|Chapter 12: Summary||Back to Contents|
||Assess the role of knowledge management and knowledge
management programs in business.
Knowledge management is a set of processes to create, store, transfer, and apply knowledge in the organization. Businesses need knowledge management programs because knowledge has become a central productive and strategic asset in todayís information economy and a potential source of competitive advantage. Much of a firmís value depends on its ability to create and manage knowledge. Knowledge management promotes organizational learning by increasing the ability of the organization to learn from its environment and to incorporate knowledge into its business processes. Effective knowledge management systems require organizational and management capital to promote a knowledge culture and programs for knowledge management, including the creation of a chief knowledge officer. There are three major types of knowledge management systems: enterprise wide knowledge management systems, knowledge work systems, and intelligent techniques.
|2.||Define and describe the types of systems used for enterprise-
wide knowledge management and demonstrate
how they provide value for organizations.
Enterprise-wide knowledge management systems are firmwide efforts to collect, store, distribute, and apply digital content and knowledge. Structured knowledge systems provide databases and tools for organizing and storing structured documents, whereas semistructured knowledge systems provide databases and tools for organizing and storing semistructured knowledge, such as e-mail or rich media. Knowledge network systems provide directories and tools for locating firm employees with special expertise who are important sources of tacit knowledge. Often these systems include group collaboration tools, portals to simplify information access, search tools, and tools for classifying information based on a taxonomy that is appropriate for the organization. Enterprise-wide knowledge management systems can provide considerable value if they are well designed and enable employees to locate, share, and use knowledge more efficiently.
|3.|| Define and describe the major types of knowledge work
systems and assess how they provide value for firms.
Knowledge work systems (KWS) support the creation of new knowledge and its integration into the organization. KWS require easy access to an external knowledge base; powerful computer hardware that can support software with intensive graphics, analysis, document management, and communications capabilities; and a user-friendly interface. These capabilities can increase the productivity of highly paid knowledge workers. KWSs often run on workstations that are customized for the work they must perform. Computeraided design (CAD) systems and virtual reality systems, which create interactive simulations that behave like the real world, require graphics and powerful modeling capabilities. KWS for financial professionals provide access to external databases and the ability to analyze massive amounts of financial data very quickly.
|4.||Evaluate the business benefits of using intelligent techniques
for knowledge management.
Artificial intelligence lacks the flexibility, breadth, and generality of human intelligence, but it can be used to capture, codify, and extend organizational knowledge. Businesses can use artificial intelligence to help them capture and preserve tacit knowledge; for knowledge discovery; to generate solutions to specific problems that are too massive and complex to be analyzed by human beings on their own; and to help firms search for and filter information.
Expert systems capture tacit knowledge from a limited domain of human expertise and express that knowledge in the form of rules. The strategy to search through the knowledge base, called the inference engine, can use either forward or backward chaining. Expert systems are most useful for problems of classification or diagnosis. Case-based reasoning represents organizational knowledge as a database of cases that can be continually expanded and refined. When the user encounters a new case, the system searches for similar cases, finds the closest fit, and applies the solutions of the old case to the new case. The new case is stored with successful solutions in the case database.
Fuzzy logic is a software technology for expressing knowledge in the form of rules that use approximate or subjective values. Fuzzy logic has been used for controlling physical devices and is starting to be used for limited decision-making applications.
Neural networks consist of hardware and software that attempt to mimic the thought processes of the human brain. Neural networks are notable for their ability to learn without programming and to recognize patterns that cannot be easily described by humans. They are being used in science, medicine, and business primarily to discriminate patterns in massive amounts of data.
Genetic algorithms develop solutions to particular problems using genetically based processes such as fitness, crossover, and mutation. Genetic algorithms are beginning to be applied to problems involving optimization, product design, and monitoring industrial systems where many alternatives or variables must be evaluated to generate an optimal solution.
Intelligent agents are software programs with builtin or learned knowledge bases that carry out specific, repetitive, and predictable tasks for an individual user, business process, or software application. Intelligent agents can be programmed to navigate through large amounts of data to locate useful information and in some cases act on that information on behalf of the user.
|5.|| Identify the challenges posed by knowledge management
systems and management solutions.
Knowledge management systems are difficult to implement successfully and they do not always provide value after they are put in place. Firms can provide appropriate organizational and management capital to make these systems successful by rewarding knowledge sharing, promoting communities of practice and a knowledge culture, and designing appropriate taxonomies for organizing knowledge. Proper planning, development of appropriate measurements of benefits, and staged rollout can increase the chances of success for knowledge management projects.Key management decisions include identifying business processes for which knowledge management systems can provide the most value.