scope, breadth, depth, credibility, accuracy, timeliness, relevance, cost, exclusivity etc.
Imagine buying wheat flour for making biscuits in your factory.
You have many vendors of wheat flour and each has given you a different specification and price for the same flour and delivery schedule.
It would be impossible to compare and come to a purchase decision even if quality and delivery schedules are the same. In this case, the data capture needs to ensure the information is standardized and only comparable data which is important for biscuit manufacturing is captured in a standard format.
In acquisition, the guiding principle is “Garbage In Garbage Out” which means people have to be trained to get first time right, whatever information they put into the system to get analyzable data downstream.
After acquiring information, it has to be stored, but all information cannot be stored. First, the information has to be converted to knowledge packets. This helps storage and retrieval to become easy in the future. This process of conversion of information to knowledge packets is called refinement.
There can be many types of refinement applied to the information depending on the requirements of the organization like:
Physical, e.g., migrating from one medium or location or software to another.
Logical, e.g., restructuring the information into preset formats, indexing and integrating this information into a larger group of information to be used later.
Cleaning, e.g., getting rid of redundant information or duplication or even removing unnecessary parts of the entire information package.
Standardization, e.g., tailoring all information into predefined templates in order to make comparisons easier and improving the usability of the information.
Storage and Retrieval
The repository of information nowadays tends to be in the form of customized software, but traditional businesses still store files, folders and other printed and written information.
This information will be used downstream during the stages of product creation, e.g., information required for recipe and label creation, packaging, and claim elements, etc.
Here the various recipients of the information are defined, and the mode in which they may receive this information is also defined, e.g., mails, prints, dossiers, etc. The timing and frequency at which they are to receive this information and even form or language may need to be specified.
This is the final step where the hitherto fore considered “information”, is going to take the shape of “knowledge”.
Presentation of the information, depending on the complexities of the organization, has to consider the recipient. Each recipient will have particular needs for different parts of the information whole. Tailoring and packaging the information for each group of recipients increases productivity.
Feedback is generated from the final users of this knowledge in order to continuously improve the repository and eliminate redundant information or add new elements to the information capture.
The Meyer and Zack model is considered one of the best models having an end-to-end scope and covering the entire organization giving a complete picture of all the elements of a robust KM model.
BUKOWITZ and WILLIAMS Model
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This model is basically a management framework that outlines “how organizations generate, maintain and expand a strategically correct stock of knowledge to create value”. All types of knowledge are recognized by this framework and may include information databases, information technologies, communication infrastructure, organizational intelligence, skills, and know-how latent at certain function etc.
The schematic diagram above shows the “Get”, “Use”, “Learn” and “Contribute” stages. These stages are linked to the strategic need of the organization.
Get Stage: Specific information required to make decisions, solve problems, or required to create new products or services, is sought or procured.
Use Stage: Here this information is combined in various ways by individuals or groups in order to make the information usable, e.g. for innovation or renovation.
Learn Stage: Whenever knowledge is used in a business environment, regardless of success or failure of the venture, new knowledge is generated. In order that the same mistakes are not repeated and to use the new knowledge to improve competitive advantage, integration of this new knowledge back into the system is fostered.
Contribute stage: Here the employee contributions are sought in order to continually update database and repositories. This is one of the ways of documenting tacit knowledge.
Karl Wiig, proposed his KM model in 1993 with the claim that knowledge will be useful and valuable only if it is organized and synchronized. According to Wiig, the ultimate purpose of KM is “to make the organization intelligent-acting by facilitating the creation, accumulation, deployment, and use of quality knowledge.” Through his KM cycle, WIIG attempts to show how knowledge is built and used by individuals and organizations.
The 4 stages of WIIG’s model are:
Building knowledge: from external and internal knowledge sources covering both tacit and explicit knowledge.
Holding knowledge: Storing the information in specific and easily retrievable physical formats and in people through training.
Pooling knowledge: Using appropriate KM systems to ensure cross-talk between pools or groups of experts.
Applying knowledge: Here the use of knowledge is in changing or improving the work processes so that new knowledge is automatically embedded.
Some of the defining characteristics of the Wiig model are
Completeness: Whether tacit or explicit there are several sources of knowledge, each with incomplete information. When building knowledge for the organization the completeness of this knowledge is an important step to utilization.
Connectedness: To understand the big picture and realize how knowledge may be used it is important that different parcels of knowledge are interconnected. This helps pull out related information quickly and assimilate in decision making.
Congruency: This is the alignment between facts and figures, concepts and content to the organization’s objectives and the utility will be directly proportional to how the knowledge becomes a crutch for problem-solving.
Purpose and Perspective: Capturing knowledge with a particular perspective is to look at the elements that may be required in future for a particular purpose. This would enable us to glean information from a particular point of view and increase relevancy to the user.
Modelling in KM is the science of pictorially depicting the KM framework that shows the integration and inter-relationships between various elements in a lucid manner. Models broadly try to capture all the different processes within an organization, the unique knowledge requirements of each of them and facilitate a system of acquiring and storing this knowledge to enable continuous learning and improvement in the functioning of the organization. A knowledge management framework is one which captures all the relevant aspects of KM with appropriate detail. As organizational needs vary, each model must choose its key focus areas and areas of redundancies so as not to waste time and resources in capturing irrelevant data.