Knowledge Management Design and Implementation - Literature review Example

Full Paper Knowledge management Design and Implementation [Type the 11/11 Knowledge Management Implementation and Design Knowledge management is also known as Knowledge Discovery in Databases (KDD). The primary function of Knowledge management or KKD is to analyze and search large number of data patterns in a database. Likewise, it utilizes computerized data analysis techniques to expose relationships of data items that were previously hidden or undetected. However, the data that is analyzed via different techniques is fetched from data warehouses, where many databases are interconnected with each other. Major techniques that are involved in the process of knowledge management are regression, classification and clustering (Wu, Ming, He, Li, & Li, 2014). Importance In today’s world there is a lot of competition between organizations and cooperated market of communication. In order to compete in this developing sector of information and communication systems the organizations needs to take a step towards learning. The benefits of learning can be attaining through Knowledge Management. However, in the previous years, the process of learning has advanced and the trends are changed along with the change in information technologies in organizations. The advancement in the fields of communication networks forces the organizations to attain maximum learning from Knowledge Management. In addition, the development of Knowledge Management can not only be observed in the field of information technology but can be seen in business management organizations also. In the near future, the experts states that the Knowledge Management will grow rapidly as compare to its advancements in recent years. Knowledge Management is a vast area of learning therefore individual definition will not justify its all aspects. However, it is defined by many researchers depending on its context available at that point. The Knowledge Management is organized and integrative procedure that connects the organizations and their activities regarding information through obtaining, generating, accumulating, allocating, distributing and implementing to the individuals in order to achieve the aims and objectives of organization. Moreover, it can also be defined as the process of generating and utilizing the organizations information in a corrective way. The organizations can gain maximum information through Knowledge management. The process of learning has been conducted through knowledge management. There are three kinds of learning procedures in any organization they are mentioned below: Individual learning Learning via nonstop communication Learning by means of a knowledge depository Creating Market Intelligence Knowledge management is incorporated for gaining in depth patterns for market intelligence from data warehouses containing massive amount of data. However, the issue that arises is not the quantity of data, as we already have massive amount of data to work with, it is the methodology that is required to learn data. Likewise, data provides all the attributes but how to utilize them for gaining benefit is another question. This is the area that is addressed by Knowledge management, as it is used for extracting valuable information from large amount of data saved on periodic basis. Likewise, information that can be extracted may contain relationships and different patterns. For instance, a retail store may indicate that some products are more in demand in one channel of distribution, there may be two different products that are sold at the same time in a specific geographic location, some specific products are more in demand in some geographic locations and similarly, some products are more demanding in certain events may be associated with religious events. If we take an example of Wal-Mart, the store has found that if there is a probability of a hurricane, the demand of beet increases in that specific geographical area, therefore, stores have to stock more beers that usual in this sort of situation (Kransdorff, 2012). Literature The research regarding Knowledge management has been a core discussion among the researchers and the scholars from years. The years passed and there is a speedy improvement in the field of Information and communication technologies. The development in the field of knowledge management helps the organizations to get utmost advantage and to spread out the information into related organizations. The maximum benefits may vary from organization to organization in terms of knowledge management. Moreover, in this research we are going to explore about the organization regarding knowledge management. In this research we will explore the following departments related to Knowledge management such as: Drivers Features Techniques Execution The above mentioned characteristics need to be examined through Knowledge Management. The research will involve the execution of Knowledge Management and the benefits we obtain by implementing tools (Barachini, Stauss, & Al-Hawamdeh, 2008). Employee associated with utilizing patterns of customer behavior from Knowledge management, i.e. a financial analyst would seek facets of the store or organization that may become bankrupt, similarly, human resource managers would seek information of a successful potential employee, employees working in a credit card department would like to get information associated with credit card debts payments from potential customers and also to analyze the legitimate credit card transactions against the falsified ones, marketing department executives would like to extract information associated with product purchases (Kransdorff, 2012). For instance, any online store would like to know what kind of brands are more popular for shoes; Adidas, Nike or Reebok. If all the mentioned information is available to any organization’s different departments, than efficient decisions will be made accordingly. Credit card department may focus and target potential customers to prioritize for minimizing fraudulent and fake transactions. Similarly, human resource department can short list based on background checks and hires the most appropriate candidate. Likewise, the marketing department will focus on demands of customer for different products. Accordingly, after making all the departments capable of taking efficient and informed decisions based on insights from knowledge management, businesses may reconstruct their objectives, strategies, goals and offerings on different products. However, Knowledge management techniques are not limited to the mentioned benefits that it injects in to business processes and decisions, law enforcement agencies also use Knowledge management for detecting and analyzing probability of crime scenarios and environment of these crimes. Moreover, stock exchange can utilize Knowledge management techniques for detecting fake activities, so do pharmaceutical organizations by mining data for predicting effectiveness in compounds and to reveal innovative chemical objects that may directly contribute for a specific disease. Similarly, knowledge management is utilized by the airline industry to forecast delayed flights, so do weather experts for predicting weather by analyzing patterns. They can forecast the weather by informing the time and day for weather types such as sunny, warm, cloudy, bright skies, snow, cold, heavy or natural disaster. Furthermore, trust organization and nonprofit organizations also use Knowledge management techniques for accessing the prospect of donations from donors for any sort of charity work or cause. Deployments in the Past As mentioned earlier, Knowledge management specialist abstracts value data from the data warehouse, however, the strategy for pulling off valuable information is to identify relationships and patterns that are located within the stored data archives. Certainly, in the past, humans have always searched for patterns of activity i.e. astronomers looking at starts, weather forecasts. Likewise, in this current information age, humans are still eager to identify and understand patterns of activity. For instance, predictions for election results, new launched products, popular products, temperature variances due to global warming. We can roughly say that over the past 30 years, there is an evolution in a slow pace from data processing to Knowledge management. In the late 1960’s data was organized and collected by organizations by database management methods that facilitated data organization along with queries. Moreover, Online Transaction Processing technique was one of the routine methods for retrieving and storing data at a rapid pace. It was possible because OLTP which is “a class of program that facilitates and manages transaction-oriented applications, typically for data entry and retrieval transaction processing” (Com & Jielin, 2007) and “also refers to computer processing in which the computer responds immediately to users’ requests” (Com & Jielin, 2007) was considered to be one of the advancements in computing. System Characteristics Implementation The information and knowledge is considered as the major positive feature of any organization especially in today’s digital environment. The core field of any organization depends upon the Information and communication technologies (IT) that connects any organization through Knowledge Management and helps to make a communication bridge between organizations. In addition, the information technology in any organization provides a platform to exchange knowledge and information. In many organizations, the executives are obtaining help from Knowledge Management in order to get the information regarding latest technology. Moreover, the core foundation of providing knowledge in the field of Computers and networks in an organization is based on Knowledge Management. Following are the tools utilized by Knowledge Management: Intranets. Extranets. Virtual Private Networks Web conference. ETC Organization learning. Innovation. Sharing. Implementing. Cyber Money The primary objective is to establish a baseline or standard for calculating the knowledge value, as the practical approach is to provide compensation to the knowledge provider within the circulation process of knowledge management. Secondly, it also provides measurements for the intellectual value of organization and individuals. Cyber Consultation The critical reason for cyber consultation is to exchange experience and knowledge on the World Wide Web via expert map executed on individual based awards that is based on the evaluation standard associated with knowledge commotion in a limited time. Further, the representation of case that is associated with outstanding knowledge utilization Deployment Mechanisms Tools for knowledge management can be categorized in four segments (Ghani, 2009): Prediction Tools Classification Tools Clustering Analysis Tools Association Rules Discovery Tools Prediction Tools are considered as a method of prediction. Likewise, the sole purpose of this tool is to utilize traditional statistical forecasting in order to calculate a value for a variable. The classification tool is the most common tool that is used for Knowledge management. The sole purpose of this tool is to differentiate unlike classes of different objects and activities. If we take an example of a credit card industry, the transactions will be only of two natures i.e. legitimate and fraudulent (Agarwal & Islam, 2014). Accordingly, by deploying Knowledge management classification tools, organizations can classify whether the transactions are legitimate that may lead to minimize risk and saving money. Another example will be of an advertising company that may want to forecast consumer interest so that the promotion can be tailored accordingly. However, there are many other aspects in this case but Knowledge management provides in-depth knowledge of targeted audience i.e. customers, so that the campaign can be designed effectively. Clustering Analysis tool is used for clustering. Likewise, this tool is considered to be most effective for clustering group of different products that will be consolidated naturally. Likewise, Knowledge management was most beneficial for identifying groups that needs to be consolidated, which are identified by this tool. However, Knowledge management eliminates unnecessary groups that are not considered for any contribution in the decision making process for businesses. Whereas, some groups that are identified, becomes vital, and can be utilized by the organization to generate business. The clustering analysis tools is most widely adopted because it is used for an economic term that is most popular called as ‘Market Segmentation’. This term refers to a division of customers, who are dispersed anywhere, in to segments. Although, there may be a limitation factor consisting location, economic conditions, culture, lifestyle, income of people etc. likewise, after the division of customers in to segments, different strategies are set for each market segment. Association Rules Discovery tool is used for linking characteristics. For example, what kind of household products are used in certain high society areas?, What sort of household items are used area wise, What kind of fast food chains are most popular in certain areas, what kind of books are popular among certain type of people etc. Organizations or marketing departments use these kinds of customer behavior strategies to target customer according to their needs. Knowledge Management Techniques and Methods Apart from the tools, there are certain applications that are required to effectively deploy Knowledge management techniques and methods. Likewise, the two major applications that are used currently are SAS enterprise Miner and SPSS. Both of these application contains a wide range of tools supporting all Knowledge management techniques i.e. prediction tool, classification tool, clustering analysis tool and association rule discovery tool. These two most widely used Knowledge management software are stand alone and have the capability to import and process data, on wired and wireless networks, in almost any format. As these two tools are stand-alone fully functional Knowledge management software, there are other various Knowledge management tools that do not support statistical support, as compare to these two, but they can be integrated with spreadsheets such as Microsoft Excel (Coulson-Thomas, 2013). Likewise, these small Knowledge management tools can provide an interface for examining effectiveness and familiarity with Knowledge management. As, Microsoft Excel is a small program, it can support Knowledge management characteristics by integrating with these small tools and can handle it effectively. Moreover, it provides a broader picture and demonstrates the usefulness of knowledge management for business (Ghani, 2009). Furthermore, these small tools also illustrate statistics associated with diagnostic that are utilized for analyzing the information retrieved from these tools incorporated with Microsoft Excel. Integrative Structure and Outcome Model of Relationship A massive amount of research is conducted on Knowledge management in order to derive business benefits by making informed decisions based on extracted data from large amount of data. A model for relationship benefits was developed (Dr, ). The purpose of this model was to analyze the influence mechanism of profits associated with relationships that were impacted on customer satisfaction and loyalty (IUGA & KIFOR, 2014). The study for this model demonstrated Knowledge management techniques to investigate the composition of relationships created on relational bonds in order to establish integrative structure model. Likewise, the research on this model investigated the impact of relationship benefits associated with satisfaction of the customers and the impact on customer satisfaction and loyalty for constructing an integrative outcome model (IUGA & KIFOR, 2014). Implementing Consumer Data in to Intelligence Implementation of Knowledge management techniques for a telecommunication company in China embraces translation of customer data in to intelligent and purposeful data. The name of the company is China mobile and is the world’s largest telecom organization. The company used Knowledge management as a strategic tool to maintain its competitive standing by focusing shifts for gaining insight of customer preferences and their habits (Corbitt, 2003). Threse Cory, who is an analyst with ‘Analysys Research’, says that the telecommunication sector should not emphasize on internal data but take a holistic approach i.e. also collect external data for getting insights to the upcoming expectation of market trends. China mobile and its subsidiaries are developing their own data warehouses, as the major benefits businesses can extract from incorporating business intelligence in Knowledge management are: Focus on Customer Centricity, Enhanced competition, liberalization and customer usage analysis (Corbitt, 2003). However, in order to achieve these major benefits major applications that must be used in this process are churn management, revenue assurance, new product launch, measurement of service success rates, measuring partnership success rates, detecting active and inactive consumers of mobile service (Corbitt, 2003). However, the approach should be from reactive to proactive. Likewise, reactive approach includes the usage of applications for data capture that will be analyzed by implementing business intelligence with Knowledge management to derive results and benefits (Corbitt, 2003). Training and Awareness The organization is keen to spread awareness related to knowledge management systems via different channels such as spreading awareness via weekly newsletters, constructing an organization wide training plan on annual basis and taking nominations from each function and arranging seminars for knowledge management. Similarly, a program for knowledge management is deployed for all employees of the organization. Bibliography Agarwal, N. K., & Islam, M. A. (2014). Knowledge management implementation in a libraryMapping tools and technologies to phases of the KM cycle. VINE: The Journal of Information & Knowledge Management Systems, 44(3), 322-344. doi:10.1108/VINE-01-2014-0002 Barachini, F., Stauss, K. A., & Al-Hawamdeh, S. (2008). Knowledge management : Competencies and professionalism. Singapore: World Scientific. Com, J. W. N., & Jielin, D. (2007). Network dictionary Javvin Technologies, Incorporated. Corbitt, T. (2003). Business intelligence and data mining. Management Services, 47(11), 18-19. Coulson-Thomas, C. (2013). Knowledge management and the high performance organisation. Management Services, 57(4), 41-47. Dr, P. F.Proceedings of the 7th european conference on knowledge management (ECKM 2006) Academic Conferences Limited. Ghani, S. R. (2009). Knowledge management: Tools and techniques. DESIDOC Journal of Library & Information Technology, 29(6), 33-38. IUGA, V., & KIFOR, C. V. (2014). Information and knowledge management and their interrelationship within lean organizations. Buletin Stiintific, 19(1), 31-38. Kransdorff, A. (2012). Knowledge management [electronic resource] : The death of wisdom : Why our companies have lost it, and how they can get it back / arnold kransdorff New York, N.Y.] (222 East 46th Street, New York, NY 10017) : Business Expert Press, 2012; 3rd edWu, Z. Y., Ming, X. G., He, L. N., Li, M., & Li, X. Z. (2014). Knowledge integration and sharing for complex product development. International Journal of Production Research, 52(21), 6296-6313. doi:10.1080/00207543.2014.923121 Read More