Introduction
Knowledge-based management systems are slowly gaining acceptance in many organizations. The application, proficient conditions, and challenges of enforcing Knowledge-Based Management Systems (KBMS) will be explored in this paper.
Data, Information, Knowledge, and Wisdom
There is a distinct difference among data, information, knowledge, and wisdom. Data is raw material composed of entities such as symbols and codes that by themselves have no meaning, or do not convey any decipherable message (Bellinger, Castro & Mill, 2010). The letters of the alphabet are examples of data. Data can also be a group of words, which do link to a meaning or do not indicate a related event, for example, ‘this is a tree’. Information is data (signs and symbols) that has been put together to form a meaningful message. Information tends to answer the questions What/When/Who. For instance, the sentence ‘the planted seed grew into a tree,’ is an example of information as it indicates a relationship and causality. Meanwhile, knowledge is the combination of the entities of data and information to form a useful process of deciphering. Knowledge answers the question ‘how?’ Knowledge exemplifies a flow that creates a plane for forecasting a trend; for example, the statement ‘when a seed is planted on the ground and watered, it is likely to germinate and grow into a tree. Wisdom meanwhile is the understanding of issues that encapsulate all levels of consciousness and matters of morality and ethics. Wisdom goes beyond the realm of the visible and tangible; it explores for answers, which may or may not be in existence. Wisdom includes judgment on what is morally and ethically sound.
Traditional database vs. knowledge base
The traditional databases were based on the premise of storage of data and information for future retrieval, while knowledge bases go a step further, by storing knowledge that the members of an organization can use to overcome functional difficulties that they encounter in the course of their work (Akerkar & Sajja, 2009, p.16). Traditional databases were primarily storage facilities that incorporated all the data within a firm or organization into files and folders, while knowledge databases aid in the functions of an organization by facilitating the ease of acquiring information for employees, acting as a sort of virtual ‘help desk’.
Challenges in Knowledge-Based Management Systems (KBMS) that make KBMS a special Data-Based Management System (DBMS)
There are four major challenges to the sustainability of KBMS and its adoption by different organizations all over the world. The first challenge is that many managers continue to view KBMS as a mere buzz idea that is soon to fade away, leaving companies relying again on more advanced sets of traditional databases. This challenge has led to slow uptake and use of KBMS by organizations (Grant & Grant, 2008, p.578). The second challenge is that the Information Technology (IT) profession has somehow inadvertently monopolized the field of Knowledge Management. This trend has sadly led to its partial isolation by many organizations that are not IT-based. The challenge for KBMS proponents, therefore, is to de-link Knowledge Management from just one profession and ensure it cuts across different professional fields. The third challenge for the KBMS is that its models tend to reduce knowledge – a wide-ranging entity – into codes and numbers that can fit into a specific KBMS database. Critics counter that this trend is to contextualize and minimize knowledge, with some critics stating that the term ‘Knowledge Management is a contradiction in terms. The fourth and last challenge for KBMS is that the information stored for retrieval in the databases may not be relevant to the organizations. The knowledge in the database will need continuous renewal and updating, a task that may prove challenging for some organizations.
Socio-Technical Considerations for Implementing a KBMS in an organization
The first consideration in developing and implementing KBMS in an organization is that they are mostly computer-based and thus not portable. Therefore, unless a user can log in to a specific computer, his or her chance of using the services of the KBMS is minimized. This occurrence can be inconvenient for users. Compared to paper-based management systems that are portable, computer-based KBMS can be inappropriate since in many work environments employees tend to go for practical handbooks over computer-based solutions (Shum, 2010). The second challenge according to Shum is that participation in, or use of, the KBMS by the employees may be very low, rendering the KBMS irrelevant. A case study of Hewlett-Packard Company and its experiment with KBMS indicates that even with incentives, many employees shunned using the KBMS. The KBMS, since it is computer-based, is susceptible to the vagaries associated with networked computer-based solutions like crashes, which can halt the entire activities of an organization at a huge financial cost. These considerations should be factored in when attempting to implement KBMS in an organization.
Wisdom Base and WBMS
As described earlier, wisdom incorporates the elements of data, information knowledge, and even understanding. Wisdom goes beyond mere relational analysis, into the sphere of judgment based on an issue’s morality and ethical soundness.
Conclusion
In my opinion, to determine whether we might be able to have a wisdom base, the qualities of a database will first need to be examined. A database typically stores knowledge (KBMS) that can be used to accomplish and understand specific related tasks. Wisdom involves fundamental issues concerning human life, often involving metaphysical questions and answers that may or may not be solvable or even practical. Wisdom requires the entity practicing it to have a soul (Bellinger, Castro & Mill, 2010). A soul cannot be fixed into a machine; neither can a machine acquire a soul. Therefore, based on the foregoing assumptions and analysis, I believe the idea of a Wisdom Base is impractical at best and unnecessary at worst.
References
Akerkar, R., & Sajja, P. (2009). Knowledge-Based Systems. Massachusetts; Jones and Bartlett Publishers.
Bellinger, G., Castro, D., & Mill, A. (2010). Data, information, knowledge, and wisdom.
Grant, K. A., &Grant, T.C, (2008). Developing a model for next generation knowledge management. Issues in Information Science and Information Technology. Volume 5.
Shum, S. (2010). Knowledge Technologies in Context. Web.