Knowledge Management Techniques - Essay Example

Knowledge Management Techniques Knowledge management is about building organisational intelligence by enabling people improves working experiences inusing knowledge, sharing and capturing. It involves using experiences and ideas of employees, suppliers and customers to improve the performance of the organisation (Bergeron, 2003). Narrowing effectively on what works well leads to better policy, practice and strategy. It can also be defined as, Knowledge management (KM) is a business optimization technique that organises, identifies, packages, distils and selects information essentials to the companies business in a manner such that it improves corporate competitiveness and employees performance (Dr. Uriarte, 2008). The parking and preservation of corporate knowledge is relevant especially in today’s era, given that majority of work force oriented service is solely composed of knowledge workers. To successfully compete in the economy, companies have to treat the personnel providing the knowledge just as they would pay attention to any other strategic irreplaceable asset (Leistner, 2010). At high levels of the hierarchy of knowledge worker, certificates and university degrees from guilds or various organisations provide the self imposed labels that professionals and managers use in order to qualify for one of the positions in the organisation (Miltiadis et al, 2008). Knowledge workers have an overall picture of the business as oppose to the lower level front line workers, but there is the likeliness duplication of mistakes in the various departments since there is no strategy or media for information sharing example in an organisation professionals in various departments may be doing some experiments with out sourcing, independently each discovering that saving promised is far much less that suggested in the popular business press. Knowledge management is fundamentally about a systematic approach to other information and managing intellectual assets in a way that the company is provided with an edge to competitive advantage. Knowledge management is an optimisation strategy for business, and it is not limited to a particular source of information or technology (Uden and Eardley, 2010). A wide variety of IT (Information Technologies) plays a key role in knowledge management initiatives, simply because of the effort provided over manual operations and savings in time. Knowledge management is agnostic when it comes to source and type of information, ranging from a document describing the process a customer support representative uses to escalate complaints of customers to mathematical description of internal working of a machine within the business organisation (Mahesh and Suresh, 2006). Take into consideration the example of a law firm, whose partners create written templates for creating specific documents easily. Such a firm has a knowledge management system that can hugely increase its productivity (Rowley, 1999). When the templates are moved to a word processing document system, the ease of legal document creation may be enhanced by several order magnitudes. In knowledge management there is the analysis of strong and week points. This is done in several ways which are strengths weakness opportunity threats analysis (SWOT) and bottleneck analysis. In SWOT the analysis of weakness and strength of an organisation and the threats and opportunities it is facing is well widely known and used technique. In knowledge management it can be used for two objectives which are; analysing the organisations knowledge from the perspective its goals and setting high level goals for the organisation. To start a SWOT analysis of knowledge we have to have a clear definition of the goals of the organisation. The first step in this analysis is to define this goal or these goals clearly. It is better to perform a SWOT analysis for each goal separately when there are many goals. When SWOT is judged and generated by different people, lumping too many goals may confuse the analysis. In order to compare their opinion they need the same frame of references (Rao, 2005). The procedure of this analysis is different, ranging from interview with knowledge people to intensive sessions lasting from one to several days. The approach we follow consists of a number of steps. i. Interviewing of relevant people separately, this is done in an open way without openly asking for SWOT’s. The interview is based on the function of organization and organisational goals in achieving it. ii. Classifying and analysing the remarks made at the interviews as one of the SWOT’s. Do an analysis of all the SWOT’s and combine comparable ones deleting irrelevant ones that do not focus on the goal. In order to prevent biases it should be done by at least three people. It is good to limit the number of SWOT’s in each category to not more than five. iii. Show the people interviewed previously the five SWOTS’ in each category. Asking them to make an addition of at most five new ones to each category. In terms of the organisational order of goals tell them to rank the SWOT’s in terms of importance. iv. Do analyses of the rank order, If there is a strong agreement about the importance of the SWOT’s introduction can be done in the SWOT Tactics Matrix. If the case is a significant disagreement, there is definitely a problem that needs solving before any other progress in the knowledge management. Disagreements in the SWOTs can reflect the difference in knowledge and values or disagreement concerning the organisations goal between the people participating in the exercise. There is also a possibility that clique exist, rank order sharing, which may be opposed to the one of another group. There will be no common ground for selecting and defining improvements, as there was no common basis for building the SWOT Tactic Matrix. v. SWOT Tactic Matrix building, the SWOT’s components are set into rows and columns. The general strategies that can be pursued are indicated in italics and the proposals for improvements are the cell entries (Tiwana, 2000). In Bottleneck analysis the act of sensitizing is important because most bottlenecks are not recognised easily, particularly not by those involved with the closely use of using knowledge assets. A list of knowledge related problems are: i. Insufficient knowledge at point of action, in a number of situations knowledge workers are asked to perform tasks for which their knowledge is sufficient. They may not be in possession of the required knowledge themselves, nor may it be available in reference material, knowledgeable co-workers and knowledge based systems. ii. Management of knowledge is not valued as an asset; knowledge in most organisations is not managed like other assets. Knowledge is not considered as an asset explicitly it is managed and considered as a commodity. iii. Narrow knowledge transfer, organisations quite often trains their workforce to perform competently routine functions, in doing so they don’t teach them to deal with exceptions. This usually happens when the knowledge workers to knowledge transfer focuses on training rudimentary skills, or when knowledge workers perform a narrow set of tasks without the opportunity to practice outside its boundaries. iv. Missed learning opportunities, often it is found that valuable knowledge flows are missing by not providing feedback from activities downstream to those who are in the business process chain upstream. v. Unnecessary division of decisions and tasks, for many reasons decisions and tasks may be divided between departments needlessly, individual workers and speciality areas. This propagates into the division of knowledge needed to perform complete task. In practice this will lead to many windows phenomena to the client and narrow task to the organisation. A list of bottleneck generic symptoms to the different aspects of knowledge is as shown: Current level of proficiency, at the low end of the scale are indicators of proficiency proliferation of supervisors, agents are not well qualified for the job. Mistakes, and increasingly controlling and checking of work. Business process, limited reuse of knowledge over business process. This is done by re inventing the wheel Nature, knowledge quality for business process. If knowledge is very heuristic and process crucial to knowledge management technique. In a range of business activities that can be considered knowledge management, a confusing aspect of the practice is narrowing down exactly the constituents of data, information and knowledge. Knowledge is processed data which is information synthesised, summarised or organised to enhance understanding, comprehension or awareness. Knowledge is a combination of an awareness and metadata of the context in which the application of metadata can be done successfully. Information is processed data in context. Information can also be defined as a data collection and associated interpretations, explanations and other materials in text concerning a particular event, object or process. Data is comprised of raw facts and figures./ in depth they comprise of attributes of numerical quantities derived from calculations, observations and experiments. Metadata is data about processed data. Metadata includes high level categories and descriptive summaries of information and data. In the context in which information was used metadata explains this. Instrumental understanding is the complete clear idea of explanation, nature and significance of something. It is an internal personal power that renders intelligible experience by relating broad concepts to specific knowledge. The concepts cubing knowledge management are related according to hierarchy, with understanding at the top and data at the bottom an example in medical practice the hierarchy would appear as Data. Patient body temperature 103F; Pulse: 110 beats per minute; Age: 78. Information. A temperature greater than 100F you have fever; a pulse greater than 100 beats per minute you have tachycardia; elderly is a person greater than 70. Metadata. The combination of tachycardia and fever can be life threatening. Knowledge. Probably the patient is suffering from a serious case of flu. Instrumental understanding. Patient should immediately be admitted at a hospital and treatment for the flu be administered as soon as possible. In the above example, the individual measurements of patient’s age, temperature and pulse are data. These have no meaning out of context. However, when this information is related to normal information, the patient is seen as someone who is elderly with tachycardia and temperature. In a wider scope of healthcare the combination of observations and findings is seen as life threatening in metadata context (Smolnik and Murray, 2010). A doctor who has seen this patient’s pattern in the past diagnoses as the patient is suffering from flu. Given the patients condition and age, the doctor makes a conclusion that he should be admitted to the hospital and treatment for the flu administered. Although the concept of knowledge is almost equivalent to the concept of metadata, unlike information, metadata, or data, knowledge does awareness incorporation a feature that denotes humans, rather than a host, computer. Although systems of artificial intelligence (AI) may be capable one day of awareness and perhaps even understanding, in the current state computers are only limited to the metadata level. Even though the knowledge management concept would be better labelled metadata management, the latter term is more confusing than referring to the metadata management concept as knowledge management. According to the concept of knowledge management, it is important to have knowledge that the process is selective, meaning that only contextual information and important facts is saved. A filter mechanism should be in place to avoid collecting a large amount of information that is expensive storing and can’t be retrieved efficiently or easily searched. Similarly, the process of knowledge management involves the conversion of data to information and that of information to knowledge. This step limits and clarifies the amount of data stored. Before information is stored in a memory system, however to facilitate later retrieval the information has to be organised. Organisation usually involves deciding on a vocabulary for concepts identification and representation language. Using several forms of information technology storage is most openly accomplished, typically including servers running database management software and PC’s. However, sitting of data is of no value unless it is put to use. Therefore, considering knowledge management as a two way process in that data is first captured, stored and manipulated, and then the information is reformatted or packaged to suite the user’s needs. Some of the themes in knowledge management are: Approaches to Knowledge Management Nature of knowledge Types of knowledge Organisations deal with knowledge in their daily operations. A few organizations are the ones that have a formal way of dealing with knowledge (Maier, 2007). Most organizations rely on processes and individuals. This has a consequence because when people leave the organisation, they leave with their knowledge resulting in the loss of valuable resources and organisational assets. References Bergeron, B. 2003, Essentials of Knowledge Management, John Wiley & Sons, Hoboken, New Jersey. Dr. Uriarte, F, A, Jr, 2008, Introduction to Knowledge Management, ASEAN Foundation, Jakarta, Indonesia. Leistner,F, 2010, Mastering Organizational Knowledge Flow: How to Make Knowledge Sharing Work, John Wiley & Sons, Hoboken, New Jersey. Maier, R, 2007, Knowledge Management Systems:Information and Communication Technologies for Knowledge Management (2nd ed.), springer-Verlag, Berlin. Miltiadis, D et al, 2008, Knowledge Management Strategies: A Handbook of Applied Technologies, Idea Group Inc (IGI), Hershey, Pennsylvania. Rao, M, 2005, Knowledge Management Tools And Techniques: Practitioners and Experts Evaluate KM Solutions, Elsevier Butterwoth-Heinemann, Amsterdam. Rowley, J, 1999, What is Knowledge Management?, MCB UP Ltd, Ormskirk, UK. Smolnik, S and Murray E 2010, Strategies for Knowledge Management Success: Exploring Organizational Efficacy, Igi Global, Hershey, PA. Mahesh, K, and Suresh, J, 2006, Ten Steps to maturity in knowledge management: lessons in economy, Chandos Pub, Oxford, UK. Tiwana, A, 2000, The Knowledge Management toolkit: practical techniques for building knowledge management system, Prentice Hall PTR, Upper Saddle River, NJ. Uden, L and Eardley, A, 2010, Innovative Knowledge Management: Concepts for Organisational Creativity and Collaborative Design, I GI Global, Hershey, PA. Read More