Knowledge management (KM) is a crucial part of organizational management since, in the contemporary economic environment, it becomes a substantial competitive advantage for an organization. The quality of this knowledge and the methods that the executives use to manage it are key factors determining the success of KM. This paper aims to summarize the conference paper “Knowledge quality and quality metrics in knowledge management systems” and explain the critical concepts of KM discussed in it.
Knowledge is an intangible asset and a collection of professional competencies, skills, personal reflections, and interpretation of information. In the article “Knowledge quality and quality metrics in knowledge management systems,” written by Tongchuay and Praneetpolgrang (2008), the authors describe the existing systems of determining the quality of knowledge, which are the eight dimensions by Garvin (1987), ISO 9000 standard, and IEEE 1061.
Although there are many ways of acquiring and transferring knowledge in a company, in general, two main types are distinguished – tacit and explicit. One can argue that not all information shared within a company through these two channels is useful or helpful, which emphasizes the need to focus on quality to preserve time, effort, and resources used to share knowledge.
In summary, the publication was written to present a new concept of a KM system that emphasizes the quality of information. Quality, from the perspective of KM, is the suitability of the information in regard to the purpose and requirements of the application. Tongchuay and Praneetpolgrang (2008) offer the following criteria for determining the quality of knowledge – “timeliness, accuracy, completeness, consistent and relevancy” (21.1). This conclusion is based on the research of other scholars’ opinions, using the Delphi method, who define the concept of quality and present a hypothesis regarding the main criteria that define it.
The main items described in this publication are the KM, the quality of KM, and the criteria of information usefulness for organizations. An example of methodology implementation is the use of five metrics introduced by the authors – accuracy, competence, timelessness, relevance, and consistency when developing KM systems (Tongchuay & Praneetpolgrang, 2008). These metrics help evaluate the information that the organization possesses and include or exclude the elements that will not bring value to the business.
The overall benefit of the methodology introduced in the discussed article is the ability to use the five criteria when evaluating KM systems and the types of knowledge that exist in the organization. The main idea that the authors promote is that KM is vital since the employees share their competencies through implicit or explicit methods. The conclusions made by Tongchuay and Praneetpolgrang (2008) are supported in other publications as well, for example, Garvin (1987) who outlines the main domains of quality for products, which can be used for KM as well or Wang and Strong (1996) who argue that data quality is essential for the data users.
Hence, the article highlights the need to focus on knowledge quality within KM, defining essential characteristics that help understand which information is relevant and can help the organization and which should be excluded.
Overall, the article “Knowledge quality and quality metrics in knowledge management systems” summarizes the main elements of KM. The authors describe the quality metrics and the definitions of knowledge quality proposed by other scholars or used in standardization systems. The conclusion is the five measurements of knowledge quality defined using the Delphi method – accuracy, competence, timelessness, relevance, and consistency that organizations can use to enhance their competitiveness.
References
Garvin, D. A. (1987). Competing on the eight dimensions of quality. Harvard Business Review. Web.
Tongchuay, C. & Praneetpolgrang, P. (2008). Knowledge quality and quality metrics in knowledge management systems. Paper presented at Fifth International Conference on eLearning for Knowledge-Based Society, Bangkok, Thailand.
Wang, R. Y. & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–34.