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8 Decision Support Systems 1 8 Learning Objectives • Identify the changes taking place in the form and use of decision support in e-business enterprises. • Identify the role and reporting alternatives of management information systems. 2 8 Learning Objectives (continued) • Describe how online analytical processing can meet key information needs of managers. • Explain the decision support system concept and how it differs from traditional management information systems. 3 8 Learning Objectives (continued) • Explain how the following information systems can support the information needs of executives, managers, and business professionals: – Executive information systems – Enterprise information portals – Enterprise knowledge portals 4 8 Learning Objectives (continued) • Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business. • How can expert systems be used in business decision-making situations? 5 8 Section I • Decision Support in Business 6 8 Business and Decision Support • To succeed, companies need information systems that can support the diverse information and decision-making needs of their managers and business professionals. 7 8 Business and Decision Support (continued) • Information, Decisions, & Management – The type of information required by decision makers is directly related to the level of management and the amount of structure in the decision situations. 8 8 Business and Decision Support (continued) 9 8 Business and Decision Support (continued) • Information Quality – Timeliness • • • • Provided WHEN it is needed Up-to-date when it is provided Provided as often as needed Provided about past, present, and future time periods as necessary 10 8 Business and Decision Support (continued) • Information Quality (continued) – Content • Free from errors • Should be related to the information needs of a specific recipient for a specific situation • Provide all the information that is needed • Only the information that is needed should be provided • Can have a broad or narrow scope, or an internal or external focus • Can reveal performance 11 8 Business and Decision Support (continued) • Information Quality (continued) – Form • Provided in a form that is easy to understand • Can be provided in detail or summary form • Can be arranged in a predetermined sequence • Can be presented in narrative, numeric, graphic, or other forms • Can be provided in hard copy, video, or other media. 12 8 Business and Decision Support (continued) 13 8 Business and Decision Support (continued) • Decision Structure – Structured decisions • Involve situations where the procedures to be followed can be specified in advance – Unstructured decisions • Involve situations where it is not possible to specify most of the decision procedures in advance 14 8 Business and Decision Support (continued) • Decision structure (continued) – Semistructured decisions • Some decision procedures can be specified in advance, but not enough to lead to a definite recommended decision 15 8 Business and Decision Support (continued) – Amount of structure is typically tied to management level • Operational – more structured • Tactical – more semistructured • Strategic – more unstructured 16 8 Decision Support Trends • The growth of corporate intranets, extranets and the Web has accelerated the development and use of “executive class” information delivery & decision support software tools to virtually every level of the organization. 17 8 Management Information Systems • The original type of information system • Produces many of the products that support day-to-day decision-making • These information products typically take the following forms: – – – – Periodic scheduled reports Exception reports Demand reports and responses Push reports 18 8 Management Information Systems (continued) • Management reporting alternatives – Periodic scheduled reports • Prespecified format • Provided on a scheduled basis – Exception reports • Produced only when exceptional conditions occur • Reduces information overload 19 8 Management Information Systems (continued) • Management reporting alternatives (continued) – Demand reports and responses • Available when demanded. • Ad hoc – Push reports • Information is sent to a networked PC over the corporate intranet. • Not specifically requested by the recipient 20 8 Online Analytical Processing • Enables managers and analysts to interactively examine & manipulate large amounts of detailed and consolidated data from many perspectives – Analyze complex relationships to discover patterns, trends, and exception conditions – Real-time 21 8 Online Analytical Processing (continued) • Involves.. – Consolidation • The aggregation of data. • From simple roll-ups to complex groupings of interrelated data – Drill-Down • Display detail data that comprise consolidated data 22 8 Online Analytical Processing (continued) – Slicing and Dicing • The ability to look at the database from different viewpoints. • When performed along a time axis, helps analyze trends and find patterns 23 8 Decision Support Systems • Computer-based information systems that provide interactive information support during the decision-making process • DSS’s use – – – – Analytical models Specialized databases The decision maker’s insights & judgments An interactive, computer-based modeling process to support making semistructured and unstructured business decisions 24 8 Decision Support Systems (continued) • Designed to be ad hoc, quick-response systems that are initiated and controlled by the decision maker • DSS Models and Software – Rely on model bases as well as databases – Might include models and analytical techniques used to express complex relationships 25 8 Decision Support Systems (continued) • DSS models and software (continued) – Can combine model components to create integrated models in support of specific types of business decisions 26 Decision Support Systems (continued) • Geographic Information & Data Visualization Systems – Special categories of DSS that integrate computer graphics with other DSS features – GIS • A DSS that uses geographic databases to construct and display maps and other graphics displays 27 8 Decision Support Systems (continued) • Geographic information and data visualization systems (continued) – Data visualization systems • Represent complex data using interactive three-dimensional graphic forms • Helps discover patterns, links, and anomalies 28 8 Using Decision Support Systems • An interactive modeling process • Four types of analytical modeling – What-if analysis – Sensitivity analysis – Goal-seeking analysis – Optimization analysis 29 8 Using Decision Support Systems (continued) • What-If Analysis – End user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variables 30 8 Using Decision Support Systems (continued) • Sensitivity Analysis – A special case of what-if analysis – The value of only one variable is changed repeatedly, and the resulting changes on other variables are observed – Typically used when there is uncertainty about the assumptions made in estimating the value of certain key variables 31 8 Using Decision Support Systems (continued) • Goal-Seeking Analysis – Instead of observing how changes in a variable affect other variables, goalseeking sets a target value (a goal) for a variable, then repeatedly changes other variables until the target value is achieved 32 8 Using Decision Support Systems (continued) • Optimization Analysis – A more complex extension of goalseeking – The goal is to find the optimum value for one or more target variables, given certain constraints 33 8 Using Decision Support Systems (continued) • Data Mining for Decision Support – Software analyzes vast amounts of data – Attempts to discover patterns, trends, & correlations – May perform regression, decision tree, neural network, cluster detection, or market basket analysis 34 8 Executive Information Systems • EIS’s combine many of the features of MIS and DSS • Originally intended to provide top executives with immediate, easy access to information about the firm’s “critical success factors” • Alternative names – Enterprise information systems – Executive support systems 35 8 Executive Information Systems (continued) • Features of an EIS – Information presented in forms tailored to the preferences of the users – Most stress use of graphical user interface and graphics displays – May also include exception reporting and trend analysis 36 8 Enterprise Portals and Decision Support • A Web-based interface and integration of intranet and other technologies that gives all intranet users and selected extranet users access to a variety of internal & external business applications and services 37 8 Enterprise Portals and Decision Support (continued) • Business benefits – More specific and selective information – Easy access to key corporate intranet website resources – Industry and business news – Access to company data for stakeholders – Less time spent on unproductive surfing 38 8 Knowledge Management Systems • IT that helps gather, organize, and share business knowledge within an organization • Hypermedia databases that store and disseminate business knowledge. May also be called knowledge bases • Best practices, policies, business solutions • Entered through the enterprise knowledge portal 39 8 Section II • Artificial Intelligence Technologies in Business 40 8 Business and AI • “Designed to leverage the capabilities of humans rather than replace them,…AI technology enables an extraordinary array of applications that forge new connections among people, computers, knowledge, and the physical world.” 41 8 Artificial Intelligence • A field of science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, & engineering • Goal is to develop computers that can think, see, hear, walk, talk, and feel • Major thrust – development of computer functions normally associated with human intelligence – reasoning, learning, problem solving 42 8 Artificial Intelligence (continued) • Domains of AI – Three major areas • Cognitive science • Robotics • Natural interfaces 43 8 Artificial Intelligence (continued) • Cognitive science – Focuses on researching how the human brain works & how humans think and learn – Applications • • • • • Expert systems Adaptive learning systems Fuzzy logic systems Neural networks Intelligent agents 44 8 Artificial Intelligence (continued) • Robotics – Produces robot machines with computer intelligence and computer controlled, humanlike physical capabilities • Natural interfaces – Natural language and speech recognition – Talking to a computer and having it understand – Virtual reality 45 8 Neural Networks • Computing systems modeled after the brain’s mesh like network of interconnected processing elements, called neurons • Goal – the neural network learns from data it processes 46 8 Fuzzy Logic Systems • A method of reasoning that resembles human reasoning • Allows for approximate values and inferences • Allows for incomplete or ambiguous data • Allows “fuzzy” systems to process incomplete data and provide approximate, but acceptable, solutions to problems 47 8 Genetic Algorithms • Uses Darwinian, randomizing, & other mathematical functions to simulate an evolutionary process that can yield increasingly better solutions • Especially useful for situations in which thousands of solutions are possible & must be evaluated 48 8 Virtual Reality • Computer-simulated reality • Relies on multi-sensory input/output devices • Allows interaction with computersimulated objects, entities, and environments in three dimensions 49 8 Intelligent Agents • A “software surrogate” for an end user or a process that fulfills a stated need or activity • Uses built-in and learned knowledge base about a person or process to make decisions and accomplish tasks 50 8 Expert Systems • A knowledge-based information system that uses its knowledge about a specific, complex application area to act as an expert consultant • Provides answers to questions in a very specific problem area • Must be able to explain reasoning process and conclusions to the user 51 8 Expert Systems (continued) • Components – Knowledge base – Software resources • Knowledge base – Contains » Facts about a specific subject area » Heuristics that express the reasoning procedures of an expert on the subject 52 8 Expert Systems (continued) • Software Resources – Contains an inference engine and other programs for refining knowledge and communicating » Inference engine processes the knowledge, and makes associations and inferences » User interface programs, including an explanation program, allows communication with user 53 8 Developing Expert Systems • Begin with an expert system shell • Add the knowledge base • Built by a “knowledge engineer” – Works with experts to capture their knowledge – Works with domain experts to build the expert system 54 8 The Value of Expert Systems 55 8 The Value of Expert Systems (continued) • Benefits – Can outperform a single human expert in many problem situations – Helps preserve and reproduce knowledge of experts • Limitations – Limited focus, inability to learn, maintenance problems, developmental costs 56 8 Discussion Questions • Is the form and use of information and decision support in e-business changing and expanding? • Has the growth of self-directed teams to manage work in organizations changed the need for strategic, tactical, and operational decision making in business? 57 8 Discussion Questions (continued) • 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? • In what ways does using an electronic spreadsheet package provide you with the capabilities of a decision support system? 58 8 Discussion Questions (continued) • Are enterprise information portals making executive information systems unnecessary? • Can computers think? Will they EVER be able to? 59 8 Discussion Questions (continued) • What are some of the most important applications of AI in business? • 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? 60 8 References • James A. O'Brien; George M. Marakas. Management Information Systems: Managing Information Technology in the Business Enterprise 6th Ed., Boston: McGraw-Hill/ Irwin,2004 61