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MIS Course "Home of the Power of Technology"

Chapter 9
Your Instructor
Drop Box
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Case Study
Extra Resources

Chapter 9: E-Business Decision Support Systems
  • Information, Decisions, and Management. Information systems can support a variety of management decision-making levels and decisions. These include the three levels of management activity (strategic, tactical, and operational decision making) and three types of decision structures (structured, semistructured, and unstructured). Information systems provide a wide range of information products to support these types of decisions at all levels of the organization.
  • Decision Support Trends. Major changes are taking place in traditional MIS, DSS, and EIS tools for providing the information and modeling managers need to support their decision making. Decision support in business is changing, driven by rapid developments in end user computing and networking; Internet and Web technologies; and Web-enabled business applications. The growth of corporate intranets, extranets, as well as the Web, has accelerated the development of "executive class" interfaces like enterprise information portals, enterprise knowledge portals, and Web-enabled decision support software tools, and their use by lower levels of management and by individuals and teams of business professionals. In addition, the growth of e-commerce and e-business applications has expanded the use of enterprise portals and DSS tools by the suppliers, customers, and other business stakeholders of a company.
  • Management Information Systems. Management information systems provide prespecified reports and responses to managers on a periodic, exception, demand, or push reporting basis, to meet their need for information to support decision making.
  • OLAP and Data Mining. Online analytical processing interactively analyzes complex relationships among large amounts of data stored in multidimensional databases. Data mining analyzes the vast amounts of historical data that have been prepared for analysis in data warehouses. Both technologies discover patterns, trends, and exception conditions in a company's data that support their business analysis and decision making.
  • Decision Support Systems. Decision support systems are interactive, computer-based information systems that use DSS software and a model base and database to provide information tailored to support semistructured and unstructured decisions faced by individual managers. They are designed to use a decision maker's own insights and judgments in an ad hoc, interactive, analytical modeling process leading to a specific decision.
  • Executive Information Systems. Executive information systems are information systems originally designed to support the strategic information needs of top management. However, their use is spreading to lower levels of management and business professionals. EIS are easy to use and enable executives to retrieve information tailored to their needs and preferences. Thus, EIS can provide information about a company's critical success factors to executives to support their planning and control responsibilities.
  • Enterprise Information and Knowledge Portals. Enterprise information portals provide a customized and personalized Web-based interface for corporate intranets to give their users easy access to a variety of internal and external business applications, databases, and information services that are tailored to their individual preferences and information needs. Thus, an EIP can supply personalized Web-enabled information, knowledge, and decision support to executives, managers, and business professionals, as well as customers, suppliers, and other business partners. An enterprise knowledge portal is a corporate intranet portal that extends the use of an EIP to include knowledge management functions and knowledge base resources so that it becomes a major form of knowledge management system for a company.
  • Artificial Intelligence. The major application domains of artificial intelligence (AI) include a variety of applications in cognitive science, robotics, and natural interfaces. The goal of AI is the development of computer functions normally associated with human physical and mental capabilities, such as robots that see, hear, talk, feel, and move, and software capable of reasoning, learning, and problem solving. Thus, AI is being applied to many applications in business operations and managerial decision making, as well as in many other fields.
  • AI Technologies. The many application areas of AI are summarized in Figure 9.23, including neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents. Neural nets are hardware or software systems based on simple models of the brain's neuron structure that can learn to recognize patterns in data. Fuzzy logic systems use rules of approximate reasoning to solve problems where data are incomplete or ambiguous. Genetic algorithms use selection, randomizing, and other mathematics functions to simulate an evolutionary process that can yield increasingly better solutions to problems. Virtual reality systems are multisensory systems that enable human users to experience computer-simulated environments as if they actually existed. Intelligent agents are knowledge-based software surrogates for a user or process in the accomplishment of selected tasks.
  • Expert Systems. Expert systems are knowledge-based information systems that use software and a knowledge base about a specific, complex application area to act as expert consultants to users in many business and technical applications. Software includes an inference engine program that makes inferences based on the facts and rules stored in the knowledge base. A knowledge base consists of facts about a specific subject area and heuristics (rules of thumb) that express the reasoning procedures of an expert. The benefits of expert systems (such as preservation and replication of expertise) must be balanced with their limited applicability in many problem situations.

1.       Is the form and use of information and decision support systems for managers and business professionals changing and expanding?  Why or why not?


Yes, the form and use of information and decision support in e-business is changing and expanding.  Certainly changes are taking place in traditional MIS, DSS, and EIS tools, and these changes are being driven by the rapid developments in end user computing and networking.  Internet, web browser, and related technologies, and the explosion of e-commerce activities are also causing rapid change.  The growth of corporate intranets, extranets, as well as the Web, has accelerated the development of “executive class” interfaces like enterprise information portals, and Web enabled decision support software tools and their use by lower of management and by individuals and teams of business professionals.  The expansion of e-commerce has increased the use of enterprise portals and DSS tools by the suppliers, customers, and other business stakeholders of a company. 


2.      Has the growth of self-directed teams to manage work in organizations changed the need for strategic, tactical, and operational decision making in business?


Although there has been tremendous growth in the use of self-directed teams in organizations in order to manage the work, the basics for decision making have not changed that much.  Strategic, tactical, and operational decision making continue to be carried out in organizations regardless of how the work is completed.  What has changed is the way in which the work is being completed.  Through technology, self-directed teams now have new and creative ways of completing their duties. 


3.      What is the difference between the ability of a manager to retrieve information instantly on demand using an MIS, and the capabilities provided by a DSS?


Managers have traditionally relied on the capabilities of MIS to obtain the data that they required.  However, the information for these requests had traditionally been structured in advance, and was of the structured type of request.  In a DSS support system, the capabilities are much broader.  Now managers can query the information in a number of ways, and these systems can handle the ad hoc queries that come about.  DSS provide the capabilities for a manager to participate in interactive analytical modeling in order to make more informed decision.  DSS software is capable of supporting semistructured and unstructured decisions faced by individual managers.  They are designed to use decision maker’s own insights and judgments in an ad hoc, interactive, analytical modeling process which will lead them to a specific decision. 


4.      Refer to the Real World Case on Ben & Jerry’s and GE Plastics in the chapter. How might a digital dashboard help you as a business professional or manager in your work activities? Give several examples to illustrate your answer.


      A digital dashboard might provide assistance by:

         Accelerating the development and use of “executive class” information delivery and decision support software tools by lower levels of management and by individuals and teams of business professionals.  The sales team can check to determine if one flavor of ice cream is gaining ground on the current no. 1 sales flavor at Ben & Jerry’s.  The marketing department can check to see what donations are currently required by Ben & Jerry’s.  Ben & Jerry’s is able to reduce the time it takes to close their monthly books.

         The digital dashboard used by several levels of management in companies such as Ben & Jerry’s and GE Plastics permit the companies to better track their products, improve and customer relations.

         Everyone in the business has access to the same real-time data and its analysis. GE Plastics has reduced the need for dozens of analysts to compile and deliver information and to deliver consistency in the analysis of the data to the user of the information quicker.


5.      In what ways does using an electronic spreadsheet package provide you with the capabilities of a decision support system?


An electronic spreadsheet package can be thought of as one of the earlier forms of decision support systems.  Spreadsheets allow users to complete “what-if”, sensitivity, goal seeking, and optimization analysis.  They also provide some features of database management and dialog management support.


6.      Are enterprise information portals making executive information systems unnecessary?  Explain your reasoning.


First of all, in answering the question students’ should explain what an EIP system is versus an EIS system.  As such, EIPs are developed by companies as a way to provide web-enabled information, knowledge, and decision support to executives, managers, employees, suppliers, customers, and other business partners.  EISs on the other hand, are designed to provide strategic information that are tailored to the needs of top management. 


Whether or not EIP’s will eventually make EIS systems unnecessary is a matter of debate.  Students’ may agree that as more and more enriched features are added to EIP systems that their importance will be heightened.  On the other hand, EIS systems are also being developed with enriched features such as Web browsing, electronic mail, groupware tools, and DSS and expert systems capabilities to make them even more useful to managers and business professionals.    


7.      Refer to the Real World Case on Wal-Mart, BankFinancial, and HP in the chapter. Why are neural network and expert system technologies used in many data-mining applications?


Reasons could include:


         Neural networks can “learn” from the data it processes, thereby learning to recognize patterns and relationships in the data it processes.  Thus neural networks can change the strengths of the interconnections between the elements in response to changing patterns in the data it receives and the results that occur.  The neural network technology can be used to evaluate or “make decisions” on its own.  An example is that of BankFinancial using neural networks to more accurately target promotions to customers and prospects.

         Expert system technologies act as a consultant to end users in very specific problem areas by making humanlike inferences about knowledge contained in a specialized knowledge base.  Expert systems must be able to explain their reasoning process and conclusions to a user.  An example would be the “If-Ten” analysis used by Wal-Mart in managing its inventory.


8.      Can computers think?  Will they ever be able to?  Explain why or why not.


Computers will probably never be able to reason in the same way that humans do.  However, computers are likely to be able to perform more and more tasks that up until now could only be performed by humans.  Experimentation continues to develop in the field of artificial intelligence, and improvements are ongoing.  Will a computer ever pass the Turing test is questionable.


9.      What are some of the most important applications of AI in business?  Defend your choices.


In business, expert systems are probably the most important application of artificial intelligence, though the use of such systems is still quite limited.  In other areas, robotics is widely used in manufacturing, and natural interface applications are becoming more and more a part of information systems for many different applications. Major areas of AI research and development include cognitive science, computer science, robotics, and natural interface applications.


10.      What are some of the limitations or dangers you see in the use of AI technologies such as expert systems, virtual reality, and intelligent agents?  What could be done to minimize such effects?


Students’ will suggest a number of answers to this question.  However, one possible solution could deal with the ethical issues of these systems.  Are they being used for the good of society or is the potential for their misuse growing increasingly with the more complex developments taking place.  The design of these systems is both complex and powerful.  We must begin to ask ourselves what is the harmful potential of these systems, and how far will we be willing to go to use them to supplement the human reasoning process that we are born with.  


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