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Decision Support Systems Decision Support MIS and DSS Artificial Intelligence Expert Systems Chapter 9 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill.

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Presentation on theme: "Decision Support Systems Decision Support MIS and DSS Artificial Intelligence Expert Systems Chapter 9 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill."— Presentation transcript:

1 Decision Support Systems Decision Support MIS and DSS Artificial Intelligence Expert Systems Chapter 9 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.

2 9-2 Levels of Management Decision Making Strategic management Executives develop organizational goals, strategies, policies, and objectives Tactical management Develop short- and medium-range plans, schedules and budgets for their subunits Operational management Develop short-range plans such as weekly production schedules

3 9-3 Decision Structure Unstructured – decision situations where it is not possible to specify in advance Semistructured - decision procedures that can be prespecified, but not enough to lead to a definite recommended decision Structured – situations where the procedures to follow when a decision is needed can be specified in advance Page 318 Fig 9.4

4 9-4 Information Quality Information has 3 dimensions: Time: currency, frequency Content: accuracy, completeness Form: clarity, order

5 9-5 Business Intelligence Applications

6 9-6 Decision Support Systems Provide interactive information support to business professionals during the decision-making process To support semistructured business decisions

7 9-7 Using DSS 4 Analytical models What-if Analysis Sensitivity Analysis Goal-Seeking Optimization

8 9-8 Management Information Systems MIS Produces information products that support many of the day-to-day decision-making needs of managers and business professionals Prespecified reports, displays and responses Support more structured decisions

9 9-9 MIS Reporting Alternatives Periodic Scheduled Reports Prespecified format on a regular basis Exception Reports Reports about exceptional conditions May be produced regularly or when exception occurs Demand Reports and Responses Information available when demanded Push Reporting Information pushed to manager

10 9-10 Online Analytical Processing OLAP Analytical Operations in real time Consolidation Aggregation of data Drill-down Display detail data that comprise consolidated data Slicing and Dicing Ability to look at the database from different viewpoints

11 9-11 Data Mining Main purpose is to provide decision support to business professionals through knowledge discovery Market Basket Analysis The purpose is to determine what products customers purchase together with other products

12 9-12 Executive Information Systems Combine many features of MIS, DSS & OLAP Customizable graphical user interfaces Exception reporting Trend analysis Drill down capability

13 9-13 Case 2 Artificial Intelligence The Dawn of the Digital Brain Numenta will translate the way the brain works into an algorithm that can run on a new type of computer The human brain does not work like a computer Intelligence, according to Hawkins, is pattern recognition

14 9-14 Case Study Questions 1. What is the business value of AI technologies in business today? What value might exist if Jeff Hawkins can build a machine to think like humans? 2. Why has artificial intelligence become so important to business? 3. Why do you think banks and other financial institutions are leading users of AI technologies? What are the benefits and limitations of this technology?

15 9-15 Section II: Artificial Intelligence (AI) A field of science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, and engineering Goal is to develop computers that can simulate the ability to think, as well as see, hear, walk, talk, and feel

16 9-16 Attributes of Intelligent Behavior Think and reason Use reason to solve problems Learn or understand from experience Acquire and apply knowledge Exhibit creativity and imagination Deal with complex or perplexing situations Respond quickly and successfully to new situations Recognize the relative importance of elements in a situation Handle ambiguous, incomplete, or erroneous information

17 9-17 Domains of Artificial Intelligence

18 9-18 Cognitive Science Based in biology, neurology, psychology, etc. Focuses on researching how the human brain works and how humans think and learn

19 9-19 Robotics Based in AI, engineering and physiology Robot machines with computer intelligence and computer controlled, humanlike physical capabilities

20 9-20 Natural Interfaces Based in linguistics, psychology, computer science, etc. Includes natural language and speech recognition Development of multisensory devices that use a variety of body movements to operate computers Virtual reality Using multisensory human-computer interfaces that enable human users to experience computer-simulated objects, spaces and “worlds” as if they actually exist

21 9-21 Expert Systems ES A knowledge-based information system (KBIS) that uses its knowledge about a specific, complex application to act as an expert consultant to end users KBIS is a system that adds a knowledge base to the other components on an IS

22 9-22 Expert System Components Knowledge Base Facts about specific subject area Heuristics that express the reasoning procedures of an expert (rules of thumb) Software Resources Inference engine processes the knowledge and makes inferences to make recommend course of action User interface programs to communicate with end user Explanation programs to explain the reasoning process to end user

23 9-23 Methods of Knowledge Representation Case-Based – knowledge organized in form of cases Cases: examples of past performance, occurrences and experiences Frame-Based – knowledge organized in a hierarchy or network of frames Frames: entities consisting of a complex package of data values

24 9-24 Methods of Knowledge Representation Object-Based – knowledge organized in network of objects Objects: data elements and the methods or processes that act on those data Rule-Based – knowledge represented in rules and statements of fact Rules: statements that typically take the form of a premise and a conclusion Such as, If (condition) then (conclusion)

25 9-25 Expert System Benefits Faster and more consistent than an expert Can have the knowledge of several experts Does not get tired or distracted by overwork or stress Helps preserve and reproduce the knowledge of experts

26 9-26 Expert System Limitations Limited focus Inability to learn Maintenance problems Developmental costs Can only solve specific types of problems in a limited domain of knowledge

27 9-27 Suitability Criteria for Expert Systems Domain: subject area relatively small and limited to well-defined area Expertise: solutions require the efforts of an expert Complexity: solution of the problem is a complex task that requires logical inference processing (not possible in conventional information processing) Structure: solution process must be able to cope with ill-structured, uncertain, missing and conflicting data Availability: an expert exists who is articulate and cooperative

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