Chapter Managing Knowledge in the Digital Firm

Transcription

1 Chapter Managing Knowledge in the Digital Firm Essay Questions: 1. What is knowledge management? Briefly outline the knowledge management chain. 2. Identify the three major types of knowledge management systems. Provide two examples of each. 3. Identify three types of knowledge. What type of enterprise knowledge management system is needed to support each type? 4. Why are knowledge workers so important to the digital firm? Which of the functions they perform do you feel is most critical to the success of the firm? Why? 5. Identify three specific requirements of knowledge work systems. 6. Discuss the concept of virtual reality, especially with regard to VRML and its applications in the business arena. 7. How might a company go about building an expert system? 8. Differentiate between each of the following pairs of words: neural networks and expert systems, fuzzy logic and genetic algorithms, hybrid AI systems and intelligent agents. 9. What management challenges are posed by knowledge management systems? How should they be addressed? 10. How do experts systems work? 109

2 Answers of Essay Questions: 1. What is knowledge management? Briefly outline the knowledge management chain. Knowledge management is the set of processes developed in an organization to create, gather, store, disseminate, and apply the firm s knowledge. The five steps in the knowledge management chain include acquisition, storage, dissemination, application, and management and organizational activities. 2. Identify the three major types of knowledge management systems. Provide two examples of each. The major types of knowledge management systems are enterprise knowledge management systems, knowledge work systems, and intelligent techniques. Structured knowledge systems and knowledge networks are types of enterprise knowledge management systems. Computer- aided design and virtual reality are two types of knowledge work systems. Data mining and neural networks are types of intelligent techniques. Figure 12-3 in the textbook provides additional examples. 3. Identify three types of knowledge. What type of enterprise knowledge management system is needed to support each type? Structured, semistructured, and network are three types of knowledge. Structured knowledge is found in the form of structured documents and reports. A structured knowledge system can be used for organizing such knowledge in a repository. Semistructured knowledge is information in the form of less structured objects and can benefit from a semistructured knowledge system. The semistructured knowledge system organizes and stores less structured information, including , voice mail, videos, and graphics. Network knowledge includes the expertise of individuals and can be supported by knowledge networks. A knowledge network is an online directory for locating corporate experts in well-defined knowledge domains. 4. Why are knowledge workers so important to the digital firm? Which of the functions they perform do you feel is most critical to the success of the firm? Why? Knowledge workers create new products or find ways to improve existing ones. Without them, the firm would stagnate and become less competitive in an environment that is always changing and is increasingly more competitive. In the modern economy, knowledge is truly power. The three major functions of knowledge workers are: keeping the organization up-to-date in knowledge as it develops in the external world, serving as internal consultants regarding their areas of knowledge and its opportunities, and acting as change agents as they evaluate, initiate, and promote new projects. 5. Identify three specific requirements of knowledge work systems. Knowledge work systems must give knowledge workers the specialized tools they need, such as powerful graphics, analytical tools, and communications and document-management tools. Knowledge work systems must provide a user-friendly interface to the KWS. These user-friendly interfaces save time by allowing the user to perform needed tasks and get to required information without having to spend a lot of time learning to use the computer. Knowledge work systems must be carefully designed to optimize the performance of the specific tasks of the pertinent knowledge worker. 110

3 6. Discuss the concept of virtual reality, especially with regard to VRML and its applications in the business arena. Virtual reality systems use interactive graphics software and hardware to create the illusion of reality in cyberspace. The original applications were in gaming, but new uses in education, science, and business are being developed and have great promise. Virtual reality applications are being developed for the Web using a standard called Virtual Reality Modeling Language (VRML), which can organize multiple media types to put users in a simulated real-world environment. VRML is platform independent, operates over a desktop computer, and requires little bandwidth. DuPont s HyperPlant is an example of a business application. HyperPlant allows users to go through three-dimensional models as if they were physically walking through a plant, which reduces errors during the construction of manufacturing structures. 7. How might a company go about building an expert system? An AI development team is chosen, composed of one or more experts, who have a thorough command of the knowledge base, and one or more knowledge engineers, who can translate the knowledge described by the expert into a set of rules or frames. The team members select a problem appropriate for the expert system. The project will balance potential savings from the proposed system against the cost. The team members develop a prototype system to test assumptions. Next, they develop the full-scale system, focusing mainly on the addition of a very large number of rules. The complexity of the system grows with the number of rules, so comprehensibility may be threatened. The system is then edited and pruned to achieve simplicity, elegance, and power. The system is tested against the performance criteria established earlier. Once tested and accepted, the system is then integrated into the data flow and work patterns of the organization. 8. Differentiate between each of the following pairs of words: neural networks and expert systems, fuzzy logic and genetic algorithms, hybrid AI systems and intelligent agents. A neural network attempts to emulate the processing patterns of the biological brain. It results in a program that can learn by comparing solutions to known problems to sets of data presented to it. An expert system works by a system of IF-THEN rules against a knowledge base. By answering a series of yes/no questions, the program arrives at a diagnosis or conclusion. Fuzzy logic uses nonspecific terms called membership functions to solve problems by comparing the ranges into which various specifications fall and reaching a conclusion based on rules covering the various relationships. Genetic algorithms are problem-solving methods that use the model of living organisms adapting to their environment. Possible solutions are evaluated, the best choices are made, then more possible solutions are created by combining the factors involved in those first best choices, and choosing again. The process continues until an optimum solution is reached. Hybrid AI systems use multiple AI technologies in a single application, taking advantage of the best features of each. This is a new field, and has great promise for business applications. Intelligent agents are software programs that use a built-in or a learned knowledge base to carry out specific, repetitive, and predictable tasks for a user, business process, or software application. 9. What management challenges are posed by knowledge management systems? How should they be addressed? Knowledge management systems are difficult to implement successfully and they do not always provide value after they are put in place. It can be difficult to prove quantitative benefits for knowledge 111

4 management systems and identify ways of genuinely increasing knowledge worker productivity. 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. 10. How do experts systems work? 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 organizations 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. 112

5 Chapter 11-2 Enhancing Decision Making for the Digital Firm Essay Questions: 1. Your text states that many t managers use the new capabilities in DSS and ESS to obtain the same information as before the new systems were implemented.. How would you induce a traditional manager to use new DSS and ESS more effectively? 2. Describe the two types of DSS. Explain circumstances in which one might be used. Give an example of the use of each system. 3. Describe/Define at least four types of information that data mining can yield. Give an example of each one. 4. Discuss the four types of models commonly found in model libraries. 5. How specifically does the digital firm use DSS? Discuss each use, giving examples. 6. List and describe at least three ways in which GIS can be used by modern business. 7. Describe and explain how a GDSS works to enhance group decision making. What are at least four factors involved in the successful outcome of any group meeting? 8. List at least three factors to consider when planning an ESS. 9. Describe MIS and DSS and differentiate between them. 10. What is the balanced scorecard model? Why is it particularly useful? Where does it get its information? 113

6 Answers of Essay Questions: 1. Your text states that many t managers use the new capabilities in DSS and ESS to obtain the same information as before the new systems were implemented.. How would you induce a traditional manager to use new DSS and ESS more effectively? Managers must be trained to ask better questions of the data. This will require major changes in traditional management thinking. Perhaps one way to induce a traditional manager to be more interested in these systems would be a dog-and-pony show at a senior-level management retreat. Of course, the introduction into mid-level management of people trained in the use of these systems could also act as a spur. 2. Describe the two types of DSS. Explain circumstances in which one might be used. Give an example of the use of each system. Model-driven DSS were primarily stand-alone systems isolated from major organizational information systems that used some type of model to perform what-if and other types of analyses. Their analysis capabilities were based on a strong theory or model combined with a good user interface to make the model easy to use. There are several examples in the textbook: the voyage-estimating DSS described in chapter 2, the Gaps planning and forecasting system described at the beginning of this chapter, and Continental Airlines system for cargo revenue optimization are mentioned on page 350. The second type of DSS is a data-driven DSS. These systems analyze large pools of data found in major organizational systems. They support decision making by allowing users to extract useful information that was previously buried in large quantities of data. Often data from transaction processing systems are collected in data warehouses for this purpose. OLAP and data mining can then be used to analyze the data. WH Smith PLC s system for online sales and profitability analysis described in the Window on Organizations, p. 352, is an example of a data-driven DSS. 114

7 3. Describe/Define at least four types of information that data mining can yield. Give an example of each one. There are five types of information discussed in the text: a) Associations are occurrences linked to a single event. Example: A study of supermarket purchasing patterns might reveal that when corn chips are purchased, a cola drink is purchased 65 percent of the time, but when there is a promotion, cola is purchased 85 percent of the time. b) Sequences events are linked over time. Example: If a house is purchased, a new refrigerator will be purchased within two weeks 65 percent of the time, and an oven will be bought within one month of the home purchase 45 percent of the time. c) Classifications recognizes patterns that describe the group to which an item belongs by examining existing items that have been classified and by inferring a set of rules. Example: Businesses such as credit card or telephone companies worry about the loss of steady customers. Classification can help discover the characteristics of customers who are likely to leave and can provide a model to help managers predict who they are so that they can devise special campaigns to retain such customers. d) Clusters working in a manner similar to classification when no groups have yet been defined. Example: A data-mining tool can discover different groupings within data, such as finding affinity groups for bank cards or partitioning a database into groups of customers based on demographics and types of personal investments. e) Forecasts uses a series of existing values to forecast what other values will be. Example: Forecasting might find patterns in data to help managers estimate the future value of continuous variables such as sales figures. 4. Discuss the four types of models commonly found in model libraries. Statistical modeling software can be used to help establish relationships, such as relating product sales to differences in age, income, or other factors between communities. Optimization models, often using linear programming, determined optimal resource allocation to maximize or minimize specified variables such as cost or time. A classic use of optimization models is to determine the proper mix of products within a given market to maximize profits. Forecasting models are often used to forecast sales. The user of this type of model might supply a range of historical data to project future conditions and the sales that might result from those conditions. Companies often use this software to predict the actions of competitors. Sensitivity analysis models ask what-if questions repeatedly to determine the impact of changes in one or more factors on outcomes. 5. How specifically does the digital firm use DSS? Discuss each use, giving examples. DSS can help companies improve supply chain management and customer relationship management. Some take advantage of the company-wide data provided by enterprise systems. DSS today can also harness the interactive capabilities of the Web to provide decision-support tools to both employees and customers. 6. List and describe at least three ways in which GIS can be used by modern business. Geographic information systems are a special category of DSS that use data visualization technology to analyze and display data for planning and decision-making in the form of digitized maps. GIS 115

8 can best be used to support decisions that require knowledge about the geographic distribution of people or other resources in scientific research, resource management, and development planning. GIS have modeling capabilities, allowing managers to change data and automatically revise business scenarios to find better solutions. For instance, a company could display its customers on a map and then design the most efficient delivery route for its products. A second way in which it could be used would be to analyze demographic information to decide where to open branch restaurants. A third use could be customer demographic data and map information to locate people who are likely to become customers for the company s services. 7. Describe and explain how a GDSS works to enhance group decision making. What are at least four factors involved in the successful outcome of any group meeting? Beyond three to five attendees the traditional meeting process breaks down. GDSS software tools contribute to a more collaborative atmosphere by guaranteeing contributors anonymity so that attendees can focus on evaluating the ideas themselves. The GDSS software tools follow structured methods for organizing and evaluating ideas and for preserving the results of meetings, allowing non-attendees to locate needed information after the meeting. The documentation of the meeting by one group at one site can also be used as input to another meeting on the same project at another site. If properly designed and supported, GDSS meetings can increase the number of ideas generated and the quality of decisions while producing the desired results in fewer meetings. The nature of electronic meeting technology is only one of a number of factors that affect meeting processes and output. The outcome of group meetings depends upon the composition of the group, the manner in which the problem is presented to the group, the facilitator s effectiveness, the organization s culture and environment, the quality of the planning, the cooperation of the attendees, and the appropriateness of tools selected for different types of meetings and decision problems. 8. List at least three factors to consider when planning an ESS. A major challenge of building executive support systems has been to integrate data from systems designed for very different purposes so that senior executives can review organizational performance from a firm-wide perspective. ESS must be designed so that high-level managers and others can use them without much training. One area that merits special attention is the determination of executive information requirements. ESS need to have some facility for environmental scanning. A key information requirement of managers at the strategic level is the capability to detect signals of problems in the organizational environment that indicate strategic threats and opportunities. The ESS need to be designed so that both external and internal sources of information can be used for environmental scanning purposes. Implementation of the DSS must be carefully managed to neutralize the opposition of managers at the lower levels of the organization, because DSS potentially could give top executives the ability to examine their work without their knowledge. 9. Describe MIS and DSS and differentiate between them. MIS provide information on the firm s performance to help managers monitor and control the business. They typically produce hard copy, fixed, regularly scheduled reports based on data extracted and summarized from the organization s underlying transaction processing systems. DSS provide new sets of capabilities for nonroutine decisions and user control. MIS accents reports 116

9 based on routine flows of data and assists in the general control of the organization. DSS emphasizes change, flexibility, and rapid response to unstructured problems. 10. What is the balanced scorecard model? Why is it particularly useful? Where does it get its information? The balanced scorecard is a model for analyzing firm performance that supplements traditional financial measures with measurements from additional business perspectives, such as customers, internal business processes, and learning and growth. Managers can use balanced scorecard systems to see how well the firm is meeting its strategic goals. Data to fill out the scorecard, from sources such as financial ledger applications and client retention and market penetration ratios, feed a central data warehouse. The data is mined and ad hoc reports can be created. 117