Definition of Knowledge - Essay Sample

Introduction

The term knowledge refers to useful information whose application improves the quality of life. For any information to qualify as knowledge, it ought to be beneficial, right, and justifiable (Edosio 2014).Hence, it suggests that knowledge is a critical economic resource that serves as a driver and a source of competitive advantages for individuals and organizations.

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Types of Knowledge

The three primary categories, in this perspective, are tacit, embedded, and explicit knowledge. The latter, which is also termed as 'know-what' is codified and formalized, and hence, it is relatively easy to store, retrieve, and identify (Argote & Ingram 2000). It is a category held in knowledge management systems (KMS). Conversely, tacit knowledge is personal and primarily experienced based. It is also called 'know-how' since it depends on an individual's involvement, commitment, and actions. Embedded knowledge, on the other hand, is entirely based on processes, structures, artifacts, culture, and products. This type is not explicit and hence not immediately evident why doing something is a specific way is beneficial to an individual or organization concerned.

How to Create Knowledge

Organizations and individuals create knowledge through experiments. People also come up with new approaches as they interact, practice their knowledge, and learn. However, the practice of knowledge management (KM) dramatically influences the generation of new ideas. For organizations to create knowledge, it should establish an environment where there are teamwork, high trust culture, and high efficiency in dissemination of new ideas (Edosio 2014).

Ways of Transferring Knowledge

Knowledge transfer is a dynamic, continuous and a complex process that depends on factors such as user needs, context and the level of receiver skills and expertise, to mention a few (Argote & Ingram 2000). The approaches to transferring knowledge between individuals are cross-training, rotational programs, and multimedia. The other mechanisms are communities of practice, instant messaging, action review and knowledge distillation, elicitation, and self-capture. In this case, ways of disseminating knowledge depend on the type of knowledge.

Measuring Knowledge

Knowledge measurement plays critical roles since it is the basis of giving additional value to some aspects of human resources. It also points out weaknesses in knowledge management besides the importance of knowledge held in the organization. However, the methods of measuring this aspect are different at the organizational, individual, and group level. The primary approach is a financial method where an organization quantifies knowledge in terms of the level of skills. The other criteria are the scorecard method, opinion-based surveys, team-tacit knowledge measure, and proxy approach (Matoskova 2016).

How to Foster Knowledge

Organizational culture and internal practices directly shape how managers foster knowledge. The best approach is to create an environment where individuals share ideas on decision-making, business strategies, and technology (Ryan et al., 2010). Such an environment encourages individuals to interact and experiment with their ideas, which are critical in creating knowledge. Also, the practice of coordinating knowledge, identifying, and addressing weaknesses in its management is critical in fostering knowledge.

Artificial Intelligence

It entails the use of computers that can react and work like humans. Artificial intelligence supports the generation of knowledge since computers can identify and predict patterns in large volumes of data. Thus, it makes it easy for humans to come up with new knowledge from computer inputs. While artificial intelligence has revolutionized knowledge management, it is no doubt that it cannot overweigh the role of humans. Precisely, it lacks human progress and self-awareness, but instead use instruction manuals to execute programs that create knowledge.

Robotic Process Automation and Artificial Intelligence

The two components are essential in knowledge management. It has high human capabilities and hence supports agents in managing knowledge. Traditionally, knowledge sharing was a primary problem in KM before the introduction of AI and RPA. It uses technologies that aid the storage, retrieval, and sharing of knowledge (Sanzogni, Guzman, & Busch 2017).

How to Manage Knowledge Successfully

The establishment and organization of knowledge assets is the first step towards its successful management. The managers should then establish the strategies of KM and its goals to ensure the practice is beneficial and in line with the overall objectives of an organization. The organization should also have skilled personnel to foster effective sharing of knowledge besides ensuring access to knowledge databases.

Challenges in Knowledge Management

A continuous change in user needs and a global environment presents multiple challenges in KM. Some of these aspects are difficulties of measuring knowledge contribution, security issues, maintaining relevance, and keeping up with the dynamics of technology. The latter is one of the significant challenges since it determines whether an organization can establish an organized, secure, and up-to-date knowledge database.

Quality Control for Knowledge Management

Organizations implement quality control strategies to enhance the reliability of its knowledge databases. The establishment of an efficient KM infrastructure is a critical quality control factor in KM. Also, equipping the knowledge management leaders with the requisite skills to check and implement quality control strategies is essential. These people ascertain and advise the managers on the implementation of quality control strategies (Kaziliunas 2012).

Strategies for Knowledge Retention

It is necessary for organizations to retain crucial knowledge that gives it competitive advantages. Knowledge is lost when key employees exit an entity without sharing or training other people on the use of specific skills. Analyzing risks that may lead to loss of knowledge is the basis of this practice. In this case, strategies underlying knowledge retention are job rotation, after-action reviews, job shadowing, mentoring programs, and encouraging critical knowledge between subordinates, seniors, and prospective retirees.

Types of Learning

The three primary learning approaches are observational, operant conditioning, and classical conditioning. The latter is an approach where people learn through associations while operant conditioning involves learning through consequences. Observational or modeling learning entails observations.

Knowledge Management Training

The practice involves equipping KM personnel with skills to manage and coordinate knowledge database. Such training programs provide KM personnel with skills to address security issues, and integrity of knowledge, among other challenges. It is essential since it enhances the efficient handling of information as an organizational resource.

Knowledge Management Process Modelling

This aspect gives more insights into KM processes. As such, modeling is the basis of studying how critical components underlying knowledge management overlap and interact. It enables decision-makers to strategize on methods that are efficient in addressing weaknesses in knowledge management. Since the models give a realistic overview of KM processes, then it guides managers to implement initiatives and KM practices that facilitate the achievement of desired goals.

References

Argote, L., & Ingram, P. (2000). Knowledge Transfer: A Basis for Competitive Advantage in Firms. Organizational Behavior and Human Decision Processes, 82(1), 150-169. DOI: 10.1006/obhd.2000.2893.

Edosio, Z. (2014). Knowledge management concept. In 2014 International Conference on Knowledge Management and Unmanned Systems (pp. 1-14). Available from: https://www.researchgate.net/publication/264129318. Accessed 16 June 2019.

Kaziliunas, A. (2012). The Knowledge Management Process for Implementing Quality Improvement Programs. Informacijos mokslai, 62, 97-108. DOI:10.15388/im.2012.0.1580.

Matoskova, J. (2016). Measuring Knowledge. Journal of Competitiveness, 8(4), 5-29. DOI:10.7441/joc.2016.04.01.

Ryan, S.D., Windsor, J.C., Ibragimova, B. & Prybutok, V.R., (2010). Organizational Practices That Foster Knowledge Sharing: Validation across Distinct National Cultures. Informing Science, 13. DOI: 10.28945/1296.

Sanzogni, L., Guzman, G., & Busch, P. (2017). Artificial intelligence and knowledge Management: questioning the tacit dimension. Prometheus, 35(1), 37-56. DOI:10.1080/08109028.2017.1364547.