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Systems Integration Models and Impacts of Management Support Systems

Learn about the crucial need for systems integration in Management Support Systems and the impacts on individuals, organizations, and society. Explore different integration models and understand the future of MSS.

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Systems Integration Models and Impacts of Management Support Systems

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  1. Chapter 16 INTEGRATION, IMPACTS, AND THE FUTURE OF MANAGEMENT SUPPORT SYSTEMS

  2. Learning Objectives • Understand the need for systems integration for MSS • Describe the difficulties in integrating systems • Describe major models of MSS integration • Describe MSS integration with enterprise systems • Describe organizational impacts of MSS

  3. Learning Objectives • Learn the potential impacts of MSS on individuals • Describe societal impacts of MSS • List and describe major ethical and legal issues of MSS implementation • Define the digital divide and discuss how to close it • Provide an overview regarding the future of MSS

  4. Systems Integration: An Overview • Types of integration • Functional integration Theprovision of different support functions as a single system through a single, consistent interface • Physical integration Thepackaging the hardware, software, and communication features required to accomplish functional integration

  5. Systems Integration: An Overview • Why integrate? • Implementing MSS • Increasing the capabilities of the MSS applications • Enhancing the capabilities of non-MSS applications • Enabling real-time decision support • Enabling more powerful applications • Facilitating system development • Enhancing with intelligent tools

  6. Systems Integration: An Overview • Levels of integration • Across different MSS • Within MSS • Embedded intelligent systems • Integration and the Web

  7. Types of Management Support Systems Integration • Models of Integrating ES and DSS • Intelligent systems attached to DSS components • Database intelligent component • Intelligent system for the model base and its management • Intelligent system for improving the user interface • Intelligent consultant to DSS builders • Intelligent consultant to users

  8. Types of Management Support Systems Integration

  9. Types of Management Support Systems Integration • Models of Integrating ES and DSS • An ES as a separate component in a DSS • ES output as input to BA • Analysis output as input to ES • Feedback • Issues and Configurations in MSS integration • Representative integration factors (see Table 16.3, p. 717 • Sharing in the decision-making process • Feedback loops in integrated systems

  10. Types of Management Support Systems Integration

  11. Integration with Enterprise Systems and Knowledge Management • Integration with ERP and SCM Systems • Integration with KMS • Integration of KMS with Other business information systems • Integrating DSS and Knowledge management • Integration of Intelligent systems and knowledge management • Other Knowledge Management–Related Integration

  12. Integration with Enterprise Systems and Knowledge Management

  13. Integration with Enterprise Systems and Knowledge Management

  14. Integration with Enterprise Systems and Knowledge Management • Integration approaches • Second-generation ERP systems • Enterprise application integration • Comprehensive systems • Web services

  15. The Impacts of Management Support Systems: An Overview • MSS impacts: • Particular individuals and jobs • Work structures of departments and units within an organization • Total organizational structures • Entire industries, communities, and society as a whole

  16. The Impacts of Management Support Systems: An Overview • MSS impacts on society: • Changing role of home-bound people • Computer crime and fraud • Consumers • The digital divide • Employment levels • Opportunities for the disabled • Quality of life • Work in hazardous environments

  17. The Impacts of Management Support Systems: An Overview

  18. Management Support Systems Impacts on Organizations • New organizational units • Management support department • BI department (unit) • Artificial intelligence department • Knowledge management department that can be combined with or replace a quantitative analysis unit

  19. Management Support Systems Impacts on Organizations • Organizational culture • Restructuring business processes and virtual teams • Business process reengineering (BPR) Changes in structure, organizational culture, and processes within an entire organization • Simulation modeling and organizational restructuring

  20. Management Support Systems Impacts on Organizations • The impacts of ADS systems • Reduction of middle management • Empowerment of customers and business partners • Improved customer service (e.g., faster reply to requests) • Increased productivity of help desks and call centers

  21. Management Support Systems Impacts on Organizations • Other organizational impacts • Increased productivity, speed, customer satisfaction, quality, and supply-chain improvements resulting in strategic advantage • Entire industries are affected

  22. Management Support Systems Impacts on Organizations

  23. Management Support Systems Impacts on Individuals • Job satisfaction • Inflexibility, dehumanization, stress, and anxiety • Job stress and anxiety • Cooperation of experts

  24. Automating Decision Making and the Manager’s Job • The affect of MSS on managers’ activities and their performance • Less expertise (experience) is required for making many decisions. • Faster decision making is possible • Less reliance on experts and analysts is required • Power is being redistributed among managers • Support for complex decisions makes them faster to make and of better quality • Information needed for high-level decision making is expedited or even self-generated • Automation of routine decisions may eliminate some managers

  25. Automating Decision Making and the Manager’s Job • Can managers’ jobs be fully automated? • Some of their routine decisions, such as scheduling, can be automated; other decisions that involve behavioral aspects cannot • The job of top managers is the least routine and therefore the most difficult to automate

  26. Issues of Legality, Privacy, And Ethics • Legal issues • What is the value of an expert opinion in court when the expertise is encoded in a computer? • Who is liable for wrong advice (or information) provided by an ES? • What happens if a manager enters an incorrect judgment value into an MSS and the result is damage or a disaster? • Who owns the knowledge in a knowledge base? • Should royalties be paid to experts who provide knowledge to an ES or a knowledge base? • Can management force experts to contribute their expertise?

  27. Issues of Legality, Privacy, And Ethics • Privacy The right to be left alone and the right to be free from unreasonable personal intrusions • Two rules followed fairly closely in court decisions: • The right of privacy is not absolute. Privacy must be balanced against the needs of society • The public’s right to know is superior to the individual’s right to privacy

  28. Issues of Legality, Privacy, And Ethics • Privacy • Collecting information about individuals • The Web and information collection • Homeland security and individual privacy

  29. Issues of Legality, Privacy, And Ethics • Ethics in decision making and support • Personal values constitute a major factor in the issue of ethical decision making • Framework describing ethics processes and systems • Who is the agent? • What action was actually taken or is being contemplated? • What are the results or consequences of the act? • Is the result fair or just for all stakeholders? • Non-work related use of the Internet

  30. Issues of Legality, Privacy, And Ethics

  31. Intelligent and Automated Systems and Employment Levels • The impact of MSS on employment levels • MSS have the potential to significantly affect the productivity and employment of many types of employees as well to partially or even completely eliminate jobs • Technology is getting less expensive and more capable and thus is bringing about substantial changes in jobs and job content

  32. Intelligent and Automated Systems and Employment Levels • The impact of MSS on employment levels • Two extreme positions are massive unemployment and increased employment • There are a number of newly created MSS-related jobs

  33. Intelligent and Automated Systems and Employment Levels • The impact of MSS on employment levels • Questions about how intelligent systems will affect employment • Is some unemployment really socially desirable? • Should the government intervene more in the distribution of income and in determination of the employment level? • Can the “invisible hand” in the economy, which has worked so well in the past, continue to be successful in the future? • Will artificial intelligence make most of us idle but wealthy?

  34. Other Societal Impacts of MSS and the Digital Divide • Representative positive effects of MSS • Work in hazardous environments • Opportunities for the disabled and elderly • The changing roles of single parents and home-bound people • Improvements in health care delivery • Aids for the consumer • Quality of life at home and in the workplace • Law enforcement and homeland security improvement

  35. Other Societal Impacts of MSS and the Digital Divide • Potential negative effects • Computer crime and internet fraud • Too much power • The dangers of the web • Blaming the computer phenomenon • Social responsibility

  36. Other Societal Impacts of MSS and the Digital Divide • Digital divide Growing gap between those who have and those who do not have the ability to use the technology • The gap exists both within and between countries as well as between large and small businesses • One device that is helping to close the gap is the smart phone that enables Internet access without the need of having a PC

  37. The Future ofManagement Support Systems • MSS will play a larger role in strategic management due to BPM systems • Increased use of the Web for MSS development and applications • BI is being combined with other Web-based enterprise systems (CRM, ERP, and KM) • Intelligent systems have become major contributors in the fight against terrorism and fraud, as well as contributors to productivity and quality of life improvements

  38. The Future ofManagement Support Systems • Web-based advisory services will mushroom on the Internet • More complex MSS applications are expected—so more complex problems will be solved. • The trend toward making MSS more intelligent will • Advancements in mobile, wireless, and pervasive computing require the use of a • greater and more diversified number of intelligent devices

  39. The Future ofManagement Support Systems • MSS will be available for dissemination via application service providers (ASP) • Natural language-based search engines will populate • the Internet, facilitating MSS construction by reducing costs • The semantic Web will increase the use of • MSS • The use of voice technologies and natural language processing will further facilitate the usage of MSS

  40. The Future ofManagement Support Systems • Frontline decision support technologies that mostly support CRM will become an integral part of IT in most medium-sized and large organizations • MSS will continue to be integrated with ERP to provide better SCM, including manufacturing planning and control • Large numbers of experts will offer expertise on the Internet and will become an important part of knowledge dissemination • More and more companies will initiate formal KM programs; some will sell that knowledge to others

  41. The Future ofManagement Support Systems • The usage of wireless technologies will allow employees to access MSS and knowledge bases anytime and from anywhere • Intelligent agents will roam the Internet and intranets, assisting decision makers in the monitoring and interpretation of information • Groupware technologies for remote collaboration and communication will become easier to use, more powerful, and less expensive

  42. The Future ofManagement Support Systems • Decision support tools for e-commerce will expand to include more and better tools • ADS systems are spreading across and within industries, empowering and sometimes replacing employees. • Grid computing will be used for analysis of very large amounts of data

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