CH8-DSSAll

Decision Support Systems : 

Decision Support Systems

Learning Objectives : 

2 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.

Section I : 

Section I Decision Support in Business

Business and Decision Support : 

4 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.

Business and Decision Support (continued) : 

5 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.

Business and Decision Support (continued) : 

6 Business and Decision Support (continued)

Business and Decision Support (continued) : 

7 Business and Decision Support (continued) 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 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 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.

Decision Support Trends : 

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. Everybody’s Information Systems

Management Information Systems : 

9 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

Online Analytical Processing (OLAP) : 

10 Online Analytical Processing (OLAP) 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 Consolidation Drill-down Slicing and Dicing

Decision Support Systems : 

11 Decision Support Systems Provide interactive information support during the decision-making process. They 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

GIS : 

12 GIS 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

Data Visualization : 

13 Data Visualization Represent complex data using interactive three-dimensional graphic forms Helps discover patterns, links, and anomalies

Using Decision Support Systems : 

14 Using Decision Support Systems An interactive modeling process Four types of analytical modeling What-if analysis Sensitivity analysis Goal-seeking analysis Optimization analysis

Data Mining : 

15 Data Mining 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

Executive Information Systems : 

16 Executive Information Systems 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 Alternative names Enterprise information systems Executive support systems

Enterprise Portals and Decision Support : 

17 Enterprise Portals and Decision Support A Web-based interface integrating resources 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

Enterprise Portals and Decision Support (continued) : 

18 Enterprise Portals and Decision Support (continued)

Knowledge Management Systems : 

19 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

Section II : 

Section II Artificial Intelligence Technologies in Business

Business and AI : 

21 Business and AI “Designed to leverage the capabilities of humans rather than replace them,… AI technology enables an array of applications that forge new connections among people, computers, knowledge, and the physical world.” 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

Artificial Intelligence : 

22 Artificial Intelligence

Neural Networks : 

23 Neural Networks Computing systems modeled after the brain’s meshlike network of interconnected processing elements, called neurons Goal – the neural network learns from data it processes

Fuzzy Logic Systems : 

24 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

Genetic Algorithms : 

25 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

Virtual Reality : 

26 Virtual Reality Computer-simulated reality Relies on multisensory input/output devices Allows interaction with computer-simulated objects, entities, and environments in three dimensions CAD

Intelligent Agents : 

27 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

Expert Systems : 

28 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

Expert Systems : 

29 Expert Systems

Expert Systems (continued) : 

30 Expert Systems (continued) Components Knowledge base Contains Facts about a specific subject area Heuristics that express the reasoning procedures of an expert on the subject 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

Slide 31: 

31

Developing Expert Systems : 

32 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

Developing Expert Systems : 

33 Developing Expert Systems

The Value of Expert Systems : 

34 The Value of Expert Systems 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